PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( DISTINCT ?country ) AS ?count ) WHERE {
  ?mountain wdt:P31 wd:Q8502 ; wdt:P2044 ?elevation ; wdt:P17 ?country .
  FILTER ( ?elevation > 2000 )
}

There are 131 countries that have mountains whose peaks are higher than 2000 meters above sea level.

How many countries have mountains whose peaks are higher than 2000m above sea level?

[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 with notes:
1. When direct properties are missing, chain related properties (e.g., child→child for grandchildren) or search for indirect connections to answer complex relationship queries.
2. For set/class queries (e.g., all cities, all holidays), use instance/subclass chains (P31/P279) for completeness and relevant filters. Be aware of data incompleteness and schema inconsistencies in Wikidata.
3. If queries return too many irrelevant or too few results, try varying properties (country, location, observed in, etc.) and subclass chains, but be ready to report data/model limitations if results remain incomplete or noisy.
4. When a direct property or class is missing or inconsistently used, try related or broader properties/classes (e.g., use inception for independence date, or musical work/composition for musicals) to increase recall.
5. For calculated properties (e.g., population density), combine relevant direct properties (e.g., population, area) in SPARQL queries, as Wikidata may not store the derived value directly.
6. When entity search returns multiple candidates, use context (description, instance type, location, etc.) to disambiguate and select the most relevant entity for the query.

No general notes for all knowledge graphs available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. 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] How many countries have mountains whose peaks are higher than 2000m above sea level?

[Assistant]
To answer this question, I need to find countries that have mountains with peaks higher than 2000 meters above sea level. The steps are:

1. Identify the property for "mountain" and "peak elevation" in Wikidata.
2. Find mountains with peak elevation greater than 2000 meters.
3. Find the countries where these mountains are located.
4. Count the distinct countries.

I will start by searching for the property related to "peak elevation" for mountains.

[Tool]
Top 10 property alternatives:
1. highest point, also known as zenith, tallest point, summit, pinnacle, highest peak (wd:P610 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): point with highest elevation in a region or path, subproperty of has part(s)
2. elevation above sea level, also known as elevation, MASL, MAMSL, height, elevation above mean sea level (wd:P2044 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): height of the item (geographical object) as measured relative to sea level
3. ranking, also known as peak position, place, placing, position, rank (wd:P1352 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): subject's ordinal position as qualitatively evaluated relative to other members of a group
4. maximum operating altitude, also known as ceiling, maximum altitude, service ceiling (wd:P2254 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): ceiling or maximum density altitude at which an aircraft can operate, subproperty of elevation above sea level
5. cumulative elevation gain (wd:P7297 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): measure of the difference in height between two points on the terrain, when following a track
6. parent peak, also known as parent mountain (wd:P3137 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): higher peak whose territory this peak resides in, where the terr...col, which can be selected based on several competing approaches
7. mountain range, also known as hill range, system of mountains, range, parent range, mountain system (wd:P4552 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): range or subrange to which the geographical item belongs, subproperty of geomorphological unit
8. Peakbagger mountain ID, also known as Peakbagger ID, Peakbagger peak ID (wd:P3109 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): identifier for a mountain, on the www.peakbagger.com website
9. PeakVisor range ID (wd:P9569 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): identifier for a mountain range in PeakVisor
10. PeakVisor peak ID (wd:P9568 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): identifier for a mountain or hill in PeakVisor

[Assistant] The property "elevation above sea level" (wdt:P2044) is suitable to find the height of mountains. Next, I will find mountains (instance of mountain) with elevation above sea level greater than 2000 meters and then find the countries where these mountains are located.

[Tool]
Got 131 rows and 1 column, showing the first 5 and last 5 rows below:
| country                                    |
| ------------------------------------------ |
| Cameroon (wd:Q1009)                        |
| Lesotho (wd:Q1013)                         |
| Libya (wd:Q1016)                           |
| Madagascar (wd:Q1019)                      |
| Malawi (wd:Q1020)                          |
| ...                                        |
| Burundi (wd:Q967)                          |
| Democratic Republic of the Congo (wd:Q974) |
| Djibouti (wd:Q977)                         |
| Equatorial Guinea (wd:Q983)                |
| Eritrea (wd:Q986)                          |

[Assistant] I found 131 distinct countries that have mountains with peaks higher than 2000 meters above sea level. Now I will count these countries to provide the final answer.

[Tool]
Got 1 row and 1 column:
| count         |
| ------------- |
| 131 (xsd:int) |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?director ?directorLabel WHERE {
  wd:Q55621114 wdt:P57 ?director .
  OPTIONAL {
    ?director rdfs:label ?directorLabel FILTER ( LANG( ?directorLabel ) = "en" )
  }
}

The director of Llamas with Hats is Jason Steele.

Who was the director of Llamas with Hats ?

[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 with notes:
1. When direct properties are missing, chain related properties (e.g., child→child for grandchildren) or search for indirect connections to answer complex relationship queries.
2. For set/class queries (e.g., all cities, all holidays), use instance/subclass chains (P31/P279) for completeness and relevant filters. Be aware of data incompleteness and schema inconsistencies in Wikidata.
3. If queries return too many irrelevant or too few results, try varying properties (country, location, observed in, etc.) and subclass chains, but be ready to report data/model limitations if results remain incomplete or noisy.
4. When a direct property or class is missing or inconsistently used, try related or broader properties/classes (e.g., use inception for independence date, or musical work/composition for musicals) to increase recall.
5. For calculated properties (e.g., population density), combine relevant direct properties (e.g., population, area) in SPARQL queries, as Wikidata may not store the derived value directly.
6. When entity search returns multiple candidates, use context (description, instance type, location, etc.) to disambiguate and select the most relevant entity for the query.

No general notes for all knowledge graphs available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. 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 was the director of Llamas with Hats ?

[Assistant] To answer the question "Who was the director of Llamas with Hats?", I will first search for the entity "Llamas with Hats" in Wikidata to find its identifier. Then, I will look for the property that indicates the director of this entity. Finally, I will query the director of "Llamas with Hats".

