PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?item ?coordinates WHERE {
  wd:Q182139 wdt:P625 ?coordinates .
  BIND( wd:Q182139 AS ?item )
}

The Isthmus of Panama is located at the coordinates: POINT(-79.000000 9.000000).

[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:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
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] where is isthmus of panama located on the map?

[Assistant] Let's start by looking at some examples.

[Tool]
Example 1:
Question:
who was marilyn monroe's parents?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q4616 wdt:P22 | wdt:P25 ?x .
}

Using entities:
Marilyn Monroe, also known as Norma Jean Miller, Norma Jean Mortenson, Norma Jeane Dougherty, Norma Jeane Mortenson, Norma Jeane Baker (wd:Q4616): American actress and model (1926–1962), Playboy Playmate, autobiographer, fashion model, film producer, photo model, film actor, singer, actor, model

Using properties:
father, also known as son of, child of, parent, is son of, is daughter of (wd:P22 as wdt): male parent of the subject. For stepfather, use "stepparent" (P3448), parent
mother, also known as mom, is child of, mommy, mum, mummy (wd:P25 as wdt): female parent of the subject. For stepmother, use "stepparent" (P3448), parent

Example 2:
Question:
what god does taoism believe in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P1049 wd:Q9598 .
}

Using entities:
Taoism, also known as Daoism (wd:Q9598): religious or philosophical tradition of Chinese origin

Using properties:
worshipped by, also known as deity of (wd:P1049 as wdt): religion or group/civilization that worships a given deity, part of

Example 3:
Question:
what did ryan dunn died from?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q316036 wdt:P509 ?x .
}

Using entities:
Ryan Dunn, also known as Ryan M. Dunn, Ryan Matthew Dunn (wd:Q316036): American actor and stunt performer (1977–2011), television presenter, stunt performer, film actor, actor

Using properties:
cause of death, also known as death cause, murder method, method of murder, die of, die from (wd:P509 as wdt): underlying or immediate cause of death.  Underlying cause (e.g. ...adest category, e.g. natural causes, accident, homicide, suicide

[Assistant] Based on the examples, we need to identify the entity "Isthmus of Panama" and then find its location. Let's first search for the entity "Isthmus of Panama".

[Tool]
Top 10 entity alternatives:
1. Isthmus of Panama, also known as Istmo de Panama, Istmo de Panamá, Panama Isthmus (wd:Q182139): narrow landstrip in Panama
2. Hydrology of the Isthmus of Panama (wd:Q33778332): scientific article
3. Ferns of the Isthmus of Panama (wd:Q56189008)
4. Formation of the Isthmus of Panama (wd:Q26740287): scientific article
5. Historical biogeography of the Isthmus of Panama (wd:Q30656167): scientific article
6. Piercing the Isthmus of Panama 1 (wd:Q60414062): scientific article published in Nature
7. Across the Isthmus of Panama in 1912 (wd:Q3604775): 1912 film
8. How old is the Isthmus of Panama? (wd:Q61465180): article published in 2013
9. Dengue-like fever on the Isthmus of Panama. (wd:Q41093706): scientific article published on January 1945
10. Fauna of the Gatun Formation, Isthmus of Panama (wd:Q106954095)

[Assistant] The top result is the entity we are looking for: "Isthmus of Panama" (wd:Q182139). Now, let's find the property that represents the location of an entity. We can search for properties related to "location" or "coordinates".

[Tool]
Top 10 property alternatives:
1. work location, also known as work place, working from, working at, worked from, worked at (wd:P937 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): location where persons or organisations were actively participating in employment, business or other work, significant place, location
2. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
3. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
4. occupant, also known as tenant, resident, renter, occupiers, lessee (wd:P466 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): person or organization occupying property, used by
5. recorded at studio or venue, also known as venue, studio, recording venue, recording studio, recorded at event (wd:P483 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): studio or location where a musical composition/release was recorded, recording location
6. home venue, also known as home water, venue, stadium, home ground, home field (wd:P115 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): home stadium or venue of a sports team or applicable performing arts organization, location
7. published in, also known as song on album, tome of the book, tome of, track of, track on (wd:P1433 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): larger work that a given work was published in, like a book, journal or music album, part of
8. located in the present-day administrative territorial entity, also known as present-day administrative territorial entity, located in the current administrative territorial entity, located in the modern-day administrative territorial entity, located in the present-day administrative territorial entity, would today be located in administrative territorial entity (wd:P3842 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): the item was located in the territory of this present-day administrative unit; however the two did not at any point coexist in time, location, part of
9. directions, also known as locality or place (wd:P2795 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): describe how to find the subject - directions, objects along way, comments
10. ranking, also known as peak position, place, placing, position, rank (wd:P1352 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): subject's ordinal position as qualitatively evaluated relative to other members of a group

[Assistant]
The property "coordinate location" (wd:P625) seems to be the most appropriate for finding the geographic coordinates of the Isthmus of Panama. Let's construct a simple SPARQL query to retrieve these coordinates.

```sparql
SELECT ?coordinates WHERE {
  wd:Q182139 wdt:P625 ?coordinates .
}
```

Let's execute this query.

[Tool]
Got 1 row and 1 column:
| coordinates                                 |
| ------------------------------------------- |
| POINT(-79.000000 9.000000) (geo:wktLiteral) |

[Assistant]
The coordinates of the Isthmus of Panama are `POINT(-79.000000 9.000000)`. These coordinates represent the geographic location of the Isthmus of Panama on a map.

To provide a more human-readable format, we can include the latitude and longitude separately. Let's modify the query to extract the latitude and longitude.

```sparql
SELECT ?latitude ?longitude WHERE {
  wd:Q182139 wdt:P625 ?coordinates .
  BIND(xsd:float(STRBEFORE(?coordinates, " ")) AS ?latitude)
  BIND(xsd:float(STRAFTER(?coordinates, " ")) AS ?longitude)
}
```

Let's execute this updated query.

[Tool]
Got 1 row and 2 columns:
| latitude | longitude |
| -------- | --------- |

[Assistant]
It seems there was an issue with the query to extract the latitude and longitude separately. Let's try a different approach using the `geof:asWKT` function to parse the coordinates.

Here's the updated query:

```sparql
SELECT ?latitude ?longitude WHERE {
  wd:Q182139 wdt:P625 ?coordinates .
  BIND(geof:asWKT(?coordinates) AS ?wkt)
  BIND(xsd:float(STRBEFORE(?wkt, " ")) AS ?latitude)
  BIND(xsd:float(STRAFTER(?wkt, " ")) AS ?longitude)
}
```

Let's execute this query.

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

[Assistant]
It appears that the `geof:asWKT` function is not supported by the QLever SPARQL endpoint. Instead, we can directly extract the coordinates from the `geo:wktLiteral` value using string manipulation functions.

Here's the updated query:

```sparql
SELECT ?latitude ?longitude WHERE {
  wd:Q182139 wdt:P625 ?coordinates .
  BIND(REPLACE(STR(?coordinates), "POINT\\(|\\)", "") AS ?coordsStr)
  BIND(xsd:float(SUBSTR(?coordsStr, 1, STRLEN(?coordsStr) - STRLEN(SUBSTRAFTER(?coordsStr, " ")))) AS ?longitude)
  BIND(xsd:float(SUBSTR(?coordsStr, STRLEN(SUBSTRBEFORE(?coordsStr, " ")) + 1)) AS ?latitude)
}
```

Let's execute this query.

[Tool]
Failed to call function execute:
failed to parse input: no matching token found from position 103: '"POINT\(|\)", "") AS ?coordsStr) BIND(xsd:float(SUBSTR(?coordsStr, 1, STRLEN(?coordsStr) - STRLEN(SUBSTRAFTER(?coordsStr, " ")))) AS ?longitude) BIND(xsd:float(SUBSTR(?coordsStr, STRLEN(SUBSTRBEFORE(?coordsStr, " ")) + 1)) AS ?latitude) }'

[Assistant]
It looks like there was an issue with the string manipulation functions. Let's simplify the query and directly extract the coordinates using a different approach. We can use the `STRBEFORE` and `STRAFTER` functions to split the coordinates string.

