PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?bodyOfWater ?bodyOfWaterLabel WHERE {
  wd:Q1297 wdt:P206 ?bodyOfWater .
  OPTIONAL {
    ?bodyOfWater rdfs:label ?bodyOfWaterLabel FILTER ( LANG( ?bodyOfWaterLabel ) = "en" )
  }
}

Got 2 rows and 2 columns:
| bodyOfWater                | bodyOfWaterLabel   |
| -------------------------- | ------------------ |
| Lake Michigan (wd:Q1169)   | Lake Michigan (en) |
| Chicago River (wd:Q643284) | Chicago River (en) |

Yes, Chicago is located at Lake Michigan as it is one of the bodies of water associated with the city of Chicago.

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

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

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

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

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

[User] Is Chicago located at Lake Michigan?

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

[Tool]
Example 1:
Question:
Which states border Illinois?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q1204 wdt:P47 ?uri .
}

Using entities:
Illinois, also known as The Prairie State, Illinois, United States, The Land of Lincoln, US-IL, Prairie State (wd:Q1204): state of the United States of America

Using properties:
shares border with, also known as shares borders with, next to, bordered by, border, borders clockwise (wd:P47 as wdt): countries or administrative subdivisions, of equal level, that t...rders, either by land or water. A single common point is enough.

Example 2:
Question:
How deep is Lake Chiemsee?

SPARQL:
SELECT DISTINCT ?n WHERE {
  wd:Q4138 wdt:P4511 ?n
}

Using entities:
Chiemsee, also known as Chiem-see (wd:Q4138): freshwater lake in Bavaria, Germany

Using properties:
vertical depth, also known as depth, oceandepth, lakedepth (wd:P4511 as wdt): vertical distance from a horizontal area to a point below. Compare with "horizontal depth" (P5524), length

[Assistant]
The question is whether Chicago is located at Lake Michigan. We need to check the geographical location or the body of water associated with Chicago. We will look for the entity "Chicago" and the property that relates a city to a body of water or location. Then we will check if Lake Michigan is the body of water associated with Chicago.

Step 1: Search for the entity "Chicago" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Chicago, also known as The Second City, The Queen of the West, The Windy City, City of Broad Shoulders, City by the Lake (wd:Q1297): city and county seat of Cook County, Illinois, United States of America
2. Chicago, also known as City of Chicago, City of Broad Shoulders, The Queen of the West, City by the Lake, Chi-Town (wd:Q1297): city and county seat of Cook County, Illinois, United States of America
3. Chicago (wd:Q189889): 2002 film by Rob Marshall
4. Chicago, also known as Chicago (band), Chicago (musical group), Chicago Transit Authority, The Big Thing (wd:Q371938): American rock band
5. 334 Chicago, also known as (334) Chicago, Chicago (wd:Q151343): outer main-belt asteroid
6. Willard, also known as Chicago, Chicago Junction, Willard, OH, Willard, Ohio (wd:Q2233885): city in Huron County, Ohio, United States
7. Chicago (wd:Q656285): 1975 musical by John Kander and Fred Ebb
8. Chicago (wd:Q3281484): 1927 film by Frank John Urson
9. Chicago, also known as One Chicago (wd:Q20649503): American television series franchise
10. Chicago, also known as Chicago II (wd:Q2451193): 1970 studio album by Chicago

[Assistant] The entity for the city Chicago is wd:Q1297. Next, I will search for properties related to location or body of water for this entity to find how Chicago is related to Lake Michigan.

[Tool]
Top 10 property alternatives:
1. located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as wdt/p): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
2. headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as wdt/p): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place
3. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as wdt/p): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
4. location map (wd:P1943 as wdt/p): blank geographic map image suitable for overlaying coordinate points, as defined at c:Category:Location maps, image
5. located in time zone, also known as TZ, time zone, timezone (wd:P421 as wdt/p): time zone for this item
6. located in or next to body of water, also known as located on body of water, ocean, on bay, next to lake, on coast of (wd:P206 as wdt/p): body of water on or next to which a place is located, location
7. located in the statistical territorial entity, also known as located in statistical territorial entity, statistical territorial entity (wd:P8138 as wdt/p): statistical territorial entity in which a place is located or is...nty is split into or part of several regions: add several values, location
8. shares border with, also known as shares borders with, next to, bordered by, border, borders clockwise (wd:P47 as wdt/p): countries or administrative subdivisions, of equal level, that t...rders, either by land or water. A single common point is enough.
9. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as wdt/p): work where this item is described, attested in
10. territory overlaps, also known as partially overlaps, partially coincident with, partly coincident with, partly located in territorial entity, partly overlaps (wd:P3179 as wdt/p): part or all of the area associated with (this) entity overlaps part or all of the area associated with that entity, partially coincident with

No other items found

[Assistant] The property "located in or next to body of water" (wdt:P206) seems to be the most relevant to check if Chicago is located at Lake Michigan. Next, I will check the object values for this property for the entity Chicago (wd:Q1297) to see if Lake Michigan is listed.

[Tool]
Got 2 rows and 2 columns:
| bodyOfWater                | bodyOfWaterLabel   |
| -------------------------- | ------------------ |
| Lake Michigan (wd:Q1169)   | Lake Michigan (en) |
| Chicago River (wd:Q643284) | Chicago River (en) |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?person ?personLabel WHERE {
  wd:Q761383 wdt:P138 ?person .
  OPTIONAL {
    ?person rdfs:label ?personLabel FILTER ( LANG( ?personLabel ) = "en" )
  }
}

The Riemannian geometry is named after Bernhard Riemann.

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

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

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

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

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

[User] After whom is the Riemannian geometry named?

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

[Tool]
Example 1:
Question:
Who was the doctoral supervisor of Albert Einstein?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q937 wdt:P184 ?uri
}

Using entities:
Albert Einstein (wd:Q937): German-born theoretical physicist (1879–1955), physicist

Using properties:
doctoral advisor, also known as PhD supervisor, promotor, supervisor, thesis advisor, advisor (wd:P184 as wdt): person who supervised the doctorate or PhD thesis of the subject, supervised by, student of

Example 2:
Question:
Where did the architect of the Eiffel Tower study?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q243 wdt:P84 ?x .
  ?x wdt:P69 ?uri
}

Using entities:
Eiffel Tower (wd:Q243): tower located on the Champ de Mars in Paris, France

Using properties:
educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as wdt): educational institution attended by subject, affiliation
architect, also known as architecture firm (wd:P84 as wdt): person or architectural firm responsible for designing this building, designed by

Example 3:
Question:
Who designed the Brooklyn Bridge?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q125006 wdt:P287 ?uri .
}

Using entities:
Brooklyn Bridge, also known as East River Bridge, New York and Brooklyn Bridge (wd:Q125006): bridge in New York City, crossing the East River

Using properties:
designed by, also known as architect, designer, has designer (wd:P287 as wdt): person or organization which designed the object, creator

[Assistant]
The examples show how to find the person related to a concept or object using properties like "doctoral supervisor," "architect," or "designer." For the question "After whom is the Riemannian geometry named?" we want to find the person after whom the concept "Riemannian geometry" is named.

Step 1: Search for the entity "Riemannian geometry" in Wikidata to get its identifier.
Step 2: Find a property that indicates naming or eponymous relation (e.g., named after, named for, eponym).

I will start by searching for the entity "Riemannian geometry."

