PREFIX osmrel: <https://www.openstreetmap.org/relation/>
PREFIX ogc: <http://www.opengis.net/rdf#>
PREFIX osmkey: <https://www.openstreetmap.org/wiki/Key:>
SELECT DISTINCT ?name WHERE {
  osmrel:4266321 ogc:sfContains ?street .
  ?street osmkey:highway ?highwayType .
  ?street osmkey:name ?name .
  VALUES ?highwayType {
    "residential" "primary" "secondary" "tertiary" "unclassified" "service" "living_street" "road"
  }
}
ORDER BY ?name

Got 1,955 rows and 1 column, showing the first 5 and last 5 rows below:
| name           |
| -------------- |
| 1              |
| 2              |
| 3              |
| 4              |
| 5              |
| ...            |
| Yule Street    |
| Zaida Way      |
| Zande Terrace  |
| Zetland Street |
| Zohrab Street  |

There are 1,955 unique street names within Wellington City, New Zealand, when filtering for typical street types (residential, primary, secondary, tertiary, unclassified, service, living_street, road). The query above lists all unique street names within the city boundary, excluding non-street features.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
osm-planet at https://qlever.cs.uni-freiburg.de/api/osm-planet

You can use the following SPARQL prefixes implicitly in all functions:
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
ogc: <http://www.opengis.net/rdf#
osm2rdf: <https://osm2rdf.cs.uni-freiburg.de/rdf#
osm2rdfgeom: <https://osm2rdf.cs.uni-freiburg.de/rdf/geom#
osm2rdfkey: <https://osm2rdf.cs.uni-freiburg.de/rdf/key#
osm2rdfmember: <https://osm2rdf.cs.uni-freiburg.de/rdf/member#
osm: <https://www.openstreetmap.org/
osmkey: <https://www.openstreetmap.org/wiki/Key:
osmmeta: <https://www.openstreetmap.org/meta/
osmnode: <https://www.openstreetmap.org/node/
osmrel: <https://www.openstreetmap.org/relation/
osmway: <https://www.openstreetmap.org/way/
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
ps: <http://www.wikidata.org/prop/statement/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
wd: <http://www.wikidata.org/entity/
wdt: <http://www.wikidata.org/prop/direct/
xsd: <http://www.w3.org/2001/XMLSchema#
owl: <http://www.w3.org/2002/07/owl#
foaf: <http://xmlns.com/foaf/0.1/
skos: <http://www.w3.org/2004/02/skos/core#
dct: <http://purl.org/dc/terms/
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
schema: <http://schema.org/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
wikibase: <http://wikiba.se/ontology#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] List the unique names of streets within Wellington City, New Zealand.

[Assistant]
Let's break down the question:

1. We need to identify "Wellington City, New Zealand" in the OSM-Planet knowledge graph.
2. We need to find all streets (likely OSM ways with a highway tag) within the boundaries of Wellington City.
3. We need to extract their names (likely via the "name" tag), and ensure uniqueness.

First, let's search for "Wellington City" to find its entity in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Wellington City (osmrel:4266321)
2. Wellington City Park (osmnode:358637857)
3. Commonsense Wellington City (osmnode:7540962604)
4. Wellington City Archives (osmway:1066010976)
5. Wellington City Dam (osmway:1052304463)
6. Wellington City Hall (osmway:470098277): townhall
7. Wellington City Mission (osmway:553203082)
8. Wellington City Park (osmway:466563640)
9. Wellington City Park (osmway:470098270)
10. Wellington City Fire Station (osmway:1040450464): fire_station

[Assistant]
The most relevant entity for "Wellington City" as an administrative boundary is osmrel:4266321.

Next, we need to find all streets (OSM ways with a "highway" tag) within this boundary. To do this, we should:
- Identify the property for the "highway" tag.
- Identify the property for the "name" tag.
- Find a way to restrict the search to ways within the Wellington City boundary (osmrel:4266321).

Let's search for the property used for the "highway" tag in OSM-Planet.

[Tool]
Top 10 property alternatives:
1. highway (osmkey:highway)
2. area:highway (<https://www.openstreetmap.org/wiki/Key:area:highway>)
3. description:highway (<https://www.openstreetmap.org/wiki/Key:description:highway>)
4. place:highway (<https://www.openstreetmap.org/wiki/Key:place:highway>)
5. outdoor:highway (<https://www.openstreetmap.org/wiki/Key:outdoor:highway>)
6. way:highway (<https://www.openstreetmap.org/wiki/Key:way:highway>)
7. ref:highway (<https://www.openstreetmap.org/wiki/Key:ref:highway>)
8. name:highway (<https://www.openstreetmap.org/wiki/Key:name:highway>)
9. was:highway (<https://www.openstreetmap.org/wiki/Key:was:highway>)
10. was:area:highway (<https://www.openstreetmap.org/wiki/Key:was:area:highway>)

[Tool]
Top 10 property alternatives:
1. ναμε (<https://www.openstreetmap.org/wiki/Key:ναμε>)
2. name_ (osmkey:name_)
3. _name_ (osmkey:_NAME_)
4. name: (<https://www.openstreetmap.org/wiki/Key:name:>)
5. name (osmkey:name)
6. source:name (<https://www.openstreetmap.org/wiki/Key:source:name>)
7. description:name (<https://www.openstreetmap.org/wiki/Key:description:name>)
8. location:name (<https://www.openstreetmap.org/wiki/Key:location:name>)
9. person:name (<https://www.openstreetmap.org/wiki/Key:person:name>)
10. link:name (<https://www.openstreetmap.org/wiki/Key:link:name>)

[Tool]
Got 65,536 rows and 3 columns, showing the first 10 rows below:
| subject                          | property                       | object                                 |
| -------------------------------- | ------------------------------ | -------------------------------------- |
| Wellington City (osmrel:4266321) | sf contains (ogc:sfContains)   | Wellington (osmnode:204648)            |
| Wellington City (osmrel:4266321) | has centroid (geo:hasCentroid) | osm2rdfgeom:osm_area_centroid_8532643  |
| Wellington City (osmrel:4266321) | has geometry (geo:hasGeometry) | osm2rdfgeom:osm_relarea_4266321        |
| Wellington City (osmrel:4266321) | sf contains (ogc:sfContains)   | Radio New Zealand (osmnode:2726276489) |
| Wellington City (osmrel:4266321) | sf contains (ogc:sfContains)   | MetService (osmnode:10605323379)       |
| Wellington City (osmrel:4266321) | sf contains (ogc:sfContains)   | Zealandia (osmnode:1690510529)         |
| Wellington City (osmrel:4266321) | sf contains (ogc:sfContains)   | Mount Victoria (osmnode:284021662)     |
| Wellington City (osmrel:4266321) | sf contains (ogc:sfContains)   | Brooklyn (osmnode:267986958)           |
| Wellington City (osmrel:4266321) | sf contains (ogc:sfContains)   | Oriental Bay (osmnode:277080852)       |
| Wellington City (osmrel:4266321) | sf contains (ogc:sfContains)   | Roseneath (osmnode:279654939)          |
| ...                              | ...                            | ...                                    |

[Assistant]
From the results, the property ogc:sfContains is used to indicate that an entity is within the spatial boundary of Wellington City (osmrel:4266321).

To find streets within Wellington City:
- We look for OSM ways that are contained by osmrel:4266321 via ogc:sfContains.
- These ways should have the tag osmkey:highway (to indicate they are streets).
- We extract their names using osmkey:name.
- We ensure uniqueness of the names.

Let's write a SPARQL query to get the unique names of all OSM ways with a highway tag, contained within Wellington City, and having a name.

[Tool]
Got 3,779 rows and 1 column, showing the first 5 and last 5 rows below:
| name                                   |
| -------------------------------------- |
| 1                                      |
| 10                                     |
| 10A                                    |
| 10B                                    |
| 10C                                    |
| ...                                    |
| Zealandia - Chaytor Street (at Tunnel) |
| Zealandia - Northland Tunnel Road      |
| Zealandia Shuttle                      |
| Zetland Street                         |
| Zohrab Street                          |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The query correctly retrieves unique street names within Wellington City using the appropriate spatial containment and highway filters. However, it does not filter out non-street features that may have a 'highway' tag but are not actual streets (such as 'footway', 'cycleway', 'path', etc.), which can lead to irrelevant results. To improve accuracy, the query should restrict ?highwayType to typical street types (e.g., 'residential', 'primary', 'secondary', 'tertiary', 'unclassified', 'service', 'living_street', 'road', etc.). This refinement will ensure the list contains only actual street names.

[Assistant]
Thank you for the feedback. You are correct: the OSM "highway" tag covers a wide range of features, not just streets for vehicles, but also paths, footways, cycleways, etc. To focus on actual streets, we should restrict the ?highwayType to typical street values such as: 'residential', 'primary', 'secondary', 'tertiary', 'unclassified', 'service', 'living_street', and 'road'.

Let's refine the query by adding a VALUES clause to restrict ?highwayType to these street types.

Here is the improved query:

[Tool]
Got 1,955 rows and 1 column, showing the first 5 and last 5 rows below:
| name           |
| -------------- |
| 1              |
| 2              |
| 3              |
| 4              |
| 5              |
| ...            |
| Yule Street    |
| Zaida Way      |
| Zande Terrace  |
| Zetland Street |
| Zohrab Street  |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves all unique street names within Wellington City, New Zealand, by filtering for relevant highway types and ensuring the features are within the city boundary. The query returns only the identifiers (street names) as required, and does not include unnecessary labels or perform unsupported operations. The answer is complete and accurate for the user's request.


