PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?team WHERE {
  wd:Q119562 wdt:P54 ?team .
}

Got 8 rows and 1 column:
| team                                                           |
| -------------------------------------------------------------- |
| Argentina national under-20 football team (wd:Q1187790)        |
| Club Atlético Independiente (wd:Q214978)                       |
| Argentina national under-23 football team (wd:Q2462207)        |
| Argentina national under-17 football team (wd:Q2902690)        |
| Manchester City F.C. (wd:Q50602)                               |
| FC Barcelona (wd:Q7156)                                        |
| Argentina men's national association football team (wd:Q79800) |
| Atlético de Madrid (wd:Q8701)                                  |

- Argentina national under-20 football team (wd:Q1187790)
- Club Atlético Independiente (wd:Q214978)
- Argentina national under-23 football team (wd:Q2462207)
- Argentina national under-17 football team (wd:Q2902690)
- Manchester City F.C. (wd:Q50602)
- FC Barcelona (wd:Q7156)
- Argentina men's national association football team (wd:Q79800)
- Atlético de Madrid (wd:Q8701)

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

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

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

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

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

[User] what team did aguero play for?

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

[Tool]
Example 1:
Question:
what instruments does john williams use?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q370293 wdt:P1303 ?x .
}

Using entities:
John Williams (wd:Q370293): Australian classical guitarist, classical guitarist, performing artist, music educator, composer

Using properties:
instrument, also known as uses this instrument, teaches instrument, instruments, plays this instrument, plays instrument (wd:P1303 as wdt): musical instrument that a person plays or teaches or used in a music occupation, uses

Example 2:
Question:
what shows did kellie martin star in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P161 wd:Q235754 .
  ?x wdt:P31 / wdt:P279 * wd:Q5398426 .
}

Using entities:
Kellie Martin, also known as Kellie Noelle Martin (wd:Q235754): American actress, television actor, film director, voice actor, film actor, 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:
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)

Example 3:
Question:
who owns skywest?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q773662 wdt:P749 ?x .
}

Using entities:
SkyWest Airlines, also known as United Express (wd:Q773662): American regional airline

Using properties:
parent organization, also known as parent company, parent institution, parent organisation, parent unit, part of (wd:P749 as wdt): parent organization of an organization, opposite of subsidiaries (P355), owned by, part of

[Assistant] Based on the examples, we need to identify the entity for Aguero and the property that indicates the team he played for. Let's start by searching for the entity Aguero.

[Tool]
Top 10 entity alternatives:
1. Agüero, also known as Agüero, Huesca (wd:Q399683): municipality in the province of Huesca, Spain
2. Agüero (wd:Q3296607): metro station in Buenos Aires
3. Agüero (wd:Q24013451): in Huesca province, Spain
4. Agüero (wd:Q61754610): family name
5. Aguero (wd:Q21491256): family name
6. Blanka Aguero, also known as Aguero, B.Shaw, Blanka Shaw (wd:Q21608757): bryologist, botanist
7. Sergio Agüero, also known as Sergio Leonel Agüero del Castillo (wd:Q119562): Argentine association football player, association football player, online streamer, businessperson
8. Taismary Agüero (wd:Q2590488): beach volleyball player, volleyball player
9. Fernando Agüero (wd:Q888684): politician (1920-2011), politician
10. Pablo Agüero (wd:Q3359955): Argentine film director, film director, screenwriter, director

[Assistant] The correct entity for Aguero is likely to be Sergio Agüero (wd:Q119562). Next, let's find out the property that indicates the team he played for. We can search for properties related to 'team' or 'club' for this entity.

[Tool]
Top 10 property alternatives:
1. member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as wdt/p): sports teams or clubs that the subject represents or represented, member of
2. position played on team / speciality, also known as position (on team), speciality, specialism, position, player position (wd:P413 as wdt/p): position or specialism of a player on a team
3. spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as wdt/p): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative
4. 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
5. given name, also known as name, proper name, personal name, middle name, forename (wd:P735 as wdt/p): first name or another given name of this person; values used with the property should not link disambiguations nor family names, name
6. 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
7. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as wdt/p): award or recognition received by a person, organization or creative work
8. participant, also known as suspect, player, party, participants, has participant (wd:P710 as wdt/p): person, group of people or organization (object) that actively t...ct has role" (P3831). Use P1923 for participants that are teams., significant person
9. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
10. occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt/p): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)

No other items found

[Assistant]
The property that indicates the team Aguero played for is 'member of sports team' (wdt:P54). Now, let's construct a simple SPARQL query to find the teams Sergio Agüero played for.

```sparql
SELECT ?team WHERE {
  wd:Q119562 wdt:P54 ?team .
}
```

I will now execute this query to get the results.

[Tool]
Got 8 rows and 1 column:
| team                                                           |
| -------------------------------------------------------------- |
| Argentina national under-20 football team (wd:Q1187790)        |
| Club Atlético Independiente (wd:Q214978)                       |
| Argentina national under-23 football team (wd:Q2462207)        |
| Argentina national under-17 football team (wd:Q2902690)        |
| Manchester City F.C. (wd:Q50602)                               |
| FC Barcelona (wd:Q7156)                                        |
| Argentina men's national association football team (wd:Q79800) |
| Atlético de Madrid (wd:Q8701)                                  |

[Assistant]
The query returned multiple teams that Sergio Agüero has played for throughout his career. To provide a more complete answer, we can include the labels of these teams. However, since the user did not specifically request labels, I will provide the IRIs of the teams as the primary result.