[Tool]
Top 10 entity alternatives:
1. Llamas with Hats (wd:Q55621114): instance of YouTube series, instance of web series, animated video series
2. hoodoos with hats (wd:Q181292)
3. Bathers with Hats (wd:Q131580210): painting by Aristarkh Lentulov, instance of painting
4. Men Without Hats (wd:Q225422): Canadian musical group; synthpop and new wave band, instance of musical group
5. Man With Two Hats (wd:Q22961916): war memorial in Apeldoorn, Netherlands, instance of war memorial, instance of sculpture
6. Man With Two Hats (wd:Q99511287): sculpture by Henk Visch in Ottawa, Canada, instance of war memorial, instance of sculpture
7. Contractors with consultant's hats (wd:Q77534162): scientific article published on 01 February 1984, instance of scholarly article
8. Five Men with Hats (wd:Q20489934): painting by Lester Johnson, instance of painting
9. fairies with three-cornered hats, also known as F236.3.1. (wd:Q117202500): narrative motif documented in Thompson's Motif-Index of Folk-Literature, instance of narrative motif, instance of folklore motif
10. Three women with hats (wd:Q124078116): painting by George Hendrik Breitner, instance of painting

[Assistant] I found the entity "Llamas with Hats" with the identifier wd:Q55621114. Now I will look for the property that indicates the director of this entity. Commonly, the property for director is "director" (wdt:P57). I will check if this property is used for this entity.

[Tool]
Got 1 row and 3 columns:
| subject                         | property           | object                      |
| ------------------------------- | ------------------ | --------------------------- |
| Llamas with Hats (wd:Q55621114) | director (wdt:P57) | Jason Steele (wd:Q57807804) |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?date WHERE {
  wd:Q69163529 wdt:P585 ?date .
}

The Berlin Wall fell in the year 1989.

[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 with notes:
1. When direct properties are missing, chain related properties (e.g., child→child for grandchildren) or search for indirect connections to answer complex relationship queries.
2. For set/class queries (e.g., all cities, all holidays), use instance/subclass chains (P31/P279) for completeness and relevant filters. Be aware of data incompleteness and schema inconsistencies in Wikidata.
3. If queries return too many irrelevant or too few results, try varying properties (country, location, observed in, etc.) and subclass chains, but be ready to report data/model limitations if results remain incomplete or noisy.
4. When a direct property or class is missing or inconsistently used, try related or broader properties/classes (e.g., use inception for independence date, or musical work/composition for musicals) to increase recall.
5. For calculated properties (e.g., population density), combine relevant direct properties (e.g., population, area) in SPARQL queries, as Wikidata may not store the derived value directly.
6. When entity search returns multiple candidates, use context (description, instance type, location, etc.) to disambiguate and select the most relevant entity for the query.

No general notes for all knowledge graphs available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. 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 year did the Berlin Wall fall?

[Assistant]
To answer the question "What year did the Berlin Wall fall?" I need to find the event "fall of the Berlin Wall" or the "Berlin Wall" entity and check for the date or year associated with its fall or demolition.

Step 1: Search for the entity "Berlin Wall" in Wikidata to identify its identifier.

[Tool]
Top 10 entity alternatives:
1. Berlin Wall (wd:Q47512154): painting by Boris Artzybasheff, instance of painting
2. Berlin Wall, also known as Star Trek Berlin Wall (wd:Q108530024): Berlin Wall as depicted in the Star Trek multiverse, instance of fictional architectural structure
3. Berlini wall (wd:Q5086): barrier constructed by the German Democratic Republic, enclosing West Berlin, instance of destroyed building or structure, instance of tourist attraction, instance of separation barrier, instance of fortified line, instance of cordon
4. fall of the Berlin Wall, also known as demolition of the Berlin Wall, Berlin Wall fall, Berlin Wall demolition (wd:Q69163529): historical event in November 1989 where the Berlin Wall was opened and demolished, instance of historical event, instance of demolition
5. Tear down this wall!, also known as Brandenburg Gate Speech, Ronald Reagan's Berlin Wall Speech, Remarks at Brandenburg Gate, Berlin, Germany, Berlin Wall Speech (wd:Q1994106): speech delivered by President Ronald Reagan of the USA in West Berlin in June 1987, instance of oration
6. Berlin Customs Wall, also known as Berliner Zoll- und Akzisemauer (wd:Q532578): instance of city walls, wall of berlin to 1860
7. Berliner Mauerweg, also known as Berlin Wall Trail (wd:Q20827135): instance of long-distance cycling route, instance of hiking trail
8. The Berlin Wall (wd:Q7716567): instance of video game, 1991 video game
9. Atlanta's Berlin Wall (wd:Q104901839): event during the civil rights movement in Atlanta, Georgia, United States in 1962.
10. Berlin Wall Memorial (wd:Q126680173): piece of the Berlin Wall at the NATO HQ in Brussels, instance of memorial

[Assistant]
I found the relevant entity for the Berlin Wall as a barrier constructed by the German Democratic Republic with the identifier wd:Q5086. Also, there is a specific event "fall of the Berlin Wall" with the identifier wd:Q69163529 which is described as the historical event in November 1989 when the Berlin Wall was opened and demolished.

Step 2: I will now query the date or year of the event "fall of the Berlin Wall" (wd:Q69163529).

[Tool]
Got 1 row and 2 columns:
| date                                | dateLabel                    |
| ----------------------------------- | ---------------------------- |
| 1989-11-09T00:00:00Z (xsd:dateTime) | fall of the Berlin Wall (en) |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?nickname WHERE {
  wd:Q1768 wdt:P1449 ?nickname .
  FILTER ( LANG( ?nickname ) = "en" )
}

Got 1 row and 1 column:
| nickname       |
| -------------- |
| Lady Ella (en) |

The English nickname of Ella Fitzgerald is "Lady Ella."

What is the english nickname of Ella Fitzgerald?

[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 with notes:
1. When direct properties are missing, chain related properties (e.g., child→child for grandchildren) or search for indirect connections to answer complex relationship queries.
2. For set/class queries (e.g., all cities, all holidays), use instance/subclass chains (P31/P279) for completeness and relevant filters. Be aware of data incompleteness and schema inconsistencies in Wikidata.
3. If queries return too many irrelevant or too few results, try varying properties (country, location, observed in, etc.) and subclass chains, but be ready to report data/model limitations if results remain incomplete or noisy.
4. When a direct property or class is missing or inconsistently used, try related or broader properties/classes (e.g., use inception for independence date, or musical work/composition for musicals) to increase recall.
5. For calculated properties (e.g., population density), combine relevant direct properties (e.g., population, area) in SPARQL queries, as Wikidata may not store the derived value directly.
6. When entity search returns multiple candidates, use context (description, instance type, location, etc.) to disambiguate and select the most relevant entity for the query.