[Tool]
Top 10 entity alternatives:
1. Riemannian geometry (wd:Q761383): branch of differential geometry dealing with (generalized) Riemannian manifolds
2. Riemannian Geometry (wd:Q60133667): scientific article published in Nature
3. Riemannian Geometry. (wd:Q115229154): scientific article published in 1927
4. Riemannian Geometry. (wd:Q115229007): scientific article published in 1985
5. Riemannian geometry (wd:Q115364222): scientific article published in 1989
6. Riemannian geometry (wd:Q115158804): scientific article published in 1992
7. Discrete Riemannian geometry (wd:Q115328318): scientific article published in 1999
8. GENERALIZED RIEMANNIAN GEOMETRY. (wd:Q36396185): scientific article
9. Generalizing Riemannian geometry (wd:Q115333889): scientific article published in 1973
10. Book Review: Riemannian geometry (wd:Q115282274): scientific article published in 1989

[Assistant]
The entity "Riemannian geometry" is identified as wd:Q761383, which is a branch of differential geometry dealing with (generalized) Riemannian manifolds.

Next, I will search for properties related to naming or eponymous relation for this entity. I will search for properties of the entity wd:Q761383 with a query related to "named after" or "eponym."

[Tool]
Top 10 property alternatives:
1. named after, also known as toponym, namesake, named in honor of, named for, 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
2. subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt/p): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
3. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
4. Library of Congress authority ID, also known as LCSH Authority File ID, LC Name Authority ID, LCSH ID, LCSH LCCN, LC Subject Heading ID (wd:P244 as wdt/p/wdtn): Library of Congress name authority (persons, families, corporate...lowed by 8-10 digits (see regex). For manifestations, use P1144]
5. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as wdt/p): main Wikimedia category
6. Encyclopædia Britannica Online ID, also known as Encyclopaedia Britannica Online ID, Encyclopedia Britannica Online ID, EBID, EB ID, Britannica online ID (wd:P1417 as wdt/p): identifier for an article in the online version of Encyclopædia Britannica
7. Quora topic ID, also known as Quora topic identifier, Quora topic name (wd:P3417 as wdt/p): identifier for a topic on Quora (English language version)
8. NDL Authority ID, also known as NDLSH (NDL Subject Headings), NDLNA (NDL Name Authority), NDLNAId, NDL identifier, NDL ID (wd:P349 as wdt/p/wdtn): identifier for authority control per the National Diet Library of Japan
9. KBpedia ID, also known as KBpedia ontology, KKO, KBpedia knowledge graph, KBpedia, Kbpedia (wd:P8408 as wdt/p/wdtn): identifier for the KBpedia knowledge graph, which provides consi...operability and extraction of training sets for machine learning
10. Commons category, also known as category on Wikimedia Commons, Wikimedia Commons category, Wikimedia Commons cat, Commons cat, commonscat (wd:P373 as wdt/p): name of the Wikimedia Commons category containing files related to this item (without the prefix "Category:")

No other items found

[Assistant]
The property "named after" (wdt:P138) is available for the entity "Riemannian geometry" (wd:Q761383). This property indicates the entity or event that inspired the subject's name.

I will now write a SPARQL query to find the entity after whom the Riemannian geometry is named using the property "named after" (wdt:P138). I will also include the label of the person for better readability.

[Tool]
Got 1 row and 2 columns:
| person                       | personLabel           |
| ---------------------------- | --------------------- |
| Bernhard Riemann (wd:Q42299) | Bernhard Riemann (en) |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( DISTINCT ?film ) AS ?count ) WHERE {
  ?film wdt:P31 wd:Q11424 ; wdt:P57 wd:Q42574 ; wdt:P577 ?date .
  FILTER ( YEAR( ?date ) < 2010 )
}

Got 1 row and 1 column:
| count        |
| ------------ |
| 11 (xsd:int) |

James Cameron has directed 11 movies prior to the year 2010.

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

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

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

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

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

[User] How many movies has James Cameron directed prior to the year 2010?

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

[Tool]
Example 1:
Question:
How many films did Leonardo DiCaprio star in?

SPARQL:
SELECT ( COUNT( DISTINCT ?uri ) AS ?c ) WHERE {
  ?uri wdt:P31 wd:Q11424 ; wdt:P161 wd:Q38111 .
}

Using entities:
film, also known as cinematic work, moving picture, movie, motion pictures, motion picture (wd:Q11424): sequence of images that give the impression of movement, stored on film stock
Leonardo DiCaprio (wd:Q38111): American actor and film producer (born 1974), television actor, environmentalist, film producer, screenwriter, stage actor, film actor, actor

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

Example 2:
Question:
Who composed the soundtrack for Cameron's Titanic?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q44578 wdt:P86 ?uri
}

Using entities:
Titanic (wd:Q44578): 1997 film by James Cameron

Using properties:
composer, also known as music by, written by, songwriter, musical score by, film score by (wd:P86 as wdt): person(s) who wrote the music [for lyricist, use "lyrics by" (P676)], creator

Example 3:
Question:
How many James Bond movies do exist?

SPARQL:
SELECT ( COUNT( ?s1 ) as ?c ) WHERE {
  ?s1 wdt:P31 wd:Q11424 .
  ?s1 ?p wd:Q2009573 .
  FILTER ( ?p = wdt:P144 || ?p = wdt:P674 )
}

Using entities:
film, also known as cinematic work, moving picture, movie, motion pictures, motion picture (wd:Q11424): sequence of images that give the impression of movement, stored on film stock
James Bond, also known as Agent 007, double o seven, 007 (wd:Q2009573): secret agent, invented by novellist Ian Fleming, 00 Agent, spy

Using properties:
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

[Assistant]
From the examples, we see that movies are represented as instances of the class "film" (wd:Q11424) and the director is linked with the property "director" (wdt:P57). We want to count the number of films directed by James Cameron (wd:Q1043) before the year 2010. The year of publication or release can be found with the property "publication date" (wdt:P577).

Next, I will search for the entity James Cameron to confirm his Wikidata ID. Then I will build a query to count the movies he directed before 2010.

[Tool]
Top 10 entity alternatives:
1. James Cameron, also known as James Francis Cameron, J. F. Cameron, J F Cameron, Jim Cameron, J.F. Cameron (wd:Q42574): Canadian filmmaker (born 1954), television producer, philanthropist, film director, film producer, screenwriter, film editor, inventor, director, engineer, explorer, actor
2. James Cameron (wd:Q3160968): 19th century Scottish artisan missionary (1800–1875), artisan
3. James Cameron (wd:Q6130912): South African cricketer, cricketer
4. James Cameron, also known as James Herbert Cameron, Jr. (wd:Q10305062): American civil rights activist (1914-2006), civil rights advocate, writer
5. James Cameron (wd:Q6130916): Scottish footballer (1868-1934), association football manager, association football player
6. James Cameron, also known as Mark James Walter Cameron (wd:Q6130915): British journalist (1911–1985), television presenter, autobiographer, journalist
7. Cameron James, also known as Cameron Lewis James (wd:Q24060497): association football player (born 1998), association football player
8. James Cameron, also known as James Gair Cameron (wd:Q6130910): Zimbabwean cricketer, cricketer
9. James R. Cameron, also known as James Cameron, James Reese Cameron (wd:Q6141583): American historian (born 1929), historian
10. James Cameron (wd:Q119824536): association football player, Canadian soccer player

[Assistant] The correct entity for the filmmaker James Cameron is wd:Q42574. Now I will write a SPARQL query to count the number of films (wd:Q11424) directed by James Cameron (wd:Q42574) with a publication date before 2010.