Here is the final SPARQL query:

```sparql
SELECT ?team WHERE {
  wd:Q119562 wdt:P54 ?team .
}
```

And the answer to the question "What team did Aguero play for?" is:

- Argentina national under-20 football team (wd:Q1187790)
- Club Atlético Independiente (wd:Q214978)
- Argentina national under-23 football team (wd:Q2462207)
- Argentina national under-17 football team (wd:Q2902690)
- Manchester City F.C. (wd:Q50602)
- FC Barcelona (wd:Q7156)
- Argentina men's national association football team (wd:Q79800)
- Atlético de Madrid (wd:Q8701)

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

[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 ?language ?languageLabel WHERE {
  wd:Q155 wdt:P37 ?language .
  OPTIONAL {
    ?language rdfs:label ?languageLabel .
    FILTER ( LANG( ?languageLabel ) = 'en' )
  }
}

Got 1 row and 2 columns:
| language              | languageLabel   |
| --------------------- | --------------- |
| Portuguese (wd:Q5146) | Portuguese (en) |

The official language of Brazil is Portuguese.

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

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

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

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

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

[User] what is the official language of brazil now?

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

[Tool]
Example 1:
Question:
what countries around the world speak french?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P37 wd:Q150 ; wdt:P31 / wdt:P279 * wd:Q6256 .
}

Using entities:
French, also known as (fr), fr, fra, French language (wd:Q150): Romance language
country, also known as countries (wd:Q6256): distinct territorial body or political entity

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

Example 2:
Question:
when was the last time the oakland raiders won the super bowl?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?y wdt:P31 / wdt:P279 * wd:Q32096 ; wdt:P1346 wd:Q324523 ; wdt:P585 ?x .
}
ORDER BY DESC ( ?x )
LIMIT 1

Using entities:
Super Bowl, also known as AFL–NFL World Championship Game (wd:Q32096): National Football League championship game
Las Vegas Raiders, also known as Los Angeles Raiders, Oakland Raiders, Raiders (wd:Q324523): National Football League franchise in Las Vegas, Nevada

Using properties:
winner, also known as nominee, prizewinner, titleholder, top dog, victor (wd:P1346 as wdt): 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
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)
point in time, also known as at time, as of, year, when, time of event (wd:P585 as wdt): date something took place, existed or a statement was true; for providing time use the "refine date" property (P4241)

Example 3:
Question:
who was vice president under ronald reagan?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x p:P39 ?p .
  ?p ps:P39 wd:Q11699 ; pq:P580 ?y .
  wd:Q9960 p:P39 ?q .
  ?q ps:P39 wd:Q11696 ; pq:P580 ?z .
  FILTER ( ?y = ?z )
}

Using entities:
President of the United States, also known as US President, U.S. President, United States President, the president of the United States, President of the U.S. (wd:Q11696): head of state and head of government of the United States of America
Vice President of the United States, also known as President of the Senate, President of the United States Senate, United States Vice President, United States VP, USA VP (wd:Q11699): second-highest constitutional office in the United States
Ronald Reagan, also known as Ronald W Reagan, Ronald W. Reagan, R. W. Reagan, President Reagan, President Ronald Reagan (wd:Q9960): president of the United States from 1981 to 1989 and actor, television actor, military officer, character actor, game show host, autobiographer, anti-communist, trade unionist, art collector, statesperson, screenwriter, voice actor, film actor, politician, announcer, lifeguard, diarist, actor

Using properties:
position held, also known as function, held position, holds position, job, office held (wd:P39 as p/ps): subject currently or formerly holds the object position or public office
start time, also known as start date, since, valid, join time, joined (wd:P580 as pq): time an entity begins to exist or a statement starts being valid, point in time

[Assistant] From the examples, we can see that the property `wdt:P37` is used to denote the official language of a country. Let's first find the entity for Brazil.

[Tool]
Top 10 entity alternatives:
1. Brazil, also known as Federative Republic of Brazil, Brasil, br (wd:Q155): country in South America
2. Brazil, also known as br, Brasil, Federative Republic of Brazil (wd:Q155): country in South America
3. Brazil (wd:Q25057): 1985 dystopian film by Terry Gilliam
4. Brazil, also known as Brazil, Indiana, Brazil, IN (wd:Q1998364): city in Clay County, Indiana, United States
5. State of Brazil, also known as Brazil, Colonial Brazil, Portuguese Brazil (wd:Q11876909): state of the Portuguese Empire
6. Brazil, also known as Stars and Guitars (wd:Q4958616): 1944 film by Joseph Santley
7. Brazil, also known as Brazil, IA (wd:Q17511873): human settlement in Appanoose County, Iowa, United States
8. Viceroyalty of Brazil, also known as Brasil, Brazil (wd:Q2920081): Portuguese viceroyalty in Brazil 1763-1815
9. Brazil (wd:Q13581616): 1991 song by Bebi Dol
10. Brazil (wd:Q4095706): 1994 novel by John Updike

[Assistant] The correct entity for Brazil is `wd:Q155`. Now let's check if there is a direct statement about the official language of Brazil using the property `wdt:P37`.

[Tool]
Got 1 row and 1 column:
| language              |
| --------------------- |
| Portuguese (wd:Q5146) |

[Assistant]
The official language of Brazil is Portuguese, represented by the entity `wd:Q5146`.

To provide a complete answer, I will include the label of the language in the final SPARQL query.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?zipCode WHERE {
  wd:Q653636 wdt:P281 ?zipCode .
}

The ZIP codes for Morgantown, WV are 26501, 26504, and 26506.

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

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

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

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

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

[User] what is the zip code for morgantown wv?