PREFIX osm2rdfkey: <https://osm2rdf.cs.uni-freiburg.de/rdf/key#>
SELECT ?osmNode ?wikidataId WHERE {
  ?osmNode osm2rdfkey:wikidata ?wikidataId .
}

The OSM-Planet knowledge graph contains information about OSM nodes and their links to Wikidata items (via the 'wikidata' tag), but it does not contain information about whether the corresponding Wikidata item has a reciprocal link back to the OSM node (such as via properties P8210, P8211, or P402 in Wikidata). This reciprocal information is only present in Wikidata, not in OSM-Planet. Therefore, it is not possible to answer the question using only the OSM-Planet knowledge graph.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
osm-planet at https://qlever.cs.uni-freiburg.de/api/osm-planet

You can use the following SPARQL prefixes implicitly in all functions:
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
ogc: <http://www.opengis.net/rdf#
osm2rdf: <https://osm2rdf.cs.uni-freiburg.de/rdf#
osm2rdfgeom: <https://osm2rdf.cs.uni-freiburg.de/rdf/geom#
osm2rdfkey: <https://osm2rdf.cs.uni-freiburg.de/rdf/key#
osm2rdfmember: <https://osm2rdf.cs.uni-freiburg.de/rdf/member#
osm: <https://www.openstreetmap.org/
osmkey: <https://www.openstreetmap.org/wiki/Key:
osmmeta: <https://www.openstreetmap.org/meta/
osmnode: <https://www.openstreetmap.org/node/
osmrel: <https://www.openstreetmap.org/relation/
osmway: <https://www.openstreetmap.org/way/
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
ps: <http://www.wikidata.org/prop/statement/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
wd: <http://www.wikidata.org/entity/
wdt: <http://www.wikidata.org/prop/direct/
xsd: <http://www.w3.org/2001/XMLSchema#
owl: <http://www.w3.org/2002/07/owl#
foaf: <http://xmlns.com/foaf/0.1/
skos: <http://www.w3.org/2004/02/skos/core#
dct: <http://purl.org/dc/terms/
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
schema: <http://schema.org/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
wikibase: <http://wikiba.se/ontology#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] Find OpenStreetMap nodes linked to a Wikidata item where the Wikidata item lacks a reciprocal link back to the OSM node.

[Assistant]
Let's break down the question:

1. We need to find OpenStreetMap (OSM) nodes that are linked to a Wikidata item. In OSM, this is typically done via a tag like wikidata=Qxxx.
2. For each such node, we need to check if the corresponding Wikidata item has a reciprocal link back to the OSM node. This would be a property in Wikidata (often "OpenStreetMap relation ID", "OpenStreetMap node ID", or "OpenStreetMap way ID" depending on the type) pointing back to the OSM node.
3. We want only those OSM nodes where the Wikidata item does NOT have such a reciprocal link.

Step 1: Find the property in OSM that links to Wikidata. This is likely osm2rdfkey:wikidata.

Step 2: For each node with a wikidata tag, get the value (the Wikidata Q-ID).

Step 3: Check if the Wikidata item has a property linking back to the OSM node. However, since we are querying only the OSM-Planet endpoint, we can only check the OSM side, not Wikidata's internal properties. But OSM-Planet may have imported some Wikidata properties.

Let me first check what properties are available for OSM nodes related to Wikidata and OSM IDs.

I'll start by searching for properties related to "wikidata" and "osm" to see what is available.

First, search for the property "wikidata".

[Tool]
Top 10 property alternatives:
1. wikidata (osm2rdfkey:wikidata)
2. wikidata (osmkey:wikidata)
3. description:wikidata (<https://osm2rdf.cs.uni-freiburg.de/rdf/key#description:wikidata>)
4. description:wikidata (<https://www.openstreetmap.org/wiki/Key:description:wikidata>)
5. about:wikidata (<https://www.openstreetmap.org/wiki/Key:about:wikidata>)
6. about:wikidata (<https://osm2rdf.cs.uni-freiburg.de/rdf/key#about:wikidata>)
7. related:wikidata (<https://www.openstreetmap.org/wiki/Key:related:wikidata>)
8. related:wikidata (<https://osm2rdf.cs.uni-freiburg.de/rdf/key#related:wikidata>)
9. content:wikidata (<https://www.openstreetmap.org/wiki/Key:content:wikidata>)
10. content:wikidata (<https://osm2rdf.cs.uni-freiburg.de/rdf/key#content:wikidata>)

[Assistant]
We have confirmed that the main property for linking OSM nodes to Wikidata is osm2rdfkey:wikidata (and also osmkey:wikidata, but osm2rdfkey:wikidata is the canonical one in this KG).

Now, for the reciprocal link: OSM nodes have unique IDs (e.g., node/123456). Wikidata has properties like "OpenStreetMap node ID" (P8210), "OpenStreetMap way ID" (P8211), and "OpenStreetMap relation ID" (P402). However, these are properties in Wikidata, not in OSM. The OSM-Planet KG may or may not have imported these reciprocal links.

Let me check if there are any properties in OSM-Planet that represent a Wikidata item's link back to an OSM node. I'll search for properties related to "osm" and "openstreetmap".

[Tool]
Top 10 property alternatives:
1. osm (osmkey:osm)
2. url:osm (<https://www.openstreetmap.org/wiki/Key:url:osm>)
3. note:osm (<https://www.openstreetmap.org/wiki/Key:note:osm>)
4. wiki:osm (<https://www.openstreetmap.org/wiki/Key:wiki:osm>)
5. osmwiki (osmkey:osmwiki)
6. website:map:osm (<https://www.openstreetmap.org/wiki/Key:website:map:osm>)
7. osm:note (<https://www.openstreetmap.org/wiki/Key:osm:note>)
8. osm_was_here (osmkey:osm_was_here)
9. osm_id (osmkey:osm_id)
10. osm_note (osmkey:osm_note)

[Tool]
Top 10 property alternatives:
1. website:map:osm (<https://www.openstreetmap.org/wiki/Key:website:map:osm>)
2. osm (osmkey:osm)
3. osmwiki (osmkey:osmwiki)
4. url:osm (<https://www.openstreetmap.org/wiki/Key:url:osm>)
5. note:osm (<https://www.openstreetmap.org/wiki/Key:note:osm>)
6. openstreetcam (osmkey:openstreetcam)
7. wiki:osm (<https://www.openstreetmap.org/wiki/Key:wiki:osm>)
8. url:map (<https://www.openstreetmap.org/wiki/Key:url:map>)
9. osm_was_here (osmkey:osm_was_here)
10. map:url (<https://www.openstreetmap.org/wiki/Key:map:url>)

[Tool]
Top 10 property alternatives:
1. related:wikidata (<https://www.openstreetmap.org/wiki/Key:related:wikidata>)
2. related:wikidata (<https://osm2rdf.cs.uni-freiburg.de/rdf/key#related:wikidata>)
3. wikidata (osm2rdfkey:wikidata)
4. wikidata (osmkey:wikidata)
5. proposed:operator:wikidata (<https://www.openstreetmap.org/wiki/Key:proposed:operator:wikidata>)
6. proposed:operator:wikidata (<https://osm2rdf.cs.uni-freiburg.de/rdf/key#proposed:operator:wikidata>)
7. type:wikidata (<https://www.openstreetmap.org/wiki/Key:type:wikidata>)
8. type:wikidata (<https://osm2rdf.cs.uni-freiburg.de/rdf/key#type:wikidata>)
9. description:wikidata (<https://osm2rdf.cs.uni-freiburg.de/rdf/key#description:wikidata>)
10. description:wikidata (<https://www.openstreetmap.org/wiki/Key:description:wikidata>)

[Assistant]
From the property searches, it appears that the OSM-Planet knowledge graph contains the OSM-to-Wikidata link (via osm2rdfkey:wikidata), but does not contain the reciprocal Wikidata-to-OSM link (such as P8210, P8211, or P402 from Wikidata). This is expected, as OSM-Planet is focused on OSM data, not Wikidata's internal properties.

Therefore, within the OSM-Planet KG alone, it is not possible to check whether the Wikidata item has a reciprocal link back to the OSM node, because that information is only present in Wikidata.

Thus, the query as requested cannot be fully answered using only the OSM-Planet knowledge graph. I will cancel and explain this limitation.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The system's explanation is correct: the OSM-Planet knowledge graph only contains information about OSM nodes and their links to Wikidata items, but does not contain data about whether the Wikidata item reciprocally links back to the OSM node. Therefore, it is not possible to answer the user's question using only the OSM-Planet knowledge graph. The attempted SPARQL query is appropriate for retrieving OSM nodes linked to Wikidata items, but cannot check for reciprocal links. No further refinement is possible given the data source.


PREFIX osmrel: <https://www.openstreetmap.org/relation/>
PREFIX ogc: <http://www.opengis.net/rdf#>
SELECT ?key ( COUNT( * ) AS ?count ) WHERE {
  osmrel:134591 ogc:sfContains ?element .
  ?element ?key ?value .
  FILTER ( STRSTARTS( STR( ?key ) , "https://www.openstreetmap.org/wiki/Key:" ) )
}
GROUP BY ?key
ORDER BY DESC ( ?count )
LIMIT 20

Got 20 rows and 2 columns, showing the first 5 and last 5 rows below:
| key                                                                      | count            |
| ------------------------------------------------------------------------ | ---------------- |
| building (osmkey:building)                                               | 217324 (xsd:int) |
| highway (osmkey:highway)                                                 | 121867 (xsd:int) |
| footway (osmkey:footway)                                                 | 44992 (xsd:int)  |
| name (osmkey:name)                                                       | 31013 (xsd:int)  |
| crossing (osmkey:crossing)                                               | 18430 (xsd:int)  |
| ...                                                                      | ...              |
| tiger:reviewed (<https://www.openstreetmap.org/wiki/Key:tiger:reviewed>) | 12153 (xsd:int)  |
| addr:postcode (<https://www.openstreetmap.org/wiki/Key:addr:postcode>)   | 11964 (xsd:int)  |
| addr:state (<https://www.openstreetmap.org/wiki/Key:addr:state>)         | 11590 (xsd:int)  |
| lanes (osmkey:lanes)                                                     | 10441 (xsd:int)  |
| oneway (osmkey:oneway)                                                   | 10166 (xsd:int)  |

This query finds the most frequently used OpenStreetMap keys (as properties with the osmkey: prefix) on elements within Detroit, using ogc:sfContains to select elements within Detroit. The results will show the top 20 keys and their usage counts.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
osm-planet at https://qlever.cs.uni-freiburg.de/api/osm-planet

You can use the following SPARQL prefixes implicitly in all functions:
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
ogc: <http://www.opengis.net/rdf#
osm2rdf: <https://osm2rdf.cs.uni-freiburg.de/rdf#
osm2rdfgeom: <https://osm2rdf.cs.uni-freiburg.de/rdf/geom#
osm2rdfkey: <https://osm2rdf.cs.uni-freiburg.de/rdf/key#
osm2rdfmember: <https://osm2rdf.cs.uni-freiburg.de/rdf/member#
osm: <https://www.openstreetmap.org/
osmkey: <https://www.openstreetmap.org/wiki/Key:
osmmeta: <https://www.openstreetmap.org/meta/
osmnode: <https://www.openstreetmap.org/node/
osmrel: <https://www.openstreetmap.org/relation/
osmway: <https://www.openstreetmap.org/way/
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
ps: <http://www.wikidata.org/prop/statement/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
wd: <http://www.wikidata.org/entity/
wdt: <http://www.wikidata.org/prop/direct/
xsd: <http://www.w3.org/2001/XMLSchema#
owl: <http://www.w3.org/2002/07/owl#
foaf: <http://xmlns.com/foaf/0.1/
skos: <http://www.w3.org/2004/02/skos/core#
dct: <http://purl.org/dc/terms/
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
schema: <http://schema.org/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
wikibase: <http://wikiba.se/ontology#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] Find the most frequently used OpenStreetMap keys on elements within Detroit.