No general notes for all knowledge graphs available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. 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 is the english nickname of Ella Fitzgerald?

[Assistant] To answer the question about the English nickname of Ella Fitzgerald, I will first search for the entity "Ella Fitzgerald" in Wikidata to find her identifier. Then, I will look for properties related to nicknames or aliases associated with her. Finally, I will filter for the English nickname if available.

[Tool]
Top 10 entity alternatives:
1. Ella Fitzgerald, also known as The First Lady of Jazz, The First Lady of Song, Lady Ella, Queen of Jazz (wd:Q1768): American jazz singer (1917–1996), singer-songwriter, instance of human, recording artist, jazz musician, film actor, bandleader, conductor, composer, singer
2. Ella Fitzgerald, also known as Donnell Robinson (wd:Q100786004): American drag queen, instance of human, drag queen
3. Ella Fitzgerald (wd:Q28732978): tram stop in the 19th arrondissement of Paris, France, instance of tram stop
4. Ella Fitzgerald 1939, also known as 1939 (wd:Q48833865): 1990 compilation album by Ella Fitzgerald, instance of album
5. Ella Fitzgerald 1938-1939, also known as 1938-1939 (wd:Q48833657): 1990 compilation album by Ella Fitzgerald, instance of album
6. Ella Fitzgerald 1935-1937, also known as 1935-1937 (wd:Q30880987): 1990 compilation album by Ella Fitzgerald, instance of album
7. Ella Fitzgerald 1937-1938, also known as 1937-1938 (wd:Q30880995): 1990 compilation album by Ella Fitzgerald, instance of album
8. Ella Fitzgeraldstraat (wd:Q52321478): street in Amsterdam, the Netherlands, instance of street
9. Ella G. Fitzgerald (wd:Q75934694): Peerage person ID=412952, instance of human
10. Ella Fitzgeraldstraat (wd:Q19116594): street in Arnhem, the Netherlands, instance of street

[Assistant] The entity for Ella Fitzgerald, the American jazz singer, is wd:Q1768. I will now look for properties related to nicknames or aliases for this entity. Common properties for nicknames in Wikidata include "nickname" (P1449) and "alias" (rdfs:label or skos:altLabel). I will check for these properties for this entity.

[Tool]
Got 3 rows and 3 columns:
| subject                    | property             | object                             |
| -------------------------- | -------------------- | ---------------------------------- |
| Ella Fitzgerald (wd:Q1768) | nickname (wdt:P1449) | Lady Ella (en)                     |
| Ella Fitzgerald (wd:Q1768) | nickname (wdt:P1449) | la Primera dama de la canción (es) |
| Ella Fitzgerald (wd:Q1768) | nickname (wdt:P1449) | la Reina del jazz (es)             |

[Assistant] Ella Fitzgerald has the English nickname "Lady Ella" according to the nickname property (P1449) in Wikidata. There are also Spanish nicknames listed, but the English one is "Lady Ella." I will now finalize the answer.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?namedAfter ?namedAfterLabel WHERE {
  wd:Q1128775 wdt:P138 ?namedAfter .
  OPTIONAL {
    ?namedAfter rdfs:label ?namedAfterLabel FILTER ( LANG( ?namedAfterLabel ) = "en" )
  }
}

The song "Vogue" by Madonna is named after the dance style "voguing" (wd:Q1112128).

What is the song Vogue by Madonna named after?

[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 with notes:
1. When direct properties are missing, chain related properties (e.g., child→child for grandchildren) or search for indirect connections to answer complex relationship queries.
2. For set/class queries (e.g., all cities, all holidays), use instance/subclass chains (P31/P279) for completeness and relevant filters. Be aware of data incompleteness and schema inconsistencies in Wikidata.
3. If queries return too many irrelevant or too few results, try varying properties (country, location, observed in, etc.) and subclass chains, but be ready to report data/model limitations if results remain incomplete or noisy.
4. When a direct property or class is missing or inconsistently used, try related or broader properties/classes (e.g., use inception for independence date, or musical work/composition for musicals) to increase recall.
5. For calculated properties (e.g., population density), combine relevant direct properties (e.g., population, area) in SPARQL queries, as Wikidata may not store the derived value directly.
6. When entity search returns multiple candidates, use context (description, instance type, location, etc.) to disambiguate and select the most relevant entity for the query.

No general notes for all knowledge graphs available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. 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 is the song Vogue by Madonna named after?

[Assistant]
To answer the question "What is the song Vogue by Madonna named after?" I need to find the entity for the song "Vogue" by Madonna in Wikidata and then check if there is any property that indicates what it is named after or inspired by.

Step 1: Search for the entity "Vogue" by Madonna in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Madonna, also known as Madonna Louise Veronica Ciccone, Madonna Louise Ciccone, Madonna L. Ciccone, Madonna Ciccone (wd:Q1744): American singer, songwriter, and actress (born 1958), instance of human, songwriter, singer, actor
2. Mary, also known as St Mary the Virgin, Most Blessed, Saint Mary, Queen of the Universe, Our Lady (wd:Q345): instance of human biblical figure, mother of Jesus
3. Vogue, also known as American Vogue, Vogue USA (wd:Q154008): American fashion and lifestyle magazine, instance of monthly magazine, instance of weekly magazine, instance of magazine, instance of brand
4. Madonna, also known as Madonna: The First Album (wd:Q177943): 1983 self-titled debut studio album by Madonna, instance of album
5. Vogüé (wd:Q391128): instance of commune of France, commune in Ardèche, France
6. Madonna (wd:Q1989780): painting composition by Edvard Munch, in different versions, instance of painting series
7. Madonna, also known as Madonna in art, Virgin Mary in art, The Madonna in art (wd:Q926743)
8. Vogue (wd:Q1128775): original song written and composed by Madonna, Shep Pettibone, instance of musical work/composition
9. vogue, also known as voguing (wd:Q1112128)
10. Vogue (wd:Q647541): instance of cigarette brand, instance of trademark, Cigarette brand

[Assistant] I found the entity for the song "Vogue" by Madonna: wd:Q1128775. Now I will check if there is any property indicating what the song is named after or inspired by. I will look for properties related to "named after," "inspired by," or "title origin" for this entity.