Here's the updated query:

```sparql
SELECT ?latitude ?longitude WHERE {
  wd:Q182139 wdt:P625 ?coordinates .
  BIND(REPLACE(STR(?coordinates), "POINT(", "") AS ?coordsStr)
  BIND(REPLACE(?coordsStr, ")", "") AS ?cleanCoords)
  BIND(xsd:float(STRAFTER(?cleanCoords, " ")) AS ?latitude)
  BIND(xsd:float(STRBEFORE(?cleanCoords, " ")) AS ?longitude)
}
```

Let's execute this query.

[Tool]
Got 1 row and 2 columns:
| latitude | longitude |
| -------- | --------- |

[Assistant]
It seems there is still an issue with the query. Let's try a simpler approach to extract the coordinates directly without complex string manipulations. We can use the `STR` function to convert the `geo:wktLiteral` to a string and then extract the values.

Here's the updated query:

```sparql
SELECT ?latitude ?longitude WHERE {
  wd:Q182139 wdt:P625 ?coordinates .
  BIND(STR(?coordinates) AS ?coordsStr)
  BIND(xsd:float(SUBSTR(?coordsStr, 7, 8)) AS ?longitude)
  BIND(xsd:float(SUBSTR(?coordsStr, 16, 8)) AS ?latitude)
}
```

Let's execute this query.

[Tool]
Got 1 row and 2 columns:
| latitude | longitude         |
| -------- | ----------------- |
|          | -79 (xsd:decimal) |

[Assistant]
It seems that the extraction of the latitude is still not working correctly. Let's break down the string manipulation step by step to ensure we are correctly extracting both the latitude and longitude.

Here's the updated query:

```sparql
SELECT ?latitude ?longitude WHERE {
  wd:Q182139 wdt:P625 ?coordinates .
  BIND(STR(?coordinates) AS ?coordsStr)
  BIND(REPLACE(?coordsStr, "POINT(", "") AS ?cleanCoords)
  BIND(REPLACE(?cleanCoords, ")", "") AS ?finalCoords)
  BIND(xsd:float(STRBEFORE(?finalCoords, " ")) AS ?longitude)
  BIND(xsd:float(STRAFTER(?finalCoords, " ")) AS ?latitude)
}
```

Let's execute this query.

[Tool]
Got 1 row and 2 columns:
| latitude | longitude |
| -------- | --------- |

[Assistant]
It seems that the extraction is still not working as expected. Let's take a different approach and directly use the `STR` function to convert the `geo:wktLiteral` to a string and then manually extract the coordinates using substring functions.

Here's the updated query:

```sparql
SELECT ?latitude ?longitude WHERE {
  wd:Q182139 wdt:P625 ?coordinates .
  BIND(STR(?coordinates) AS ?coordsStr)
  BIND(xsd:float(SUBSTR(?coordsStr, 7, 8)) AS ?longitude)
  BIND(xsd:float(SUBSTR(?coordsStr, 16, 8)) AS ?latitude)
}
```

Let's execute this query again to ensure it works correctly.

[Tool]
Got 1 row and 2 columns:
| latitude | longitude         |
| -------- | ----------------- |
|          | -79 (xsd:decimal) |

[Assistant]
It seems that the extraction of the latitude is still not working correctly. Let's manually inspect the string to understand the issue better. The `geo:wktLiteral` format is typically `POINT(longitude latitude)`, so we need to ensure we are correctly extracting both values.

Here's a more detailed approach to extract the coordinates:

```sparql
SELECT ?latitude ?longitude WHERE {
  wd:Q182139 wdt:P625 ?coordinates .
  BIND(STR(?coordinates) AS ?coordsStr)
  BIND(REPLACE(?coordsStr, "POINT(", "") AS ?cleanCoords)
  BIND(REPLACE(?cleanCoords, ")", "") AS ?finalCoords)
  BIND(xsd:float(STRBEFORE(?finalCoords, " ")) AS ?longitude)
  BIND(xsd:float(STRAFTER(?finalCoords, " ")) AS ?latitude)
}
```

Let's execute this query again to ensure it works correctly.

[Tool]
Got 1 row and 2 columns:
| latitude | longitude |
| -------- | --------- |

[Assistant]
It seems that the extraction is still not working as expected. Let's take a different approach and manually inspect the string to ensure we are correctly extracting both the latitude and longitude.

We can use the `STR` function to convert the `geo:wktLiteral` to a string and then manually extract the coordinates using substring functions. Let's break it down step by step to ensure we are correctly extracting both values.

Here's the updated query:

```sparql
SELECT ?latitude ?longitude WHERE {
  wd:Q182139 wdt:P625 ?coordinates .
  BIND(STR(?coordinates) AS ?coordsStr)
  BIND(SUBSTR(?coordsStr, 7, 8) AS ?longitudeStr)
  BIND(SUBSTR(?coordsStr, 16, 8) AS ?latitudeStr)
  BIND(xsd:float(?longitudeStr) AS ?longitude)
  BIND(xsd:float(?latitudeStr) AS ?latitude)
}
```

Let's execute this query again to ensure it works correctly.

[Tool]
Got 1 row and 2 columns:
| latitude | longitude         |
| -------- | ----------------- |
|          | -79 (xsd:decimal) |

[Assistant]
It seems that the extraction of the latitude is still not working correctly. Let's manually inspect the string to understand the issue better. The `geo:wktLiteral` format is typically `POINT(longitude latitude)`, so we need to ensure we are correctly extracting both values.

Let's break it down step by step and print the intermediate results to debug the issue:

```sparql
SELECT ?coordinates ?coordsStr ?cleanCoords ?longitudeStr ?latitudeStr ?longitude ?latitude WHERE {
  wd:Q182139 wdt:P625 ?coordinates .
  BIND(STR(?coordinates) AS ?coordsStr)
  BIND(REPLACE(?coordsStr, "POINT(", "") AS ?cleanCoords)
  BIND(REPLACE(?cleanCoords, ")", "") AS ?finalCoords)
  BIND(STRBEFORE(?finalCoords, " ") AS ?longitudeStr)
  BIND(STRAFTER(?finalCoords, " ") AS ?latitudeStr)
  BIND(xsd:float(?longitudeStr) AS ?longitude)
  BIND(xsd:float(?latitudeStr) AS ?latitude)
}
```

Let's execute this query to see the intermediate results and debug the issue.

[Tool]
Got 1 row and 7 columns:
| coordinates                                 | coordsStr                  | cleanCoords | longitudeStr | latitudeStr | longitude | latitude |
| ------------------------------------------- | -------------------------- | ----------- | ------------ | ----------- | --------- | -------- |
| POINT(-79.000000 9.000000) (geo:wktLiteral) | POINT(-79.000000 9.000000) |             |              |             |           |          |

[Assistant]
It seems that the `REPLACE` functions are not working as expected. Let's simplify the query and manually inspect the string to ensure we are correctly extracting both the latitude and longitude.

Here's the updated query with manual inspection:

```sparql
SELECT ?coordinates ?coordsStr ?longitudeStr ?latitudeStr ?longitude ?latitude WHERE {
  wd:Q182139 wdt:P625 ?coordinates .
  BIND(STR(?coordinates) AS ?coordsStr)
  BIND(SUBSTR(?coordsStr, 7, 8) AS ?longitudeStr)
  BIND(SUBSTR(?coordsStr, 16, 8) AS ?latitudeStr)
  BIND(xsd:float(?longitudeStr) AS ?longitude)
  BIND(xsd:float(?latitudeStr) AS ?latitude)
}
```

Let's execute this query to see the intermediate results and debug the issue.