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

[Tool]
Example 1:
Question:
what was basketball player michael jordan's major in college?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q41421 p:P69 ?y .
  ?y pq:P812 ?x .
}

Using entities:
Michael Jordan, also known as His Airness, Air Jordan (wd:Q41421): American basketball player and businessman (born 1963), basketball player, baseball player, autobiographer, spokesperson, entrepreneur

Using properties:
educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as p): educational institution attended by subject, affiliation
academic major, also known as academic subject, college major, field of study, major, studied (wd:P812 as pq): major someone studied at college/university

Example 2:
Question:
what did mary harris jones accomplish?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q107082 wdt:P166 ?x .
}

Using entities:
Mary Harris Jones, also known as Mother Jones, Mary Harris (wd:Q107082): Irish-born American labor and community organizer (1837–1930), human rights activist, community organizer, union organizer, trade unionist, teacher, writer

Using properties:
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

Example 3:
Question:
where was nicki minaj born?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q162202 wdt:P19 ?x .
}

Using entities:
Nicki Minaj, also known as Onika Tanya Maraj-Petty, Trinidadian singer, Onika Maraj, Onika Tanya Maraj (wd:Q162202): Trinidadian rapper, singer, and songwriter, songwriter, lyricist, singer, rapper, model, actor

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

[Assistant] Based on the examples, we need to identify the entity for Morgantown, WV and then find the property that corresponds to the ZIP code. Let's first search for the entity representing Morgantown, WV.

[Tool]
Top 10 entity alternatives:
1. Morgantown, also known as Morgantown, West Virginia, Morgantown, WV (wd:Q653636): city in and county seat of Monongalia County, West Virginia, United States
2. Morgantown urban area, also known as Morgantown, WV, Morgantown, WV Urban Area (wd:Q125805682): urban area in West Virginia
3. Morgantown metropolitan area, also known as Morgantown, WV Metropolitan Statistical Area, Morgantown, WV MSA, Morgantown, WV metropolitan area, Morgantown MSA, Morgantown metropolitan statistical area (wd:Q17081833): metropolitan area in West Virginia, United States
4. Morgantown, also known as Morgantown, Kentucky, Morgantown, KY (wd:Q2555567): county seat in Kentucky
5. Morgantown, also known as Morgantown, Indiana (wd:Q644950): human settlement in Morgan County, Indiana, United States of America
6. Morgantown, also known as Morgantown, PA, Morgantown, Pennsylvania (wd:Q3960025): census-designated place in Berks and Lancaster counties in Pennsylvania, United States
7. Morgantown, also known as Morgantown, Adams County, Mississippi, Morgantown, MS (wd:Q13580455): census-designated place in Adams County, Mississippi
8. Morgantown, also known as Morgantown, MS (wd:Q3612521): unincorporated community in Marion County, Mississippi
9. Morgantown, also known as Morgantown, Maryland, Morgantown, MD (wd:Q6911981): unincorporated community in Charles County, Maryland
10. Morgantown, also known as Morgantown, MS (wd:Q20658077): human settlement in Oktibbeha County, Mississippi, United States

[Assistant] The correct entity for Morgantown, WV is `wd:Q653636`. Now, let's find the property that corresponds to the ZIP code. We can search for properties related to "ZIP code" or "postal code" for this entity.

[Tool]
Top 10 property alternatives:
1. postal code, also known as pincode, PIN Code, postal index number, post code, postcode (wd:P281 as wdt/p): identifier assigned by postal authorities for the subject area or building
2. local dialing code, also known as area code, dialling code, local calling code, local dialling code, STD code (wd:P473 as wdt/p): identifier dedicated to subject city by the area communication network
3. FIPS 55-3 (locations in the US), also known as fips code for US locations, Federal Information Processing Standard 55-3, FIPS 55-3 (wd:P774 as wdt/p): identifier for places in the United States per former Federal Information Processing Standard FIPS 55-3
4. UN/LOCODE, also known as LOCCODE, LOCODE, UNECE location code, UNECE LOCODE, United Nations location code (wd:P1937 as wdt/p): geographic location code maintained by UNECE
5. 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
6. area, also known as total area, surface area, surface, size, resolution (wd:P2046 as wdt/p): area occupied by an object
7. FactGrid item ID, also known as FG ID, FactGrid ID (wd:P8168 as wdtn/wdt/p): identifier for an item in FactGrid
8. located in time zone, also known as TZ, time zone, timezone (wd:P421 as wdt/p): time zone for this item
9. GeoNames ID, also known as GeoNames, Geonames Id (wd:P1566 as wdtn/wdt/p): identifier in the GeoNames geographical database
10. 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

No other items found

[Assistant]
The property for the ZIP code is `wd:P281`. Now, let's construct a SPARQL query to find the ZIP code for Morgantown, WV.

```sparql
SELECT ?zipCode WHERE {
  wd:Q653636 wdt:P281 ?zipCode .
}
```

Let's execute this query to get the result.

[Tool]
Got 4 rows and 1 column:
| zipCode     |
| ----------- |
| 26501       |
| 26501–26508 |
| 26504       |
| 26506       |

[Assistant]
The ZIP codes for Morgantown, WV are 26501, 26504, and 26506. The range 26501–26508 is also listed, which includes these ZIP codes.

Here is the final SPARQL query and answer:

```sparql
SELECT ?zipCode WHERE {
  wd:Q653636 wdt:P281 ?zipCode .
}
```

Answer: The ZIP codes for Morgantown, WV are 26501, 26504, and 26506.

[Tool] Stopped generation process


Failed to generate SPARQL query

[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] when was the last time the la kings won a playoff series?