[Tool]
Got 183 rows and 3 columns, showing the first 10 rows below:
| subject             | property                            | object                                                                                |
| ------------------- | ----------------------------------- | --------------------------------------------------------------------------------------------- |
| Vogue (wd:Q1128775) | instance of (wdt:P31)               | musical work/composition (wd:Q105543609)                                                      |
| Vogue (wd:Q1128775) | title (wdt:P1476)                   | Vogue (en)                                                                                |
| Vogue (wd:Q1128775) | publication date (wdt:P577)         | 1990-01-01T00:00:00Z (xsd:dateTime)                                                           |
| Vogue (wd:Q1128775) | language of work or name (wdt:P407) | English (wd:Q1860)                                                                            |
| Vogue (wd:Q1128775) | Commons category (wdt:P373)         | Vogue (Madonna)                                                                               |
| Vogue (wd:Q1128775) | image (wdt:P18)                     | <http://commons.wikimedia.org/wiki/Special:FilePath/Madonna-vogue-sire-back-to-back-hits.jpg> |
| Vogue (wd:Q1128775) | part of (wdt:P361)                  | I'm Breathless – Music from and Inspired by the Film Dick Tracy (wd:Q746450)                  |
| Vogue (wd:Q1128775) | genre (wdt:P136)                    | house music (wd:Q20502)                                                                       |
| Vogue (wd:Q1128775) | follows (wdt:P155)                  | Keep It Together (wd:Q2085975)                                                                |
| Vogue (wd:Q1128775) | followed by (wdt:P156)              | Hanky Panky (wd:Q1342443)                                                                     |
| ...                 | ...                                 | ...                                                                                |

[Assistant] The direct properties of the song "Vogue" by Madonna do not explicitly indicate what it is named after or inspired by. I will now search for properties related to "named after," "inspiration," or "title origin" in general to see if any of these properties are used for musical works or compositions.

[Tool]
Top 10 property alternatives:
1. named after, also known as named in honor of, toponym, namesake, name after, etymology (wd:P138 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): entity or event that inspired the subject's name, or namesake (i...fier "applies to name" (P5168) can be used to indicate which one
2. theorized by, also known as posed by, supported by, suggested by, proposer, proposed by (wd:P8403 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): subject who suggested or proposed this concept or immaterial invention
3. named by, also known as coined by, namer (wd:P3938 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): person or organisation that coined the name; use as qualifier for P2561 and its subproperties
4. appointed by, also known as named by (wd:P748 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): who appointed the person to the office, can be used as a qualifier
5. patronym or matronym for this name, also known as matronym, parentonym for this name, parentonymic for this name, patronym (wd:P2976 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): patronym or matronym based on this given name
6. troponym of, also known as definition by troponym, troponym (wd:P5975 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): this verb describes more narrowly the action of the more general verb used as value, subproperty of hyperonym
7. nickname, also known as informal name, sobriquet, moniker, other name, othername (wd:P1449 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): informal name (for a pseudonym use P742), subproperty of name
8. applies to name of subject, also known as applies to subject's name, applies to name, for the name, involved name, limited to the name (wd:P5168 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): (qualifier) label or alias name to which the claim applies (subj...er to name of the value, use "applies to name of object" (P8338), subproperty of subject named as
9. object named as, also known as original wording, place name string, printed as, reference wording, [sic] (wd:P1932 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): use as qualifier to indicate how the object's value was given in the source, subproperty of name
10. subject named as, also known as established as, entity named as, established form, established heading, named as (wd:P1810 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): name by which a subject is recorded in a database, mentioned as a contributor of a work, or is referred to in a particular context, subproperty of name

[Assistant] The property "named after" (wdt:P138) is the most relevant property for indicating what an entity is named after or inspired by. I will now check if the song "Vogue" (wd:Q1128775) has any value for the property "named after" (wdt:P138).

[Tool]
Got 1 row and 2 columns:
| namedAfter          | namedAfterLabel |
| ------------------- | --------------- |
| vogue (wd:Q1112128) | vogue (en)      |

[Assistant] The song "Vogue" by Madonna (wd:Q1128775) is named after "vogue" (wd:Q1112128), which refers to the dance style "voguing." I will now provide the final answer.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?country ?countryLabel ?headOfState ?headOfStateLabel WHERE {
  VALUES ?country {
    wd:Q183 wd:Q142
  }
  ?country wdt:P35 ?headOfState .
  OPTIONAL {
    ?country rdfs:label ?countryLabel FILTER ( LANG( ?countryLabel ) = "en" )
  }
  OPTIONAL {
    ?headOfState rdfs:label ?headOfStateLabel FILTER ( LANG( ?headOfStateLabel ) = "en" )
  }
}

Got 2 rows and 4 columns:
| country           | countryLabel | headOfState                         | headOfStateLabel             |
| ----------------- | ------------ | ----------------------------------- | ---------------------------- |
| France (wd:Q142)  | France (en)  | Emmanuel Macron (wd:Q3052772)       | Emmanuel Macron (en)         |
| Germany (wd:Q183) | Germany (en) | Frank-Walter Steinmeier (wd:Q76658) | Frank-Walter Steinmeier (en) |

The head of state of Germany is Frank-Walter Steinmeier and the head of state of France is Emmanuel Macron.

What are the names of the head of states of Germany and France ?

[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 with notes:
1. When direct properties are missing, chain related properties (e.g., child→child for grandchildren) or search for indirect connections to answer complex relationship queries.
2. For set/class queries (e.g., all cities, all holidays), use instance/subclass chains (P31/P279) for completeness and relevant filters. Be aware of data incompleteness and schema inconsistencies in Wikidata.
3. If queries return too many irrelevant or too few results, try varying properties (country, location, observed in, etc.) and subclass chains, but be ready to report data/model limitations if results remain incomplete or noisy.
4. When a direct property or class is missing or inconsistently used, try related or broader properties/classes (e.g., use inception for independence date, or musical work/composition for musicals) to increase recall.
5. For calculated properties (e.g., population density), combine relevant direct properties (e.g., population, area) in SPARQL queries, as Wikidata may not store the derived value directly.
6. When entity search returns multiple candidates, use context (description, instance type, location, etc.) to disambiguate and select the most relevant entity for the query.

No general notes for all knowledge graphs available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. 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 are the names of the head of states of Germany and France ?