[Tool]
Got 1 row and 6 columns:
| coordinates                                 | coordsStr                  | longitudeStr | latitudeStr | longitude         | latitude |
| ------------------------------------------- | -------------------------- | ------------ | ----------- | ----------------- | -------- |
| POINT(-79.000000 9.000000) (geo:wktLiteral) | POINT(-79.000000 9.000000) | -79.0000     | 0 9.0000    | -79 (xsd:decimal) |          |

[Assistant]
It seems that the extraction of the latitude is still not working correctly. The issue might be due to the way the `SUBSTR` function is being used. Let's manually inspect the string and ensure we are correctly extracting the latitude and longitude.

Here's the updated query with a more detailed approach:

```sparql
SELECT ?coordinates ?coordsStr ?longitudeStr ?latitudeStr ?longitude ?latitude WHERE {
  wd:Q182139 wdt:P625 ?coordinates .
  BIND(STR(?coordinates) AS ?coordsStr)
  BIND(SUBSTR(?coordsStr, 7, 8) AS ?longitudeStr)
  BIND(SUBSTR(?coordsStr, 16, 8) AS ?latitudeStr)
  BIND(xsd:float(?longitudeStr) AS ?longitude)
  BIND(xsd:float(?latitudeStr) AS ?latitude)
}
```

Let's execute this query again to ensure it works correctly.

[Tool]
Got 1 row and 6 columns:
| coordinates                                 | coordsStr                  | longitudeStr | latitudeStr | longitude         | latitude |
| ------------------------------------------- | -------------------------- | ------------ | ----------- | ----------------- | -------- |
| POINT(-79.000000 9.000000) (geo:wktLiteral) | POINT(-79.000000 9.000000) | -79.0000     | 0 9.0000    | -79 (xsd:decimal) |          |

[Assistant]
It seems that the extraction of the latitude is still not working correctly. The issue might be due to the way the `SUBSTR` function is being used. Let's manually inspect the string and ensure we are correctly extracting the latitude and longitude.

Here's a more detailed approach to extract the coordinates:

```sparql
SELECT ?coordinates ?coordsStr ?longitudeStr ?latitudeStr ?longitude ?latitude WHERE {
  wd:Q182139 wdt:P625 ?coordinates .
  BIND(STR(?coordinates) AS ?coordsStr)
  BIND(SUBSTR(?coordsStr, 7, 8) AS ?longitudeStr)
  BIND(SUBSTR(?coordsStr, 16, 8) AS ?latitudeStr)
  BIND(xsd:float(?longitudeStr) AS ?longitude)
  BIND(xsd:float(REPLACE(?latitudeStr, " ", "")) AS ?latitude)
}
```

Let's execute this query again to ensure it works correctly.

[Tool]
Got 1 row and 6 columns:
| coordinates                                 | coordsStr                  | longitudeStr | latitudeStr | longitude         | latitude        |
| ------------------------------------------- | -------------------------- | ------------ | ----------- | ----------------- | --------------- |
| POINT(-79.000000 9.000000) (geo:wktLiteral) | POINT(-79.000000 9.000000) | -79.0000     | 0 9.0000    | -79 (xsd:decimal) | 9 (xsd:decimal) |

[Assistant]
The query now correctly extracts both the latitude and longitude of the Isthmus of Panama. The coordinates are:

- Longitude: -79.000000
- Latitude: 9.000000

Here is the final SPARQL query that retrieves the coordinates of the Isthmus of Panama:

```sparql
SELECT ?latitude ?longitude WHERE {
  wd:Q182139 wdt:P625 ?coordinates .
  BIND(STR(?coordinates) AS ?coordsStr)
  BIND(SUBSTR(?coordsStr, 7, 8) AS ?longitudeStr)
  BIND(SUBSTR(?coordsStr, 16, 8) AS ?latitudeStr)
  BIND(xsd:float(?longitudeStr) AS ?longitude)
  BIND(xsd:float(REPLACE(?latitudeStr, " ", "")) AS ?latitude)
}
```

The Isthmus of Panama is located at the coordinates: **Longitude: -79.000000, Latitude: 9.000000**.

Let's finalize the answer.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query is mostly correct, but it could be improved to directly return the coordinate property as a whole, rather than splitting it into separate latitude and longitude values. This would make the query simpler and more robust. Additionally, the query should return the IRI of the item as well, according to the rule that the SPARQL query should always return the actual identifiers / IRIs of the items in its result.

[Assistant]
Thank you for the feedback. Let's improve the SPARQL query to directly return the coordinate property as a whole and include the IRI of the item.

Here's the updated query:

```sparql
SELECT ?item ?coordinates WHERE {
  wd:Q182139 wdt:P625 ?coordinates .
  BIND(wd:Q182139 AS ?item)
}
```

This query will return the IRI of the Isthmus of Panama and its coordinates as a whole.

Let's execute this query to ensure it works correctly.

[Tool]
Got 1 row and 2 columns:
| item                           | coordinates                                 |
| ------------------------------ | ------------------------------------------- |
| Isthmus of Panama (wd:Q182139) | POINT(-79.000000 9.000000) (geo:wktLiteral) |

[Assistant]
The updated query correctly returns the IRI of the Isthmus of Panama and its coordinates as a whole. Here is the final SPARQL query:

```sparql
SELECT ?item ?coordinates WHERE {
  wd:Q182139 wdt:P625 ?coordinates .
  BIND(wd:Q182139 AS ?item)
}
```

The Isthmus of Panama is located at the coordinates: **POINT(-79.000000 9.000000)**.

Let's finalize the answer.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is correct and returns the expected coordinates for the Isthmus of Panama. The answer provided is accurate and complete.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?governmentType WHERE {
  wd:Q183 wdt:P122 ?governmentType .
  FILTER ( ?governmentType = wd:Q5440547 )
}

Germany is a federal parliamentary republic.

[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:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
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] what type of government does germany have now?

[Assistant] Let's start by looking at some examples.

[Tool]
Example 1:
Question:
what time zone is it in london england?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q84 wdt:P421 ?x .
}

Using entities:
London, also known as Loniniensi, Trinovantum, the Big Smoke, Lundenwic, Lundenburh (wd:Q84): capital and largest city of England and the United Kingdom

Using properties:
located in time zone, also known as TZ, time zone, timezone (wd:P421 as wdt): time zone for this item

Example 2:
Question:
what country do they speak farsi?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P37 wd:Q9168 ; wdt:P31 / wdt:P279 * wd:Q6256 .
}

Using entities:
country, also known as countries (wd:Q6256): distinct territorial body or political entity
Persian, also known as Farsi, Farsic-Caucasian Tat, Farsic–Caucasian Tat, Farsi language, Iranian (wd:Q9168): Western Iranian language

Using properties:
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as wdt): language designated as official by this item, language used

Example 3:
Question:
what movies have adam sandler been in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P161 wd:Q132952 ; wdt:P31 / wdt:P279 * wd:Q11424 .
}

Using entities:
film, also known as cinematic work, moving picture, movie, motion pictures, motion picture (wd:Q11424): sequence of images that give the impression of movement, stored on film stock
Adam Sandler, also known as Adam Richard Sandler (wd:Q132952): American comedian and actor (born 1966), television producer, executive producer, video game actor, television actor, film producer, screenwriter, voice actor, film actor, guitarist, musician, comedian, composer, writer, singer, actor

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as wdt): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

[Assistant] Based on the examples, we need to identify the entity for Germany and the property for the type of government. Let's start by searching for the entity "Germany".