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

[Tool]
Example 1:
Question:
who plays stewie griffin's voice family guy?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q5930 p:P725 ?p .
  ?p ps:P725 ?x ; pq:P453 wd:Q837909 .
}

Using entities:
Family Guy (wd:Q5930): American adult animated sitcom
Stewie Griffin, also known as Stewart Gilligan Griffin, Stewart Gilligan "Stewie" Griffin (wd:Q837909): fictional character from the Family Guy franchise

Using properties:
character role, also known as role, plays, performer of, as, acting role (wd:P453 as pq): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)
voice actor, also known as voice actors, voice dubber, voice actress, voice actresses, voiced by (wd:P725 as p/ps): performer of a spoken role in a creative work such as animation,... (P453) as qualifier] [use "cast member" (P161) for live acting], film crew member, cast member

Example 2:
Question:
what did charles dickens believe in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q5686 wdt:P140 ?x .
}

Using entities:
Charles Dickens, also known as Dickens, C. Dickens, Charles John Huffam Dickens, Boz (wd:Q5686): English novelist and social critic (1812–1870), short story writer, children's writer, social critic, prose writer, playwright, journalist, botanist, novelist, writer, author, editor

Using properties:
religion or worldview, also known as believes, worldview, religious affiliation, religion or world view, religion (wd:P140 as wdt): religion of a person, organization or religious building, or associated with this subject

Example 3:
Question:
what language is cyprus using?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q229 wdt:P37 ?x .
}

Using entities:
Cyprus, also known as CY, Republic of Cyprus, Greek Cypriot State, CYP, Greek Administration of Southern Cyprus (wd:Q229): Mediterranean island nation in Europe

Using properties:
official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as wdt): language designated as official by this item, language used

[Assistant] Based on the examples, we need to identify the relevant entities and properties for our question. We are looking for the Los Angeles Kings (LA Kings) and their playoff series wins. Let's start by searching for the LA Kings entity.

[Tool]
Top 10 entity alternatives:
1. Los Angeles Kings, also known as LA Kings (wd:Q203008): hockey team of the National Hockey League
2. Los Angeles Kings Monument (wd:Q114414620): monument in Los Angeles, California, U.S
3. 2011–12 Los Angeles Kings season, also known as 2011-12 Los Angeles Kings season (wd:Q3468052): NHL team season; 2012 Stanley Cup Champions
4. 2016–17 Los Angeles Kings season (wd:Q24891849): national Hockey League team season
5. 2013–14 Los Angeles Kings season (wd:Q16245445): NHL team season; 2014 Stanley Cup Champions
6. 1996–97 Los Angeles Kings season (wd:Q4592028): national Hockey League team season
7. 2007–08 Los Angeles Kings season (wd:Q4267114): national Hockey League team season
8. 2008–09 Los Angeles Kings season (wd:Q4267113): national Hockey League team season
9. 2012–13 Los Angeles Kings season (wd:Q4628292): national Hockey League team season
10. 1995–96 Los Angeles Kings season (wd:Q4591002): national Hockey League team season

[Assistant] The correct entity for the Los Angeles Kings is `wd:Q203008`. Now, let's find the property that might indicate when they won playoff series. We can search for properties related to "playoff" or "win".

[Tool]
Top 10 property alternatives:
1. member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): sports teams or clubs that the subject represents or represented, member of
2. winner, also known as nominee, prizewinner, titleholder, top dog, victor (wd:P1346 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): 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
3. number of wins, also known as games won, won, wins, W, sporting wins (wd:P1355 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): number of sporting matches, games or events won
4. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): award or recognition received by a person, organization or creative work
5. competition won, also known as won event, won, winner of, victory (wd:P2522 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): competition or sports event won by the subject, participant in
6. number of points/goals/set scored, also known as goals scored, score for, points scored, number of points, number of goals (wd:P1351 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): goals / points scored in a match or an event used as qualifier to the participant. Use P1358 for league points.
7. instrumentation, also known as scoring, scored for, orchestration, instruments employed, orchestrated for (wd:P870 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): combination of musical instruments employed in a composition or accompanying a (folk) dance
8. trophy awarded, also known as cup awarded, diploma awarded, medal awarded (wd:P4622 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): 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
9. occupant, also known as tenant, resident, renter, occupiers, lessee (wd:P466 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): person or organization occupying property, used by
10. 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 wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): discipline an athlete competed in within a sport, field of work

[Assistant]
From the list, the most relevant property seems to be `P2522` (competition won). This property indicates competitions or sports events won by the subject. Let's check if this property is used for the LA Kings and if it includes playoff series wins.

We will start with a simple query to see if the LA Kings have any values for this property.

```sparql
SELECT ?competitionWon WHERE {
  wd:Q203008 wdt:P2522 ?competitionWon .
}
```

Let's execute this query.

[Tool] Got no rows and 1 columns

[Assistant]
It appears that the property `P2522` (competition won) does not provide the information we need for the LA Kings. Let's try another approach by looking at the seasons of the LA Kings and checking if there are any properties related to playoff performance.

We can start by listing the seasons of the LA Kings and then look for properties related to playoff performance.

```sparql
SELECT ?season WHERE {
  wd:Q203008 wdt:P527 ?season .
}
```

This query will list the seasons of the LA Kings. Let's execute this query.

[Tool] Got no rows and 1 columns

[Assistant]
It seems that the property `P527` (has part) does not provide the seasons of the LA Kings. Let's try another approach by searching for properties related to playoff performance directly.

We can search for properties related to "playoff" or "series win" to see if there are any specific properties that might be used for this purpose.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?occupation WHERE {
  wd:Q651203 wdt:P106 ?occupation .
}

George Wilson is a basketball player.

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

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

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

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

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

[User] what does george wilson do for a living?