[Assistant]
To answer the question about the names of the heads of state of Germany and France, I need to:

1. Identify the entities for Germany and France.
2. Identify the property that represents the head of state for a country.
3. Query the heads of state for Germany and France.
4. Retrieve their names.

I will start by searching for the entities of Germany and France.

[Tool]
Top 10 entity alternatives:
1. Germany, also known as Federal Republic of Germany, Deutschland, Bundesrepublik Deutschland, BR Deutschland (wd:Q183): instance of sovereign state, country in Central Europe, instance of country
2. Weimar Republic, also known as Germany, Weimar Germany, Republic of Germany, German Republic, German Reich (wd:Q41304): Germany in the years 1918/1919–1933, instance of historical country, instance of historical period
3. German Reich, also known as Imperial Germany, Germany, German Realm, German Empire, Deutsches Reich (wd:Q1206012): official name for the German nation state from 1871 to 1945, and name of Germany until 1949, instance of historical country
4. Burg Drachenfels, also known as Germany (wd:Q1011486): instance of castle, castle
5. Germany (wd:Q5552078): instance of constituency of the European Parliament, European Parliament constituency
6. Geilenkirchen-Heinsberg, also known as Germany (wd:Q2268218): instance of district of Germany
7. Germany, also known as Germany, IN, Germany, Indiana (wd:Q18151573): instance of unincorporated community in the United States, unincorporated community in Clark County, Indiana
8. Germany (wd:Q19147844): poem by Vladimir Mayakovsky, instance of literary work
9. Germany (wd:Q22006587): instance of horse, race horse
10. Germany (wd:Q37444958): instance of family name, family name

[Tool]
Top 10 entity alternatives:
1. France, also known as French Republic, FRA, FR (wd:Q142): instance of sovereign state, country in Western Europe, instance of republic, instance of country
2. France men's national association football team, also known as France national football team, Les Bleus, France national soccer team, France national association football team, France men's national football team (wd:Q47774)
3. French Fifth Republic, also known as 5th French Republic, French Republic, French 5th Republic, France, Fifth Republic (wd:Q200686): current system of government of France (1958–present), instance of republic regime in France
4. Bourbon Restoration in France, also known as France, Kingdom of France (wd:Q207162): period of French history, 1814–1830, instance of historical country, instance of regime
5. French Community, also known as France (wd:Q1120363): International political association, instance of coalition
6. France at the 2008 Summer Olympics, also known as France (wd:Q146845): instance of Olympic delegation, sporting event delegation
7. France, also known as French battleship France (wd:Q49644): 1912 Courbet-class battleship, instance of dreadnought
8. France, also known as On a Half Clear Morning (wd:Q76488728): 2021 film directed by Bruno Dumont, instance of film
9. La France, also known as France (wd:Q3209212): 2007 film by Serge Bozon, instance of film
10. France (wd:Q5478259): instance of constituency of the European Parliament, constituency of the European Parliament

[Assistant]
The entities for Germany and France are wd:Q183 and wd:Q142 respectively.

Next, I need to find the property that represents the head of state for a country. I will search for properties related to "head of state" to identify the correct property.

[Tool]
Top 10 property alternatives:
1. office held by head of state, also known as head of state, position held by head of state, state headed by (wd:P1906 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): political office that is fulfilled by the head of state of this item
2. head of state, also known as state headed by, queen, president, monarch, leader (wd:P35 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): official with the highest formal authority in a country/state, subproperty of director / manager, subproperty of chairperson
3. head of government, also known as head of national government, executive power headed by, mayor, premier, president (wd:P6 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): head of the executive power of this town, city, municipality, state, country, or other governmental body, subproperty of director / manager, subproperty of chairperson
4. office held by head of government, also known as head of government's office, office of head of government, position held by head of government, position of head of government, title of head of government (wd:P1313 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): political office that is fulfilled by the head of the government of this item
5. rector, also known as university president, Rector (academia), president, chancellor (wd:P1075 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): senior official in an educational institution., subproperty of director / manager, subproperty of chairperson
6. chairperson, also known as dean, headed by, leader, chairman, president (wd:P488 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): presiding member of an organization, group or body, subproperty of director / manager, subproperty of significant person
7. organization directed by the office or position, also known as leader of, head of, leads, organization directed by, organization directed from the office (wd:P2389 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): organization which is directed by this office
8. position held by head of the organization, also known as position held by head of the organisation, secretary's position, president's position, position held by head of the organization, office held by head of the organisation (wd:P2388 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): position of the head of this item
9. position holder, also known as incumbent, noble title holder, office holder, position held by (wd:P1308 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): persons who hold and/or held the position
10. country, also known as state, sovereign state, land, host country (wd:P17 as psn/wdt/ps/prn/pr/wdtn/pq/pqv/p/prv/psv/pqn): sovereign state that this item is in (not to be used for human beings), subproperty of located in the administrative territorial entity

[Assistant]
The property "head of state" (wdt:P35) represents the official with the highest formal authority in a country/state.

Now I will query the heads of state for Germany (wd:Q183) and France (wd:Q142) using this property and retrieve their names.

[Tool]
Got 2 rows and 4 columns:
| country           | countryLabel | headOfState                         | headOfStateLabel             |
| ----------------- | ------------ | ----------------------------------- | ---------------------------- |
| France (wd:Q142)  | France (en)  | Emmanuel Macron (wd:Q3052772)       | Emmanuel Macron (en)         |
| Germany (wd:Q183) | Germany (en) | Frank-Walter Steinmeier (wd:Q76658) | Frank-Walter Steinmeier (en) |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?dateOfDeath WHERE {
  wd:Q4124918 wdt:P570 ?dateOfDeath .
}

The brother of the author of Slaughterhouse Five, Bernard Vonnegut, died on April 25, 1997.

When did the brother of the author of Slaughterhouse Five die?

[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 with notes:
1. When direct properties are missing, chain related properties (e.g., child→child for grandchildren) or search for indirect connections to answer complex relationship queries.
2. For set/class queries (e.g., all cities, all holidays), use instance/subclass chains (P31/P279) for completeness and relevant filters. Be aware of data incompleteness and schema inconsistencies in Wikidata.
3. If queries return too many irrelevant or too few results, try varying properties (country, location, observed in, etc.) and subclass chains, but be ready to report data/model limitations if results remain incomplete or noisy.
4. When a direct property or class is missing or inconsistently used, try related or broader properties/classes (e.g., use inception for independence date, or musical work/composition for musicals) to increase recall.
5. For calculated properties (e.g., population density), combine relevant direct properties (e.g., population, area) in SPARQL queries, as Wikidata may not store the derived value directly.
6. When entity search returns multiple candidates, use context (description, instance type, location, etc.) to disambiguate and select the most relevant entity for the query.