[Tool]
Got 1 row and 1 column:
| count        |
| ------------ |
| 11 (xsd:int) |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?inventor ?inventorLabel ?namedAfter ?namedAfterLabel WHERE {
  wd:Q623561 wdt:P61 ?inventor .
  wd:Q623561 wdt:P138 ?namedAfter .
  OPTIONAL {
    ?inventor rdfs:label ?inventorLabel FILTER ( LANG( ?inventorLabel ) = "en" )
  }
  OPTIONAL {
    ?namedAfter rdfs:label ?namedAfterLabel FILTER ( LANG( ?namedAfterLabel ) = "en" )
  }
}

Dr. Pepper's inventor is Charles Courtice Alderton, but it is named after Charles T. Pepper. So, Dr. Pepper is not named after its inventor.

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

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

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

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

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

[User] Is Dr. Pepper named after its inventor?

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

[Tool]
Example 1:
Question:
Who created Goofy?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q111135 wdt:P170 ?uri .
}

Using entities:
Goofy, also known as Dippy Dawg, George Geef, Goofy Goof (wd:Q111135): Disney cartoon character

Using properties:
creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as wdt): maker of this creative work or other object (where no more specific property exists)

Example 2:
Question:
Who created Wikipedia?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q52 wdt:P112 ?uri .
}

Using entities:
Wikipedia, also known as Wikipedia, the free encyclopedia, The Free Encyclopedia, Wikipedia, the free encyclopedia that anyone can edit, WP, Wikipaedia (wd:Q52): free multilingual online encyclopedia

Using properties:
founded by, also known as starter, co-founded by, started by, institutor, instituted by (wd:P112 as wdt): founder or co-founder of this organization, religion, place or entity, creator

Example 3:
Question:
Who founded Intel?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q248 wdt:P112 ?uri .
}

Using entities:
Intel, also known as INTC, Integrated Electronics, Integrated Electronics Corporation, INTEL CORPORATION (Santa Clara, CA), N M Electronics (wd:Q248): American multinational technology corporation, American multinational technology company

Using properties:
founded by, also known as starter, co-founded by, started by, institutor, instituted by (wd:P112 as wdt): founder or co-founder of this organization, religion, place or entity, creator

[Assistant]
The examples suggest that to find the inventor or founder of something, we can look for properties like "creator" (wdt:P170) or "founder" (wdt:P112). In the case of Dr. Pepper, we want to find the inventor or creator of the product and check if the product is named after that person.

Step 1: Identify the entity for Dr. Pepper.
Step 2: Find the inventor or creator of Dr. Pepper.
Step 3: Check if the name of Dr. Pepper corresponds to the inventor's name.

I will start by searching for the entity "Dr. Pepper" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Dr Pepper, also known as Dr. Pepper (wd:Q623561): carbonated soft drink
2. Keurig Dr Pepper, also known as Green Mountain Coffee, Green Mountain Coffee Roasters, Keurig Green Mountain (wd:Q3116111): American beverage company
3. Comerica Center, also known as Deja Blue Arena, Dr Pepper Arena (wd:Q637300): stadium
4. Dr. Pepper Museum (wd:Q25421126): museum
5. Dublin Dr Pepper (wd:Q5310881): popular name for a style of Dr Pepper soft drink
6. Dr. Pepper Syrup Plant, also known as Dr. Pepper Building (wd:Q124038489): historic building in Birmingham, Alabama, United States
7. Diet Dr Pepper (wd:Q19903950): low-calorie soft drink
8. Pepper Drain (wd:Q49265671): canal in Imperial County, California, United States of America
9. Dr. William Pepper (wd:Q94045516): scientific article published in September 1898
10. Dr. Peppercorn (wd:Q20536983): painting by Gene Davis

[Assistant] I found the entity for Dr. Pepper as a carbonated soft drink with the identifier wd:Q623561. Now I will look for the inventor or creator of Dr. Pepper using properties like "creator" (wdt:P170) or "inventor" (wdt:P61) or "founder" (wdt:P112).

[Tool]
Got 227 rows and 3 columns, showing the first 10 rows below:
| subject                | property                           | object                                                                             |
| ---------------------- | ---------------------------------- | ---------------------------------------------------------------------------------- |
| Dr Pepper (wd:Q623561) | instance of (wdt:P31)              | invention (wd:Q14208553)                                                           |
| Dr Pepper (wd:Q623561) | country (wdt:P17)                  | United States (wd:Q30)                                                             |
| Dr Pepper (wd:Q623561) | Commons category (wdt:P373)        | Dr Pepper                                                                          |
| Dr Pepper (wd:Q623561) | image (wdt:P18)                    | <http://commons.wikimedia.org/wiki/Special:FilePath/Dr%20Pepper%20Dose%202024.jpg> |
| Dr Pepper (wd:Q623561) | subclass of (wdt:P279)             | soft drink (wd:Q147538)                                                            |
| Dr Pepper (wd:Q623561) | inception (wdt:P571)               | 1885-01-01T00:00:00Z (xsd:dateTime)                                                |
| Dr Pepper (wd:Q623561) | country of origin (wdt:P495)       | United States (wd:Q30)                                                             |
| Dr Pepper (wd:Q623561) | official name (wdt:P1448)          | Dr Pepper (en)                                                                     |
| Dr Pepper (wd:Q623561) | official website (wdt:P856)        | <https://www.drpepper.com/>                                                        |
| Dr Pepper (wd:Q623561) | social media followers (wdt:P8687) | 461950 (xsd:decimal)                                                               |
| ...                    | ...                                | ...                                                                                |

[Assistant] The list of properties for Dr. Pepper does not immediately show an inventor or creator property. I will specifically search for properties related to "inventor" or "creator" for Dr. Pepper.

[Tool]
Top 10 property alternatives:
1. discoverer or inventor, also known as inventor or discoverer, inventor, invented by, invented, introduced by (wd:P61 as wdt/p): subject who discovered, first described, invented, or developed this discovery or invention or scientific hypothesis or theory
2. manufacturer, also known as manufactured by, provider, provided by, product of, producer (wd:P176 as wdt/p): (main or final) manufacturer or producer of this product
3. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as wdt/p): time when an entity begins to exist; for date of official opening use P1619, start time
4. named after, also known as toponym, namesake, named in honor of, named for, 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
5. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
6. official name, also known as long title, name, official title, registered name, full title (wd:P1448 as wdt/p): official name of the subject in its official language(s), name
7. country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as wdt/p): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country
8. logo image, also known as masthead, wordmark, trademark, trade mark, sign (wd:P154 as wdt/p): graphic mark or emblem commonly used by commercial enterprises, organizations and products, icon

No other items found

[Assistant] There is a property "discoverer or inventor" (wdt:P61) and a property "named after" (wdt:P138) which seem relevant. I will check if Dr. Pepper has a value for "discoverer or inventor" (wdt:P61).

[Tool]
Got 1 row and 3 columns:
| subject                | property                         | object                                   |
| ---------------------- | -------------------------------- | ---------------------------------------- |
| Dr Pepper (wd:Q623561) | discoverer or inventor (wdt:P61) | Charles Courtice Alderton (wd:Q24004555) |

[Assistant] Dr. Pepper's inventor is Charles Courtice Alderton (wd:Q24004555). Now I will check if Dr. Pepper is named after this inventor by looking at the "named after" property (wdt:P138).

