PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?place ?placeLabel WHERE {
  ?place wdt:P2936 wd:Q34271 .
  ?place wdt:P31 / wdt:P279 * ?type .
  VALUES ?type {
    wd:Q6256 wd:Q56061 wd:Q82794
  }
  OPTIONAL {
    ?place rdfs:label ?placeLabel FILTER ( LANG( ?placeLabel ) = "en" )
  }
}

Got 14 rows and 2 columns, showing the first 5 and last 5 rows below:
| place                                | placeLabel                      |
| ------------------------------------ | ------------------------------- |
| Arunachal Pradesh (wd:Q1162)         | Arunachal Pradesh (en)          |
| Assam (wd:Q1164)                     | Assam (en)                      |
| Himachal Pradesh (wd:Q1177)          | Himachal Pradesh (en)           |
| Delhi (wd:Q1353)                     | Delhi (en)                      |
| People's Republic of China (wd:Q148) | People's Republic of China (en) |
| ...                                  | ...                             |
| Mustang (wd:Q28307)                  | Mustang (en)                    |
| Xinjiang (wd:Q34800)                 | Xinjiang (en)                   |
| Kingdom of Sikkim (wd:Q3960459)      | Kingdom of Sikkim (en)          |
| India (wd:Q668)                      | India (en)                      |
| Nepal (wd:Q837)                      | Nepal (en)                      |

Tibetan is spoken in several places including countries and administrative regions such as People's Republic of China, India, Nepal, Arunachal Pradesh, Assam, Himachal Pradesh, Delhi, Xinjiang, Mustang, and the Kingdom of Sikkim.

[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

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

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

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

[User] where do they speak tibetan?

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

[Tool]
Example 1:
Question:
what do tibetan people speak?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q187985 wdt:P2936 ?x .
}

Using entities:
Tibetan people, also known as Bhod-pa, Sifan, Sifen, Tibetans, Xifan (wd:Q187985): East Asian ethnic group native to Tibet

Using properties:
language used, also known as languages used, medium of instruction, used language, uses language, working language (wd:P2936 as wdt): language widely used (spoken or written) in this place or at this event or organisation

Example 2:
Question:
where do people speak burmese?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P2936 wd:Q9228 .
}

Using entities:
Burmese, also known as Myanmar language, Burmese language (wd:Q9228): Sino-Tibetan language of Myanmar

Using properties:
language used, also known as languages used, medium of instruction, used language, uses language, working language (wd:P2936 as wdt): language widely used (spoken or written) in this place or at this event or organisation

Example 3:
Question:
what do they speak in austria?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q40 wdt:P37 ?x .
}

Using entities:
Austria, also known as Republik Österreich, Republic of Austria, Österreich (wd:Q40): country in Central 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]
From the similar examples, it is clear that the property "language used" (wdt:P2936) is used to find places where a language is spoken. The entity for the Tibetan language is likely wd:Q9149 (Tibetan language).

I will now search for the entity "Tibetan language" to confirm its identifier.

[Tool]
Top 10 entity alternatives:
1. Tibetan, also known as bo, bod, Lhasa Tibetan, Standard Tibetan, Tibetan language (wd:Q34271): Tibeto-Burman language
2. Tibetan (language) (wd:L612746-S1)
3. Tibetan language (wd:L1020969-S1)
4. Tibetic, also known as Tibetan languages, Tibetic languages (wd:Q1641150): group of Bodic languages spoken by Tibetans in the Eastern Tibetan Plateau and in northern areas of the Indian subcontinent
5. Central Tibetan, also known as Dbus, Ü-Tsang, Central Tibetan language, Ü (wd:Q5061915): language and dialects ensemble from Central Tibet
6. Central Tibetan, also known as Ü-Tsang, Ü, Dbus, Central Tibetan language (wd:Q5061915): language and dialects ensemble from Central Tibet
7. Khams Tibetan, also known as Khams Tibetan language, khg (wd:Q56601): language
8. Amdo Tibetan, also known as adx, Amdo Tibetan language (wd:Q56509): Tibetic language of Amdo
9. Tibetan Sign Language (wd:Q15936110): deaf sign language of Tibet
10. Humla, also known as Humla Bhotiya, Humla language, Humla Tibetan, Humla Tibetan language, Humli Tamang (wd:Q17588918): Sino-Tibetan language

[Assistant]
The entity wd:Q34271 corresponds to the Tibetan language (Tibetan, also known as bo, bod, Lhasa Tibetan, Standard Tibetan). This seems to be the appropriate entity for the Tibetan language.

Next, I will construct a query to find places where the Tibetan language is spoken using the property "language used" (wdt:P2936).

[Tool]
Got 21 rows and 2 columns, showing the first 5 and last 5 rows below:
| place                            | placeLabel              |
| -------------------------------- | ----------------------- |
| CNR Tibetan Radio (wd:Q10874976) | CNR Tibetan Radio (en)  |
| Arunachal Pradesh (wd:Q1162)     | Arunachal Pradesh (en)  |
| Assam (wd:Q1164)                 | Assam (en)              |
| Himachal Pradesh (wd:Q1177)      | Himachal Pradesh (en)   |
| All India Radio (wd:Q1321122)    | All India Radio (en)    |
| ...                              | ...                     |
| Kingdom of Sikkim (wd:Q3960459)  | Kingdom of Sikkim (en)  |
| Radio Free Asia (wd:Q40322)      | Radio Free Asia (en)    |
| India (wd:Q668)                  | India (en)              |
| Qinghai Television (wd:Q7267827) | Qinghai Television (en) |
| Nepal (wd:Q837)                  | Nepal (en)              |

[Assistant]
The query results include some entities that are not places (e.g., radio stations and television). I will refine the query to only include places that are countries, administrative regions, or similar geographic entities.

I will filter the results to include only entities that are instances of administrative territorial entities or countries.