[Tool]
Top 10 entity alternatives:
1. Germany, also known as BR Deutschland, Bundesrepublik Deutschland, Deutschland, Federal Republic of Germany (wd:Q183): country in Central Europe
2. Weimar Republic, also known as German Republic, Weimar Germany, Republic of Germany, Germany, German Reich (wd:Q41304): Germany in the years 1918/1919–1933
3. German Reich, also known as Deutsches Reich, German Empire, German Realm, Germany, Imperial Germany (wd:Q1206012): official name for the German nation state from 1871 to 1945, and name of Germany until 1949
4. Burg Drachenfels, also known as Germany (wd:Q1011486): castle
5. Germany (wd:Q5552078): European Parliament constituency
6. Geilenkirchen-Heinsberg, also known as Germany (wd:Q2268218)
7. Germany, also known as Germany, IN, Germany, Indiana (wd:Q18151573): unincorporated community in Clark County, Indiana
8. Germany (wd:Q19147844): poem by Vladimir Mayakovsky
9. Germany, also known as Ludwig, West (wd:Q3839160): Hetalia character
10. Germany, also known as Germany, Texas, Germany, TX (wd:Q15221573): unincorporated community in Houston County, Texas, United States

[Assistant] The correct entity for Germany is `wd:Q183`. Now, let's search for the property that represents the type of government.

[Tool]
Top 10 property alternatives:
1. basic form of government, also known as form of government, government, type of government (wd:P122 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): subject's government
2. capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): seat of government of a country, province, state or other type of administrative territorial entity
3. head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson
4. Classification of the Functions of Government, also known as COFOG ID, COFOG number (wd:P9798 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): UN classification to compare government agencies across countries
5. office held by head of government, also known as title of head of government, position of head of government, office of head of government, head of government's office, position held by head of government (wd:P1313 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): political office that is fulfilled by the head of the government of this item
6. authority, also known as executive authority, governed by, governing authority, governing body, has authority (wd:P797 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): entity having executive power on given entity
7. voting system, also known as electoral system, voting system, type of election (wd:P8196 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): system used for this election or vote
8. position held, also known as function, held position, holds position, job, office held (wd:P39 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): subject currently or formerly holds the object position or public office
9. political ideology, also known as editorial viewpoint, has political ideology, ideology, official ideology, official political ideology (wd:P1142 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): political ideology of an organization or person or of a work (such as a newspaper)
10. office held by head of state, also known as head of state, position held by head of state, state headed by (wd:P1906 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): political office that is fulfilled by the head of state of this item

[Assistant]
The correct property for the type of government is `wd:P122`. Now, let's construct a simple SPARQL query to find the type of government for Germany.

```sparql
SELECT ?governmentType WHERE {
  wd:Q183 wdt:P122 ?governmentType .
}
```

Let's execute this query to see the results.

[Tool]
Got 4 rows and 1 column:
| governmentType                               |
| -------------------------------------------- |
| parliamentary republic (wd:Q4198907)         |
| federation (wd:Q43702)                       |
| federal parliamentary republic (wd:Q5440547) |
| republic (wd:Q7270)                          |

[Assistant]
The results show multiple types of government for Germany. To provide a more precise answer, we can combine these results into a single, more descriptive term. However, for the purpose of this query, we can consider the most specific term, which is "federal parliamentary republic."

Here is the final SPARQL query and the answer:

```sparql
SELECT ?governmentType WHERE {
  wd:Q183 wdt:P122 ?governmentType .
}
```

Answer: Germany is a federal parliamentary republic.

Let's finalize this with the answer function.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query returns multiple types of government, which might be confusing. It would be better to refine the query to return only the most specific type of government, which is 'federal parliamentary republic'. This can be achieved by adding a filter to prioritize the most specific type.

[Assistant]
To refine the query and ensure it returns only the most specific type of government, we can add a filter to prioritize the most specific type, which is "federal parliamentary republic" (wd:Q5440547).

Here is the refined SPARQL query:

```sparql
SELECT ?governmentType WHERE {
  wd:Q183 wdt:P122 ?governmentType .
  FILTER(?governmentType = wd:Q5440547)
}
```

Let's execute this refined query to see the results.

[Tool]
Got 1 row and 1 column:
| governmentType                               |
| -------------------------------------------- |
| federal parliamentary republic (wd:Q5440547) |

[Assistant]
The refined query successfully returns only the most specific type of government for Germany, which is "federal parliamentary republic."

Here is the final SPARQL query and the answer:

```sparql
SELECT ?governmentType WHERE {
  wd:Q183 wdt:P122 ?governmentType .
  FILTER(?governmentType = wd:Q5440547)
}
```

Answer: Germany is a federal parliamentary republic.

Let's finalize this with the answer function.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The output is correct and complete. The SPARQL query correctly identifies the type of government in Germany and returns the expected result.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?state WHERE {
  wd:Q1265 wdt:P131 ?state .
  ?state wdt:P17 wd:Q30 .
}

Got 5 rows and 1 column:
| state               |
| ------------------- |
| Nevada (wd:Q1227)   |
| Colorado (wd:Q1261) |
| Arizona (wd:Q816)   |
| Utah (wd:Q829)      |
| California (wd:Q99) |

The Colorado River runs through the states of Nevada, Colorado, Arizona, Utah, and California.

[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:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
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] which states does the colorado river run through?

[Assistant] Let's start by looking at some examples.

[Tool]
Example 1:
Question:
what is george washington's hometown?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q23 wdt:P19 ?x .
}

Using entities:
George Washington, also known as Father of the United States (wd:Q23): Founding Father and first U.S. president (1789–1797), revolutionary, statesperson, army officer, cartographer, politician, engineer, geometer, writer, farmer

Using properties:
place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt): most specific known birth location of a person, animal or fictional character, location

Example 2:
Question:
what movie did marlee matlin won an academy award for?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q213287 p:P166 ?p .
  ?p ps:P166 ?z ; pq:P805 ?y ; pq:P1686 ?x .
  ?y wdt:P31 wd:Q16913666 .
}

Using entities:
Academy Awards ceremony, also known as Academy Awards, Oscars (wd:Q16913666): annual event at which Academy Awards are presented
Marlee Matlin, also known as Marlee Beth Matlin (wd:Q213287): executive producer, television actor, American actress, social activist, stage actor, film actor, author, actor

Using properties:
award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as ps/p): award or recognition received by a person, organization or creative work
for work, also known as awarded for work, citation for award, for their work on, nominated for work (wd:P1686 as pq): qualifier of award received (P166) to specify the work that an award was given to the creator for
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
statement is subject of, also known as statement is the subject of, subject of the statement, subject of the claim, subject of, related item of statement (wd:P805 as pq): (qualifying) item that describes the relation identified in this statement

Example 3:
Question:
what town was abe lincoln born in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q91 wdt:P19 ?x .
}

Using entities:
Abraham Lincoln, also known as President Lincoln, Uncle Abe, Honest Abe, Abe Lincoln (wd:Q91): president of the United States from 1861 to 1865, military officer, statesperson, postmaster, politician, farmer, writer, lawyer

Using properties:
place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt): most specific known birth location of a person, animal or fictional character, location

[Assistant] Based on the examples, we can see that to answer a question about locations, we often need to use the property `place of birth` (P19). However, since we are asking about the states the Colorado River runs through, we need to look for a different property that relates to the course of a river. Let's search for the Colorado River entity first.

[Tool]
Top 10 entity alternatives:
1. Colorado River, also known as Rio de Buena Guia, Rio Colorado, Rio Colorado del Norte, Rio Colorado Del Norte, Rio Cosnina (wd:Q1265): major river in the western United States and Mexico
2. Colorado River (wd:Q270627): river in Argentina
3. Brazos River, also known as Los Brazos de Dios, Uhkto'wusi'yohe, Tokonohono, The River of the Arms of God, Rio Trinidad (wd:Q903306): river in Texas, United States
4. Colorado River (wd:Q847785): river in Texas, United States
5. Colorado River (wd:Q2984377): river in Costa Rica
6. Colorado River (wd:Q5148881): river in Bolivia
7. Colorado River (wd:Q5148884)
8. Colorado River, also known as Colorado River (Maipo) (wd:Q5148879): tributary of Maipo River in RM, Chile
9. Colorado river (wd:Q23649107): watercourse in Chile
10. Colorado River, also known as Rio Colorado (wd:Q5148883): river in Rondônia, Brazil

[Assistant] The top result is the Colorado River in the western United States and Mexico, which is the one we're interested in. Now let's find out what property might relate to the states the river runs through. We can try searching for properties of this entity that might indicate its course or the regions it passes through.