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

[Tool]
Example 1:
Question:
who plays paul blart?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?p p:P161 ?y .
  ?y ps:P161 ?x ; pq:P453 wd:Q55730078 .
}

Using entities:
Paul Blart (wd:Q55730078): title character from Paul Blart, police officer

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as p/ps): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
character role, also known as role, plays, performer of, as, acting role (wd:P453 as pq): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)

Example 2:
Question:
who all has kim kardashian dated?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q186304 wdt:P451 | wdt:P26 ?x .
}

Using entities:
Kim Kardashian, also known as Kim Kardashian West, Kim K, Kim K., Kimberly Noel Kardashian-West, Kim Kardashian-West (wd:Q186304): American media personality, businesswoman, model and actress (born 1980), erotic photography model, television producer, fashion designer, entrepreneur, voice actor, celebrity, socialite, blogger, actor, model

Using properties:
spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as wdt): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative
unmarried partner, also known as romantic partner, partner of, partners, posslq, relationship (wd:P451 as wdt): someone with whom the person is in a relationship without being married. Use "spouse" (P26) for married couples, significant person

Example 3:
Question:
where does sally pearson live?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q6026 wdt:P551 ?x .
}

Using entities:
Sally Pearson (wd:Q6026): Australian short-distance runner and hurdler, athletics competitor

Using properties:
residence, also known as living in, place of residence, resided at, resided in, resident in (wd:P551 as wdt): the place where the person is or has been, resident, location

[Assistant] Based on the examples, we need to identify the entity George Wilson and then look for his occupation or job. Let's first search for the entity George Wilson.

[Tool]
Top 10 entity alternatives:
1. Ajita Wilson, also known as George Wilson (wd:Q164526): American actress (1950–1987), pornographic actor, actor
2. George Wilson (wd:Q651203): basketball player from the United States born in 1942, basketball player
3. George A. Wilson, also known as George Allison Wilson, George Wilson (wd:Q382688): American politician (1884-1953), politician, lawyer, judge
4. George Washington Wilson, also known as George Wilson, G. W. Wilson, George W. Wilson (wd:Q2179710): Scottish painter and photographer (1823-1893), businessperson, photographer, painter
5. George Wilson (wd:Q5546405): English footballer (1892-1961), association football player
6. George Wilson (wd:Q5546401): American football coach (1914-1978), American football player, American football coach, basketball player
7. George Wilson, also known as George Washington Wilson, Teddy Wilson (wd:Q5546410): baseball outfielder from the United States (1925-1974), baseball player
8. George Wilson, also known as George Patterson Wilson (wd:Q18392304): Australian footballer (1920-2014), Australian rules football player
9. George Wilson, also known as George Charles Lee Wilson (wd:Q18129280): New Zealand cricketer (1887-1917), cricketer
10. George Wilson, also known as Wilson, George, 1818-1859 (wd:Q14949042): Scottish chemist, Regius Professor of Technology at the University of Edinburgh (1818-1859), chemist

[Assistant]
There are multiple entities named George Wilson. We need more context to determine which one is relevant. However, since the question asks about his occupation, let's try to find the occupation for the most prominent George Wilson, which seems to be the basketball player (wd:Q651203).

We will check if this George Wilson has an occupation listed and proceed from there.

Let's execute a SPARQL query to find the occupation of George Wilson (wd:Q651203).

[Tool]
Got 1 row and 1 column:
| occupation                      |
| ------------------------------- |
| basketball player (wd:Q3665646) |

[Assistant]
The SPARQL query returned that George Wilson (wd:Q651203) is a basketball player.

Since this matches the context of the most prominent George Wilson in the search results, we can conclude that George Wilson is a basketball player.

Here is the final SPARQL query and answer:

```sparql
SELECT ?occupation WHERE { wd:Q651203 wdt:P106 ?occupation . }
```

Answer: George Wilson is a basketball player.

Let's finalize this with the `answer` function.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?county ?state WHERE {
  VALUES ?county {
    wd:Q488701 wd:Q511150
  }
  .
  ?county wdt:P131 ?state .
}

The Chesapeake Bay Bridge is located in Anne Arundel County and Queen Anne's County, both of which are in the state of Maryland.

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

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

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

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

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

[User] where is chesapeake bay bridge?

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

[Tool]
Example 1:
Question:
what country is located in the balkan peninsula?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q23522 wdt:P17 ?x .
}

Using entities:
Balkans, also known as The Balkans, South Balkan area, Peninsula of Haemus, Balkanoid, Haemus Peninsula (wd:Q23522): geopolitical and cultural region of Southeast Europe

Using properties:
country, also known as sovereign state, state, land, host country (wd:P17 as wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity

Example 2:
Question:
who did stephenie meyer play in twilight?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q160071 p:P161 ?p .
  ?p ps:P161 wd:Q160219 ; pq:P453 ?x .
}

Using entities:
Twilight (wd:Q160071): 2008 American film directed by Catherine Hardwicke
Stephenie Meyer, also known as Stephenie Morgan Meyer (wd:Q160219): science fiction writer, film screenwriter, children's writer, American author, businessperson, film producer, screenwriter, entrepreneur, novelist, writer, actor

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as p/ps): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
character role, also known as role, plays, performer of, as, acting role (wd:P453 as pq): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)

Example 3:
Question:
what to do if you have one day in bangkok?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P31 / wdt:P279 * wd:Q570116 ; wdt:P131 wd:Q1861 .
}

Using entities:
Bangkok, also known as Bangkok, Thailand, Sia-Yut'hia, Krungthepmahanakhon Amonrattanak...it Sakkathattiyawitsanukamprasit, Krung Thep Maha Nakhon, Krung Thep (wd:Q1861): capital of Thailand
tourist attraction, also known as attraction for tourists, POI for tourists, tourism attraction, touristic attraction, tourist place (wd:Q570116): place of interest where tourists visit

Using properties:
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): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

[Assistant] Based on the examples, we need to identify the entity for Chesapeake Bay Bridge and then find its location. Let's first search for the entity.