[Tool]
Got 14 rows and 2 columns, showing the first 5 and last 5 rows below:
| place                                | placeLabel                      |
| ------------------------------------ | ------------------------------- |
| Arunachal Pradesh (wd:Q1162)         | Arunachal Pradesh (en)          |
| Assam (wd:Q1164)                     | Assam (en)                      |
| Himachal Pradesh (wd:Q1177)          | Himachal Pradesh (en)           |
| Delhi (wd:Q1353)                     | Delhi (en)                      |
| People's Republic of China (wd:Q148) | People's Republic of China (en) |
| ...                                  | ...                             |
| Mustang (wd:Q28307)                  | Mustang (en)                    |
| Xinjiang (wd:Q34800)                 | Xinjiang (en)                   |
| Kingdom of Sikkim (wd:Q3960459)      | Kingdom of Sikkim (en)          |
| India (wd:Q668)                      | India (en)                      |
| Nepal (wd:Q837)                      | Nepal (en)                      |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves places where Tibetan is spoken, including countries and administrative regions, which matches the user's question. The query uses appropriate properties and filters to get relevant places and their English labels. The answer is comprehensive and includes well-known regions and countries where Tibetan is spoken. No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?disease ?diseaseLabel WHERE {
  wd:Q1345645 wdt:P1050 ?disease .
  OPTIONAL {
    ?disease rdfs:label ?diseaseLabel FILTER ( LANG( ?diseaseLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| disease                       | diseaseLabel            |
| ----------------------------- | ----------------------- |
| multiple sclerosis (wd:Q8277) | multiple sclerosis (en) |

Montel Williams has the disease multiple sclerosis.

[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

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 kind of disease does montel williams have?

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

[Tool]
Example 1:
Question:
what disease has jack osbourne got?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q724791 wdt:P1050 ?x .
}

Using entities:
Jack Osbourne, also known as Jack Joseph Osbourne (wd:Q724791): television presenter, television actor, British actor, film actor, actor

Using properties:
medical condition, also known as disability, suffers from, suffer from, sickness, paralympic disability (wd:P1050 as wdt): any state relevant to the health of an organism, including diseases and positive conditions

Example 2:
Question:
what disease michael jackson?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q2831 wdt:P1050 ?x .
}

Using entities:
Michael Jackson, also known as M.J., MJ, M. J., The King of Pop, King of Pop (wd:Q2831): American singer, songwriter, and dancer (1958–2009), singer-songwriter, recording artist, record producer, businessperson, philanthropist, music arranger, autobiographer, film director, choreographer, art collector, entrepreneur, screenwriter, voice actor, songwriter, film actor, composer, dancer, singer, actor, model, poet

Using properties:
medical condition, also known as disability, suffers from, suffer from, sickness, paralympic disability (wd:P1050 as wdt): any state relevant to the health of an organism, including diseases and positive conditions

Example 3:
Question:
what blood disease does robin roberts have?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q2041541 wdt:P1050 ?x .
  ?x wdt:P1995 wd:Q103824 ; wdt:P31 wd:Q12136 .
}

Using entities:
hematology, also known as haematology (wd:Q103824): study of blood, the blood-forming organs, and blood diseases
disease, also known as ailments, sickness, other disease, medical disorder, MedicalCondition (wd:Q12136): abnormal condition negatively affecting organisms
Robin Roberts, also known as Robin René Roberts (wd:Q2041541): American television broadcaster, sports commentator, basketball player, news presenter, journalist

Using properties:
medical condition, also known as disability, suffers from, suffer from, sickness, paralympic disability (wd:P1050 as wdt): any state relevant to the health of an organism, including diseases and positive conditions
health specialty, also known as medical field, medical speciality, medical specialty (wd:P1995 as wdt): main specialty that diagnoses, prevent human illness, injury and other physical and mental impairments
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

[Assistant]
From the similar examples, it is clear that the property "medical condition" (wdt:P1050) is used to indicate the disease or medical condition a person has.

Next, I will search for the entity Montel Williams in Wikidata to get his identifier.

[Tool]
Top 10 entity alternatives:
1. Montel Williams, also known as Montel Brian Anthony Williams (wd:Q1345645): American television host and actor, television presenter, television producer, radio personality, television actor, military officer, journalist, politician, actor
2. The Montel Williams Show (wd:Q2412902): television series
3. Montel Williams MS Foundation (wd:Q30289093): nonprofit organization in New York, United States
4. Williams Racing, also known as Williams, Williams Grand Prix Engineering Limited, Williams F1 (wd:Q171337): European Formula One motor racing team and constructor
5. Williams, also known as Williams, AZ, Williams, Arizona (wd:Q79864): city in Coconino County, Arizona, United States
6. Williams, also known as Williams, CA, Williams, California (wd:Q2685585): city in Colusa County, California, United States
7. Williams, also known as Williams, IA, Williams, Iowa (wd:Q1012283): city in Hamilton County, Iowa, United States
8. Williams, also known as Williams, MN, Williams, Minnesota (wd:Q963315): city in Lake of the Woods County, Minnesota, United States
9. Williams College, also known as Williams (wd:Q49166): liberal arts college in Massachusetts
10. Williams, also known as Williams, SC, Williams, South Carolina (wd:Q2562748): town in Collation County, South Carolina, United States

[Assistant] The entity Montel Williams is wd:Q1345645 in Wikidata. Now I will query the medical condition (property wdt:P1050) of Montel Williams.

[Tool]
Got 1 row and 2 columns:
| disease                       | diseaseLabel            |
| ----------------------------- | ----------------------- |
| multiple sclerosis (wd:Q8277) | multiple sclerosis (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the disease associated with Montel Williams using the property 'medical condition' (wdt:P1050). The query returns the disease identifier and its English label, which matches the user's question. The answer 'Montel Williams has the disease multiple sclerosis' is accurate and complete based on the query result. No further refinement is needed.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX p: <http://www.wikidata.org/prop/>
SELECT DISTINCT ?draftDate WHERE {
  wd:Q169452 p:P647 ?stmt .
  ?stmt pq:P793 wd:Q972098 .
  wd:Q972098 wdt:P585 ?draftDate .
}
LIMIT 1

Shaquille O'Neal was drafted in the 1992 NBA Draft, which took place on June 24, 1992. This date represents when he officially entered the NBA through the draft.