[Assistant]
Let's break down the question:

1. We need to identify the area corresponding to Detroit.
2. For all OSM elements within Detroit, we want to find the keys (tags) used.
3. We need to count the frequency of each key and return the most frequently used ones.

Step 1: Find the entity for Detroit in OSM.
Step 2: Find how to get all elements within Detroit.
Step 3: Find how keys are represented in OSM RDF.
Step 4: Aggregate and count key usage.

Let's start by searching for "Detroit" in the OSM-Planet knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Detroit, also known as Detroit (osmnode:18994998)
2. Detroit, also known as Detroit (osmrel:134591)
3. Detroit, also known as Detroit (osmnode:153402739)
4. Detroit, also known as Detroit (osmrel:16849747)
5. Detroit (osmrel:186606)
6. Detroit (osmnode:151775539)
7. Detroit (osmrel:127012)
8. Detroit (osmnode:158858861)
9. Detroit (osmrel:12203917)
10. Detroit (osmnode:151501760)

[Assistant]
We have several entities for Detroit. The most likely candidate for the city boundary is a relation, commonly used for administrative boundaries in OSM. The top relation candidates are:

- osmrel:134591
- osmrel:186606
- osmrel:127012

Let's check which of these relations represents the administrative boundary for Detroit by listing their properties. I'll start with osmrel:134591.

[Tool]
Got 65,536 rows and 3 columns, showing the first 10 rows below:
| subject                 | property                       | object                                                             |
| ----------------------- | ------------------------------ | ------------------------------------------------------------------ |
| Detroit (osmrel:134591) | sf contains (ogc:sfContains)   | Detroit (osmnode:18994998)                                         |
| Detroit (osmrel:134591) | has centroid (geo:hasCentroid) | osm2rdfgeom:osm_area_centroid_269183                               |
| Detroit (osmrel:134591) | has geometry (geo:hasGeometry) | osm2rdfgeom:osm_relarea_134591                                     |
| Detroit (osmrel:134591) | sf contains (ogc:sfContains)   | McKinsey & Company (osmnode:6661096928)                            |
| Detroit (osmrel:134591) | sf contains (ogc:sfContains)   | Order of the Cannons Regular of the Holy Cross (osmnode:354028194) |
| Detroit (osmrel:134591) | sf contains (ogc:sfContains)   | Delray (osmnode:154292257)                                         |
| Detroit (osmrel:134591) | sf contains (ogc:sfContains)   | New Center (osmnode:5612651985)                                    |
| Detroit (osmrel:134591) | sf contains (ogc:sfContains)   | Fox Theatre (osmnode:6150469184)                                   |
| Detroit (osmrel:134591) | sf contains (ogc:sfContains)   | Indian Village (osmnode:1282269991)                                |
| Detroit (osmrel:134591) | sf contains (ogc:sfContains)   | Detroit (osmnode:7002689053)                                       |
| ...                     | ...                            | ...                                                                |

[Assistant]
osmrel:134591 appears to be the correct relation for the Detroit administrative boundary, as it contains many nodes and has a geometry.

Next, we need to find all elements (nodes, ways, relations) within Detroit. The property ogc:sfContains seems to relate the Detroit relation to contained elements.

Now, let's determine how OSM keys (tags) are represented in RDF. I'll search for properties related to "key".

[Tool]
Top 10 property alternatives:
1. key (osmkey:KEY)
2. key (osmkey:key)
3. note:keys (<https://www.openstreetmap.org/wiki/Key:note:keys>)
4. keys (osmkey:keys)
5. source:pkey (<https://www.openstreetmap.org/wiki/Key:source:pkey>)
6. source:note (<https://www.openstreetmap.org/wiki/Key:source:note>)
7. access:key (<https://www.openstreetmap.org/wiki/Key:access:key>)
8. source:title (<https://www.openstreetmap.org/wiki/Key:source:title>)
9. note:source:note (<https://www.openstreetmap.org/wiki/Key:note:source:note>)
10. source:note:type (<https://www.openstreetmap.org/wiki/Key:source:note:type>)

[Tool]
Got 58 rows and 3 columns, showing the first 10 rows below:
| subject                    | property                         | object                                              |
| -------------------------- | -------------------------------- | --------------------------------------------------- |
| Detroit (osmnode:18994998) | sf intersects (ogc:sfIntersects) | United States (osmrel:148838)                       |
| Detroit (osmnode:18994998) | type (rdf:type)                  | osm:node                                            |
| Detroit (osmnode:18994998) | facts (osm2rdf:facts)            | 35 (xsd:int)                                        |
| Detroit (osmnode:18994998) | changeset (osmmeta:changeset)    | <https://www.openstreetmap.org/changeset/151282261> |
| Detroit (osmnode:18994998) | timestamp (osmmeta:timestamp)    | 2024-05-13T19:12:58 (xsd:dateTime)                  |
| Detroit (osmnode:18994998) | version (osmmeta:version)        | 54 (xsd:int)                                        |
| Detroit (osmnode:18994998) | uid (osmmeta:uid)                | 4515353 (xsd:int)                                   |
| Detroit (osmnode:18994998) | user (osmmeta:user)              | quincylvania                                        |
| Detroit (osmnode:18994998) | has centroid (geo:hasCentroid)   | osm2rdfgeom:osm_node_centroid_18994998              |
| Detroit (osmnode:18994998) | has geometry (geo:hasGeometry)   | osm2rdfgeom:osm_node_18994998                       |
| ...                        | ...                              | ...                                                 |

[Tool]
Got 33 rows and 3 columns, showing the first 10 rows below:
| subject            | property         | object                                    |
| ------------------ | ---------------- | ----------------------------------------- |
| osmnode:6281974999 | key (osmkey:KEY) | uuid:9d4d1623-0121-46ee-a881-47466f57ab31 |
| osmnode:6284878498 | key (osmkey:KEY) | uuid:f441feac-8a8c-426b-b601-53610e0ce0e2 |
| osmnode:6284950986 | key (osmkey:KEY) | uuid:f9967dd4-c230-45e0-9315-3898f636eab8 |
| osmnode:6284950987 | key (osmkey:KEY) | uuid:52e37f44-001f-4be1-9cb1-28801af2d68f |
| osmnode:6285040780 | key (osmkey:KEY) | uuid:32906f94-329d-42c4-ae3a-f1d99e220e43 |
| osmnode:6292362637 | key (osmkey:KEY) | uuid:e90baf30-14fc-4607-9aba-a84222e79a6c |
| osmnode:6394264655 | key (osmkey:KEY) | uuid:367a9715-e36c-4366-b9d8-b5f777a6b62c |
| osmnode:6403157178 | key (osmkey:KEY) | uuid:89f57abb-b6de-4bad-af71-c5c03ac2ebf9 |
| osmnode:6403157179 | key (osmkey:KEY) | uuid:3df2af3d-c623-4dbc-9e23-eb9286bd6d1f |
| osmnode:6403157181 | key (osmkey:KEY) | uuid:84d07dd4-d453-418c-ba21-2cc020273770 |
| ...                | ...              | ...                                       |

[Tool]
Got 1,223 rows and 3 columns, showing the first 10 rows below:
| subject                                       | property         | object                 |
| --------------------------------------------- | ---------------- | ---------------------- |
| Гагаринский старт (osmway:172571408)          | key (osmkey:key) | Pad 1                  |
| Hreðavatn (osmrel:69068)                      | key (osmkey:key) | Hreðavatn              |
| Srimushnam (osmnode:891394186)                | key (osmkey:key) | Boovaraha swami Temple |
| بھوانہ (osmnode:1029602169)                   | key (osmkey:key) | Bhawana,Bhowana        |
| Besant Nagar (osmnode:249497705)              | key (osmkey:key) | 600090                 |
| Santhome (osmnode:247689726)                  | key (osmkey:key) | 600004                 |
| Albanova (osmnode:25399516)                   | key (osmkey:key) | 0003                   |
| Fontaine Ardente (osmnode:748776326)          | key (osmkey:key) | natural                |
| Ratzeburger Ruderclub e.V. (osmway:193139849) | key (osmkey:key) | club                   |
| Williams Fieldhouse (osmway:103552323)        | key (osmkey:key) | UW Platteville         |
| ...                                           | ...              | ...                    |

[Tool] Got no rows and 3 columns

[Tool]
Top 10 property alternatives:
1. tag (osmkey:Tag)
2. tag (osmkey:TAG)
3. tag (osm:tag)
4. tag (osmkey:tag)
5. name:tag (<https://www.openstreetmap.org/wiki/Key:name:TAG>)
6. name:tag (<https://www.openstreetmap.org/wiki/Key:name:tag>)
7. source:tags (<https://www.openstreetmap.org/wiki/Key:source:tags>)
8. general_tag (osmkey:general_tag)
9. ol_tag (osmkey:ol_tag)
10. graffiti:tag (<https://www.openstreetmap.org/wiki/Key:graffiti:tag>)

[Tool]
Got 173 rows and 3 columns, showing the first 10 rows below:
| subject                                  | property      | object          |
| ---------------------------------------- | ------------- | --------------- |
| Nové Město (osmnode:1601422877)          | tag (osm:tag) | _:bn8746510630  |
| Lenné-Haus (osmway:68809451)             | tag (osm:tag) | _:bn9891947755  |
| osmnode:12250833129                      | tag (osm:tag) | _:bn3976131635  |
| osmnode:7230110859                       | tag (osm:tag) | _:bn5570723535  |
| osmnode:7232223917                       | tag (osm:tag) | _:bn11088636251 |
| avenue H. Bourguiba (osmnode:7241834376) | tag (osm:tag) | _:bn0           |
| maghreb arabi (osmnode:7241895717)       | tag (osm:tag) | _:bn4772219331  |
| cité el arfaouin (osmnode:7241912272)    | tag (osm:tag) | _:bn7964774182  |
| Rue Ben Aziza (osmnode:7241921343)       | tag (osm:tag) | _:bn6370535062  |
| osmnode:7241948056                       | tag (osm:tag) | _:bn3180102655  |
| ...                                      | ...           | ...             |