[Tool]
Top 10 property alternatives:
1. located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as p/wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
2. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
3. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as p/wdt): label for the items in their official language  or their original language, name
4. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
5. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as p/wdt): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
6. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as p/wdt): work where this item is described, attested in
7. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
8. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as p/wdt): main Wikimedia category
9. continent (wd:P30 as p/wdt): continent of which the subject is a part, located in/on physical feature

No other items found

[Assistant]
The property `located in the administrative territorial entity` (P131) seems like it could be relevant for finding the states the Colorado River runs through. Let's use this property in a SPARQL query to find the states.

I'll start with a simple query to see if we can get the states directly linked to the Colorado River via this property.

```sparql
SELECT DISTINCT ?state WHERE {
  wd:Q1265 wdt:P131 ?state .
}
```

Let's execute this query and see the results.

[Tool]
Got 7 rows and 1 column:
| state                       |
| --------------------------- |
| Nevada (wd:Q1227)           |
| Colorado (wd:Q1261)         |
| Sonora (wd:Q46422)          |
| Baja California (wd:Q58731) |
| Arizona (wd:Q816)           |
| Utah (wd:Q829)              |
| California (wd:Q99)         |

[Assistant]
The query returned the states through which the Colorado River runs. These states include:

- Nevada (wd:Q1227)
- Colorado (wd:Q1261)
- Sonora (wd:Q46422)
- Baja California (wd:Q58731)
- Arizona (wd:Q816)
- Utah (wd:Q829)
- California (wd:Q99)

Since the question specifically asks for states, and Sonora and Baja California are Mexican states, we can filter out the Mexican states if the user is only interested in U.S. states. However, the query as it stands correctly answers the question.

Here is the final SPARQL query and the answer:

```sparql
SELECT DISTINCT ?state WHERE {
  wd:Q1265 wdt:P131 ?state .
}
```

Answer: The Colorado River runs through the states of Nevada, Colorado, Sonora, Baja California, Arizona, Utah, and California.

If the user wants only U.S. states, we can refine the query further.

Would you like to refine the query to include only U.S. states?

[User]
Feedback (status=refine):
The query is correct but could be refined to filter out non-U.S. states if the user is only interested in U.S. states. We can add a condition to check if the state is located in the United States (wd:Q30). Here is the refined query:

```sparql
SELECT DISTINCT ?state WHERE {
  wd:Q1265 wdt:P131 ?state .
  ?state wdt:P17 wd:Q30 .
}
```

This will ensure that only U.S. states are included in the results.

[Assistant]
Thank you for the feedback. Let's refine the query to filter out non-U.S. states by adding a condition to check if the state is located in the United States (wd:Q30).

Here is the refined SPARQL query:

```sparql
SELECT DISTINCT ?state WHERE {
  wd:Q1265 wdt:P131 ?state .
  ?state wdt:P17 wd:Q30 .
}
```

Let's execute this refined query to get the U.S. states through which the Colorado River runs.

[Tool]
Got 5 rows and 1 column:
| state               |
| ------------------- |
| Nevada (wd:Q1227)   |
| Colorado (wd:Q1261) |
| Arizona (wd:Q816)   |
| Utah (wd:Q829)      |
| California (wd:Q99) |

[Assistant]
The refined query has successfully filtered out the non-U.S. states and returned the U.S. states through which the Colorado River runs. These states are:

- Nevada (wd:Q1227)
- Colorado (wd:Q1261)
- Arizona (wd:Q816)
- Utah (wd:Q829)
- California (wd:Q99)

Here is the final SPARQL query and the answer:

```sparql
SELECT DISTINCT ?state WHERE {
  wd:Q1265 wdt:P131 ?state .
  ?state wdt:P17 wd:Q30 .
}
```

Answer: The Colorado River runs through the states of Nevada, Colorado, Arizona, Utah, and California.

Thank you for the feedback, and I hope this refined query meets your requirements.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The output is correct and complete. The SPARQL query successfully identified all the states through which the Colorado River runs, and the human-readable answer accurately reflects the results.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?character ?voiceActor WHERE {
  wd:Q908772 wdt:P725 ?voiceActor .
  OPTIONAL {
    ?voiceActor rdfs:label ?voiceActorLabel .
    FILTER ( LANG( ?voiceActorLabel ) = "en" )
  }
  BIND( wd:Q908772 AS ?character ) OPTIONAL {
    ?character rdfs:label ?characterLabel .
    FILTER ( LANG( ?characterLabel ) = "en" )
  }
}

The results show that Mila Kunis (wd:Q37628) is indeed one of the voice actors for Meg Griffin (wd:Q908772) in Family Guy. Lacey Chabert (wd:Q232910) is also listed as a voice actor for the character, but the primary voice actor is Mila Kunis.

Let's construct the final SPARQL query to confirm this information and provide the answer.

```sparql
SELECT ?character ?voiceActor
WHERE {
  wd:Q908772 wdt:P725 ?voiceActor .
  OPTIONAL { ?voiceActor rdfs:label ?voiceActorLabel . FILTER(LANG(?voiceActorLabel) = "en") }
  BIND(wd:Q908772 AS ?character)
  OPTIONAL { ?character rdfs:label ?characterLabel . FILTER(LANG(?characterLabel) = "en") }
}
```

This query will return the character and the voice actor, along with their labels for better readability.

<tool_call>
{"name": "execute", "arguments": {"kg": "wikidata", "sparql": "SELECT ?character ?voiceActor\\nWHERE {\\n  wd:Q908772 wdt:P725 ?voiceActor .\\n  OPTIONAL { ?voiceActor rdfs:label ?voiceActorLabel . FILTER(LANG(?voiceActorLabel) = \\"en\\") }\\n  BIND(wd:Q908772 AS ?character)\\n  OPTIONAL { ?character rdfs:label ?characterLabel . FILTER(LANG(?characterLabel) = \\"en\\") }\\n}"}}
</tool_call>

[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:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
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] who does mila kunis play on family guy?

[Assistant] Let's start by looking at some examples.

[Tool]
Example 1:
Question:
who is the senator of the united states 2010?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x p:P39 ?p .
  ?p ps:P39 wd:Q4416090 ; pq:P580 ?y ; pq:P582 ?z .
  FILTER ( ( ?y < "2011-01-01T00:00:00Z" ^^ xsd:dateTime ) && ( ?z >= "2010-01-01T00:00:00Z" ^^ xsd:dateTime ) )
}

Using entities:
United States senator, also known as U.S. senator, US senator (wd:Q4416090): member of the United States Senate

Using properties:
position held, also known as function, held position, holds position, job, office held (wd:P39 as ps/p): subject currently or formerly holds the object position or public office
start time, also known as start date, since, valid, join time, joined (wd:P580 as pq): time an entity begins to exist or a statement starts being valid, point in time
end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as pq): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time

Example 2:
Question:
what are taylor swift's albums?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P31 wd:Q482994 ; wdt:P175 wd:Q26876 .
}

Using entities:
Taylor Swift, also known as Taylor Alison Swift (wd:Q26876): American singer-songwriter (born 1989), music video director, singer-songwriter, record producer, philanthropist, film director, lyricist, composer, singer, actor
album, also known as full album, record album, music album, full-length album, audio album (wd:Q482994): grouping of album releases by an artist usually released at the ...racks but in different formats for consumption (digital, CD, LP)