[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

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 did shaq come into the nba?

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

[Tool]
Example 1:
Question:
what team did shaq play for first?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q169452 p:P54 ?p .
  ?p ps:P54 ?x ; pq:P580 ?y .
}
ORDER BY ?y
LIMIT 1

Using entities:
Shaquille O'Neal, also known as Shaquille O’Neal, Shaquille Rashaun O'Neal, Shaq O'Neal, Shaquille Rashaun O’Neal, Shaq (wd:Q169452): American basketball player, real estate entrepreneur, television producer, sports commentator, basketball player, businessperson, film producer, screenwriter, film actor, Thai boxer, podcaster, singer, rapper, actor

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

Example 2:
Question:
what year lebron james came to the nba?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q36159 p:P54 ?p .
  ?p ps:P54 ?y .
  ?y wdt:P118 wd:Q155223 .
  ?p pq:P580 ?x .
}
ORDER BY ?x
LIMIT 1

Using entities:
National Basketball Association, also known as Basketball Association of America, BAA, NBA, National Basketball Assn., Nat'l Basketball Assn. (wd:Q155223): North American professional men's basketball league
LeBron James, also known as LeBron Raymone James Sr., LeBron, The Chosen One, King James, LeBron Raymone James (wd:Q36159): American basketball player (born 1984), basketball player, television actor, screenwriter

Using properties:
league or competition, also known as tournament, sports league, division, cup, competition (wd:P118 as wdt): league or competition in which team or player has played, or in which an event occurs, participant in
member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as ps/p): sports teams or clubs that the subject represents or represented, member of
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

Example 3:
Question:
what year did dwayne wade came to the nba?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q31683 p:P54 ?p .
  ?p ps:P54 ?y .
  ?y wdt:P118 wd:Q155223 .
  ?p pq:P580 ?x .
}
ORDER BY ?x
LIMIT 1

Using entities:
National Basketball Association, also known as Basketball Association of America, BAA, NBA, National Basketball Assn., Nat'l Basketball Assn. (wd:Q155223): North American professional men's basketball league
Dwyane Wade, also known as WOW (Way of Wade), Pookie, Dwyane Tyrone Wade, Jr., Flash, Father Prime (wd:Q31683): American basketball player, sports commentator, basketball player

Using properties:
league or competition, also known as tournament, sports league, division, cup, competition (wd:P118 as wdt): league or competition in which team or player has played, or in which an event occurs, participant in
member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as ps/p): sports teams or clubs that the subject represents or represented, member of
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, it seems the approach to find when a player came into the NBA is to look at the "member of sports team" (P54) statements for the player, filter for teams in the NBA (P118 = NBA), and then get the start time (P580) of that membership.

Next, I will search for the entity "Shaquille O'Neal" to get his Wikidata ID.

[Tool]
Top 10 entity alternatives:
1. Shaquille O'Neal, also known as Shaquille O’Neal, Shaquille Rashaun O'Neal, Shaq O'Neal, Shaquille Rashaun O’Neal, Shaq (wd:Q169452): American basketball player, real estate entrepreneur, television producer, sports commentator, basketball player, businessperson, film producer, screenwriter, film actor, Thai boxer, podcaster, singer, rapper, actor
2. Shaquille O'Neal (wd:Q125446160): episode of All That (S5 E3)
3. Shaquille Cleare, also known as Shaquille O'Neal Cleare (wd:Q61953486): college basketball player (2013–2017) Maryland; Texas, basketball player
4. Shaquille O'Neal Motors (wd:Q114535400): episode of Fresh Off the Boat (S2 E3)
5. Shaq Belson, also known as Shaquille Belson, Shaquille O'Neal Belson (wd:Q106725566): American American football player, American football player
6. Shaquille Allen, also known as Shaquille O'Neal Allen (wd:Q106725550): American football player
7. Upload with Shaquille O'Neal (wd:Q7898386): American comedy television series
8. Statue of Shaquille O'Neal (wd:Q114363921): sculpture in Los Angeles, California, U.S
9. The Best of Shaquille O'Neal (wd:Q7717219): album by Shaquille O'Neal
10. A Message from Shaquille O'Neal (wd:Q110058550): sketch from Saturday Night Live

[Assistant] The entity for Shaquille O'Neal is wd:Q169452. Now I will write a SPARQL query to find the start time when Shaquille O'Neal joined a sports team that is part of the NBA (wd:Q155223). I will order by the start time and limit to 1 to get the earliest date.

[Tool]
Got 1 row and 1 column:
| startTime                           |
| ----------------------------------- |
| 1992-06-01T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly identifies the start time of Shaquille O'Neal's membership in an NBA team, which corresponds to when he came into the NBA. However, the answer date June 1, 1992, is likely the start of the month rather than the exact date of his NBA debut or draft. Typically, NBA seasons and drafts occur in specific months (e.g., June for the draft). To improve accuracy, the query could be refined to check for the exact event of his NBA draft or first game date if available. Also, the answer should clarify that this date corresponds to the start of his membership in an NBA team rather than explicitly stating "came into the NBA" which might be ambiguous. Overall, the output is sensible but could be more precise and clear.

[Assistant] Thank you for the feedback. To improve the precision and clarity, I will try to find the exact date of Shaquille O'Neal's NBA draft event if available, as the draft date is a more precise indicator of when he officially entered the NBA. I will search for properties related to "draft" for Shaquille O'Neal to see if there is a specific draft date recorded.

[Tool]
Top 10 property alternatives:
1. drafted by (wd:P647 as wdt/p): which team the player was drafted by
2. The Draft Review ID, also known as Draft Review identifier, The Draft Review identifier, Draft Review ID (wd:P9514 as wdt/p): identifier for a basketball player in the database of The Draft Review
3. nominated for, also known as nominee for, shortlisted for, selected for award, selected for, nominee for award (wd:P1411 as wdt/p): award nomination received by a person, organisation or creative work (inspired from "award received" (Property:P166))
4. 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
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. 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)
7. league or competition, also known as tournament, sports league, division, cup, competition (wd:P118 as wdt/p): league or competition in which team or player has played, or in which an event occurs, participant in
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. 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

No other items found

[Assistant] There is a property "drafted by" (wdt:P647) which indicates the team that drafted the player, but there is no direct property for draft date. I will now check the statements for Shaquille O'Neal related to "drafted by" to see if there is a qualifier for the draft date.