[Tool]
Got 1 row and 3 columns:
| subject                | property               | object                          |
| ---------------------- | ---------------------- | ------------------------------- |
| Dr Pepper (wd:Q623561) | named after (wdt:P138) | Charles T. Pepper (wd:Q5082829) |

[Assistant] Dr. Pepper is named after Charles T. Pepper (wd:Q5082829), not Charles Courtice Alderton, the inventor. Therefore, Dr. Pepper is not named after its inventor. I will now provide the final answer.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT DISTINCT ?album ?albumLabel ?date WHERE {
  ?album wdt:P31 wd:Q482994 .
  ?album wdt:P175 wd:Q238819 .
  ?album wdt:P577 ?date .
  OPTIONAL {
    ?album rdfs:label ?albumLabel FILTER ( LANG( ?albumLabel ) = "en" )
  }
}
ORDER BY ?date
LIMIT 1

The first album of Jay Chou is "Jay" (wd:Q221115), released on November 6, 2000.

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

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

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

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

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

[User] The first album of Jay Chou

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

[Tool]
Example 1:
Question:
What was the first Queen album?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q482994 .
  ?uri wdt:P175 wd:Q15862 .
  ?uri wdt:P577 ?date
}
ORDER BY ?date
LIMIT 1

Using entities:
Queen (wd:Q15862): British musical group; rock band
album, also known as full album, record album, music album, full-length album, audio album (wd:Q482994): grouping of album releases by an artist usually released at the ...racks but in different formats for consumption (digital, CD, LP)

Using properties:
performer, also known as actor, sung by, singer, recording by, recorded by (wd:P175 as wdt): actor, musician, band or other performer associated with this role or musical work, contributor to the creative work or subject
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
publication date, also known as launched, published, publication time, publication, pubdate (wd:P577 as wdt): date or point in time when a work was first published or released, point in time

[Assistant]
From the example, we see that to find the first album of an artist, we can query for items that are instances of "album" (wd:Q482994) and have the artist as the performer (wdt:P175). Then we order by the publication date (wdt:P577) and limit the result to 1 to get the first album.

Next, I will search for the entity "Jay Chou" to get his Wikidata ID.

[Tool]
Top 10 entity alternatives:
1. Jay Chou, also known as President Chou, Zhou Jielun, Chou Chieh-lun (wd:Q238819): Taiwanese pop singer, songwriter, and actor, recording artist, record producer, film director, songwriter, composer, director, rapper, singer, actor
2. Jayanta Choudhury (wd:Q102339960): Ph.D. University of Louisiana at Lafayette 2008
3. Jaya Choudhary (wd:Q88317282): researcher
4. Jayadratha Choudhury (wd:Q107562664): Indian Odia-language writer, writer
5. Jay Chou's Bedtime Stories (wd:Q24595331): 2016 studio album by Jay Chou
6. Jayanta Narayan Choudhury, also known as Jayanto Narayan Choudhury (wd:Q110437452): Indian police officer
7. Choudhury Jayprakash Das, also known as Choudhury Jayaprakash Das, Caudhurī Jaẏaprakāśa Dāsa (wd:Q60511536): Indian actor and academic, film actor, teacher, actor
8. Jay Chou 2007 World Tour Concert Live (wd:Q1100149): live album
9. J, also known as ᴊ, Juliett, Juliet, j, jay (wd:Q9773): 10th-17th letter of Latin alphabets
10. Eurasian Jay, also known as Garrulus glandarius, Jay, European Jay (wd:Q25354): species of bird

[Assistant] The entity for Jay Chou is wd:Q238819. Now I will write a SPARQL query to find the first album of Jay Chou by looking for albums where he is the performer and ordering by publication date.

[Tool]
Got 1 row and 3 columns:
| album            | albumLabel | date                                |
| ---------------- | ---------- | ----------------------------------- |
| Jay (wd:Q221115) | Jay (en)   | 2000-11-06T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?show ?showLabel WHERE {
  ?show wdt:P31 wd:Q5398426 .
  ?show wdt:P580 ?startTime .
  FILTER ( YEAR( ?startTime ) = 1975 ) OPTIONAL {
    ?show rdfs:label ?showLabel FILTER ( LANG( ?showLabel ) = "en" )
  }
}

Got 249 rows and 2 columns, showing the first 5 and last 5 rows below:
| show                                               | showLabel                                  |
| -------------------------------------------------- | ------------------------------------------ |
| Gabriela (wd:Q10287918)                            | Gabriela (en)                              |
| On the Mat (wd:Q10340891)                          | On the Mat (en)                            |
| Cher (wd:Q10381261)                                | Cher (en)                                  |
| Carry On Laughing (wd:Q1045360)                    | Carry On Laughing (en)                     |
| Space: 1999 (wd:Q1045743)                          | Space: 1999 (en)                           |
| ...                                                | ...                                        |
| Beschlossen und verkündet (wd:Q829585)             | Beschlossen und verkündet (en)             |
| wd:Q86210547                                       |                                            |
| Krempoli - Ein Platz für wilde Kinder (wd:Q872205) | Krempoli - Ein Platz für wilde Kinder (en) |
| Krempoli - Ein Platz für wilde Kinder (wd:Q872205) | Krempoli - Ein Platz für wilde Kinder (en) |
| Miś Uszatek (wd:Q929924)                           | Miś Uszatek (en)                           |

The shows that aired for the first time in the same year as Saturday Night Live (1975) include Gabriela, On the Mat, Cher, Carry On Laughing, Space: 1999, Beschlossen und verkündet, Krempoli - Ein Platz für wilde Kinder, Miś Uszatek, and many others.

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

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

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

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

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

[User] Which shows aired for the first time the same year as Saturday Night Live ?

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

[Tool]
Example 1:
Question:
Which television shows were created by John Cleese?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q5398426 .
  {
    ?uri wdt:P170 wd:Q25014 .
  } UNION {
    ?uri wdt:P170 / wdt:P527 wd:Q25014 .
  }
}

Using entities:
John Cleese, also known as John Marwood Cleese (wd:Q25014): English comedian and actor (born 1939), television actor, autobiographer, film producer, film director, screenwriter, stage actor, voice actor, film actor, comedian, writer, actor
television series, also known as TV show, TV-series, television show, TV series (wd:Q5398426): connected set of television program episodes under the same title

Using properties:
creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as wdt): maker of this creative work or other object (where no more specific property exists)
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as wdt): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).

Example 2:
Question:
List all episodes of the first season of the HBO television series The Sopranos!

SPARQL:
SELECT ( COUNT( ?episode ) AS ?count ) WHERE {
  ?episode wdt:P4908 wd:Q5274359 .
}

Using entities:
The Sopranos, season 1 (wd:Q5274359): season of television series

Using properties:
season, also known as TV series, television season, TV season, television series, series of television program (wd:P4908 as wdt): season of a series (televison, web, podcast), part of

Example 3:
Question:
Give me all the TV shows with Neil Patrick Harris.

SPARQL:
SELECT ?uri WHERE {
  ?type wdt:P279 * wd:Q15416 .
  ?uri wdt:P161 wd:Q485310 .
  ?uri wdt:P31 ?type .
}

Using entities:
television program, also known as TV show, television broadcast, T.V. show, T. V. show, TV programme (wd:Q15416): segment of audiovisual content intended for broadcast on television
Neil Patrick Harris, also known as NPH (wd:Q485310): American actor (born 1973), television presenter, television producer, theatrical director, television actor, stage magician, autobiographer, film director, film producer, screenwriter, voice actor, stage actor, illusionist, film actor, dub actor, memoirist, musician, comedian, dancer, singer, actor

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

[Assistant]
The question is about finding shows that aired for the first time in the same year as "Saturday Night Live." To answer this, we need to:

1. Identify the entity for "Saturday Night Live."
2. Find the year it first aired.
3. Find other shows that first aired in the same year.