No general notes for all knowledge graphs available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. 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] When did the brother of the author of Slaughterhouse Five die?

[Assistant]
Step 1: Identify the author of "Slaughterhouse Five."
Step 2: Find the brother of this author.
Step 3: Find the date of death of the brother.

I will start by searching for the author of "Slaughterhouse Five" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Slaughterhouse-Five, also known as Slaughterhouse Five (wd:Q648299): 1972 film by George Roy Hill, instance of film
2. Slaughterhouse-Five, also known as Slaughterhouse Five or, The Children's Crusade (wd:Q265954): instance of literary work, novel by Kurt Vonnegut
3. 5, also known as number five, number 5, the number 5, 5 (number), five (wd:Q203): instance of centered tetrahedral number, instance of square pyramidal number, instance of centered square number, instance of automorphic number, instance of pentagonal number, instance of Fibonacci number, instance of pentatope number, instance of primorial prime, instance of Fibonacci prime, instance of factorial prime, instance of harshad number, instance of natural number, instance of Fermat number, instance of prime number, instance of odd number, natural number
4. slaughterhouse, also known as abattoir, slaughterhouses, slaughter, freezing works, abattoirs (wd:Q385557)
5. Channel 5, also known as Channel Five, Five (wd:Q1062280): instance of television station, British TV station
6. Five (wd:Q24791): instance of musical group, British boy band
7. Slaughterhouse (wd:Q574919): instance of musical group, American hip hop group
8. Five (wd:Q2972918): 1951 film by Arch Oboler, instance of film
9. Five (wd:Q2526859): 2011 EP by Ayumi Hamasaki, instance of extended play
10. Five (wd:Q41644640): album by Hollywood Undead, instance of album

[Assistant] The author of the novel "Slaughterhouse Five" is Kurt Vonnegut (wd:Q265954). Next, I will find the brother of Kurt Vonnegut.

[Tool] Got no rows and 3 columns

[Assistant] No direct property "brother" (wdt:P3373) found for Kurt Vonnegut. I will try to find the brother by searching for family relations or siblings of Kurt Vonnegut using a broader property search.

[Tool]
Top 10 property alternatives:
1. country of origin, also known as comes from, place of origin, origin country, originates from, country (wd:P495 as wdt/p): country of origin of this item (creative work, food, phrase, product, etc.), subproperty of significant place, subproperty of country
2. main subject, also known as main topic, primary subject, primary keyword, plot keyword, of (wd:P921 as wdt/p): primary topic of a work, subproperty of depicts
3. title, also known as page name, titled, original title, name, known as (wd:P1476 as wdt/p): published name of a work, such as a newspaper article, a literary work, piece of music, a website, or a performance work, subproperty of name
4. author, also known as co-author, written by, writer, poet, playwright (wd:P50 as wdt/p): main creator(s) of a written work (use on works, not humans); us...hor name string) when Wikidata item is unknown or does not exist, subproperty of creator
5. named after, also known as named in honor of, toponym, namesake, name after, etymology (wd:P138 as wdt/p): entity or event that inspired the subject's name, or namesake (i...fier "applies to name" (P5168) can be used to indicate which one
6. image, also known as img, infobox image, photo, photograph, picture (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
7. has characteristic, also known as trait, has quality, inherent property, object has characteristic, parameter (wd:P1552 as wdt/p): inherent or distinguishing quality or feature of the entity. Use a more specific property when possible
8. has edition or translation, also known as released as, version, translation(s), modified as, has version (wd:P747 as wdt/p): item that is an edition or translation of this item
9. instance of, also known as example of, has type, is a, is an, is of type (wd:P31 as wdt/p): type to which this subject corresponds/belongs. Different from P...tains, and the volcano is a type (instance) of volcanic landform
10. award received, also known as winner of, win, recognition title, received award, award won (wd:P166 as wdt/p): award or recognition received by a person, organization or creative work

No other items found

[Assistant] No direct property for "brother" found for Kurt Vonnegut. I will try to find siblings of Kurt Vonnegut using the property "sibling" (wdt:P3373) in a broader search to see if any sibling is listed.

[Tool] Got no rows and 3 columns

[Assistant] No siblings or brothers of Kurt Vonnegut are directly linked in Wikidata using the property "sibling" (wdt:P3373). I will try to find any family members of Kurt Vonnegut to see if a brother is mentioned under a different property.

[Tool]
Got 330 rows and 3 columns, showing the first 10 rows below:
| subject                          | property                            | object                                                                                |
| -------------------------------- | ----------------------------------- | -------------------------------------------------------------------------------------------------------------------------- |
| Slaughterhouse-Five (wd:Q265954) | instance of (wdt:P31)               | literary work (wd:Q7725634)                                                                                |
| Slaughterhouse-Five (wd:Q265954) | title (wdt:P1476)                   | Slaughterhouse-Five (en)                                                                                |
| Slaughterhouse-Five (wd:Q265954) | publication date (wdt:P577)         | 1969-03-01T00:00:00Z (xsd:dateTime)                                                                                |
| Slaughterhouse-Five (wd:Q265954) | author (wdt:P50)                    | Kurt Vonnegut (wd:Q49074)                                                                                |
| Slaughterhouse-Five (wd:Q265954) | main subject (wdt:P921)             | World War II (wd:Q362)                                                                                |
| Slaughterhouse-Five (wd:Q265954) | language of work or name (wdt:P407) | English (wd:Q1860)                                                                                |
| Slaughterhouse-Five (wd:Q265954) | Commons category (wdt:P373)         | Slaughterhouse-Five                                                                                |
| Slaughterhouse-Five (wd:Q265954) | image (wdt:P18)                     | <http://commons.wikimedia.org/wiki/Special:FilePath/Slaughterhouse-Five%20%28first%20edition%29%20-%20Kurt%20Vonnegut.jpg> |
| Slaughterhouse-Five (wd:Q265954) | country of origin (wdt:P495)        | United States (wd:Q30)                                                                                |
| Slaughterhouse-Five (wd:Q265954) | official website (wdt:P856)         | <https://www.vonnegut.com/>                                                                                |
| ...                              | ...                                 | ...                                                                                |

[Assistant] I mistakenly listed properties of the book "Slaughterhouse-Five" instead of Kurt Vonnegut. I will now list properties of Kurt Vonnegut (wd:Q49074) to find family relations or siblings.