[Tool]
Got 1 row and 3 columns:
| subject                       | property              | object                     |
| ----------------------------- | --------------------- | -------------------------- |
| Shaquille O'Neal (wd:Q169452) | drafted by (wdt:P647) | Orlando Magic (wd:Q161337) |

[Assistant] Shaquille O'Neal was drafted by the Orlando Magic (wd:Q161337). Now I will check the statements for the drafted by property (P647) for qualifiers that might indicate the draft date.

[Tool]
Got 1 row and 3 columns:
| subject                       | property            | object                                         |
| ----------------------------- | ------------------- | ---------------------------------------------- |
| Shaquille O'Neal (wd:Q169452) | drafted by (p:P647) | s:Q169452-36F066C0-6342-46C4-A85A-7533DBD9FBA4 |

[Assistant] There is a statement node for the drafted by property. I will now check the qualifiers of this statement to find if there is a draft date.

[Tool]
Got 9 rows and 3 columns:
| subject                                        | property                            | object                                       |
| ---------------------------------------------- | ----------------------------------- | -------------------------------------------- |
| s:Q169452-36F066C0-6342-46C4-A85A-7533DBD9FBA4 | significant event (pq:P793)         | 1992 NBA Draft (wd:Q972098)                  |
| s:Q169452-36F066C0-6342-46C4-A85A-7533DBD9FBA4 | drafted by (ps:P647)                | Orlando Magic (wd:Q161337)                   |
| s:Q169452-36F066C0-6342-46C4-A85A-7533DBD9FBA4 | age of subject at event (pq:P3629)  | 20 (xsd:decimal)                             |
| s:Q169452-36F066C0-6342-46C4-A85A-7533DBD9FBA4 | draft pick number (pq:P1836)        | 1                                            |
| s:Q169452-36F066C0-6342-46C4-A85A-7533DBD9FBA4 | wikibase:rank                       | wikibase:NormalRank                          |
| s:Q169452-36F066C0-6342-46C4-A85A-7533DBD9FBA4 | rdf:type                            | wikibase:BestRank                            |
| s:Q169452-36F066C0-6342-46C4-A85A-7533DBD9FBA4 | prov:wasDerivedFrom                 | ref:fa278ebfc458360e5aed63d5058cca83c46134f1 |
| s:Q169452-36F066C0-6342-46C4-A85A-7533DBD9FBA4 | age of subject at event (pqv:P3629) | v:97f68cb36e9dc8548bee490dd5bf4b12           |
| s:Q169452-36F066C0-6342-46C4-A85A-7533DBD9FBA4 | rdf:type                            | wikibase:Statement                           |

[Assistant] The statement for "drafted by" has a qualifier "significant event" (pq:P793) which is the "1992 NBA Draft" (wd:Q972098). I will now check if there is a date associated with the "1992 NBA Draft" event.

[Tool]
Got 71 rows and 3 columns, showing the first 10 rows below:
| subject                     | property                                                    | object                                             |
| --------------------------- | ----------------------------------------------------------- | -------------------------------------------------- |
| 1992 NBA Draft (wd:Q972098) | instance of (wdt:P31)                                       | National Basketball Association draft (wd:Q622521) |
| 1992 NBA Draft (wd:Q972098) | country (wdt:P17)                                           | United States (wd:Q30)                             |
| 1992 NBA Draft (wd:Q972098) | located in the administrative territorial entity (wdt:P131) | Portland (wd:Q6106)                                |
| 1992 NBA Draft (wd:Q972098) | sport (wdt:P641)                                            | basketball (wd:Q5372)                              |
| 1992 NBA Draft (wd:Q972098) | follows (wdt:P155)                                          | 1991 NBA Draft (wd:Q1673830)                       |
| 1992 NBA Draft (wd:Q972098) | followed by (wdt:P156)                                      | 1993 NBA Draft (wd:Q1959898)                       |
| 1992 NBA Draft (wd:Q972098) | point in time (wdt:P585)                                    | 1992-06-24T00:00:00Z (xsd:dateTime)                |
| 1992 NBA Draft (wd:Q972098) | organizer (wdt:P664)                                        | National Basketball Association (wd:Q155223)       |
| 1992 NBA Draft (wd:Q972098) | significant person (wdt:P3342)                              | Shaquille O'Neal (wd:Q169452)                      |
| 1992 NBA Draft (wd:Q972098) | Freebase ID (wdt:P646)                                      | /m/06jnjz                                          |
| ...                         | ...                                                         | ...                                                |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the date when Shaquille O'Neal was drafted into the NBA, which is the appropriate event to indicate when he came into the NBA. The query uses the property for draft event (P647) and filters for the 1992 NBA Draft (Q972098), then extracts the draft date (P585). The answer is accurate and complete, providing the exact date of June 24, 1992. No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?spouse ?spouseLabel WHERE {
  wd:Q34969 wdt:P26 ?spouse .
  OPTIONAL {
    ?spouse rdfs:label ?spouseLabel FILTER ( LANG( ?spouseLabel ) = "en" )
  }
}

Benjamin Franklin married Deborah Read Franklin.

[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

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 did ben franklin marry?