I will start by searching for the entity "Saturday Night Live" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Saturday Night Live, also known as Saturday Night, NBC's Saturday Night (wd:Q13979): American late-night live television sketch comedy show
2. Saturday Night Live (wd:Q6122059): television series
3. Saturday Night Live (wd:Q23039888): tv show aired in 2016
4. Saturday Night Live (wd:Q28452163): album by Trouble Funk
5. Saturday Night Live Korea, also known as SNL Korea, SNL.KOREA, SNL Korea 6 (wd:Q7426718): 2011 South Korean television series
6. Le Saturday Night Live (wd:Q28194825): French late-night live television comedy show
7. Saturday Night Live Japan (wd:Q11304712): Japanese TV series or program
8. history of Saturday Night Live, also known as Saturday Night Live history (wd:Q5866387): List article
9. Katy Perry/Robyn, also known as Saturday Night Live Season 37 Episode 9, Saturday Night Live S37E9, Saturday Night Live, season 37 episode 9 (wd:Q5483492): episode of Saturday Night Live (S37 E9)
10. Saturday Night Live Samurai (wd:Q7426709): recurring SNL character, samurai

[Assistant] The entity "Saturday Night Live" as an American late-night live television sketch comedy show is wd:Q13979. Now I will find the year it first aired. I will look for the property related to the first air date or inception.

[Tool]
Top 10 property alternatives:
1. original broadcaster, also known as TV channel, television channel, radio station, radio network, original network (wd:P449 as wdt/p): network(s) or service(s) that originally broadcast a radio or television program, broadcast by
2. start time, also known as start date, since, valid, join time, joined (wd:P580 as wdt/p): time an entity begins to exist or a statement starts being valid, point in time
3. TheTVDB series ID, also known as TheTVDB.com series ID (wd:P4835 as wdt/p): identifier for a television series at TheTVDB.com
4. number of episodes, also known as series length, no. of episodes, episodes, episode count (wd:P1113 as wdt/p): number of episodes in a film/TV/radio series, number of parts of this work
5. Television Academy Foundation show ID, also known as The Interviews title ID (wd:P5829 as wdt/p): identifier for a television show discussed on the Television Academy Foundation's The Interviews website
6. presenter, also known as TV host, TV presenter, presented by, hostess, hosted by (wd:P371 as wdt/p): main role in presenting a radio or television program or a performing arts show, significant person, cast member
7. TMDB TV series ID, also known as TMDb TV show ID, themoviedb.org TV show ID, The Movie Database TV show ID, The Movie Database TV series ID, themoviedb.org TV series ID (wd:P4983 as wdt/p): identifier for a TV show at The Movie Database
8. original language of film or TV show, also known as media language, original language, language of the original work, created on language (wd:P364 as wdt/p): language in which a film or a performance work was originally cr... works and songs; use P407 ("language of work or name") instead., language of work or name
9. RatingGraph TV show ID, also known as RatinGraph TV show ID (wd:P12544 as wdt/p): identifier for a TV show on the RatingGraph site
10. TV Tropes ID, also known as Tropes ID, Tropes identifier, TV Tropes, TVTropes ID, TV Tropes identifier (wd:P6839 as wdt/p): identifier in the TV Tropes online wiki

No other items found

[Assistant] The property "start time" (wdt:P580) seems to be the appropriate property for the first air date or the time an entity begins to exist. I will now query the start time for Saturday Night Live (wd:Q13979).

[Tool]
Got 1 row and 1 column:
| startTime                           |
| ----------------------------------- |
| 1975-10-11T00:00:00Z (xsd:dateTime) |

[Assistant] Saturday Night Live first aired in the year 1975. Now I will find other shows that first aired in the same year 1975. I will look for entities that are instances of television shows and have a start time in 1975.

[Tool]
Top 10 entity alternatives:
1. television program, also known as TV show, television broadcast, T.V. show, T. V. show, TV programme (wd:Q15416): segment of audiovisual content intended for broadcast on television
2. television series, also known as TV show, TV-series, television show, TV series (wd:Q5398426): connected set of television program episodes under the same title
3. reality television, also known as reality TV program, TV reality show, TV reality program, television reality show, television reality program (wd:Q182415): genre of television programming that documents unscripted situations and actual occurrences
4. television presenter, also known as television anchor, TV show host, TV presenter, TV host, TV anchor (wd:Q947873): person who introduces or hosts television programs
5. variety show, also known as television variety program, television variety show, variety, variety entertainment, variety program (wd:Q336181): television genre characterized by a series of specialty acts such as music, dance, comedy, magic, acrobatics and ventriloquism
6. showrunner, also known as television show creator (wd:Q1440873): person who is responsible for the day-to-day operation of a television show
7. breakfast television, also known as breakfast show, morning show, morning talk show, morning television show (wd:Q1472288): type of morning television show
8. reality show, also known as reality television program, TV reality show, TV reality program, television reality show, television reality program (wd:Q3421644): television genre
9. television series season, also known as TV show season, TV series season, TV season, season of a TV show, television show season (wd:Q3464665): set of episodes produced for a television series
10. drama television program, also known as TV drama, television drama show, television drama program, television drama, teledrama (wd:Q110593089): television genre

[Assistant] The entity "television series" (wd:Q5398426) seems to be the most suitable for the concept of a TV show. I will now write a query to find television series that first aired in 1975.

[Tool]
Got 249 rows and 2 columns, showing the first 5 and last 5 rows below:
| show                                               | showLabel                                  |
| -------------------------------------------------- | ------------------------------------------ |
| Gabriela (wd:Q10287918)                            | Gabriela (en)                              |
| On the Mat (wd:Q10340891)                          | On the Mat (en)                            |
| Cher (wd:Q10381261)                                | Cher (en)                                  |
| Carry On Laughing (wd:Q1045360)                    | Carry On Laughing (en)                     |
| Space: 1999 (wd:Q1045743)                          | Space: 1999 (en)                           |
| ...                                                | ...                                        |
| Beschlossen und verkündet (wd:Q829585)             | Beschlossen und verkündet (en)             |
| wd:Q86210547                                       |                                            |
| Krempoli - Ein Platz für wilde Kinder (wd:Q872205) | Krempoli - Ein Platz für wilde Kinder (en) |
| Krempoli - Ein Platz für wilde Kinder (wd:Q872205) | Krempoli - Ein Platz für wilde Kinder (en) |
| Miś Uszatek (wd:Q929924)                           | Miś Uszatek (en)                           |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?team ?teamLabel ( COUNT( ?final ) AS ?wins ) WHERE {
  ?final wdt:P31 wd:Q842375 .
  ?final wdt:P1346 ?team .
  OPTIONAL {
    ?team rdfs:label ?teamLabel FILTER ( LANG( ?teamLabel ) = "en" )
  }
}
GROUP BY ?team ?teamLabel
ORDER BY DESC ( ?wins )
LIMIT 10

Got 10 rows and 3 columns:
| team                               | teamLabel                  | wins         |
| ---------------------------------- | -------------------------- | ------------ |
| Boston Celtics (wd:Q131371)        | Boston Celtics (en)        | 17 (xsd:int) |
| Los Angeles Lakers (wd:Q121783)    | Los Angeles Lakers (en)    | 16 (xsd:int) |
| Chicago Bulls (wd:Q128109)         | Chicago Bulls (en)         | 6 (xsd:int)  |
| San Antonio Spurs (wd:Q159729)     | San Antonio Spurs (en)     | 5 (xsd:int)  |
| Golden State Warriors (wd:Q157376) | Golden State Warriors (en) | 4 (xsd:int)  |
| Detroit Pistons (wd:Q169661)       | Detroit Pistons (en)       | 3 (xsd:int)  |
| Philadelphia 76ers (wd:Q138089)    | Philadelphia 76ers (en)    | 3 (xsd:int)  |
| Houston Rockets (wd:Q161345)       | Houston Rockets (en)       | 2 (xsd:int)  |
| Milwaukee Bucks (wd:Q169637)       | Milwaukee Bucks (en)       | 2 (xsd:int)  |
| Miami Heat (wd:Q169138)            | Miami Heat (en)            | 2 (xsd:int)  |