[Tool]
Got 10 rows and 3 columns:
| subject                                        | property         | object                       |
| ---------------------------------------------- | ---------------- | ---------------------------- |
| Panchos Tacos and Pizza (osmnode:10718979690)  | tag (osmkey:Tag) | Restaurant                   |
| Centre Aéré ALSH Langlade (osmnode:6551360133) | tag (osmkey:Tag) | Description                  |
| Raemor Mansions (osmnode:8069047906)           | tag (osmkey:Tag) | Hatfield Digital Twin City   |
| osmnode:9269987865                             | tag (osmkey:Tag) | Building Restoration Service |
| OmniCare PTE Ltd (osmnode:9406387681)          | tag (osmkey:Tag) | OmniCare Suva                |
| Avenida C (osmway:673522728)                   | tag (osmkey:Tag) | bridge                       |
| osmway:96455567                                | tag (osmkey:Tag) | Yellow tag                   |
| Avenida Tiradentes (osmway:673522730)          | tag (osmkey:Tag) | bridge                       |
| Avenida C (osmway:751932055)                   | tag (osmkey:Tag) | bridge                       |
| Avenida C (osmway:751932056)                   | tag (osmkey:Tag) | bridge                       |

[Tool]
Got 5 rows and 3 columns:
| subject                                      | property           | object |
| -------------------------------------------- | ------------------ | ------ |
| osmnode:1470907954                           | keys (osmkey:keys) | yes    |
| osmnode:9768683850                           | keys (osmkey:keys) | 88     |
| Cordonnerie clés minute (osmnode:2329961778) | keys (osmkey:keys) | yes    |
| Clé Express (osmnode:3497083691)             | keys (osmkey:keys) | yes    |
| osmnode:6340679166                           | keys (osmkey:keys) | yes    |

[Tool]
Top 10 property alternatives:
1. access:key (<https://www.openstreetmap.org/wiki/Key:access:key>)
2. note:keys (<https://www.openstreetmap.org/wiki/Key:note:keys>)
3. keys (osmkey:keys)
4. mykey (osmkey:mykey)
5. key_needed (osmkey:key_needed)
6. locked:key (<https://www.openstreetmap.org/wiki/Key:locked:key>)
7. source:pkey (<https://www.openstreetmap.org/wiki/Key:source:pkey>)
8. kapor2:key (<https://www.openstreetmap.org/wiki/Key:kapor2:key>)
9. key_info (osmkey:key_info)
10. street_cabinet:key (<https://www.openstreetmap.org/wiki/Key:street_cabinet:key>)

[Assistant]
It appears that OSM keys are not represented as a single property, but rather as individual properties for each key, such as osmkey:name, osmkey:highway, etc. This means that to count the most frequently used keys, we need to count the frequency of each property with the osmkey: prefix on elements within Detroit.

To do this, we need to:
1. Get all elements contained within osmrel:134591 (Detroit).
2. For each element, get all properties with the osmkey: prefix.
3. Count the frequency of each property.

Let's first check what properties are used on a sample node within Detroit to confirm this pattern.

[Tool]
Got 58 rows and 3 columns, showing the first 10 rows below:
| subject                    | property                         | object                                              |
| -------------------------- | -------------------------------- | --------------------------------------------------- |
| Detroit (osmnode:18994998) | sf intersects (ogc:sfIntersects) | United States (osmrel:148838)                       |
| Detroit (osmnode:18994998) | type (rdf:type)                  | osm:node                                            |
| Detroit (osmnode:18994998) | facts (osm2rdf:facts)            | 35 (xsd:int)                                        |
| Detroit (osmnode:18994998) | changeset (osmmeta:changeset)    | <https://www.openstreetmap.org/changeset/151282261> |
| Detroit (osmnode:18994998) | timestamp (osmmeta:timestamp)    | 2024-05-13T19:12:58 (xsd:dateTime)                  |
| Detroit (osmnode:18994998) | version (osmmeta:version)        | 54 (xsd:int)                                        |
| Detroit (osmnode:18994998) | uid (osmmeta:uid)                | 4515353 (xsd:int)                                   |
| Detroit (osmnode:18994998) | user (osmmeta:user)              | quincylvania                                        |
| Detroit (osmnode:18994998) | has centroid (geo:hasCentroid)   | osm2rdfgeom:osm_node_centroid_18994998              |
| Detroit (osmnode:18994998) | has geometry (geo:hasGeometry)   | osm2rdfgeom:osm_node_18994998                       |
| ...                        | ...                              | ...                                                 |

[Tool]
Got 39 rows and 3 columns, showing the first 10 rows below:
| subject                      | property                         | object                                              |
| ---------------------------- | -------------------------------- | --------------------------------------------------- |
| Detroit (osmnode:7002689053) | sf intersects (ogc:sfIntersects) | United States (osmrel:148838)                       |
| Detroit (osmnode:7002689053) | type (rdf:type)                  | osm:node                                            |
| Detroit (osmnode:7002689053) | facts (osm2rdf:facts)            | 18 (xsd:int)                                        |
| Detroit (osmnode:7002689053) | changeset (osmmeta:changeset)    | <https://www.openstreetmap.org/changeset/143310426> |
| Detroit (osmnode:7002689053) | timestamp (osmmeta:timestamp)    | 2023-10-29T13:35:46 (xsd:dateTime)                  |
| Detroit (osmnode:7002689053) | version (osmmeta:version)        | 7 (xsd:int)                                         |
| Detroit (osmnode:7002689053) | uid (osmmeta:uid)                | 17561309 (xsd:int)                                  |
| Detroit (osmnode:7002689053) | user (osmmeta:user)              | Lucas Brandt                                        |
| Detroit (osmnode:7002689053) | has centroid (geo:hasCentroid)   | osm2rdfgeom:osm_node_centroid_7002689053            |
| Detroit (osmnode:7002689053) | has geometry (geo:hasGeometry)   | osm2rdfgeom:osm_node_7002689053                     |
| ...                          | ...                              | ...                                                 |

[Tool]
Got 39 rows and 3 columns, showing the first 10 rows below:
| subject                      | property                         | object                                              |
| ---------------------------- | -------------------------------- | --------------------------------------------------- |
| Detroit (osmnode:7002689053) | sf intersects (ogc:sfIntersects) | United States (osmrel:148838)                       |
| Detroit (osmnode:7002689053) | type (rdf:type)                  | osm:node                                            |
| Detroit (osmnode:7002689053) | facts (osm2rdf:facts)            | 18 (xsd:int)                                        |
| Detroit (osmnode:7002689053) | changeset (osmmeta:changeset)    | <https://www.openstreetmap.org/changeset/143310426> |
| Detroit (osmnode:7002689053) | timestamp (osmmeta:timestamp)    | 2023-10-29T13:35:46 (xsd:dateTime)                  |
| Detroit (osmnode:7002689053) | version (osmmeta:version)        | 7 (xsd:int)                                         |
| Detroit (osmnode:7002689053) | uid (osmmeta:uid)                | 17561309 (xsd:int)                                  |
| Detroit (osmnode:7002689053) | user (osmmeta:user)              | Lucas Brandt                                        |
| Detroit (osmnode:7002689053) | has centroid (geo:hasCentroid)   | osm2rdfgeom:osm_node_centroid_7002689053            |
| Detroit (osmnode:7002689053) | has geometry (geo:hasGeometry)   | osm2rdfgeom:osm_node_7002689053                     |
| ...                          | ...                              | ...                                                 |

[Tool]
Got 39 rows and 3 columns, showing the first 10 rows below:
| subject                      | property                         | object                                              |
| ---------------------------- | -------------------------------- | --------------------------------------------------- |
| Detroit (osmnode:7002689053) | sf intersects (ogc:sfIntersects) | United States (osmrel:148838)                       |
| Detroit (osmnode:7002689053) | type (rdf:type)                  | osm:node                                            |
| Detroit (osmnode:7002689053) | facts (osm2rdf:facts)            | 18 (xsd:int)                                        |
| Detroit (osmnode:7002689053) | changeset (osmmeta:changeset)    | <https://www.openstreetmap.org/changeset/143310426> |
| Detroit (osmnode:7002689053) | timestamp (osmmeta:timestamp)    | 2023-10-29T13:35:46 (xsd:dateTime)                  |
| Detroit (osmnode:7002689053) | version (osmmeta:version)        | 7 (xsd:int)                                         |
| Detroit (osmnode:7002689053) | uid (osmmeta:uid)                | 17561309 (xsd:int)                                  |
| Detroit (osmnode:7002689053) | user (osmmeta:user)              | Lucas Brandt                                        |
| Detroit (osmnode:7002689053) | has centroid (geo:hasCentroid)   | osm2rdfgeom:osm_node_centroid_7002689053            |
| Detroit (osmnode:7002689053) | has geometry (geo:hasGeometry)   | osm2rdfgeom:osm_node_7002689053                     |
| ...                          | ...                              | ...                                                 |

[Assistant]
It seems that the properties for OSM tags are not directly visible in the sample nodes, but based on OSM RDF conventions, tags are typically represented as properties with the osmkey: prefix (e.g., osmkey:name, osmkey:highway, etc.).

Given this, the best approach is:
- For all elements contained in osmrel:134591 (Detroit), count the frequency of each property with the osmkey: prefix.

Let's construct a SPARQL query that:
1. Finds all elements contained in osmrel:134591 using ogc:sfWithin or ogc:sfContains.
2. For each element, finds all properties with the osmkey: prefix.
3. Groups by property and counts occurrences.
4. Orders by count descending.

Here's the SPARQL query.

[Tool] Stopped generation process

[User]
Feedback (status=retry):
The query is well-structured for counting key usage within Detroit, but the execution result returned no rows, indicating that either the spatial containment triple (?element ogc:sfWithin osmrel:134591) is not matching any elements, or the keys are not represented as properties with the expected prefix in this knowledge graph.

Suggestions:
1. Verify that 'ogc:sfWithin' is the correct property for spatial containment in this dataset. If not, try using other spatial or location-based properties.
2. Check if 'osmrel:134591' is the correct identifier for Detroit and is used in the relevant triples.
3. Confirm that keys are indeed represented as properties with the 'https://www.openstreetmap.org/wiki/Key:' prefix in this dataset, or if they are modelled differently (e.g., as key-value pairs or tags).
4. Consider querying for elements within Detroit first, then inspecting their properties to adjust the query accordingly.

The query needs to be reworked based on the actual data structure in the knowledge graph.

[Assistant]
Thank you for the feedback. Let's address the suggestions step by step:

1. Verify spatial containment: In the previous exploration, we saw that osmrel:134591 (Detroit) uses ogc:sfContains to relate to contained elements. So, instead of ogc:sfWithin, we should use ogc:sfContains with Detroit as the subject.
2. Confirm Detroit's identifier: osmrel:134591 is correct.
3. Check how keys/tags are represented: Previous listings suggest that tags may be represented as properties with the osmkey: prefix (e.g., osmkey:name, osmkey:highway, etc.), but let's confirm this by listing properties for a few elements contained in Detroit.
4. Query for elements within Detroit and inspect their properties.