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

[Tool]
Example 1:
Question:
where was ben franklin born?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q34969 wdt:P19 ?x .
}

Using entities:
Benjamin Franklin, also known as The First American, Silence Dogood, Poor Richard, Ben Franklin, Franklin (wd:Q34969): American polymath and statesman (1706–1790), politician, polymath, diplomat, writer

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

Example 2:
Question:
where did benjamin franklin died?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q34969 wdt:P20 ?x .
}

Using entities:
Benjamin Franklin, also known as The First American, Silence Dogood, Poor Richard, Ben Franklin, Franklin (wd:Q34969): American polymath and statesman (1706–1790), politician, polymath, diplomat, writer

Using properties:
place of death, also known as POD, location of death, killed in, deathplace, died in (wd:P20 as wdt): most specific known (e.g. city instead of country, or hospital i... city) death location of a person, animal or fictional character, location

Example 3:
Question:
what jobs did ben franklin do?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q34969 wdt:P106 ?x .
}

Using entities:
Benjamin Franklin, also known as The First American, Silence Dogood, Poor Richard, Ben Franklin, Franklin (wd:Q34969): American polymath and statesman (1706–1790), politician, polymath, diplomat, writer

Using properties:
occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)

[Assistant] From the examples, I see that Benjamin Franklin is represented by the entity wd:Q34969 in Wikidata. Now, I need to find the property that represents "spouse" or "married to" to answer the question "who did Ben Franklin marry?". I will search for properties related to marriage or spouse for the entity Benjamin Franklin.

[Tool]
Top 10 property alternatives:
1. 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
2. relative, also known as relatives, grandparent, relation, non-binary parent, niece (wd:P1038 as wdt/p): family member (qualify with "kinship to subject", P1039; for direct family member please use specific property), significant person
3. 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)
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. child, also known as has son, kids, mother of, kid, issue (wd:P40 as wdt/p): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative
6. father, also known as son of, child of, parent, is son of, is daughter of (wd:P22 as wdt/p): male parent of the subject. For stepfather, use "stepparent" (P3448), parent
7. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as wdt/p): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)
8. mother, also known as mom, is child of, mommy, mum, mummy (wd:P25 as wdt/p): female parent of the subject. For stepmother, use "stepparent" (P3448), parent
9. family name, also known as clan name, last name, surname (wd:P734 as wdt/p): part of full name of person, name
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 "spouse" (wdt:P26) is the appropriate property to find who Ben Franklin married. Now I will write a SPARQL query to get the spouse(s) of Benjamin Franklin (wd:Q34969).

[Tool]
Got 1 row and 2 columns:
| spouse                              | spouseLabel                |
| ----------------------------------- | -------------------------- |
| Deborah Read Franklin (wd:Q3020859) | Deborah Read Franklin (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the spouse of Benjamin Franklin using the property wdt:P26. The query also optionally fetches the English label of the spouse, which is Deborah Read Franklin. The answer provided is accurate and complete based on the query result. No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?language ?languageLabel WHERE {
  wd:Q148 wdt:P37 ?language .
  FILTER ( ?language = wd:Q727694 ) OPTIONAL {
    ?language rdfs:label ?languageLabel FILTER ( LANG( ?languageLabel ) = "en" )
  }
}

Chinese people write in Standard Chinese, which is the standard written form of the Chinese language used in China.

[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

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 language do chinese people write in?

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

[Tool]
Example 1:
Question:
what language do chinese?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q148 wdt:P37 ?x .
}

Using entities:
People's Republic of China, also known as Zhōngguó, The PRC, RPC, CHN, Red China (wd:Q148): country in East Asia

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

Example 2:
Question:
what kind of language do they speak in china?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q148 wdt:P37 ?x .
}

Using entities:
People's Republic of China, also known as Zhōngguó, The PRC, RPC, CHN, Red China (wd:Q148): country in East Asia

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

Example 3:
Question:
what kind of language do china speak?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q148 wdt:P37 ?x .
}

Using entities:
People's Republic of China, also known as Zhōngguó, The PRC, RPC, CHN, Red China (wd:Q148): country in East Asia

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] From the similar examples, it is clear that the entity for China is wd:Q148 and the property for official language is wdt:P37. The question asks about the language Chinese people write in, which is closely related to the official language(s) of China. I will write a SPARQL query to get the official languages of China.

[Tool]
Got 3 rows and 2 columns:
| language                        | languageLabel           |
| ------------------------------- | ----------------------- |
| Standard Chinese (wd:Q727694)   | Standard Chinese (en)   |
| Chinese (wd:Q7850)              | Chinese (en)            |
| languages of China (wd:Q835866) | languages of China (en) |

[Assistant] The official languages of China include "Standard Chinese," "Chinese," and "languages of China." Since the question is about the language Chinese people write in, the most relevant answer is "Standard Chinese," which is the standard written form of the Chinese language. I will now provide the final answer.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly retrieves the official languages of China, including Standard Chinese and Chinese. However, the question specifically asks about the language Chinese people write in, which is best answered by focusing on the standard written form. The query returns multiple languages including 'languages of China,' which is too broad and not a specific language. It would be better to refine the query to focus on the standard written language used by Chinese people, possibly by querying for the 'standard written language' or 'written language' property if available, or by filtering to the most relevant language such as Standard Chinese (Mandarin). Additionally, the answer should clarify that Standard Chinese is the standard written form, distinct from spoken dialects.

[Assistant] Thank you for the feedback. I will refine the query to specifically target the standard written language used by Chinese people. I will search for properties related to "written language" or "standard written language" for China (wd:Q148) to see if there is a more precise property than the general official language property (wdt:P37). Then I will use that property in the query to get a more accurate answer.

[Tool]
Top 10 property alternatives:
1. language used, also known as languages used, medium of instruction, used language, uses language, working language (wd:P2936 as wdt/p): language widely used (spoken or written) in this place or at this event or organisation
2. official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as wdt/p): language designated as official by this item, language used
3. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
4. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as wdt/p): work where this item is described, attested in
5. 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
6. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as wdt/p): label for the items in their official language  or their original language, name
7. Unicode character, also known as emoji, emote, pictograph, Unicode symbol (wd:P487 as wdt/p): Unicode character representing the item (only if this is not a c...acter or a compatiblity character: in that case, use only P4213)
8. literacy rate, also known as percentage of literate population, literate population (%) (wd:P6897 as wdt/p): percentage of the population that is not illiterate
9. main regulatory text, also known as regulated by, statutory authorization, statutory authority, legally established by, legal basis (wd:P92 as wdt/p): text setting the main rules by which the subject is regulated
10. 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)

No other items found

[Assistant] There is no specific property for "written language" or "standard written language" for China. The closest relevant property is "language used" (wdt:P2936), which indicates languages widely used (spoken or written) in the place. I will now query for the languages used in China using this property and check if it provides a more precise answer.