The NBA teams that have won the most seasons (NBA Finals championships) are:
1. Boston Celtics with 17 wins
2. Los Angeles Lakers with 16 wins
3. Chicago Bulls with 6 wins
4. San Antonio Spurs with 5 wins
5. Golden State Warriors with 4 wins
6. Detroit Pistons with 3 wins
7. Philadelphia 76ers with 3 wins
8. Houston Rockets with 2 wins
9. Milwaukee Bucks with 2 wins
10. Miami Heat with 2 wins

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

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

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

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

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

[User] Which NBA teams have won the most seasons?

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

[Tool]
Example 1:
Question:
Who is the tallest basketball player?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P106 wd:Q3665646 ; wdt:P2048 ?height .
}
ORDER BY DESC ( ?height )
LIMIT 1

Using entities:
basketball player, also known as basketballer, basketeer, cager, hoopster, professional basketball player (wd:Q3665646): person who plays in basketball

Using properties:
occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
height, also known as heighth, size, depth over terrain (wd:P2048 as wdt): vertical length of an entity, length

Example 2:
Question:
Show me all basketball players that are higher than 2 meters.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P106 wd:Q3665646 .
  ?uri wdt:P2048 ?height .
  FILTER ( ?height > 200 )
}

Using entities:
basketball player, also known as basketballer, basketeer, cager, hoopster, professional basketball player (wd:Q3665646): person who plays in basketball

Using properties:
occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
height, also known as heighth, size, depth over terrain (wd:P2048 as wdt): vertical length of an entity, length

Example 3:
Question:
Who are the four youngest MVP basketball players?

SPARQL:
SELECT ?uri WHERE {
  ?uri wdt:P106 wd:Q3665646 ; wdt:P569 ?birthDate ; wdt:P166 ?award .
  ?award rdfs:label ?awardLabel
  FILTER ( CONTAINS( STR( ?awardLabel ) , "MVP" ) || CONTAINS( STR( ?awardLabel ) , "Most Valuable Player" ) ) .
  FILTER ( LANGMATCHES( LANG( ?awardLabel ) , "EN" ) )
}
ORDER BY DESC ( ?birthDate )
LIMIT 4

Using entities:
basketball player, also known as basketballer, basketeer, cager, hoopster, professional basketball player (wd:Q3665646): person who plays in basketball

Using properties:
occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as wdt): award or recognition received by a person, organization or creative work
date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as wdt): date on which the subject was born, inception

[Assistant]
The examples found are related to basketball players and their attributes, but not directly about NBA teams and their championship wins.

To answer the question "Which NBA teams have won the most seasons?" we need to identify the NBA teams and the property that indicates the number of seasons or championships won by each team.

Step 1: Search for the entity "NBA team" to find the correct entity for NBA teams.
Step 2: Search for properties related to "championships won" or "seasons won" for NBA teams.

I will start by searching for the entity "NBA team".

[Tool]
Top 10 entity alternatives:
1. NBA All-Defensive Team (wd:Q1465181): annual National Basketball Association honor
2. NBA All-Rookie Team (wd:Q1418009): award
3. NBA 35th Anniversary Team (wd:Q6130281): Wikipedia list article
4. NBA 25th Anniversary Team (wd:Q4383249): Lists of player who still playing in NBA
5. NBA anniversary teams (wd:Q109299766): Fantasy teams to commemorate the NBA's anniversaries
6. Valley Suns, also known as Phoenix NBA G League team (wd:Q124649324): basketball team in Tempe, Arizona
7. NBA Live Legend All-Stars Teams (wd:Q16955386)
8. Billionaires Lay Out Bucks for NBA Team (wd:Q114844156): Wall Street Journal article (April 16, 2014)
9. National Basketball Association, also known as Basketball Association of America, BAA, NBA, National Basketball Assn., Nat'l Basketball Assn. (wd:Q155223): North American professional men's basketball league
10. team (wd:Q327245): group linked in a common purpose

[Assistant]
The search for "NBA team" did not return a direct entity for NBA teams, but the National Basketball Association itself is wd:Q155223. NBA teams are likely instances or members of this league.

Next, I will search for properties related to championships or titles won by NBA teams. I will search for properties with the query "championships won".

[Tool]
Top 10 property alternatives:
1. number of wins, also known as games won, won, wins, W, sporting wins (wd:P1355 as psv/pr/pqn/prv/psn/wdt/wdtn/pq/prn/p/pqv/ps): number of sporting matches, games or events won
2. competition won, also known as won event, won, winner of, victory (wd:P2522 as psv/pr/pqn/prv/psn/wdt/wdtn/pq/prn/p/pqv/ps): competition or sports event won by the subject, participant in
3. sports competition competed at (wd:P5249 as psv/pr/pqn/prv/psn/wdt/wdtn/pq/prn/p/pqv/ps): edition of sports competitions at which the club or team that pl...ple: 2012–13 FC Barcelona season → 2012–13 UEFA Champions League
4. winner, also known as nominee, prizewinner, titleholder, top dog, victor (wd:P1346 as psv/pr/pqn/prv/psn/wdt/wdtn/pq/prn/p/pqv/ps): winner of a competition or similar event, not to be used for awa...ssibly qualified with "for work" (P1686)) or for wars or battles, participating team, participant
5. participant in, also known as participated in, present at, takes part, took part, took part in (wd:P1344 as psv/pr/pqn/prv/psn/wdt/wdtn/pq/prn/p/pqv/ps): event in which a person or organization was/is a participant; inverse of P710 or P1923, significant event, part of
6. points for, also known as championship points, competition points, league points, pf, points (wd:P1358 as psv/pr/pqn/prv/psn/wdt/wdtn/pq/prn/p/pqv/ps): number of points in a league table or decathlon. (Use P1351 for goals/points in a match)
7. trophy awarded, also known as cup awarded, diploma awarded, medal awarded (wd:P4622 as psv/pr/pqn/prv/psn/wdt/wdtn/pq/prn/p/pqv/ps): trophy awarded at the end of a selection process or of a competi...winners or finishers under the form of a cup, a medal, a diploma
8. commemorates, also known as monument to, memorial to, memorializes, marks, in memory of (wd:P547 as psv/pr/pqn/prv/psn/wdt/wdtn/pq/prn/p/pqv/ps): what the place, monument, memorial, or holiday, commemorates, main subject
9. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as psv/pr/pqn/prv/psn/wdt/wdtn/pq/prn/p/pqv/ps): award or recognition received by a person, organization or creative work
10. member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as psv/pr/pqn/prv/psn/wdt/wdtn/pq/prn/p/pqv/ps): sports teams or clubs that the subject represents or represented, member of

[Assistant]
The property "number of wins" (wdt:P1355) and "competition won" (wdt:P2522) seem relevant. Also, "award received" (wdt:P166) might be useful for championships.

I will now search for NBA teams by querying for instances or members of the National Basketball Association (wd:Q155223). Then, I will check if they have any property related to championships or titles won.

I will start by finding teams that are part of the NBA.