[Tool]
Top 10 entity alternatives:
1. Chesapeake Bay Bridge, also known as Bay Bridge, Governor William Preston Lane Jr. Memorial Bridge, Gov. William Preston Lane Jr. Memorial Bridge, William Preston Lane Junior Memorial Bridge (wd:Q1319988): major dual-span bridge in the U.S. state of Maryland, spanning the Chesapeake Bay
2. Chesapeake Bay Bridge-Tunnel, also known as Lucius J. Kellam, Jr. Bridge-Tunnel, CBBT (wd:Q1070563): bridge-tunnel beginning in Chesapeake Bay, Virginia
3. Chesapeake Bay Bridge–Tunnel (wd:Q60094303): scholarly article
4. Chesapeake Bay Bridge and Tunnel (wd:Q114520613): episode of Modern Marvels (S8 E5)
5. Chesapeake Bay Bridge and Tunnel District (wd:Q5092828): political subdivision of Virginia
6. Chesapeake Bay (wd:Q216868): estuary in the U.S. states of Maryland, Delaware, District of Columbia, and Virginia
7. San Francisco–Oakland Bay Bridge, also known as Emperor Norton Bridge, Bay Bridge, San Francisco-Oakland Bay Bridge (wd:Q771404): suspension bridge connecting San Francisco and Oakland, California, USA
8. Yokohama Bay Bridge, also known as Bay Bridge (wd:Q1138655): cable-stayed bridge
9. Bridge Bay (wd:Q49374128): bay in Teton County, Wyoming, United States of America
10. Bay Bridge (wd:Q112811780): British racehorse

[Assistant] The correct entity for Chesapeake Bay Bridge is `wd:Q1319988`. Now, let's find out where it is located. We will look for the property that indicates the location of the bridge.

[Tool]
Top 10 property alternatives:
1. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as wdt/p): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
2. 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
3. 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
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. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
6. length, also known as size, long, LOA, distance, dimension (wd:P2043 as wdt/p): measured dimension of an object
7. height, also known as heighth, size, depth over terrain (wd:P2048 as wdt/p): vertical length of an entity, length

No other items found

[Assistant] The most relevant property for the location of the Chesapeake Bay Bridge is `wdt:P131` (located in the administrative territorial entity). Let's use this property to find the location of the bridge.

[Tool]
Got 2 rows and 1 column:
| location                         |
| -------------------------------- |
| Anne Arundel County (wd:Q488701) |
| Queen Anne's County (wd:Q511150) |

[Assistant]
The Chesapeake Bay Bridge is located in two counties: Anne Arundel County and Queen Anne's County. To provide a more complete answer, let's also find the state these counties are in.

We will use the `wdt:P131` property again to find the state that these counties are located in.

[Tool]
Got 2 rows and 2 columns:
| county                           | state               |
| -------------------------------- | ------------------- |
| Anne Arundel County (wd:Q488701) | Maryland (wd:Q1391) |
| Queen Anne's County (wd:Q511150) | Maryland (wd:Q1391) |

[Assistant]
Both Anne Arundel County and Queen Anne's County are located in the state of Maryland. Therefore, the Chesapeake Bay Bridge is located in Maryland.

Here is the final SPARQL query and answer:

```sparql
SELECT ?county ?state WHERE {
  VALUES ?county { wd:Q488701 wd:Q511150 } .
  ?county wdt:P131 ?state .
}
```

Answer: The Chesapeake Bay Bridge is located in Anne Arundel County and Queen Anne's County, both of which are in the state of Maryland.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?state WHERE {
  wd:Q734774 wdt:P131 ?city .
  ?city wdt:P131 ?state .
}

Saint Louis University is located in the state of Missouri.

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

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

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

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

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

[User] what state is saint louis university in?

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

[Tool]
Example 1:
Question:
where is azerbaijan?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q227 wdt:P30 ?x .
}

Using entities:
Azerbaijan, also known as az, AZE, Azərbaycan, Azərbaycan Respublikası, Republic of Azerbaijan (wd:Q227): country in the Caucasus in Eastern Europe and Western Asia

Using properties:
continent (wd:P30 as wdt): continent of which the subject is a part, located in/on physical feature

Example 2:
Question:
where did the massive allied invasion of northern france take place in june 1944?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q16471 wdt:P276 ?x .
}

Using entities:
Invasion of Normandy (wd:Q16471): 1944 invasion and establishment of Western Allied forces in Normandy during WWII

Using properties:
location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as wdt): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object

Example 3:
Question:
what highschool did bill gates graduated from?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q5284 wdt:P69 ?x .
  ?x wdt:P31 / wdt:P279 * wd:Q9826 .
}

Using entities:
Bill Gates, also known as William Henry "Bill" Gates III, William Henry Gates, William Henry Gates III, William H. Gates, William H. Gates III (wd:Q5284): American businessman, investor, and philanthropist (born 1955), philanthropist, entrepreneur, programmer
high school, also known as H.S., upper middle school, senior high school, HS (wd:Q9826): institution which provides all or part of secondary education

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

[Assistant] Based on the examples, we need to identify the entity for Saint Louis University and then find the state it is located in. Let's start by searching for the entity "Saint Louis University".