Let's start by listing a few elements that Detroit (osmrel:134591) ogc:sfContains, and then inspect their properties.

[Tool]
Got 65,536 rows and 3 columns, showing the first 10 rows below:
| subject                 | property                     | object                                                             |
| ----------------------- | ---------------------------- | ------------------------------------------------------------------ |
| Detroit (osmrel:134591) | sf contains (ogc:sfContains) | Detroit (osmnode:18994998)                                         |
| Detroit (osmrel:134591) | sf contains (ogc:sfContains) | McKinsey & Company (osmnode:6661096928)                            |
| Detroit (osmrel:134591) | sf contains (ogc:sfContains) | Order of the Cannons Regular of the Holy Cross (osmnode:354028194) |
| Detroit (osmrel:134591) | sf contains (ogc:sfContains) | Delray (osmnode:154292257)                                         |
| Detroit (osmrel:134591) | sf contains (ogc:sfContains) | New Center (osmnode:5612651985)                                    |
| Detroit (osmrel:134591) | sf contains (ogc:sfContains) | Fox Theatre (osmnode:6150469184)                                   |
| Detroit (osmrel:134591) | sf contains (ogc:sfContains) | Indian Village (osmnode:1282269991)                                |
| Detroit (osmrel:134591) | sf contains (ogc:sfContains) | Detroit (osmnode:7002689053)                                       |
| Detroit (osmrel:134591) | sf contains (ogc:sfContains) | Detroit Police Department HQ (osmnode:2365997488)                  |
| Detroit (osmrel:134591) | sf contains (ogc:sfContains) | Brewster Homes (osmnode:2924126430)                                |
| ...                     | ...                          | ...                                                                |

[Tool]
Got 38 rows and 3 columns, showing the first 10 rows below:
| subject                                 | property                         | object                                              |
| --------------------------------------- | -------------------------------- | --------------------------------------------------- |
| McKinsey & Company (osmnode:6661096928) | sf intersects (ogc:sfIntersects) | United States (osmrel:148838)                       |
| McKinsey & Company (osmnode:6661096928) | type (rdf:type)                  | osm:node                                            |
| McKinsey & Company (osmnode:6661096928) | facts (osm2rdf:facts)            | 12 (xsd:int)                                        |
| McKinsey & Company (osmnode:6661096928) | changeset (osmmeta:changeset)    | <https://www.openstreetmap.org/changeset/132465481> |
| McKinsey & Company (osmnode:6661096928) | timestamp (osmmeta:timestamp)    | 2023-02-12T22:44:47 (xsd:dateTime)                  |
| McKinsey & Company (osmnode:6661096928) | version (osmmeta:version)        | 2 (xsd:int)                                         |
| McKinsey & Company (osmnode:6661096928) | uid (osmmeta:uid)                | 11548585 (xsd:int)                                  |
| McKinsey & Company (osmnode:6661096928) | user (osmmeta:user)              | emersonveenstra                                     |
| McKinsey & Company (osmnode:6661096928) | has centroid (geo:hasCentroid)   | osm2rdfgeom:osm_node_centroid_6661096928            |
| McKinsey & Company (osmnode:6661096928) | has geometry (geo:hasGeometry)   | osm2rdfgeom:osm_node_6661096928                     |
| ...                                     | ...                              | ...                                                 |

[Tool]
Got 36 rows and 3 columns, showing the first 10 rows below:
| subject                                                            | property                         | object                                              |
| ------------------------------------------------------------------ | -------------------------------- | --------------------------------------------------- |
| Order of the Cannons Regular of the Holy Cross (osmnode:354028194) | sf intersects (ogc:sfIntersects) | United States (osmrel:148838)                       |
| Order of the Cannons Regular of the Holy Cross (osmnode:354028194) | type (rdf:type)                  | osm:node                                            |
| Order of the Cannons Regular of the Holy Cross (osmnode:354028194) | facts (osm2rdf:facts)            | 14 (xsd:int)                                        |
| Order of the Cannons Regular of the Holy Cross (osmnode:354028194) | changeset (osmmeta:changeset)    | <https://www.openstreetmap.org/changeset/155208301> |
| Order of the Cannons Regular of the Holy Cross (osmnode:354028194) | timestamp (osmmeta:timestamp)    | 2024-08-13T18:05:42 (xsd:dateTime)                  |
| Order of the Cannons Regular of the Holy Cross (osmnode:354028194) | version (osmmeta:version)        | 4 (xsd:int)                                         |
| Order of the Cannons Regular of the Holy Cross (osmnode:354028194) | uid (osmmeta:uid)                | 3199858 (xsd:int)                                   |
| Order of the Cannons Regular of the Holy Cross (osmnode:354028194) | user (osmmeta:user)              | Mateusz Konieczny - bot account                     |
| Order of the Cannons Regular of the Holy Cross (osmnode:354028194) | has centroid (geo:hasCentroid)   | osm2rdfgeom:osm_node_centroid_354028194             |
| Order of the Cannons Regular of the Holy Cross (osmnode:354028194) | has geometry (geo:hasGeometry)   | osm2rdfgeom:osm_node_354028194                      |
| ...                                                                | ...                              | ...                                                 |

[Tool]
Got 24 rows and 3 columns, showing the first 10 rows below:
| subject                         | property                         | object                                              |
| ------------------------------- | -------------------------------- | --------------------------------------------------- |
| New Center (osmnode:5612651985) | sf intersects (ogc:sfIntersects) | United States (osmrel:148838)                       |
| New Center (osmnode:5612651985) | type (rdf:type)                  | osm:node                                            |
| New Center (osmnode:5612651985) | facts (osm2rdf:facts)            | 4 (xsd:int)                                         |
| New Center (osmnode:5612651985) | changeset (osmmeta:changeset)    | <https://www.openstreetmap.org/changeset/119928147> |
| New Center (osmnode:5612651985) | timestamp (osmmeta:timestamp)    | 2022-04-19T23:39:22 (xsd:dateTime)                  |
| New Center (osmnode:5612651985) | version (osmmeta:version)        | 3 (xsd:int)                                         |
| New Center (osmnode:5612651985) | uid (osmmeta:uid)                | 1796825 (xsd:int)                                   |
| New Center (osmnode:5612651985) | user (osmmeta:user)              | mapper175                                           |
| New Center (osmnode:5612651985) | has centroid (geo:hasCentroid)   | osm2rdfgeom:osm_node_centroid_5612651985            |
| New Center (osmnode:5612651985) | has geometry (geo:hasGeometry)   | osm2rdfgeom:osm_node_5612651985                     |
| ...                             | ...                              | ...                                                 |

[Assistant]
From the property listings for several nodes within Detroit, we do not see any properties with the osmkey: prefix or any obvious key-value tag representation. This suggests that OSM tags might be represented differently in this dataset.

Let's try a different approach:
- List all properties for one of these nodes, but focus on the property names to see if any match common OSM tags (like "name", "highway", "amenity", etc.), even if not prefixed.
- Alternatively, search for all properties used in the dataset to see if common OSM keys appear as properties.

Let's search for all properties in the dataset to see if OSM keys are represented as direct properties (e.g., osmkey:name, osmkey:highway, etc.).

[Tool]
Top 10 property alternatives:
1. ναμε (<https://www.openstreetmap.org/wiki/Key:ναμε>)
2. name_ (osmkey:name_)
3. _name_ (osmkey:_NAME_)
4. name: (<https://www.openstreetmap.org/wiki/Key:name:>)
5. name (osmkey:name)
6. source:name (<https://www.openstreetmap.org/wiki/Key:source:name>)
7. description:name (<https://www.openstreetmap.org/wiki/Key:description:name>)
8. location:name (<https://www.openstreetmap.org/wiki/Key:location:name>)
9. person:name (<https://www.openstreetmap.org/wiki/Key:person:name>)
10. link:name (<https://www.openstreetmap.org/wiki/Key:link:name>)

[Tool]
Got 65,536 rows and 3 columns, showing the first 10 rows below:
| subject                                   | property           | object              |
| ----------------------------------------- | ------------------ | ------------------- |
| Leicester (osmnode:10021976)              | name (osmkey:name) | Leicester           |
| Galați (osmnode:100035698)                | name (osmkey:name) | Galați              |
| Candi Prambanan (osmnode:10020006010)     | name (osmkey:name) | Candi Prambanan     |
| Terminalia catappa (osmnode:10006546510)  | name (osmkey:name) | Terminalia catappa  |
| وادي حلفا (osmnode:100013911)             | name (osmkey:name) | وادي حلفا           |
| Baterno (osmnode:1002095355)              | name (osmkey:name) | Baterno             |
| M60 (osmnode:10001289048)                 | name (osmkey:name) | M60                 |
| Loughborough (osmnode:10021975)           | name (osmkey:name) | Loughborough        |
| Bodman-Ludwigshafen (osmnode:10006131742) | name (osmkey:name) | Bodman-Ludwigshafen |
| Haines City (osmnode:100062095)           | name (osmkey:name) | Haines City         |
| ...                                       | ...                | ...                 |

[Tool]
Top 10 property alternatives:
1. highway (osmkey:highway)
2. area:highway (<https://www.openstreetmap.org/wiki/Key:area:highway>)
3. description:highway (<https://www.openstreetmap.org/wiki/Key:description:highway>)
4. place:highway (<https://www.openstreetmap.org/wiki/Key:place:highway>)
5. outdoor:highway (<https://www.openstreetmap.org/wiki/Key:outdoor:highway>)
6. way:highway (<https://www.openstreetmap.org/wiki/Key:way:highway>)
7. ref:highway (<https://www.openstreetmap.org/wiki/Key:ref:highway>)
8. name:highway (<https://www.openstreetmap.org/wiki/Key:name:highway>)
9. was:highway (<https://www.openstreetmap.org/wiki/Key:was:highway>)
10. was:area:highway (<https://www.openstreetmap.org/wiki/Key:was:area:highway>)

[Tool]
Failed to list triples with error:
Tried to allocate 4.1 GB, but only 3.6 GB were available. Clear the cache or allow more memory for QLever during startup

[Tool]
Top 10 property alternatives:
1. _amenity (osmkey:_amenity)
2. amenity (osmkey:amenity)
3. amenity (osmkey:Amenity)
4. description:amenity (<https://www.openstreetmap.org/wiki/Key:description:amenity>)
5. source:amenity (<https://www.openstreetmap.org/wiki/Key:source:amenity>)
6. was:amenity (<https://www.openstreetmap.org/wiki/Key:was:amenity>)
7. informal:amenity (<https://www.openstreetmap.org/wiki/Key:informal:amenity>)
8. amenity:-2019 (<https://www.openstreetmap.org/wiki/Key:amenity:-2019>)
9. amenity2 (osmkey:amenity2)
10. amenity_1 (osmkey:amenity_1)

[Assistant]
We have confirmed that OSM keys like name, highway, and amenity are represented as properties with the osmkey: prefix (e.g., osmkey:name, osmkey:highway, osmkey:amenity).