[Tool]
Got 10 rows and 2 columns:
| team                              | teamLabel              |
| --------------------------------- | ---------------------- |
| John Jenkins (wd:Q1000791)        | John Jenkins (en)      |
| Jabari Smith Jr. (wd:Q100268254)  | Jabari Smith Jr. (en)  |
| Ron Harper Jr. (wd:Q100324395)    | Ron Harper Jr. (en)    |
| Jean-Paul Afif (wd:Q100718566)    | Jean-Paul Afif (en)    |
| Dalano Banton (wd:Q100744432)     | Dalano Banton (en)     |
| Buddy Boeheim (wd:Q100753966)     | Buddy Boeheim (en)     |
| Christian Braun (wd:Q100759022)   | Christian Braun (en)   |
| Trevon Scott (wd:Q100763518)      | Trevon Scott (en)      |
| Julian Champagnie (wd:Q100768908) | Julian Champagnie (en) |
| Justin Champagnie (wd:Q100768909) | Justin Champagnie (en) |

[Assistant]
The query returned basketball players, not teams. The property P118 (league) points to the NBA for players as well.

I will try a different approach: I will search for entities with the label "NBA team" or similar to find the class or category for NBA teams. Then I will find instances of that class.

I will search for entities with the query "NBA team" again but this time looking for classes or categories.

[Tool]
Top 10 entity alternatives:
1. NBA All-Defensive Team (wd:Q1465181): annual National Basketball Association honor
2. NBA All-Rookie Team (wd:Q1418009): award
3. NBA 35th Anniversary Team (wd:Q6130281): Wikipedia list article
4. NBA 25th Anniversary Team (wd:Q4383249): Lists of player who still playing in NBA
5. NBA anniversary teams (wd:Q109299766): Fantasy teams to commemorate the NBA's anniversaries
6. Valley Suns, also known as Phoenix NBA G League team (wd:Q124649324): basketball team in Tempe, Arizona
7. NBA Live Legend All-Stars Teams (wd:Q16955386)
8. Billionaires Lay Out Bucks for NBA Team (wd:Q114844156): Wall Street Journal article (April 16, 2014)
9. National Basketball Association, also known as Basketball Association of America, BAA, NBA, National Basketball Assn., Nat'l Basketball Assn. (wd:Q155223): North American professional men's basketball league
10. team (wd:Q327245): group linked in a common purpose

[Assistant]
The search did not return a clear class or category for NBA teams. I will try to find the property "sports team" or "basketball team" and then filter for NBA teams.

I will search for entities with the query "basketball team".

[Tool]
Top 10 entity alternatives:
1. Basketball Team (wd:Q117247086): photograph by Kors (20th century)
2. basketball team, also known as basket club (wd:Q13393265): collective name of a constituted group of players of basketball
3. Duke Blue Devils men's basketball, also known as Duke University Blue Devils basketball team, Duke University Blue Devils men's basketball, Duke University Blue Devils men's basketball team, Duke University men's basketball, Duke University men's basketball team (wd:Q4171772): college men's basketball team representing Duke University
4. North Carolina Tar Heels men's basketball, also known as North Carolina Tar Heels, UNC Tar Heels men's basketball team, UNC Tarheels men's basketball team, UNC Tar Heels men's basketball, UNC Tarheels men's basketball (wd:Q4412061): sports team of the University of North Carolina at Chapel Hill
5. UCLA Bruins men's basketball, also known as University of California Los Angeles men's basketball, UCLA men's basketball, UCLA Bruins men's basketball team, UCLA Bruins bball, UCLA Bruins basketball team (wd:Q3615392): college basketball team of the University of California, Los Angeles
6. Hong Kong Eastern Basketball Team, also known as Eastern Basketball team, Eastern Long Lions, Eastern Long Lions Basketball Team, Eastern Sports Club, HK Eastern Basketball Team (wd:Q23035583): Hong Kong basketball team
7. Team USA Basketball (wd:Q3516725): 1992 video game
8. Auburn Tigers men's basketball, also known as Auburn University men's basketball team, Auburn University Tigers men's basketball team, Auburn University Tigers men's basketball, Auburn University Tigers basketball team, Auburn University Tigers basketball (wd:Q4819312): men's basketball team at Auburn University
9. Oregon Ducks men's basketball, also known as University of Oregon men's basketball, University of Oregon men's basketball team, University of Oregon Ducks men's basketball team, University of Oregon Ducks men's basketball, University of Oregon Ducks basketball team (wd:Q7101188): basketball team representing the University of Oregon
10. Villanova Wildcats men's basketball, also known as Villanova men's basketball, Villanova University Wildcats basketball, Villanova University Wildcats basketball team, Villanova University Wildcats men's basketball, Villanova University's men's basketball team (wd:Q7930886): basketball team for Villanova University

[Assistant]
The entity "basketball team" is wd:Q13393265. NBA teams should be instances or subclasses of this.

I will now find instances of basketball teams that are part of the NBA (wd:Q155223).

I will query for basketball teams that have the NBA as their league.

[Tool]
Got 10 rows and 2 columns:
| team                               | teamLabel                  |
| ---------------------------------- | -------------------------- |
| Los Angeles Lakers (wd:Q121783)    | Los Angeles Lakers (en)    |
| Chicago Bulls (wd:Q128109)         | Chicago Bulls (en)         |
| New York Knicks (wd:Q131364)       | New York Knicks (en)       |
| Boston Celtics (wd:Q131371)        | Boston Celtics (en)        |
| Toronto Raptors (wd:Q132880)       | Toronto Raptors (en)       |
| Dallas Mavericks (wd:Q132893)      | Dallas Mavericks (en)      |
| Philadelphia 76ers (wd:Q138089)    | Philadelphia 76ers (en)    |
| Golden State Warriors (wd:Q157376) | Golden State Warriors (en) |
| San Antonio Spurs (wd:Q159729)     | San Antonio Spurs (en)     |
| Atlanta Hawks (wd:Q159893)         | Atlanta Hawks (en)         |

[Assistant]
I found NBA teams as instances of basketball teams that are part of the NBA. Now I need to find the property that indicates the number of seasons or championships won by these teams.

I will check the properties of one of these teams, for example, the Los Angeles Lakers (wd:Q121783), to find relevant properties related to championships or titles won.

[Tool]
Top 10 property alternatives:
1. league or competition, also known as tournament, sports league, division, cup, competition (wd:P118 as wdt/p): league or competition in which team or player has played, or in which an event occurs, participant in
2. sport, also known as play, plays, sport played, sports (wd:P641 as wdt/p): sport that the subject participates or participated in or is associated with
3. home venue, also known as home water, venue, stadium, home ground, home field (wd:P115 as wdt/p): home stadium or venue of a sports team or applicable performing arts organization, location
4. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
5. head coach, also known as team manager, trainer, senior coach, manager, coached by (wd:P286 as wdt/p): on-field manager or head coach of a sports club (not to be confu...eneral manager P505, which is not a coaching position) or person
6. logo image, also known as masthead, wordmark, trademark, trade mark, sign (wd:P154 as wdt/p): graphic mark or emblem commonly used by commercial enterprises, organizations and products, icon
7. owned by, also known as belongs to, stockholders, stockholder, shareholders, shareholder (wd:P127 as wdt/p): owner of the subject
8. headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as wdt/p): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place
9. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as wdt/p): URL of the official page of an item (current or former). Usage: ...but see the "Hijacked or dead websites" section of the Talk page, URL
10. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as wdt/p): time when an entity begins to exist; for date of official opening use P1619, start time

No other items found

[Assistant]
The search for properties related to "championship" for the Los Angeles Lakers did not return a direct property indicating championships or seasons won.