[Tool]
Top 10 entity alternatives:
1. Saint Louis University, also known as SLU, St. Louis University (wd:Q734774): private research university with campuses in St. Louis, Missouri, and Madrid, Spain
2. Saint Louis University, also known as SLU, St. Louis University (wd:Q7401676): university in Baguio, Philippines
3. Washington University in St. Louis, also known as WUSTL, WashU, Wash. U., Washington University in Saint Louis, Washington University (Saint Louis, Mo.) (wd:Q777403): private research university in St. Louis, Missouri, United States
4. Saint Louis Billikens, also known as Saint Louis University athletics (wd:Q7401655): athletic program of Saint Louis University
5. Saint Louis University Hospital, also known as Firmin Desloge Hospital, SLU Hospital (wd:Q7401677): hospital in Missouri, United States
6. Saint Louis University Bookstore (wd:Q99475974): bookshop in Saint Louis, MO, United States of America
7. Saint Louis University Madrid Campus (wd:Q4116998)
8. Maryville University, also known as Maryville College of the Sacred Heart, Maryville University of St. Louis, Maryville University of Saint Louis (wd:Q6781811): private university located in Missouri
9. University of Saint Louis Tuguegarao (wd:Q7896224): private university in the Philippines
10. Saint Louis University Law Journal (wd:Q15767443): journal

[Assistant] The correct entity for Saint Louis University is `wd:Q734774`. Now, we need to find out the state where this university is located. We can use the property `located in the administrative territorial entity` (P131) to find the state. Let's check if this property is used for Saint Louis University.

[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. street address, also known as postal address, physical address, mailing address, located at street address, full address (wd:P6375 as wdt/p): full street address where subject is located. Include building n...t country; use also P669 if the street has its own separate item
3. 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
4. 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
5. MusicBrainz place ID, also known as MBP, place MBID, place ID, MusicBrainz location ID, MB place id (wd:P1004 as wdtn/wdt/p): Identifier for a place in the MusicBrainz open music encyclopedia
6. category of associated people, also known as key people category, category of people associated with this place, category for people associated with this place (wd:P1792 as wdt/p): Wikimedia category for people associated with this place or organization, related category
7. member of, also known as band member of, membership, member of musical group, in musical group, be member of (wd:P463 as wdt/p): organization, club or musical group to which the subject belongs...ical position, such as a member of parliament (use P39 for that), part of
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

No other items found

[Assistant]
The property `located in the administrative territorial entity` (P131) is indeed used for Saint Louis University. Now, let's construct a SPARQL query to find the state where Saint Louis University is located.

We will use the following pattern:
```sparql
SELECT ?state WHERE {
  wd:Q734774 wdt:P131 ?state .
}
```

Let's execute this query to get the state.

[Tool]
Got 1 row and 1 column:
| state                 |
| --------------------- |
| St. Louis (wd:Q38022) |

[Assistant]
The result shows that Saint Louis University is located in St. Louis. However, we need to find the state, not the city. To get the state, we need to look at the higher-level administrative division of St. Louis. We can use the same property `located in the administrative territorial entity` (P131) again to find the state.

Let's modify the query to find the state:

```sparql
SELECT ?state WHERE {
  wd:Q734774 wdt:P131 ?city .
  ?city wdt:P131 ?state .
}
```

Let's execute this query to get the state.

[Tool]
Got 1 row and 1 column:
| state               |
| ------------------- |
| Missouri (wd:Q1581) |

[Assistant]
The result shows that Saint Louis University is located in the state of Missouri.

Here is the final SPARQL query and the answer:

```sparql
SELECT ?state WHERE {
  wd:Q734774 wdt:P131 ?city .
  ?city wdt:P131 ?state .
}
```

Answer: Saint Louis University is located in the state of Missouri.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?team WHERE {
  wd:Q3887743 wdt:P54 ?team .
}

Got 3 rows and 1 column:
| team                             |
| -------------------------------- |
| Philadelphia Eagles (wd:Q219714) |
| Seattle Seahawks (wd:Q221878)    |
| Las Vegas Raiders (wd:Q324523)   |

Owen Schmitt has played for the Philadelphia Eagles, the Seattle Seahawks, and the Las Vegas Raiders.

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

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

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

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

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

[User] who does owen schmitt play for?

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

[Tool]
Example 1:
Question:
what clubs has peter crouch played for?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q180939 wdt:P54 ?x .
}

Using entities:
Peter Crouch, also known as Peter James Crouch (wd:Q180939): English association football player (born 1981), association football player, podcaster

Using properties:
member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as wdt): sports teams or clubs that the subject represents or represented, member of

Example 2:
Question:
when did braves win the world series?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?y wdt:P3450 wd:Q265538 ; wdt:P1346 wd:Q461595 ; wdt:P585 ?x .
}

Using entities:
World Series, also known as Fall Classic (wd:Q265538): Championship of Major League Baseball
Atlanta Braves, also known as Beaneaters, Rustlers, Milwaukee Braves, Doves, Braves (wd:Q461595): Major League Baseball team in Cumberland, Georgia

Using properties:
winner, also known as nominee, prizewinner, titleholder, top dog, victor (wd:P1346 as wdt): 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
sports season of league or competition, also known as sport season, seasons of, edition of annual athletics meeting, season of sports tournament, season of sports league (wd:P3450 as wdt): property that shows the competition of which the item is a season. Use P5138 for "season of club or team"., part of
point in time, also known as at time, as of, year, when, time of event (wd:P585 as wdt): date something took place, existed or a statement was true; for providing time use the "refine date" property (P4241)

Example 3:
Question:
who will play clary in city of bones?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q59346 p:P161 ?p .
  ?p ps:P161 ?x ; pq:P453 wd:Q65510149 .
}

Using entities:
The Mortal Instruments: City of Bones, also known as Mortal Instruments: City of Bones (wd:Q59346): 2013 film directed by Harald Zwart
Clary Fray, also known as Clarissa Adele Fairchild, Clary Morgenstern, Clary Fairchild, Clarissa Morgenstern, Clarissa Fairchild (wd:Q65510149): fictional character of the Shadowhunters series, demon hunter