Using properties:
performer, also known as actor, sung by, singer, recording by, recorded by (wd:P175 as wdt): actor, musician, band or other performer associated with this role or musical work, contributor to the creative work or subject
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 3:
Question:
where is mitsubishi headquarters?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q183275 wdt:P159 ?x .
}

Using entities:
Mitsubishi, also known as Mitsubishi Companies, Mitsubishi Group of Companies (wd:Q183275): group of autonomous, Japanese multinational companies

Using properties:
headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as wdt): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place

[Assistant] Based on the examples, we need to identify the character Mila Kunis plays in Family Guy. Let's first search for Mila Kunis and Family Guy in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Mila Kunis, also known as Milena Markivna Kunis, Milena Markovna (wd:Q37628): Ukrainian-American actress, television producer, television actor, child actor, voice actor, film actor, model, actor
2. Mila (wd:Q335676): commune and town in Algeria
3. Wiska, also known as Nastya C., Nastya, Nastja, Mila, Nastika (wd:Q4149842): Ukrainian pornographic actress, pornographic actor, model
4. Mila, also known as Mila District (wd:Q9384879): district in Pidie Regency, Aceh Province, Indonesia
5. Mila, also known as Mila (given name), Mila (first name) (wd:Q3217317): unisex given name
6. Mila (wd:Q132982762): 2025 single by Princ od Vranje
7. Milá (wd:Q12037654): village in Most District of Ústí nad Labem region
8. Mila (wd:Q66759429): American pornographic actress, pornographic actor, film director
9. Mila (wd:Q132982762): 2025 single by Princ od Vranje
10. Milá (wd:Q1935990): mountain in Czech Republic

[Tool]
Top 10 entity alternatives:
1. Family Guy (wd:Q5930): American adult animated sitcom
2. Family Guy (wd:Q5930): American adult animated sitcom
3. Family Guy (wd:Q5433143): pinball table
4. Family Guy, also known as Family Guy franchise (wd:Q55012102): American media franchise
5. Family Guy (wd:Q108370888): video game series
6. Inside Family Guy (wd:Q27877310): episode of Family Guy (S15 E4)
7. Family Guy: Uncensored, also known as Uncensored (wd:Q18928703): iOS game
8. Family Guy Online (wd:Q5433145): 2012 video game
9. Family Guy controversies, also known as Criticism of Family Guy (wd:Q5186798): Wikimedia list article
10. Family Guy Lite (wd:Q102842382): episode of Family Guy (S17 E14)

[Assistant]
From the search results, we can see that the correct entities for Mila Kunis and Family Guy are:

- Mila Kunis: wd:Q37628
- Family Guy: wd:Q5930

Next, let's find out what character Mila Kunis voices in Family Guy. We'll look for a property that connects actors to their roles in TV shows.

[Tool]
Top 10 property alternatives:
1. Behind The Voice Actors person ID, also known as behindthevoiceactors.com person ID, BTVA person ID, BTVA ID (wd:P5007 as p/wdt): identifier of a person on the website Behind The Voice Actors
2. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as p/wdt): language(s) that a person or a people speaks, writes or signs, including the native language(s)
3. native language, also known as first language, L1 speaker of, language native, mother tongue (wd:P103 as p/wdt): language or languages a person has learned from early childhood, languages spoken, written or signed
4. occupation, also known as job, work, vocation, profession, employment (wd:P106 as p/wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
5. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as p/wdt): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)
6. pseudonym, also known as nom de plume, nom-de-plume, nome de guerre, pen name, ring name (wd:P742 as p/wdt): alias used by someone (for nickname use P1449), name
7. work period (start), also known as start working, flourished (start), start time for work, start date of activity, fl. (start) (wd:P2031 as p/wdt): start of period during which a person or group flourished (fl. = "floruit") in their professional activity, start time, floruit
8. represented by, also known as agent, managed by, manager, managing agent, rep (wd:P1875 as p/wdt): person or agency that represents or manages the subject
9. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as p/wdt): the object is a country that recognizes the subject as its citizen, country
10. MovieGe person ID, also known as movie.ge person ID (wd:P7653 as p/wdt): identifier for a person on the movie.ge site

No other items found

[Assistant]
It seems that the property "voice role" is not directly listed among the top properties for Mila Kunis. However, we can try using the property `voice actor` or `voice role` to find the character she voices in Family Guy. Let's check the property `voice actor` (wd:P725).

We will use the `list` function to see if there are any triples connecting Mila Kunis to a character in Family Guy through the `voice actor` property.

[Tool] Got no rows and 3 columns

[Assistant]
It appears that there are no direct triples connecting Mila Kunis to a character in Family Guy using the `voice actor` property. Let's try another approach by searching for the character Mila Kunis voices in Family Guy directly.

We can use the `search_object_of_property` function to find the character Mila Kunis voices in Family Guy.

[Tool]
Top 10 entity alternatives:
1. Mila Kunis, also known as Milena Markivna Kunis, Milena Markovna (wd:Q37628): Ukrainian-American actress, television producer, television actor, child actor, voice actor, film actor, model, actor
2. Guy Pearce, also known as Guy Parce (wd:Q223745): English-born Australian actor, television actor, film director, stage actor, film actor, musician, actor
3. Jasmine Guy (wd:Q448141): American actress, director, singer, and dancer (born 1962), television actor, film director, voice actor, stage actor, film actor, dancer, singer
4. Guy Nadon (wd:Q3122036): French-Canadian actor, television actor, dub actor, actor
5. Guy Mowbray, also known as Guy Nicholas Mowbray (wd:Q5622489): English association football commentator (born 1972), sports commentator, broadcaster
6. Zwangere Guy, also known as Omar G, Gorik van Oudheusden (wd:Q30524684): construction worker, Belgian rapper, screenwriter, voice actor, film actor, rapper, baker
7. Guy Piérauld, also known as Guy Pierauld (wd:Q3122079): French actor, film actor, dub actor
8. Guy Kelly (wd:Q115633638): voice actor
9. Guy Paul (wd:Q111336552): American actor, actor
10. Swiss Family Fraunfelder, also known as Fraunfelder Family, Swiss Echo Yodelers, The Fraunfelder Family (wd:Q29784900): singing group

No other items found

No literal items found

[Assistant]
It seems that the search did not return the specific character Mila Kunis voices in Family Guy. Let's try a different approach by searching for the character directly and then checking if Mila Kunis is associated with it.

First, let's search for the character "Meg Griffin" in Family Guy, as this is the character Mila Kunis is known to voice.

[Tool]
Top 10 entity alternatives:
1. Stewie Griffin: The Untold Story, also known as Bang-o Was His Name-o, Stewie B. Goode, Stewie and Stu's Excellent Adventure, Family Guy Presents Stewie Griffin: The Untold Story, Bango Was His Name, Oh! (wd:Q684288): 2005 American adult animated Driect-to-DVD film Directed by Peter Michels and Peter Shin
2. Family Guy (wd:Q5930): American adult animated sitcom
3. Family Guy (wd:Q5930): American adult animated sitcom
4. Meg Griffin, also known as Megan Griffin, Megatron "Meg" Harvey Oswald Griffin, Megatron Harvey Oswald Griffin, Megan "Meg" Griffin (wd:Q908772): fictional character from the Family Guy franchise, high school student
5. Griffin family (wd:Q10860912): fictional family from the animated series Family Guy
6. Family Guy (wd:Q5433143): pinball table
7. Family Guy, also known as Family Guy franchise (wd:Q55012102): American media franchise
8. Meg Griffin (wd:Q6807983): American radio disc jockey, radio personality, disc jockey
9. Family Guy: Peter Griffin's Guide to the Holidays, also known as Peter Griffin's Guide to the Holidays (wd:Q5433141): book by Danny Smith
10. Family Guy (wd:Q108370888): video game series

[Assistant]
From the search results, we can see that the correct entity for Meg Griffin is:

- Meg Griffin: wd:Q908772

Now, let's verify if Mila Kunis is indeed the voice actor for Meg Griffin by checking the `voice actor` property (wdt:P725) for Meg Griffin.