I will try searching for properties related to "titles" or "wins" for the Los Angeles Lakers.

[Tool]
Top 10 property alternatives:
1. subreddit, also known as r/, reddit, Reddit community ID, Reddit forum, Reddit sub ID (wd:P3984 as wdt/p): name of the Reddit forum associated to this subject
2. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as wdt/p): URL of the official page of an item (current or former). Usage: ...but see the "Hijacked or dead websites" section of the Talk page, URL
3. owned by, also known as belongs to, stockholders, stockholder, shareholders, shareholder (wd:P127 as wdt/p): owner of the subject
4. logo image, also known as masthead, wordmark, trademark, trade mark, sign (wd:P154 as wdt/p): graphic mark or emblem commonly used by commercial enterprises, organizations and products, icon
5. topic's main template, also known as topic has template, topic's main module, topic's main infobox, topic infobox, main template (wd:P1424 as wdt/p): the main template relating to a topic
6. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as wdt/p): main Wikimedia category
7. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
8. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as wdt/p): time when an entity begins to exist; for date of official opening use P1619, start time
9. part of, also known as of, within, system of, subsystem of, subgroup of (wd:P361 as wdt/p): object of which the subject is a part (if this subject is alread... of "has part" (P527, see also "has parts of the class" (P2670))
10. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

No other items found

[Assistant]
There is no direct property for titles or championships won for the Los Angeles Lakers in the search results.

I will try a different approach: I will check if there is a property for "championships won" or "NBA championships" for the teams in general by searching for properties with the query "NBA championships".

[Tool]
Top 10 property alternatives:
1. sports discipline competed in, also known as sport discipline competed in, weight class competed in, sports event, sports disciplines competed in, sports discipline (wd:P2416 as psv/pr/pqn/prv/psn/wdt/wdtn/pq/prn/p/pqv/ps): discipline an athlete competed in within a sport, field of work
2. Hoopla artist ID, also known as hoopladigital.com (wd:P6868 as psv/pr/pqn/prv/psn/wdt/wdtn/pq/prn/p/pqv/ps): identifier for an individual on Hoopla
3. number of wins, also known as games won, won, wins, W, sporting wins (wd:P1355 as psv/pr/pqn/prv/psn/wdt/wdtn/pq/prn/p/pqv/ps): number of sporting matches, games or events won
4. member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as psv/pr/pqn/prv/psn/wdt/wdtn/pq/prn/p/pqv/ps): sports teams or clubs that the subject represents or represented, member of
5. LNB Élite player ID, also known as French basketball championship ID (new schema), French basketball championship ID identifier (new schema) (wd:P11344 as psv/pr/pqn/prv/psn/wdt/wdtn/pq/prn/p/pqv/ps): new schema for the identifiers of the French league of basketball
6. points for, also known as championship points, competition points, league points, pf, points (wd:P1358 as psv/pr/pqn/prv/psn/wdt/wdtn/pq/prn/p/pqv/ps): number of points in a league table or decathlon. (Use P1351 for goals/points in a match)
7. sports league level, also known as league level, sport league level, level on sport league pyramid, level on league pyramid, level on pyramid (wd:P3983 as psv/pr/pqn/prv/psn/wdt/wdtn/pq/prn/p/pqv/ps): the level of the sport league in the sport league system
8. sport, also known as play, plays, sport played, sports (wd:P641 as psv/pr/pqn/prv/psn/wdt/wdtn/pq/prn/p/pqv/ps): sport that the subject participates or participated in or is associated with
9. winner, also known as nominee, prizewinner, titleholder, top dog, victor (wd:P1346 as psv/pr/pqn/prv/psn/wdt/wdtn/pq/prn/p/pqv/ps): winner of a competition or similar event, not to be used for awa...ssibly qualified with "for work" (P1686)) or for wars or battles, participating team, participant
10. ABA League player ID, also known as ABA League ID (wd:P6850 as psv/pr/pqn/prv/psn/wdt/wdtn/pq/prn/p/pqv/ps): identifier for a player in the ABA League website

[Assistant]
The property "number of wins" (wdt:P1355) could be relevant, but it might refer to individual games, not seasons or championships.

The property "winner" (wdt:P1346) indicates the winner of a competition or event. This might be used to link teams to the NBA championship events they won.

I will try to find NBA championship events and then count how many times each team is linked as a winner.

I will search for NBA championship events.

[Tool]
Top 10 entity alternatives:
1. NBA Finals, also known as NBA World Championship Series [until 1987], NBA title, National Basketball Association ...Championship Series [until 1987], BAA World Championship Series [1947-49], Basketball Association of Americ...ld Championship Series [1947-49] (wd:Q842375): championship series of the National Basketball Association, annu...al Basketball Association World Championship Series through 1987
2. Bill Russell NBA Finals Most Valuable Player Award, also known as Bill Russell NBA Finals MVP Award, NBA Finals Most Valuable Player, NBA Finals Most Valuable Player Award, NBA Finals MVP, NBA Finals MVP Award (wd:Q739499): award
3. 2022 NBA Finals (wd:Q112083544): 2022 edition of the NBA Finals
4. 2019 NBA Finals (wd:Q63940565): 2019 edition of the NBA Finals, between the Golden State Warriors and the Toronto Raptors
5. NBA conference finals, also known as National Basketball Association conference finals (wd:Q2628047): Eastern and Western championship series of the NBA
6. 2023 NBA Finals (wd:Q118126592): 2023 edition of the NBA Finals
7. 2021 NBA Finals (wd:Q107377340): 2021 edition of the NBA Finals between the Phoenix Suns and Milwaukee Bucks
8. 2008 NBA Finals (wd:Q2036161): 2008 basketball championship series
9. 2012 NBA Finals (wd:Q2628013): 2012 basketball championship series
10. 2016 NBA Finals (wd:Q24264147): 2016 edition of the Finals between the Cleveland Cavaliers and Golden State Warriors

[Assistant]
The entity for the NBA Finals (the championship series) is wd:Q842375.

I will now find the winners of the NBA Finals and count how many times each team has won.

I will query for winners of the NBA Finals and count the occurrences for each team.

[Tool]
Got 10 rows and 3 columns:
| team                               | teamLabel                  | wins         |
| ---------------------------------- | -------------------------- | ------------ |
| Boston Celtics (wd:Q131371)        | Boston Celtics (en)        | 17 (xsd:int) |
| Los Angeles Lakers (wd:Q121783)    | Los Angeles Lakers (en)    | 16 (xsd:int) |
| Chicago Bulls (wd:Q128109)         | Chicago Bulls (en)         | 6 (xsd:int)  |
| San Antonio Spurs (wd:Q159729)     | San Antonio Spurs (en)     | 5 (xsd:int)  |
| Golden State Warriors (wd:Q157376) | Golden State Warriors (en) | 4 (xsd:int)  |
| Detroit Pistons (wd:Q169661)       | Detroit Pistons (en)       | 3 (xsd:int)  |
| Philadelphia 76ers (wd:Q138089)    | Philadelphia 76ers (en)    | 3 (xsd:int)  |
| Houston Rockets (wd:Q161345)       | Houston Rockets (en)       | 2 (xsd:int)  |
| Milwaukee Bucks (wd:Q169637)       | Milwaukee Bucks (en)       | 2 (xsd:int)  |
| Miami Heat (wd:Q169138)            | Miami Heat (en)            | 2 (xsd:int)  |

[Tool] Stopped generation process