[Tool]
Got 279 rows and 2 columns, showing the first 5 and last 5 rows below:
| language                            | languageLabel              |
| ----------------------------------- | -------------------------- |
| Wutun (wd:Q1012917)                 | Wutun (en)                 |
| Sani (wd:Q1055287)                  | Sani (en)                  |
| Chinese Sign Language (wd:Q1094190) | Chinese Sign Language (en) |
| Ache Yi (wd:Q10949828)              | Ache Yi (en)               |
| A-Hmao (wd:Q1108934)                | A-Hmao (en)                |
| ...                                 | ...                        |
| Kazakh (wd:Q9252)                   | Kazakh (en)                |
| Kyrgyz (wd:Q9255)                   | Kyrgyz (en)                |
| Chadong (wd:Q926742)                | Chadong (en)               |
| Hlai (wd:Q934738)                   | Hlai (en)                  |
| U (wd:Q953082)                      | U (en)                     |

[Assistant] The property "language used" (wdt:P2936) for China returns many languages, including minority and regional languages. This is too broad for the question about the language Chinese people write in, which is best answered by the standard written language. Since there is no direct property for "written language," I will revert to the official language property (wdt:P37) and filter to the most relevant language "Standard Chinese" (wd:Q727694) as the answer. I will also clarify in the answer that Standard Chinese is the standard written form used by Chinese people.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly identifies Standard Chinese (wd:Q727694) as the language written by Chinese people, using the property for official language (wdt:P37) of China (wd:Q148). The query returns the language and its English label, which matches the answer provided. The answer is accurate and complete for the question asked. No further refinement is necessary.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?owner ?ownerLabel ?start ?end WHERE {
  wd:Q29610 p:P127 ?statement .
  ?statement ps:P127 ?owner .
  OPTIONAL {
    ?statement pq:P580 ?start .
  }
  OPTIONAL {
    ?statement pq:P582 ?end .
  }
  OPTIONAL {
    ?owner rdfs:label ?ownerLabel FILTER ( LANG( ?ownerLabel ) = "en" )
  }
}
ORDER BY ?start

Chrysler Corporation was owned by Fiat Chrysler Automobiles from 2014 to 2021, and since 2021 it has been owned by Stellantis North America. There is no explicit ownership information in Wikidata for the year 2011, but historically Chrysler was controlled by the US Treasury and private equity firms after its 2009 bankruptcy.

[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

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 owns chrysler corporation 2011?

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

[Tool]
Example 1:
Question:
who owns chrysler corporation 2012?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q29610 wdt:P127 ?x .
}

Using entities:
Chrysler, also known as Chrysler brand (wd:Q29610): US automotive brand

Using properties:
owned by, also known as belongs to, stockholders, stockholder, shareholders, shareholder (wd:P127 as wdt): owner of the subject

Example 2:
Question:
who owns nissan car manufacturer?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q20165 wdt:P112 ?x .
}

Using entities:
Nissan Motor Co. Ltd., also known as Nissan Motors, Nissan Motor Company Ltd, Nissan Motor Company, Nissan Motor Co., Ltd., NISSAN (wd:Q20165): Japanese company

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

Example 3:
Question:
what car companies does ford motor company own?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q44294 wdt:P1830 ?x .
  ?x wdt:P31 wd:Q10429667 .
}

Using entities:
car brand, also known as automobile brand, automobile marque, badge, car marque, make of car (wd:Q10429667): brand or make of a car
Ford Motor Company, also known as FoMoCo, Ford Motors, Ford Motor Corporation, Ford Motor Co., Ford Motor (wd:Q44294): American multinational automotive company

Using properties:
owner of, also known as owns, owns property, shareholder of (wd:P1830 as wdt): entities owned by the subject
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

[Assistant]
The first example shows a query for "who owns chrysler corporation 2012?" which uses the property "owned by" (wdt:P127) for the entity Chrysler (wd:Q29610). This property seems appropriate to find the owner of Chrysler Corporation in 2011 as well.

Next, I will check the ownership of Chrysler Corporation (wd:Q29610) using the property "owned by" (wdt:P127) to see if there is any information about the owner in 2011.

[Tool]
Got 1 row and 2 columns:
| owner                                 | ownerLabel                    |
| ------------------------------------- | ----------------------------- |
| Stellantis North America (wd:Q181114) | Stellantis North America (en) |

[Assistant] The current owner of Chrysler Corporation is Stellantis North America. However, the user specifically asked about the owner in 2011. I will now check if there is any historical ownership information or qualifiers related to the ownership statement for the year 2011. I will look for statements about ownership of Chrysler (wd:Q29610) with qualifiers indicating the time period.

[Tool]
Got 1 row and 3 columns:
| subject              | property            | object                                |
| -------------------- | ------------------- | ------------------------------------- |
| Chrysler (wd:Q29610) | owned by (wdt:P127) | Stellantis North America (wd:Q181114) |

[Assistant]
There is only one direct ownership statement for Chrysler (wd:Q29610) with property owned by (wdt:P127), which points to Stellantis North America. This does not provide historical ownership information.

I will now check the statements (wd:statement) for the property P127 (owned by) for Chrysler (wd:Q29610) to see if there are qualifiers indicating the time period, specifically around 2011.

[Tool]
Got 2 rows and 3 columns:
| subject              | property          | object                                        |
| -------------------- | ----------------- | --------------------------------------------- |
| Chrysler (wd:Q29610) | owned by (p:P127) | s:Q29610-46bfe8e7-47b3-432c-0af0-96ae440c4b3b |
| Chrysler (wd:Q29610) | owned by (p:P127) | s:Q29610-B0C82F9E-AB2C-4E89-B10F-29B2863D9FB6 |

[Assistant] There are two statements for the property "owned by" (P127) for Chrysler (wd:Q29610). I will now check the qualifiers of these statements to find any time-related information, especially for the year 2011.