Given the memory error when listing all osmkey:highway triples, we should limit our queries to elements within Detroit.

Let's try a SPARQL query that:
- Gets all elements that Detroit (osmrel:134591) ogc:sfContains.
- For each element, gets all properties with the osmkey: prefix.
- Groups by property and counts occurrences.

We will use ?element as the object of ogc:sfContains, and then for each ?element, count the osmkey:* properties.

Here's the revised query:

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly identifies the most frequently used OpenStreetMap keys on elements within Detroit by counting the occurrences of properties with the osmkey: prefix on elements contained within the Detroit relation. The query groups by key, orders by count, and limits the results to the top 20, which matches the user's request. The answer is complete and follows all specified rules.


PREFIX osmkey: <https://www.openstreetmap.org/wiki/Key:>
SELECT ?office ?name WHERE {
  ?office osmkey:office "newspaper" .
  ?office osmkey:name ?name .
}

Got 6,444 rows and 2 columns, showing the first 5 and last 5 rows below:
| office                                           | name                       |
| ------------------------------------------------ | -------------------------- |
| Waldeckische Landeszeitung (osmnode:10006003804) | Waldeckische Landeszeitung |
| Payson Roundup (osmnode:10006740959)             | Payson Roundup             |
| Ema (osmnode:10012737037)                        | Ema                        |
| SCOP L'Âge de Faire (osmnode:10021541813)        | SCOP L'Âge de Faire        |
| جريدة تشرين (osmnode:10024250880)                | جريدة تشرين                |
| ...                                              | ...                        |
| Casa del Periodista (osmway:988460607)           | Casa del Periodista        |
| Типография (osmway:99453269)                     | Типография                 |
| Fort Frances Times (osmway:995913571)            | Fort Frances Times         |
| Herald Journal (osmway:998724117)                | Herald Journal             |
| Leipziger Volkszeitung (osmway:99873803)         | Leipziger Volkszeitung     |

All named newspaper offices globally can be found by selecting entities with office=newspaper and a name tag. The query returns their OSM IRIs and names.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
osm-planet at https://qlever.cs.uni-freiburg.de/api/osm-planet

You can use the following SPARQL prefixes implicitly in all functions:
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
ogc: <http://www.opengis.net/rdf#
osm2rdf: <https://osm2rdf.cs.uni-freiburg.de/rdf#
osm2rdfgeom: <https://osm2rdf.cs.uni-freiburg.de/rdf/geom#
osm2rdfkey: <https://osm2rdf.cs.uni-freiburg.de/rdf/key#
osm2rdfmember: <https://osm2rdf.cs.uni-freiburg.de/rdf/member#
osm: <https://www.openstreetmap.org/
osmkey: <https://www.openstreetmap.org/wiki/Key:
osmmeta: <https://www.openstreetmap.org/meta/
osmnode: <https://www.openstreetmap.org/node/
osmrel: <https://www.openstreetmap.org/relation/
osmway: <https://www.openstreetmap.org/way/
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
ps: <http://www.wikidata.org/prop/statement/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
wd: <http://www.wikidata.org/entity/
wdt: <http://www.wikidata.org/prop/direct/
xsd: <http://www.w3.org/2001/XMLSchema#
owl: <http://www.w3.org/2002/07/owl#
foaf: <http://xmlns.com/foaf/0.1/
skos: <http://www.w3.org/2004/02/skos/core#
dct: <http://purl.org/dc/terms/
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
schema: <http://schema.org/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
wikibase: <http://wikiba.se/ontology#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] Find all named newspaper offices globally.

[Assistant]
Let's break down the question:

1. We are looking for all newspaper offices globally.
2. We want only those that are "named" (i.e., have a name).
3. The entities of interest are "newspaper offices" in OpenStreetMap.

Step 1: Identify how newspaper offices are tagged in OSM. Commonly, OSM uses tags like office=newspaper or amenity=newspaper.

Step 2: We need to find entities with such tags and that also have a name (usually tagged as name=*).

Step 3: We will retrieve their IRIs and optionally their names.

Let's first search for the property or tag used for "office" and "newspaper" in OSM.

[Tool]
Top 10 property alternatives:
1. office (osmkey:office)
2. name:office (<https://www.openstreetmap.org/wiki/Key:name:office>)
3. right:office (<https://www.openstreetmap.org/wiki/Key:right:office>)
4. was:office (<https://www.openstreetmap.org/wiki/Key:was:office>)
5. offices (osmkey:offices)
6. old:office (<https://www.openstreetmap.org/wiki/Key:old:office>)
7. source:office (<https://www.openstreetmap.org/wiki/Key:source:office>)
8. contact:office (<https://www.openstreetmap.org/wiki/Key:contact:office>)
9. note:office (<https://www.openstreetmap.org/wiki/Key:note:office>)
10. left:office (<https://www.openstreetmap.org/wiki/Key:left:office>)

[Tool]
No entity items found

No other items found

Top 10 literal alternatives:
1. newspaper
2. newspaper;company

[Tool]
Top 10 property alternatives:
1. ναμε (<https://www.openstreetmap.org/wiki/Key:ναμε>)
2. name_ (osmkey:name_)
3. _name_ (osmkey:_NAME_)
4. name: (<https://www.openstreetmap.org/wiki/Key:name:>)
5. name (osmkey:name)
6. source:name (<https://www.openstreetmap.org/wiki/Key:source:name>)
7. description:name (<https://www.openstreetmap.org/wiki/Key:description:name>)
8. location:name (<https://www.openstreetmap.org/wiki/Key:location:name>)
9. person:name (<https://www.openstreetmap.org/wiki/Key:person:name>)
10. link:name (<https://www.openstreetmap.org/wiki/Key:link:name>)

[Tool]
Got 6,444 rows and 2 columns, showing the first 5 and last 5 rows below:
| office                                           | name                       |
| ------------------------------------------------ | -------------------------- |
| Waldeckische Landeszeitung (osmnode:10006003804) | Waldeckische Landeszeitung |
| Payson Roundup (osmnode:10006740959)             | Payson Roundup             |
| Ema (osmnode:10012737037)                        | Ema                        |
| SCOP L'Âge de Faire (osmnode:10021541813)        | SCOP L'Âge de Faire        |
| جريدة تشرين (osmnode:10024250880)                | جريدة تشرين                |
| ...                                              | ...                        |
| Casa del Periodista (osmway:988460607)           | Casa del Periodista        |
| Типография (osmway:99453269)                     | Типография                 |
| Fort Frances Times (osmway:995913571)            | Fort Frances Times         |
| Herald Journal (osmway:998724117)                | Herald Journal             |
| Leipziger Volkszeitung (osmway:99873803)         | Leipziger Volkszeitung     |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is correct and complete for the user's question. It retrieves all entities globally that have the tag office=newspaper and a name, returning both their OSM IRIs and names. The query follows all the required rules, including returning the actual identifiers and not using unsupported label services. No further refinement is necessary.


The OSM-Planet knowledge graph is OSM-centric: it contains OSM objects and their tags, including 'wikidata' tags that point to Wikidata Q-IDs. However, it does not contain the reverse: statements from Wikidata items that link to OSM ways. Therefore, it is not possible to answer the question 'Find Wikidata items that link to an OpenStreetMap way, but the OSM way does not link back to the Wikidata item' using only the OSM-Planet KG, because the KG does not contain Wikidata's internal statements or cross-links to OSM ways. The required information about Wikidata items linking to OSM ways is not present in this KG.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
osm-planet at https://qlever.cs.uni-freiburg.de/api/osm-planet

You can use the following SPARQL prefixes implicitly in all functions:
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
ogc: <http://www.opengis.net/rdf#
osm2rdf: <https://osm2rdf.cs.uni-freiburg.de/rdf#
osm2rdfgeom: <https://osm2rdf.cs.uni-freiburg.de/rdf/geom#
osm2rdfkey: <https://osm2rdf.cs.uni-freiburg.de/rdf/key#
osm2rdfmember: <https://osm2rdf.cs.uni-freiburg.de/rdf/member#
osm: <https://www.openstreetmap.org/
osmkey: <https://www.openstreetmap.org/wiki/Key:
osmmeta: <https://www.openstreetmap.org/meta/
osmnode: <https://www.openstreetmap.org/node/
osmrel: <https://www.openstreetmap.org/relation/
osmway: <https://www.openstreetmap.org/way/
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
ps: <http://www.wikidata.org/prop/statement/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
wd: <http://www.wikidata.org/entity/
wdt: <http://www.wikidata.org/prop/direct/
xsd: <http://www.w3.org/2001/XMLSchema#
owl: <http://www.w3.org/2002/07/owl#
foaf: <http://xmlns.com/foaf/0.1/
skos: <http://www.w3.org/2004/02/skos/core#
dct: <http://purl.org/dc/terms/
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
schema: <http://schema.org/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
wikibase: <http://wikiba.se/ontology#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] Find Wikidata items that link to an OpenStreetMap way, but the OSM way does not link back to the Wikidata item.

[Assistant]
Let's break down the question:

1. We are looking for Wikidata items that link to an OpenStreetMap (OSM) way.
2. The OSM way does not link back to the Wikidata item.

Step 1: Determine how Wikidata items link to OSM ways in the OSM-Planet KG.
- Usually, OSM objects may have a "wikidata" tag (osm2rdfkey:wikidata) pointing to a Wikidata Q-ID.
- The reverse (Wikidata linking to OSM) is less common in OSM-Planet, but let's check if there is a property for "wikidata" or "wikidata tag" on OSM ways.

Step 2: Find how OSM ways are referenced from Wikidata.
- In OSM-Planet, there may be a property for "osm" or "OpenStreetMap way" on Wikidata items.

Let's start by searching for properties related to "OpenStreetMap" and "wikidata" to clarify the linkage direction.