[Tool]
Got 2 rows and 3 columns:
| subject                  | property               | object                     |
| ------------------------ | ---------------------- | -------------------------- |
| Meg Griffin (wd:Q908772) | voice actor (wdt:P725) | Mila Kunis (wd:Q37628)     |
| Meg Griffin (wd:Q908772) | voice actor (wdt:P725) | Lacey Chabert (wd:Q232910) |

[Assistant]
The results show that Mila Kunis (wd:Q37628) is indeed one of the voice actors for Meg Griffin (wd:Q908772) in Family Guy. Lacey Chabert (wd:Q232910) is also listed as a voice actor for the character, but the primary voice actor is Mila Kunis.

Let's construct the final SPARQL query to confirm this information and provide the answer.

```sparql
SELECT ?character ?voiceActor
WHERE {
  wd:Q908772 wdt:P725 ?voiceActor .
  OPTIONAL { ?voiceActor rdfs:label ?voiceActorLabel . FILTER(LANG(?voiceActorLabel) = "en") }
  BIND(wd:Q908772 AS ?character)
  OPTIONAL { ?character rdfs:label ?characterLabel . FILTER(LANG(?characterLabel) = "en") }
}
```

This query will return the character and the voice actor, along with their labels for better readability.

<tool_call>
{"name": "execute", "arguments": {"kg": "wikidata", "sparql": "SELECT ?character ?voiceActor\\nWHERE {\\n  wd:Q908772 wdt:P725 ?voiceActor .\\n  OPTIONAL { ?voiceActor rdfs:label ?voiceActorLabel . FILTER(LANG(?voiceActorLabel) = \\"en\\") }\\n  BIND(wd:Q908772 AS ?character)\\n  OPTIONAL { ?character rdfs:label ?characterLabel . FILTER(LANG(?characterLabel) = \\"en\\") }\\n}"}}
</tool_call>

[User]
Feedback (status=done):
The SPARQL query is correct and returns the expected results. It confirms that Mila Kunis (wd:Q37628) is the primary voice actor for Meg Griffin (wd:Q908772) in Family Guy, with Lacey Chabert (wd:Q232910) also listed as a voice actor. The query follows all the rules and provides the necessary information.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?placeOfDeath ?placeOfDeathLabel WHERE {
  wd:Q1203 wdt:P20 ?placeOfDeath .
  OPTIONAL {
    ?placeOfDeath rdfs:label ?placeOfDeathLabel .
    FILTER ( LANG( ?placeOfDeathLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| placeOfDeath           | placeOfDeathLabel  |
| ---------------------- | ------------------ |
| New York City (wd:Q60) | New York City (en) |

New York City

[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:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
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] where do john lennon die?

[Assistant] Let's start by looking at some examples.

[Tool]
Example 1:
Question:
what did bruce jenner win gold for?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q365144 p:P1344 ?p .
  ?p ps:P1344 ?x ; pq:P166 wd:Q15243387 .
}

Using entities:
Olympic gold medal (wd:Q15243387): first-place medal awarded to Olympic Games participants
Caitlyn Jenner (wd:Q365144): American media personality and retired decathlete, racing automobile driver, motivational speaker, athletics competitor, sports commentator, television actor, businessperson, film producer, actor, model

Using properties:
participant in, also known as participated in, present at, takes part, took part, took part in (wd:P1344 as ps/p): event in which a person or organization was/is a participant; inverse of P710 or P1923, significant event, part of
award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as pq): award or recognition received by a person, organization or creative work

Example 2:
Question:
when did the 7th harry potter book come out?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q46758 wdt:P577 ?x .
}

Using entities:
Harry Potter and the Deathly Hallows, also known as last Harry Potter book (wd:Q46758): fantasy novel by J. K. Rowling concluding the Harry Potter series

Using properties:
publication date, also known as launched, published, publication time, publication, pubdate (wd:P577 as wdt): date or point in time when a work was first published or released, point in time

Example 3:
Question:
what style of art does andy warhol do?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q5603 wdt:P135 ?x .
}

Using entities:
Andy Warhol, also known as Andrew Warhola, Andrew Warhol, Drella, Andrej Varchol, Andrej Warhol (wd:Q5603): American artist, film director, and producer (1928–1987), installation artist, performance artist, cinematographer, graphic artist, visual artist, film producer, film director, draftsperson, photographer, screenwriter, illustrator, printmaker, filmmaker, merchant, sculptor, producer, designer, painter, diarist, author, artist

Using properties:
movement, also known as subculture, trend, scientific movement, school, philosophical movement (wd:P135 as wdt): literary, artistic, scientific or philosophical movement or scen...ed with this person or work. For political ideologies use P1142.

[Assistant]
From the examples, we can see how specific entities and properties are used to construct SPARQL queries. For the question about where John Lennon died, we need to identify the entity for John Lennon and the property for place of death.

Let's start by searching for the entity "John Lennon".

[Tool]
Top 10 entity alternatives:
1. John Lennon, also known as John Winston Ono Lennon, John Ono Lennon (wd:Q1203): British musician (1940–1980), political activist, singer-songwriter, recording artist, record producer, peace activist, public figure, film director, film producer, prose writer, film actor, guitarist, composer, painter, pianist, singer, writer, actor, poet
2. Liverpool John Lennon Airport, also known as John Lennon, John Lennon airport, Liverpool Airport, Liverpool (John Lennon), LPL (wd:Q8727): airport in Liverpool, England
3. John Lennon Silva Santos, also known as John Lennon (wd:Q6244563): association football player, Brazilian footballer
4. John Brown Lennon, also known as John B. Lennon, John Lennon (wd:Q6223555): American labor leader (1850–1923), trade unionist
5. John Lennon, also known as J. John Lennon, Justin John Lennon (wd:Q11979004): Scottish tourism researcher, university teacher, tourism scholar
6. John Lennon (wd:Q65548791): Irish hurler born 1996
7. John Lennon (wd:Q6244553): British naval captain, military personnel
8. John Lennon (wd:Q12871620): 1855 - 3 Aug 1921
9. John Lennon (wd:Q125643070): 2005 edition of written work by Jordi Sierra i Fabra
10. John Lennon (wd:Q106781630): 2015 song by SCH

[Assistant] The top result is the correct entity for John Lennon, which is `wd:Q1203`. Now, let's find the property for "place of death". We can use the `search_property` function to look for it.

[Tool]
Top 10 property alternatives:
1. place of death, also known as POD, location of death, killed in, deathplace, died in (wd:P20 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): most specific known (e.g. city instead of country, or hospital i... city) death location of a person, animal or fictional character, location
2. place of burial, also known as interment, interment location, interment place, interred at, location of burial (wd:P119 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): location of grave, resting place, place of ash-scattering, etc. ...veral places: e.g., re-burials, parts of body buried separately., location
3. date of death, also known as DOD, deathdate, died, died on, year of death (wd:P570 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): dissolved, abolished or demolished date, date on which the subject died, end time
4. category for people who died here, also known as category for place of death, category of people who died here (wd:P1465 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): category item for people who died in this location, related category
5. manner of death, also known as type of death, nature of death, death manner, death type, circumstance of death (wd:P1196 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): general circumstances of a person's death; e.g. natural causes, ...ysiological mechanism, e.g. heart attack, trauma, pneumonia etc.
6. number of deaths, also known as dead, qty fatalities, qty deaths, number of fatalities, fatalities (wd:P1120 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): total (cumulative) number of people who died since start as a direct result of an event or cause
7. category for people buried here, also known as buried here: Wikimedia category for, category of people buried here, category for place of burial, category for burials (wd:P1791 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): Wikimedia category for people with a burial site within this area, related category
8. cause of death, also known as death cause, murder method, method of murder, die of, die from (wd:P509 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): underlying or immediate cause of death.  Underlying cause (e.g. ...adest category, e.g. natural causes, accident, homicide, suicide
9. date of burial or cremation, also known as burial date, cremation date, date of cremation, funeral date (wd:P4602 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): date on which the person was buried or cremated soon after death, point in time
10. commemorates, also known as monument to, memorial to, memorializes, marks, in memory of (wd:P547 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): what the place, monument, memorial, or holiday, commemorates, main subject

[Assistant]
The correct property for "place of death" is `wd:P20`. Now, we can construct a simple SPARQL query to find the place of death for John Lennon.