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as p/ps): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
character role, also known as role, plays, performer of, as, acting role (wd:P453 as pq): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)

[Assistant] From the examples, we can see that to find out who Owen Schmitt plays for, we need to identify the entity representing Owen Schmitt and then look for the property that indicates the team he plays for. Let's start by searching for Owen Schmitt in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Owen Schmitt (wd:Q3887743): American football fullback, American football player
2. Richard Owen, also known as R. Owen, Owen, Richard, Prof OWEN F.R.S., Sir Richard Owen, Sir R. Owen (wd:Q151556): English biologist and paleontologist (1804–1892), paleoanthropologist, university teacher, paleontologist, zoologist, anatomist, biologist, curator, writer
3. Wilfred Owen, also known as Owen, Wilfred Edward Salter Owen (wd:Q212719): English poet and soldier (1893-1918), writer, poet
4. Owen (wd:Q81006): municipality in Germany
5. Owen, also known as City of Owen, Owen, WI (wd:Q1569456): city in Clark County, Wisconsin
6. Schmitt (wd:Q654052): municipality of Germany
7. Owain Owain, also known as Owen Owen (wd:Q3398027): Welsh novelist, short story writer and poet (1929–1993), nuclear physicist, educator, writer, poet
8. Schmitt (wd:Q2246512): family name
9. Owen, also known as Owen surname, Owen family name (wd:Q1158545): family name
10. Mount Owen, also known as Mount Owen (Antarctica), Owen (wd:Q6922630): mountain in Antarctica

[Assistant] The first result, Owen Schmitt (wd:Q3887743), seems to be the correct entity for the American football player. Next, let's confirm that this entity indeed represents Owen Schmitt and check if it has any properties related to the team he plays for. We can use the `list` function to explore the properties of this entity.

[Tool]
Got 155 rows and 3 columns, showing the first 10 rows below:
| subject                    | property                         | object                                                                         |
| -------------------------- | -------------------------------- | ------------------------------------------------------------------------------ |
| Owen Schmitt (wd:Q3887743) | instance of (wdt:P31)            | human (wd:Q5)                                                                  |
| Owen Schmitt (wd:Q3887743) | occupation (wdt:P106)            | American football player (wd:Q19204627)                                        |
| Owen Schmitt (wd:Q3887743) | sex or gender (wdt:P21)          | male (wd:Q6581097)                                                             |
| Owen Schmitt (wd:Q3887743) | given name (wdt:P735)            | Owen (wd:Q3887735)                                                             |
| Owen Schmitt (wd:Q3887743) | date of birth (wdt:P569)         | 1985-02-13T00:00:00Z (xsd:dateTime)                                            |
| Owen Schmitt (wd:Q3887743) | Commons category (wdt:P373)      | Owen Schmitt                                                                   |
| Owen Schmitt (wd:Q3887743) | image (wdt:P18)                  | <http://commons.wikimedia.org/wiki/Special:FilePath/Owen%20Schmitt%202012.JPG> |
| Owen Schmitt (wd:Q3887743) | country of citizenship (wdt:P27) | United States (wd:Q30)                                                         |
| Owen Schmitt (wd:Q3887743) | family name (wdt:P734)           | Schmitt (wd:Q2246512)                                                          |
| Owen Schmitt (wd:Q3887743) | place of birth (wdt:P19)         | Gilman (wd:Q2222039)                                                           |
| ...                        | ...                              | ...                                                                            |

[Assistant] From the list of properties, we can see that Owen Schmitt is indeed an American football player. However, the property indicating the team he plays for is not immediately visible. The property `member of sports team` (P54) is commonly used to indicate the team a player is associated with. Let's search for this property specifically for Owen Schmitt.

[Tool]
Top 10 property alternatives:
1. member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as wdt/p): sports teams or clubs that the subject represents or represented, member of
2. position played on team / speciality, also known as position (on team), speciality, specialism, position, player position (wd:P413 as wdt/p): position or specialism of a player on a team
3. educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as wdt/p): educational institution attended by subject, affiliation
4. given name, also known as name, proper name, personal name, middle name, forename (wd:P735 as wdt/p): first name or another given name of this person; values used with the property should not link disambiguations nor family names, name
5. 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
6. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
7. occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt/p): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
8. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt/p): most specific known birth location of a person, animal or fictional character, location
9. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as wdt/p): date on which the subject was born, inception
10. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdt/p): the object is a country that recognizes the subject as its citizen, country

No other items found

[Assistant]
The property `member of sports team` (P54) is indeed listed as one of the top results. Now, let's construct a SPARQL query to find out which team Owen Schmitt plays for using this property.

Here is the SPARQL query:

```sparql
SELECT ?team WHERE {
  wd:Q3887743 wdt:P54 ?team .
}
```

Let's execute this query to get the result.

[Tool]
Got 3 rows and 1 column:
| team                             |
| -------------------------------- |
| Philadelphia Eagles (wd:Q219714) |
| Seattle Seahawks (wd:Q221878)    |
| Las Vegas Raiders (wd:Q324523)   |

[Assistant]
The SPARQL query returned three teams that Owen Schmitt has played for: the Philadelphia Eagles, the Seattle Seahawks, and the Las Vegas Raiders.

To provide a clear answer, we can state that Owen Schmitt has played for these teams. Here is the final SPARQL query and the answer:

```sparql
SELECT ?team WHERE {
  wd:Q3887743 wdt:P54 ?team .
}
```

Answer: Owen Schmitt has played for the Philadelphia Eagles, the Seattle Seahawks, and the Las Vegas Raiders.

Now, let's finalize the answer.

[Tool] Stopped generation process