[Tool]
Top 10 property alternatives:
1. website:map:osm (<https://www.openstreetmap.org/wiki/Key:website:map:osm>)
2. osm (osmkey:osm)
3. osmwiki (osmkey:osmwiki)
4. url:osm (<https://www.openstreetmap.org/wiki/Key:url:osm>)
5. note:osm (<https://www.openstreetmap.org/wiki/Key:note:osm>)
6. openstreetcam (osmkey:openstreetcam)
7. wiki:osm (<https://www.openstreetmap.org/wiki/Key:wiki:osm>)
8. url:map (<https://www.openstreetmap.org/wiki/Key:url:map>)
9. osm_was_here (osmkey:osm_was_here)
10. map:url (<https://www.openstreetmap.org/wiki/Key:map:url>)

[Tool]
Top 10 property alternatives:
1. wikidata (osm2rdfkey:wikidata)
2. wikidata (osmkey:wikidata)
3. description:wikidata (<https://osm2rdf.cs.uni-freiburg.de/rdf/key#description:wikidata>)
4. description:wikidata (<https://www.openstreetmap.org/wiki/Key:description:wikidata>)
5. about:wikidata (<https://www.openstreetmap.org/wiki/Key:about:wikidata>)
6. about:wikidata (<https://osm2rdf.cs.uni-freiburg.de/rdf/key#about:wikidata>)
7. related:wikidata (<https://www.openstreetmap.org/wiki/Key:related:wikidata>)
8. related:wikidata (<https://osm2rdf.cs.uni-freiburg.de/rdf/key#related:wikidata>)
9. content:wikidata (<https://www.openstreetmap.org/wiki/Key:content:wikidata>)
10. content:wikidata (<https://osm2rdf.cs.uni-freiburg.de/rdf/key#content:wikidata>)

[Tool] No entity items found

[Tool] No entity items found

[Tool]
Got 65,536 rows and 3 columns, showing the first 10 rows below:
| subject                                    | property                       | object    |
| ------------------------------------------ | ------------------------------ | --------- |
| London (osmnode:107775)                    | wikidata (osm2rdfkey:wikidata) | wd:Q84    |
| تاركى أوخضير (osmnode:11077587840)         | wikidata (osm2rdfkey:wikidata) | wd:Q13955 |
| Karl Marx (osmnode:10917424377)            | wikidata (osm2rdfkey:wikidata) | wd:Q9061  |
| памятник В.И. Ленину (osmnode:10577048476) | wikidata (osm2rdfkey:wikidata) | wd:Q1394  |
| 上海市 (osmnode:10823521483)                  | wikidata (osm2rdfkey:wikidata) | wd:Q8686  |
| دمشق (osmnode:1091272140)                  | wikidata (osm2rdfkey:wikidata) | wd:Q3766  |
| 한국마이크로소프트 (osmnode:10149108968)            | wikidata (osm2rdfkey:wikidata) | wd:Q2283  |
| Apple (osmnode:10291118242)                | wikidata (osm2rdfkey:wikidata) | wd:Q312   |
| Glasgow (osmnode:11127374)                 | wikidata (osm2rdfkey:wikidata) | wd:Q4093  |
| Дагестан (osmnode:10725090310)             | wikidata (osm2rdfkey:wikidata) | wd:Q5118  |
| ...                                        | ...                            | ...       |

[Tool]
Got 65,536 rows and 3 columns, showing the first 10 rows below:
| subject                                    | property                   | object |
| ------------------------------------------ | -------------------------- | ------ |
| London (osmnode:107775)                    | wikidata (osmkey:wikidata) | Q84    |
| تاركى أوخضير (osmnode:11077587840)         | wikidata (osmkey:wikidata) | Q13955 |
| Karl Marx (osmnode:10917424377)            | wikidata (osmkey:wikidata) | Q9061  |
| памятник В.И. Ленину (osmnode:10577048476) | wikidata (osmkey:wikidata) | Q1394  |
| 上海市 (osmnode:10823521483)                  | wikidata (osmkey:wikidata) | Q8686  |
| دمشق (osmnode:1091272140)                  | wikidata (osmkey:wikidata) | Q3766  |
| 한국마이크로소프트 (osmnode:10149108968)            | wikidata (osmkey:wikidata) | Q2283  |
| Apple (osmnode:10291118242)                | wikidata (osmkey:wikidata) | Q312   |
| Glasgow (osmnode:11127374)                 | wikidata (osmkey:wikidata) | Q4093  |
| Дагестан (osmnode:10725090310)             | wikidata (osmkey:wikidata) | Q5118  |
| ...                                        | ...                        | ...    |

[Tool]
Got 317 rows and 3 columns, showing the first 10 rows below:
| subject            | property         | object                |
| ------------------ | ---------------- | --------------------- |
| osmnode:5483544647 | osm (osmkey:osm) | experimental          |
| osmnode:809882716  | osm (osmkey:osm) | survey_point          |
| osmrel:3532400     | osm (osmkey:osm) | workset               |
| osmrel:7281732     | osm (osmkey:osm) | planter               |
| osmway:102657904   | osm (osmkey:osm) | wokrset               |
| osmway:1247693019  | osm (osmkey:osm) | unfinished            |
| osmway:1286879521  | osm (osmkey:osm) | architecture_line     |
| osmway:1315074285  | osm (osmkey:osm) | work_in_progress      |
| osmway:1375890364  | osm (osmkey:osm) | building = collapsed  |
| osmway:1375890366  | osm (osmkey:osm) | Builkding = collapsed |
| ...                | ...              | ...                   |

[Tool]
Top 10 property alternatives:
1. wikidata (osm2rdfkey:wikidata)
2. wikidata (osmkey:wikidata)
3. description:wikidata (<https://osm2rdf.cs.uni-freiburg.de/rdf/key#description:wikidata>)
4. description:wikidata (<https://www.openstreetmap.org/wiki/Key:description:wikidata>)
5. about:wikidata (<https://www.openstreetmap.org/wiki/Key:about:wikidata>)
6. about:wikidata (<https://osm2rdf.cs.uni-freiburg.de/rdf/key#about:wikidata>)
7. related:wikidata (<https://www.openstreetmap.org/wiki/Key:related:wikidata>)
8. related:wikidata (<https://osm2rdf.cs.uni-freiburg.de/rdf/key#related:wikidata>)
9. content:wikidata (<https://www.openstreetmap.org/wiki/Key:content:wikidata>)
10. content:wikidata (<https://osm2rdf.cs.uni-freiburg.de/rdf/key#content:wikidata>)

[Tool]
Got 317 rows and 3 columns, showing the first 10 rows below:
| subject            | property         | object                |
| ------------------ | ---------------- | --------------------- |
| osmnode:5483544647 | osm (osmkey:osm) | experimental          |
| osmnode:809882716  | osm (osmkey:osm) | survey_point          |
| osmrel:3532400     | osm (osmkey:osm) | workset               |
| osmrel:7281732     | osm (osmkey:osm) | planter               |
| osmway:102657904   | osm (osmkey:osm) | wokrset               |
| osmway:1247693019  | osm (osmkey:osm) | unfinished            |
| osmway:1286879521  | osm (osmkey:osm) | architecture_line     |
| osmway:1315074285  | osm (osmkey:osm) | work_in_progress      |
| osmway:1375890364  | osm (osmkey:osm) | building = collapsed  |
| osmway:1375890366  | osm (osmkey:osm) | Builkding = collapsed |
| ...                | ...              | ...                   |

[Tool]
Got 65,536 rows and 3 columns, showing the first 10 rows below:
| subject                                    | property                       | object    |
| ------------------------------------------ | ------------------------------ | --------- |
| London (osmnode:107775)                    | wikidata (osm2rdfkey:wikidata) | wd:Q84    |
| تاركى أوخضير (osmnode:11077587840)         | wikidata (osm2rdfkey:wikidata) | wd:Q13955 |
| Karl Marx (osmnode:10917424377)            | wikidata (osm2rdfkey:wikidata) | wd:Q9061  |
| памятник В.И. Ленину (osmnode:10577048476) | wikidata (osm2rdfkey:wikidata) | wd:Q1394  |
| 上海市 (osmnode:10823521483)                  | wikidata (osm2rdfkey:wikidata) | wd:Q8686  |
| دمشق (osmnode:1091272140)                  | wikidata (osm2rdfkey:wikidata) | wd:Q3766  |
| 한국마이크로소프트 (osmnode:10149108968)            | wikidata (osm2rdfkey:wikidata) | wd:Q2283  |
| Apple (osmnode:10291118242)                | wikidata (osm2rdfkey:wikidata) | wd:Q312   |
| Glasgow (osmnode:11127374)                 | wikidata (osm2rdfkey:wikidata) | wd:Q4093  |
| Дагестан (osmnode:10725090310)             | wikidata (osm2rdfkey:wikidata) | wd:Q5118  |
| ...                                        | ...                            | ...       |

[Tool]
Got 65,536 rows and 3 columns, showing the first 10 rows below:
| subject                                    | property                   | object |
| ------------------------------------------ | -------------------------- | ------ |
| London (osmnode:107775)                    | wikidata (osmkey:wikidata) | Q84    |
| تاركى أوخضير (osmnode:11077587840)         | wikidata (osmkey:wikidata) | Q13955 |
| Karl Marx (osmnode:10917424377)            | wikidata (osmkey:wikidata) | Q9061  |
| памятник В.И. Ленину (osmnode:10577048476) | wikidata (osmkey:wikidata) | Q1394  |
| 上海市 (osmnode:10823521483)                  | wikidata (osmkey:wikidata) | Q8686  |
| دمشق (osmnode:1091272140)                  | wikidata (osmkey:wikidata) | Q3766  |
| 한국마이크로소프트 (osmnode:10149108968)            | wikidata (osmkey:wikidata) | Q2283  |
| Apple (osmnode:10291118242)                | wikidata (osmkey:wikidata) | Q312   |
| Glasgow (osmnode:11127374)                 | wikidata (osmkey:wikidata) | Q4093  |
| Дагестан (osmnode:10725090310)             | wikidata (osmkey:wikidata) | Q5118  |
| ...                                        | ...                        | ...    |

[Tool]
Got 317 rows and 3 columns, showing the first 10 rows below:
| subject            | property         | object                |
| ------------------ | ---------------- | --------------------- |
| osmnode:5483544647 | osm (osmkey:osm) | experimental          |
| osmnode:809882716  | osm (osmkey:osm) | survey_point          |
| osmrel:3532400     | osm (osmkey:osm) | workset               |
| osmrel:7281732     | osm (osmkey:osm) | planter               |
| osmway:102657904   | osm (osmkey:osm) | wokrset               |
| osmway:1247693019  | osm (osmkey:osm) | unfinished            |
| osmway:1286879521  | osm (osmkey:osm) | architecture_line     |
| osmway:1315074285  | osm (osmkey:osm) | work_in_progress      |
| osmway:1375890364  | osm (osmkey:osm) | building = collapsed  |
| osmway:1375890366  | osm (osmkey:osm) | Builkding = collapsed |
| ...                | ...              | ...                   |