Let's execute the following SPARQL query:

```sparql
SELECT ?placeOfDeath WHERE {
  wd:Q1203 wdt:P20 ?placeOfDeath .
}
```

This query will return the place of death for John Lennon.

[Tool]
Got 1 row and 1 column:
| placeOfDeath           |
| ---------------------- |
| New York City (wd:Q60) |

[Assistant]
The SPARQL query has returned the place of death for John Lennon, which is New York City (wd:Q60).

To provide a complete and clear answer, we can include the label of the place of death in the query. Let's modify the query to include the label of the place of death.

```sparql
SELECT ?placeOfDeath ?placeOfDeathLabel WHERE {
  wd:Q1203 wdt:P20 ?placeOfDeath .
  OPTIONAL { ?placeOfDeath rdfs:label ?placeOfDeathLabel . FILTER(LANG(?placeOfDeathLabel) = "en") }
}
```

This query will return both the IRI and the English label of the place of death.

[Tool]
Got 1 row and 2 columns:
| placeOfDeath           | placeOfDeathLabel  |
| ---------------------- | ------------------ |
| New York City (wd:Q60) | New York City (en) |

[Assistant]
The SPARQL query has successfully returned the place of death for John Lennon, which is New York City (wd:Q60), along with its English label.

Now, I will provide the final answer using the `answer` function.

```sparql
SELECT ?placeOfDeath ?placeOfDeathLabel WHERE {
  wd:Q1203 wdt:P20 ?placeOfDeath .
  OPTIONAL { ?placeOfDeath rdfs:label ?placeOfDeathLabel . FILTER(LANG(?placeOfDeathLabel) = "en") }
}
```

The place of death for John Lennon is New York City.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The output is correct and complete. The SPARQL query correctly identifies the place of death for John Lennon and returns the IRI along with the label. The answer provided, 'New York City', is accurate based on the execution result.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?team WHERE {
  wd:Q221048 wdt:P54 ?team .
}

Jackie Robinson played for the Los Angeles Dodgers.

[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:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
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] what baseball team was jackie robinson on?

[Assistant] Let's start by looking at some examples.

[Tool]
Example 1:
Question:
where is tommy emmanuel from?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q310298 wdt:P19 ?x .
}

Using entities:
Tommy Emmanuel, also known as William Thomas Emmanuel (wd:Q310298): Australian guitarist, jazz guitarist, percussionist, jazz musician, songwriter, guitarist, composer, lecturer, singer

Using properties:
place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt): most specific known birth location of a person, animal or fictional character, location

Example 2:
Question:
who was the president of indian national congress?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P39 wd:Q7241327 .
}

Using entities:
President of the Indian National Congress, also known as president of Indian National Congress (wd:Q7241327): head of INC

Using properties:
position held, also known as function, held position, holds position, job, office held (wd:P39 as wdt): subject currently or formerly holds the object position or public office

Example 3:
Question:
where did saki live?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q311526 wdt:P19 ?x .
}

Using entities:
Saki, also known as H. H. Munro, Hector Hugh Munro (wd:Q311526): British writer, playwright, journalist, historian, novelist, writer

Using properties:
place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt): most specific known birth location of a person, animal or fictional character, location

[Assistant] Based on the examples, we need to identify the entity for Jackie Robinson and the property for the baseball team he played for. Let's start by searching for Jackie Robinson in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Jackie Robinson, also known as Jack Roosevelt "Jackie" Robinson (wd:Q221048): American baseball player, athletics competitor, military officer, basketball coach, baseball player, vice president
2. Jackie Robinson, also known as Jack Robinson, Robert Lloyd Jackson Robinson (wd:Q731871): American basketball player (1927–2022), basketball player
3. Jackie Robinson (wd:Q1631748): American basketball player, basketball player
4. Jackie Robinson (wd:Q6116621): English footballer (1917–1972), association football player
5. Jackie Robinson, also known as Harry Hippy, Loren Jackson Robinson (wd:Q3805723): Jamaican musician, singer
6. Jackie Robinson (wd:Q25206446): 2016 film by Ken Burns
7. Jackie Robinson (wd:Q110043656): sketch from Saturday Night Live
8. Jackie Robinson (wd:Q100985462): college basketball player (1991–1993) South Carolina State, basketball player
9. Jackie Robinson (wd:Q112457903): 1944-
10. Jackie Robinson (wd:Q124413502): lecturer of marketing, academic, university teacher, researcher, academic

[Assistant] The correct entity for Jackie Robinson, the American baseball player, is `wd:Q221048`. Now, let's find the property that indicates the baseball team he played for. We can search for properties related to "baseball team" or "played for" for this entity.

[Tool]
Top 10 property alternatives:
1. member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as p/wdt): sports teams or clubs that the subject represents or represented, member of
2. MLB.com player ID, also known as milb.com player ID, MLB ID, Minor League Baseball player ID, Minor League Baseball ID, Major League Baseball player ID (wd:P3541 as p/wdt): identifier for a Major League Baseball player
3. FanGraphs player ID, also known as Fangraphs ID (wd:P3574 as p/wdt): ID for a baseball player in FanGraphs.com
4. league or competition, also known as tournament, sports league, division, cup, competition (wd:P118 as p/wdt): league or competition in which team or player has played, or in which an event occurs, participant in
5. position played on team / speciality, also known as position (on team), speciality, specialism, position, player position (wd:P413 as p/wdt): position or specialism of a player on a team
6. The Baseball Cube player ID, also known as TheBaseballCube.com ID, TheBaseballCube.com player ID (wd:P4731 as p/wdt): identifier of a baseball player at thebaseballcube.com
7. sport, also known as play, plays, sport played, sports (wd:P641 as p/wdt): sport that the subject participates or participated in or is associated with
8. Baseball Reference minor & foreign league player ID, also known as brcmilbid (wd:P1826 as p/wdt): identifier for a Minor League Baseball player assigned by Baseball-Reference.com
9. Baseball Reference major league player ID, also known as brcmlbid (wd:P1825 as p/wdt): identifier for a Major League Baseball player assigned by Baseball-Reference.com
10. ESPN.com MLB player ID, also known as ESPN MLB player ID (wd:P3571 as p/wdt): ID for a Major League Baseball player at ESPN.com

No other items found

[Assistant]
The property `wdt:P54` (member of sports team) seems to be the most relevant for finding the baseball team Jackie Robinson played for. Let's construct a SPARQL query to retrieve this information.

```sparql
SELECT ?team WHERE {
  wd:Q221048 wdt:P54 ?team .
}
```

I will now execute this query to get the result.

[Tool]
Got 1 row and 1 column:
| team                             |
| -------------------------------- |
| Los Angeles Dodgers (wd:Q334634) |

[Assistant]
The SPARQL query successfully returned the baseball team Jackie Robinson played for, which is the Los Angeles Dodgers.

Here is the final SPARQL query and the answer:

```sparql
SELECT ?team WHERE {
  wd:Q221048 wdt:P54 ?team .
}
```

Answer: Jackie Robinson played for the Los Angeles Dodgers.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The output is correct and complete. The SPARQL query correctly identifies the team Jackie Robinson played for, and the answer provided is accurate.