[Tool]
Got 974 rows and 3 columns, showing the first 10 rows below:
| subject                   | property                         | object                                                                                |
| ------------------------- | -------------------------------- | -------------------------------------------------------------------------------------------------------------- |
| Kurt Vonnegut (wd:Q49074) | instance of (wdt:P31)            | human (wd:Q5)                                                                                |
| Kurt Vonnegut (wd:Q49074) | occupation (wdt:P106)            | writer (wd:Q36180)                                                                                |
| Kurt Vonnegut (wd:Q49074) | sex or gender (wdt:P21)          | male (wd:Q6581097)                                                                                |
| Kurt Vonnegut (wd:Q49074) | given name (wdt:P735)            | Kurt (wd:Q1158489)                                                                                |
| Kurt Vonnegut (wd:Q49074) | date of birth (wdt:P569)         | 1922-11-11T00:00:00Z (xsd:dateTime)                                                                            |
| Kurt Vonnegut (wd:Q49074) | Commons category (wdt:P373)      | Kurt Vonnegut                                                                                |
| Kurt Vonnegut (wd:Q49074) | image (wdt:P18)                  | <http://commons.wikimedia.org/wiki/Special:FilePath/Kurt%20Vonnegut%20by%20Bernard%20Gotfryd%20%281965%29.jpg> |
| Kurt Vonnegut (wd:Q49074) | family name (wdt:P734)           | Vonnegut (wd:Q30525499)                                                                                |
| Kurt Vonnegut (wd:Q49074) | country of citizenship (wdt:P27) | United States (wd:Q30)                                                                                |
| Kurt Vonnegut (wd:Q49074) | place of birth (wdt:P19)         | Indianapolis (wd:Q6346)                                                                                |
| ...                       | ...                              | ...                                                                                |

[Assistant] I found many properties for Kurt Vonnegut but no direct "brother" or "sibling" property. I will now try to find family members using the property "relative" (wdt:P1038) which might include siblings.

[Tool]
Got 1 row and 3 columns:
| subject                   | property             | object                      |
| ------------------------- | -------------------- | --------------------------- |
| Kurt Vonnegut (wd:Q49074) | relative (wdt:P1038) | Steve Adams (wd:Q113512097) |

[Assistant] Kurt Vonnegut has a relative listed: Steve Adams (wd:Q113512097). I will check if Steve Adams is his brother and find the date of death of this relative.

[Tool]
Got 45 rows and 3 columns, showing the first 10 rows below:
| subject                     | property                         | object                                                                                |
| --------------------------- | -------------------------------- | --------------------------------------------------------------------------------------------- |
| Steve Adams (wd:Q113512097) | instance of (wdt:P31)            | human (wd:Q5)                                                                                |
| Steve Adams (wd:Q113512097) | occupation (wdt:P106)            | screenwriter (wd:Q28389)                                                                      |
| Steve Adams (wd:Q113512097) | sex or gender (wdt:P21)          | male (wd:Q6581097)                                                                            |
| Steve Adams (wd:Q113512097) | given name (wdt:P735)            | Steve (wd:Q18336566)                                                                          |
| Steve Adams (wd:Q113512097) | date of birth (wdt:P569)         | 1947-02-08T00:00:00Z (xsd:dateTime)                                                           |
| Steve Adams (wd:Q113512097) | image (wdt:P18)                  | <http://commons.wikimedia.org/wiki/Special:FilePath/Steve%20Adams%20aka%20Waldo%20Mellon.jpg> |
| Steve Adams (wd:Q113512097) | family name (wdt:P734)           | wd:Q351735                                                                                |
| Steve Adams (wd:Q113512097) | country of citizenship (wdt:P27) | United States (wd:Q30)                                                                        |
| Steve Adams (wd:Q113512097) | pseudonym (wdt:P742)             | Waldo Mellon                                                                                |
| Steve Adams (wd:Q113512097) | relative (wdt:P1038)             | Kurt Vonnegut (wd:Q49074)                                                                     |
| ...                         | ...                              | ...                                                                                |

[Assistant] Steve Adams is a relative of Kurt Vonnegut but not necessarily his brother. I will check if there is any other relative or sibling of Kurt Vonnegut. I will also try to find if Kurt Vonnegut has a brother by searching for "brother of Kurt Vonnegut" explicitly.

[Tool]
Top 10 entity alternatives:
1. Worlds of Wordcraft: The Metafiction of Kurt Vonnegut, also known as Worlds of Wordcraft (wd:Q101500247): instance of chapter, chapter
2. Kurt Vonnegut, also known as Kurt Vonnegut, Jr. (wd:Q49074): American author (1922–2007), instance of human, writer
3. Ep 023 - Breakfast of Champions, by Kurt Vonnegut (wd:Q116821819): instance of podcast episode, Overdue podcast episode
4. sibling, also known as sib, sis, is sister of, sibling of, siblings (wd:P3373): the subject and the object have at least one common parent (brot...law, etc.) and step-siblings (step-brothers, step-sisters, etc.), instance of Wikidata property encoding a vCard value, instance of symmetric property, instance of Mohamed B.AMMAR
5. uncle, also known as brother-in-law of parent, parent's brother-in-law, parent's brother, brother of parent (wd:Q76557)
6. Brother of Sleep (wd:Q870768): 1995 film by Joseph Vilsmaier, instance of film
7. Brother Officers (wd:Q4975540): 1915 film by Harold M. Shaw, instance of film
8. granduncle, also known as grand uncle, grand-uncle, great uncle, brother of grandparent, great-uncle (wd:Q3813877)
9. Brother of Sleep (wd:Q1538580): 1992 novel by Robert Schneider, instance of literary work
10. Brother of Bommali (wd:Q28180170): 2014 Telugu comedy film, instance of film

[Assistant] I found no direct entity for "brother of Kurt Vonnegut." I will now try to find siblings of Kurt Vonnegut by searching for the property "sibling" (wdt:P3373) with Kurt Vonnegut as the subject.