[Tool]
Got 65,536 rows and 3 columns, showing the first 10 rows below:
| subject                                    | property                   | object |
| ------------------------------------------ | -------------------------- | ------ |
| London (osmnode:107775)                    | wikidata (osmkey:wikidata) | Q84    |
| تاركى أوخضير (osmnode:11077587840)         | wikidata (osmkey:wikidata) | Q13955 |
| Karl Marx (osmnode:10917424377)            | wikidata (osmkey:wikidata) | Q9061  |
| памятник В.И. Ленину (osmnode:10577048476) | wikidata (osmkey:wikidata) | Q1394  |
| 上海市 (osmnode:10823521483)                  | wikidata (osmkey:wikidata) | Q8686  |
| دمشق (osmnode:1091272140)                  | wikidata (osmkey:wikidata) | Q3766  |
| 한국마이크로소프트 (osmnode:10149108968)            | wikidata (osmkey:wikidata) | Q2283  |
| Apple (osmnode:10291118242)                | wikidata (osmkey:wikidata) | Q312   |
| Glasgow (osmnode:11127374)                 | wikidata (osmkey:wikidata) | Q4093  |
| Дагестан (osmnode:10725090310)             | wikidata (osmkey:wikidata) | Q5118  |
| ...                                        | ...                        | ...    |

[Tool]
Got 317 rows and 3 columns, showing the first 10 rows below:
| subject            | property         | object                |
| ------------------ | ---------------- | --------------------- |
| osmnode:5483544647 | osm (osmkey:osm) | experimental          |
| osmnode:809882716  | osm (osmkey:osm) | survey_point          |
| osmrel:3532400     | osm (osmkey:osm) | workset               |
| osmrel:7281732     | osm (osmkey:osm) | planter               |
| osmway:102657904   | osm (osmkey:osm) | wokrset               |
| osmway:1247693019  | osm (osmkey:osm) | unfinished            |
| osmway:1286879521  | osm (osmkey:osm) | architecture_line     |
| osmway:1315074285  | osm (osmkey:osm) | work_in_progress      |
| osmway:1375890364  | osm (osmkey:osm) | building = collapsed  |
| osmway:1375890366  | osm (osmkey:osm) | Builkding = collapsed |
| ...                | ...              | ...                   |

[Assistant]
Here's my reasoning so far:

- The "wikidata" tag (osmkey:wikidata or osm2rdfkey:wikidata) is used on OSM objects (nodes, ways, relations) to link to Wikidata Q-IDs.
- There is no direct evidence in the OSM-Planet KG that Wikidata items link to OSM ways, as the data model is OSM-centric.
- However, the question asks for Wikidata items that link to an OSM way, but the OSM way does not link back.

Given the structure, the only direction we can check is: For each OSM way that has a "wikidata" tag, does the corresponding Wikidata item have a property that links back to the OSM way? But in OSM-Planet, we do not have Wikidata's internal properties.

However, we can try to find OSM ways that have a "wikidata" tag, and see if there is any property on the corresponding Wikidata item that links back to the OSM way (e.g., via "osm" or "osmway" property). If not, then that would match the question.

But since the OSM-Planet KG is OSM-centric and does not contain Wikidata's internal statements, we cannot check the reverse direction (from Wikidata to OSM) in this KG.

Therefore, it is not possible to answer the question as stated using only the OSM-Planet KG, because it does not contain the necessary cross-links from Wikidata items to OSM ways.

I will cancel with a detailed explanation.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The explanation is correct. The OSM-Planet knowledge graph only contains OSM data and tags, including 'wikidata' tags that point to Wikidata Q-IDs, but does not contain information about Wikidata items or their statements linking to OSM ways. Therefore, it is not possible to answer the question using only this KG. No SPARQL query is possible in this context, and the system's output is complete and accurate.


PREFIX osm2rdfgeom: <https://osm2rdf.cs.uni-freiburg.de/rdf/geom#>
PREFIX osmkey: <https://www.openstreetmap.org/wiki/Key:>
SELECT ?park ?name ?geom WHERE {
  ?park osmkey:leisure "park" ; osmkey:name ?name ; osm2rdfgeom:has-geometry ?geom .
}

The geof:centroid function, which is required to compute centroid locations of geometries in SPARQL, is not supported by the OSM-Planet QLever endpoint. Therefore, it is not possible to return centroid locations of all named parks globally directly from SPARQL. The best possible query retrieves the geometries of all named parks, but centroid computation would have to be done externally, which is not allowed by the instructions.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
osm-planet at https://qlever.cs.uni-freiburg.de/api/osm-planet

You can use the following SPARQL prefixes implicitly in all functions:
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
ogc: <http://www.opengis.net/rdf#
osm2rdf: <https://osm2rdf.cs.uni-freiburg.de/rdf#
osm2rdfgeom: <https://osm2rdf.cs.uni-freiburg.de/rdf/geom#
osm2rdfkey: <https://osm2rdf.cs.uni-freiburg.de/rdf/key#
osm2rdfmember: <https://osm2rdf.cs.uni-freiburg.de/rdf/member#
osm: <https://www.openstreetmap.org/
osmkey: <https://www.openstreetmap.org/wiki/Key:
osmmeta: <https://www.openstreetmap.org/meta/
osmnode: <https://www.openstreetmap.org/node/
osmrel: <https://www.openstreetmap.org/relation/
osmway: <https://www.openstreetmap.org/way/
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
ps: <http://www.wikidata.org/prop/statement/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
wd: <http://www.wikidata.org/entity/
wdt: <http://www.wikidata.org/prop/direct/
xsd: <http://www.w3.org/2001/XMLSchema#
owl: <http://www.w3.org/2002/07/owl#
foaf: <http://xmlns.com/foaf/0.1/
skos: <http://www.w3.org/2004/02/skos/core#
dct: <http://purl.org/dc/terms/
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
schema: <http://schema.org/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
wikibase: <http://wikiba.se/ontology#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] Find the centroid locations of all named parks globally.

[Assistant]
Let's break down the question:

1. We need to find all parks that have a name (i.e., are "named parks").
2. For each, we want the centroid location.

Step 1: Identify how parks are represented in OSM. Typically, parks are tagged with leisure=park.
Step 2: Named parks will have a name tag.
Step 3: We need to retrieve their centroid locations. In OSM2RDF, geometries are often linked via osm2rdfgeom:has-geometry, and centroids can be obtained via geof:centroid.

First, let's verify the property for "leisure" and "name" in OSM2RDF. I'll search for the "leisure" property.

[Tool]
Top 10 property alternatives:
1. leisure (osmkey:leisure)
2. area:leisure (<https://www.openstreetmap.org/wiki/Key:area:leisure>)
3. was:leisure (<https://www.openstreetmap.org/wiki/Key:was:leisure>)
4. note:leisure (<https://www.openstreetmap.org/wiki/Key:note:leisure>)
5. leisure_2 (osmkey:leisure_2)
6. leisure_3 (osmkey:leisure_3)
7. source:leisure (<https://www.openstreetmap.org/wiki/Key:source:leisure>)
8. leisure:part (<https://www.openstreetmap.org/wiki/Key:leisure:part>)
9. leisure:-2019 (<https://www.openstreetmap.org/wiki/Key:leisure:-2019>)
10. leisure_1 (osmkey:leisure_1)

[Assistant]
The property for "leisure" is osmkey:leisure. Next, let's confirm the value for "park" under this property and check for the "name" property.

I'll search for objects of property osmkey:leisure with the query "park".

[Tool]
No entity items found

No other items found

Top 10 literal alternatives:
1. park
2. bus park
3. children park
4. dirt park
5. marina park
6. Nala park
7. park pianoro
8. park_bench
9. park_connector
10. park_footway

[Assistant]
The value for a park under the leisure key is the literal "park". Now, let's confirm the property for "name" in OSM2RDF.

I'll search for the "name" property.

[Tool]
Top 10 property alternatives:
1. ναμε (<https://www.openstreetmap.org/wiki/Key:ναμε>)
2. name_ (osmkey:name_)
3. _name_ (osmkey:_NAME_)
4. name: (<https://www.openstreetmap.org/wiki/Key:name:>)
5. name (osmkey:name)
6. source:name (<https://www.openstreetmap.org/wiki/Key:source:name>)
7. description:name (<https://www.openstreetmap.org/wiki/Key:description:name>)
8. location:name (<https://www.openstreetmap.org/wiki/Key:location:name>)
9. person:name (<https://www.openstreetmap.org/wiki/Key:person:name>)
10. link:name (<https://www.openstreetmap.org/wiki/Key:link:name>)

[Assistant]
The property for "name" is osmkey:name.

Now, for the centroid, OSM2RDF geometries are often linked via osm2rdfgeom:has-geometry, and we can use geof:centroid to compute the centroid of a geometry.

Let's put this together:
- Find all entities with osmkey:leisure "park" and osmkey:name ?name.
- Get their geometry via osm2rdfgeom:has-geometry.
- Compute the centroid using geof:centroid.

I'll write a SPARQL query that retrieves the IRIs of all named parks and their centroid locations.

[Tool]
SPARQL execution failed:
Not supported: Function "<http://www.opengis.net/def/function/geosparql/centroid>" is currently not supported by QLever.

[Assistant]
The geof:centroid function is not supported by the QLever endpoint for OSM-Planet, so I cannot compute the centroid directly in the SPARQL query. However, I can retrieve the geometries of all named parks, which can be post-processed to compute centroids externally, but this is not allowed per the instructions.

Therefore, I cannot provide a SPARQL query that directly returns the centroid locations of all named parks globally using the current capabilities of the OSM-Planet endpoint.

Here is my best attempt, which retrieves the geometries of all named parks (so that centroids could be computed externally):

```sparql
SELECT ?park ?name ?geom WHERE {
  ?park osmkey:leisure "park" ;
        osmkey:name ?name ;
        osm2rdfgeom:has-geometry ?geom .
}
```

But this does not compute the centroid within SPARQL.

I will cancel and explain the limitation.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The explanation correctly identifies that the required geof:centroid function is not supported by the OSM-Planet QLever endpoint, making it impossible to compute centroid locations directly in SPARQL. The provided query sensibly retrieves the geometries of named parks, which is the closest possible result given the constraints. The answer follows the instructions by not performing centroid computation outside of SPARQL. No further refinement is possible under these limitations.