[Tool]
Got 7 rows and 3 columns:
| subject                                       | property              | object                                       |
| --------------------------------------------- | --------------------- | -------------------------------------------- |
| s:Q29610-46bfe8e7-47b3-432c-0af0-96ae440c4b3b | owned by (ps:P127)    | Stellantis North America (wd:Q181114)        |
| s:Q29610-46bfe8e7-47b3-432c-0af0-96ae440c4b3b | start time (pq:P580)  | 2021-01-01T00:00:00Z (xsd:dateTime)          |
| s:Q29610-46bfe8e7-47b3-432c-0af0-96ae440c4b3b | wikibase:rank         | wikibase:PreferredRank                       |
| s:Q29610-46bfe8e7-47b3-432c-0af0-96ae440c4b3b | rdf:type              | wikibase:BestRank                            |
| s:Q29610-46bfe8e7-47b3-432c-0af0-96ae440c4b3b | prov:wasDerivedFrom   | ref:ed0016ffcbc832c857c8124f34111ba7d4e9336d |
| s:Q29610-46bfe8e7-47b3-432c-0af0-96ae440c4b3b | start time (pqv:P580) | v:068defc300d06ed22eb72f44c2fe8914           |
| s:Q29610-46bfe8e7-47b3-432c-0af0-96ae440c4b3b | rdf:type              | wikibase:Statement                           |

[Tool]
Got 7 rows and 3 columns:
| subject                                       | property              | object                                   |
| --------------------------------------------- | --------------------- | ---------------------------------------- |
| s:Q29610-B0C82F9E-AB2C-4E89-B10F-29B2863D9FB6 | owned by (ps:P127)    | Fiat Chrysler Automobiles (wd:Q15678788) |
| s:Q29610-B0C82F9E-AB2C-4E89-B10F-29B2863D9FB6 | start time (pq:P580)  | 2014-01-01T00:00:00Z (xsd:dateTime)      |
| s:Q29610-B0C82F9E-AB2C-4E89-B10F-29B2863D9FB6 | end time (pq:P582)    | 2021-01-01T00:00:00Z (xsd:dateTime)      |
| s:Q29610-B0C82F9E-AB2C-4E89-B10F-29B2863D9FB6 | wikibase:rank         | wikibase:NormalRank                      |
| s:Q29610-B0C82F9E-AB2C-4E89-B10F-29B2863D9FB6 | rdf:type              | wikibase:Statement                       |
| s:Q29610-B0C82F9E-AB2C-4E89-B10F-29B2863D9FB6 | start time (pqv:P580) | v:4755748741739c53456596b64165b84b       |
| s:Q29610-B0C82F9E-AB2C-4E89-B10F-29B2863D9FB6 | end time (pqv:P582)   | v:068defc300d06ed22eb72f44c2fe8914       |

[Assistant]
The ownership statements for Chrysler show two different owners with time qualifiers:
- Stellantis North America owns Chrysler starting from 2021.
- Fiat Chrysler Automobiles owned Chrysler from 2014 to 2021.

Since the user asked about the owner in 2011, I will now check if there is any ownership information before 2014. I will try to find the owner of Chrysler with a time qualifier that includes the year 2011. I will write a query to find owners of Chrysler with start and end times that cover 2011.

[Tool] Got no rows and 4 columns

[Assistant]
There is no explicit ownership information for Chrysler Corporation covering the year 2011 in the data. However, based on historical knowledge, Chrysler was owned by Chrysler Group LLC in 2011, which was a company controlled by the United States Treasury and private equity firms after the 2009 bankruptcy.

I will now try to find the entity for Chrysler Group LLC or similar and check if it is listed as an owner of Chrysler in 2011 or before 2014.

[Tool]
Top 10 entity alternatives:
1. Stellantis North America, also known as Chrysler Corporation, Chrysler LLC, FCA US (wd:Q181114): American automotive manufacturer
2. Jefferies & Company, also known as Jefferies Group, Jefferies Group LLC, Jefferies LLC (wd:Q325789): company
3. OSI Group, also known as OSI, OSI Group, LLC, OSI Industries, OSI Industries, LLC. (wd:Q2008123): American company of meat processors
4. The Kraft Group, also known as Kraft Group, Kraft Group, LLC (wd:Q7744946): American group of large corporations
5. Apparel Group LLC, also known as APPAREL GROUP, Apparel Group (wd:Q115806042): Fashion and lifestyle industry offering 80 brands across 2,025 and more stores in 14 countries
6. Crumpton Group LLC, also known as Crumpton Group (wd:Q60492734): International research/advisory and business development firm
7. ILO Group, also known as ILO Group, LLC (wd:Q108822279): American education-focused leadership consultancy
8. JETX, also known as JEFFERIES GROUP LLC, JEFX (wd:Q93361416): Dark pool for NMS equities
9. Kaart, also known as Kaart Group, Kaart Group, LLC (wd:Q108353551): American GIS consulting and surveying firm
10. L4 Group LLC, also known as L4 Group, L4 Group Media (wd:Q78339997): Media Agency in Pennsylvania

[Assistant]
There is no direct entity named "Chrysler Group LLC" in the top search results. However, the first result Stellantis North America (wd:Q181114) is also known as Chrysler Corporation, Chrysler LLC, FCA US, which might be the current or later name.

I will now try to find the owner of Chrysler Corporation (wd:Q181114) before 2014 to see if there is any historical owner listed. I will check the ownership statements with time qualifiers for this entity.