[Tool]
Got 1 row and 3 columns:
| subject                   | property            | object                         |
| ------------------------- | ------------------- | ------------------------------ |
| Kurt Vonnegut (wd:Q49074) | sibling (wdt:P3373) | Bernard Vonnegut (wd:Q4124918) |

[Assistant] Kurt Vonnegut has a sibling named Bernard Vonnegut (wd:Q4124918). I will now find the date of death of Bernard Vonnegut.

[Tool]
Got 1 row and 3 columns:
| subject                        | property                 | object                              |
| ------------------------------ | ------------------------ | ----------------------------------- |
| Bernard Vonnegut (wd:Q4124918) | date of death (wdt:P570) | 1997-04-25T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?maxPlayers WHERE {
  wd:Q545129 wdt:P1873 ?maxPlayers .
}

Got 1 row and 1 column:
| maxPlayers      |
| --------------- |
| 8 (xsd:decimal) |

The maximum number of people who can play "Mensch ärgere dich nicht" is 8.

How many people can play "Mensch ärgere dich nicht" at most?

[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 with notes:
1. When direct properties are missing, chain related properties (e.g., child→child for grandchildren) or search for indirect connections to answer complex relationship queries.
2. For set/class queries (e.g., all cities, all holidays), use instance/subclass chains (P31/P279) for completeness and relevant filters. Be aware of data incompleteness and schema inconsistencies in Wikidata.
3. If queries return too many irrelevant or too few results, try varying properties (country, location, observed in, etc.) and subclass chains, but be ready to report data/model limitations if results remain incomplete or noisy.
4. When a direct property or class is missing or inconsistently used, try related or broader properties/classes (e.g., use inception for independence date, or musical work/composition for musicals) to increase recall.
5. For calculated properties (e.g., population density), combine relevant direct properties (e.g., population, area) in SPARQL queries, as Wikidata may not store the derived value directly.
6. When entity search returns multiple candidates, use context (description, instance type, location, etc.) to disambiguate and select the most relevant entity for the query.

No general notes for all knowledge graphs available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. 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] How many people can play "Mensch ärgere dich nicht" at most?

[Assistant]
Step 1: Identify the entity "Mensch ärgere dich nicht" in Wikidata. It is a board game, so I will search for it as an entity.

I will now search for the entity "Mensch ärgere dich nicht" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Mensch ärgere dich nicht, also known as Man, don't get annoyed, Pachisi, Man, don't get angry! (German: mensch ärgere rich night) (wd:Q545129): German board dice-and-pieces game, based on Pachisi (Indian origin), instance of cross and circle game, instance of tabletop game, instance of board game
2. Mensch Ärgere Dich Nicht (wd:Q126186091): instance of video game, 1991 video game
3. ludo video game, also known as pachisi video game, mensch ärgere Dich nicht video game (wd:Q131717871)
4. Unser Schatzerl oder Mensch, ärgere dich nicht. Posse in drei Akten (wd:Q126494466): performing arts production of the Theater Basel during the season 1882-1883, instance of performing arts production
5. Fürchte dich nicht, also known as BWV 228, Do not fear, Fürchte dich nicht, ich bin bei dir (wd:Q2603263): motet for a funeral by Johann Sebastian Bach, set for double chorus, instance of musical work/composition
6. Fürchte dich nicht (wd:Q127156481): Christian hymn text, instance of lyrics
7. O sichrer Mensch! bekehre dich, Du lebest hier nicht ewiglich (wd:Q127169916): Christian hymn text, instance of lyrics
8. Ich lasse dich nicht, BWV Anh. 159, also known as BWV Anh. 159, Ich lasse dich nicht, Ich lasse dich nicht, du segnest mich denn, I will not let you go unless you bless me (wd:Q21998553): instance of musical work/composition, motet possibly by J. S. Bach
9. Ich lasse dich nicht (wd:Q127222210): Christian hymn text, instance of lyrics
10. Denk, Mensch, wie dich (wd:Q127139713): Christian hymn text, instance of lyrics

[Assistant]
The entity "Mensch ärgere dich nicht" as a German board dice-and-pieces game is identified as wd:Q545129 in Wikidata.

Step 2: Find the property that indicates the maximum number of players for this board game. Typically, the property for "number of players" is P710 or P1342 or similar. I will search for properties related to "number of players" for this entity.

[Tool]
Top 10 property alternatives:
1. maximum number of players, also known as maximum players, max players, number of players, maximum, players max, players, maximum number (wd:P1873 as wdt/p): maximum numbers of players of a game
2. minimum number of players, also known as players, minimum number, number of players, minimum, minimum players (wd:P1872 as wdt/p): minimum numbers of players of a game
3. publisher, also known as video game publisher, software publisher, sheet music publisher, publishing house, music publisher (wd:P123 as wdt/p): organization or person responsible for publishing books, periodicals, printed music, podcasts, games or software
4. BoardGameGeek ID, also known as BGG ID, Board Game Geek ID (wd:P2339 as wdt/p): identifier for a board game in the BoardGameGeek database
5. Luding game ID, also known as Luding game identifier (wd:P3528 as wdt/p): identifier for a game at the Luding database
6. image, also known as img, infobox image, photo, photograph, picture (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
7. based on, also known as modelled after, inspired by, iteration of, modeled after, input (wd:P144 as wdt/p): the work(s) or inputs used as the basis for subject item; for fictional analog use P1074, subproperty of references work, tradition or theory, subproperty of inspired by
8. Freebase ID, also known as FID, Freebase, Freebase identifier, MID (wd:P646 as wdt/p): identifier for a page in the Freebase database. Format: "/m/0" f...r IDs starting with "/g/", use Google Knowledge Graph ID (P2671)
9. GND ID, also known as GND identifier, Universal Authority File, Integrated Authority File, IndividualisedGnd, GND-IDN (wd:P227 as wdt/p/wdtn): identifier from an international authority file of names, subjects, and organizations
10. publication date, also known as published, publication time, publication, pubdate, launched (wd:P577 as wdt/p): date or point in time when a work was first published or released, subproperty of point in time

No other items found

[Assistant]
The property "maximum number of players" (wdt:P1873) is the relevant property for the maximum number of players of a game.

Step 3: Query the maximum number of players for the entity "Mensch ärgere dich nicht" (wd:Q545129) using property wdt:P1873.

[Tool]
Got 1 row and 1 column:
| maxPlayers      |
| --------------- |
| 8 (xsd:decimal) |

[Tool] Stopped generation process