[Tool]
Got 1 row and 3 columns:
| subject                               | property          | object                                         |
| ------------------------------------- | ----------------- | ---------------------------------------------- |
| Stellantis North America (wd:Q181114) | owned by (p:P127) | s:Q181114-204b06bd-49ca-04a7-b398-f5652b02baae |

[Tool]
Got 8 rows and 3 columns:
| subject                                        | property              | object                                       |
| ---------------------------------------------- | --------------------- | -------------------------------------------- |
| s:Q181114-204b06bd-49ca-04a7-b398-f5652b02baae | owned by (ps:P127)    | Stellantis (wd:Q97439162)                    |
| s:Q181114-204b06bd-49ca-04a7-b398-f5652b02baae | start time (pq:P580)  | 2021-01-16T00:00:00Z (xsd:dateTime)          |
| s:Q181114-204b06bd-49ca-04a7-b398-f5652b02baae | wikibase:rank         | wikibase:NormalRank                          |
| s:Q181114-204b06bd-49ca-04a7-b398-f5652b02baae | rdf:type              | wikibase:BestRank                            |
| s:Q181114-204b06bd-49ca-04a7-b398-f5652b02baae | prov:wasDerivedFrom   | ref:64a55cd2156959c80115e57597614772ad320886 |
| s:Q181114-204b06bd-49ca-04a7-b398-f5652b02baae | start time (pqv:P580) | v:348e732dabe8383809ebd01e184db783           |
| s:Q181114-204b06bd-49ca-04a7-b398-f5652b02baae | rdf:type              | wikibase:Statement                           |
| s:Q181114-204b06bd-49ca-04a7-b398-f5652b02baae | prov:wasDerivedFrom   | ref:d416ed307bc452b4f889e47d0cf887c3c4d36953 |

[Assistant]
Stellantis North America (wd:Q181114) is owned by Stellantis (wd:Q97439162) starting from 2021. There is no ownership information before 2021 for this entity.

Given the lack of explicit data for 2011 ownership in Wikidata, I will provide the best available information: Chrysler was owned by Fiat Chrysler Automobiles from 2014 to 2021, and before that, it was a separate entity likely controlled by the US Treasury and private equity after the 2009 bankruptcy. I will formulate a query that returns the owners of Chrysler with their ownership periods to provide a comprehensive answer.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The answer correctly explains the ownership of Chrysler Corporation around 2011, noting the absence of explicit ownership data for that year in Wikidata and providing historical context about Chrysler's control after its 2009 bankruptcy. The SPARQL query is appropriate as it retrieves ownership statements with start and end times, allowing to infer ownership periods. The query results align with the answer, showing ownership starting from 2014 and 2021, which supports the explanation. The answer is clear, informative, and the query follows best practices by including optional labels and time qualifiers. No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?occupation ?occupationLabel WHERE {
  wd:Q302 wdt:P106 ?occupation .
  OPTIONAL {
    ?occupation rdfs:label ?occupationLabel FILTER ( LANG( ?occupationLabel ) = "en" )
  }
}

Got 12 rows and 2 columns, showing the first 5 and last 5 rows below:
| occupation                      | occupationLabel       |
| ------------------------------- | --------------------- |
| rabbi (wd:Q133485)              | rabbi (en)            |
| thaumaturge (wd:Q1349880)       | thaumaturge (en)      |
| carpenter (wd:Q154549)          | carpenter (en)        |
| religious leader (wd:Q15995642) | religious leader (en) |
| father of faith (wd:Q2142783)   | father of faith (en)  |
| ...                             | ...                   |
| teacher (wd:Q37226)             | teacher (en)          |
| prophet (wd:Q42857)             | prophet (en)          |
| preacher (wd:Q432386)           | preacher (en)         |
| Messiah (wd:Q51626)             | Messiah (en)          |
| tektōn (wd:Q7695510)            | tektōn (en)           |

Jesus had multiple occupations or roles including rabbi, thaumaturge, carpenter, religious leader, father of faith, teacher, prophet, preacher, Messiah, and tektōn (a craftsman or builder).

[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

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 did jesus do for living?

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

[Tool]
Example 1:
Question:
what did st. matthew do?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q43600 wdt:P106 ?x .
}

Using entities:
Matthew the Apostle, also known as Saint Matthew, Matthew the Evangelist, Matthew (wd:Q43600): Christian evangelist and apostle, tax collector, presbyter, publican

Using properties:
occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)

Example 2:
Question:
what did martin luther do?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q9554 wdt:P106 ?x .
}

Using entities:
Martin Luther (wd:Q9554): German priest and theologian (1483–1546), Protestant reformer, Bible translator, Catholic priest, philosopher, translator, hymnwriter, reformator, theologian, professor, preacher, composer, scribe, lawyer, writer, pastor

Using properties:
occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)

Example 3:
Question:
where was jesus born and raised?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q302 wdt:P19 ?x .
}

Using entities:
Jesus, also known as The Messiah, Son of Man, The Saviour, Lord of Lords, Saviour of the world (wd:Q302): central figure of Christianity (6 or 4 BC – AD 30 or 33), religious leader, father of faith, thaumaturge, carpenter, preacher, Messiah, teacher, prophet, pastor, healer, tektōn, rabbi

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] From the similar examples, it is clear that the property "occupation" (wdt:P106) is used to find what a person did for a living. The entity for Jesus is wd:Q302. I will now write a SPARQL query to find the occupation(s) of Jesus using this property and entity.

[Tool]
Got 12 rows and 2 columns, showing the first 5 and last 5 rows below:
| occupation                      | occupationLabel       |
| ------------------------------- | --------------------- |
| rabbi (wd:Q133485)              | rabbi (en)            |
| thaumaturge (wd:Q1349880)       | thaumaturge (en)      |
| carpenter (wd:Q154549)          | carpenter (en)        |
| religious leader (wd:Q15995642) | religious leader (en) |
| father of faith (wd:Q2142783)   | father of faith (en)  |
| ...                             | ...                   |
| teacher (wd:Q37226)             | teacher (en)          |
| prophet (wd:Q42857)             | prophet (en)          |
| preacher (wd:Q432386)           | preacher (en)         |
| Messiah (wd:Q51626)             | Messiah (en)          |
| tektōn (wd:Q7695510)            | tektōn (en)           |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the occupations of Jesus from Wikidata using the property P106 (occupation). The answer lists multiple relevant roles and occupations such as rabbi, thaumaturge, carpenter, religious leader, teacher, prophet, preacher, Messiah, and tektōn, which aligns well with the data retrieved. The query also includes English labels for readability. The response is complete and accurate for the user's question about what Jesus did for a living.