PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?fullName WHERE {
  wd:Q312581 wdt:P1559 ?fullName .
}

Got 1 row and 1 column:
| fullName                   |
| -------------------------- |
| Charles Edward Stuart (en) |

The full name of Bonnie Prince Charlie is Charles Edward Stuart.

[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 was bonnie prince charlie full name?

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

[Tool]
Example 1:
Question:
what was prince charles last name?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q43274 wdt:P1559 ?x .
}

Using entities:
Charles III, also known as HM King Charles III, King Charles, His Royal Highness Charles III of Great Britain, King of England, King Charles III (wd:Q43274): King of the United Kingdom and other Commonwealth realms since 2022, children's writer, helicopter pilot, environmentalist, philanthropist, entrepreneur, polo player, aristocrat, politician, writer

Using properties:
name in native language, also known as native name (wd:P1559 as wdt): name of a person in their native language, name

Example 2:
Question:
what is the king of spain's name?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q29 wdt:P35 ?x .
}

Using entities:
Spain, also known as Kingdom of Spain (wd:Q29): country in southwestern Europe with territories in Africa

Using properties:
head of state, also known as leader, state headed by, monarch, president, queen (wd:P35 as wdt): official with the highest formal authority in a country/state, director / manager, chairperson

Example 3:
Question:
who was queen victoria's parents called?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q9439 wdt:P22 | wdt:P25 ?x .
}

Using entities:
Victoria, also known as Victoria, Queen of Great Britain, Victoria of the United Kingdom, Victoria Hanover, Alexandrina Victoria von Hannover, Victoria Alexandrina (wd:Q9439): Queen of the United Kingdom from 1837 to 1901, monarch

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

[Assistant] From the examples, the property wdt:P1559 (name in native language, also known as native name) is used to get the full or native name of a person. We should first find the Wikidata entity for "Bonnie Prince Charlie" and then query for his full name using the property wdt:P1559. Let's start by searching for the entity "Bonnie Prince Charlie".

[Tool]
Top 10 entity alternatives:
1. Charles Edward Stuart, also known as The Young Pretender, The Young Chevalier, Charles III of England, Scotland, and Ireland, Charles III of England, Scotland and Ireland, Bonnie Prince Charlie (wd:Q312581): Jacobite pretender to the thrones of England, Scotland, Ireland, and France; (1720-1788), military leader, pretender
2. Bonnie Prince Charlie (wd:Q4942424): 1923 British silent historical film directed by Charles Calvert
3. Bonnie Prince Charlie (wd:Q4942426): 1948 film
4. Bonnie Prince Charlie (wd:Q58446788)
5. Bonnie Prince Charlie (1720–1788) (wd:Q119867964): painting by Louis Tocqué (1696–1772) (after), Kirkcaldy Galleries
6. Grevillea rosmarinifolia ‘Bonnie Prince Charlie’ (wd:Q104183391)
7. Bonnie Prince Charlie's Cave (wd:Q106963412): cave in Highland, Scotland, UK
8. Bonnie Prince Charlie (Prince Charles Edward Stuart, 1720–1788) (wd:Q119438652): painting by Roy Petrie (b.1946), Skye and Lochalsh Archive Centre (High Life Highland)
9. Flora MacDonald's Introduction to Bonnie Prince Charlie (wd:Q119729269): painting by Alexander Johnston (1815–1891), Museums Sheffield
10. Prince Charles Edward Stuart (1720–1788) ('Bonnie Prince Charlie') (wd:Q119947071): painting by unknown artist, Provand’s Lordship

[Assistant] The entity "Charles Edward Stuart" (wd:Q312581) is the one that corresponds to Bonnie Prince Charlie, the Jacobite pretender. Now, I will query for his full name using the property wdt:P1559 (name in native language or also known as).

[Tool]
Got 1 row and 1 column:
| fullName                   |
| -------------------------- |
| Charles Edward Stuart (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The system correctly identified the full name of Bonnie Prince Charlie as Charles Edward Stuart using the property wdt:P1559 (name) on the entity wd:Q312581. The SPARQL query is appropriate and returns the expected result. The answer is accurate and complete.


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:Q11881 wdt:P106 ?occupation .
  OPTIONAL {
    ?occupation rdfs:label ?occupationLabel FILTER ( LANG( ?occupationLabel ) = "en" )
  }
}

Got 3 rows and 2 columns:
| occupation                | occupationLabel   |
| ------------------------- | ----------------- |
| statesperson (wd:Q372436) | statesperson (en) |
| lawyer (wd:Q40348)        | lawyer (en)       |
| politician (wd:Q82955)    | politician (en)   |

John Tyler was a statesperson, lawyer, and politician.

[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 was john tyler?

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

[Tool]
Example 1:
Question:
what party did john tyler belong to?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q11881 wdt:P102 ?x .
}

Using entities:
John Tyler, also known as John Tyler, Jr., J. Tyler, President Tyler, John Tyler Jr, John Tyler, Jr (wd:Q11881): president of the United States from 1841 to 1845, statesperson, politician, lawyer

Using properties:
member of political party, also known as political party member, political party, party membership, party, member of party (wd:P102 as wdt): the political party of which a person is or has been a member or otherwise affiliated, member of

Example 2:
Question:
where john tyler was born?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q11881 wdt:P19 ?x .
}

Using entities:
John Tyler, also known as John Tyler, Jr., J. Tyler, President Tyler, John Tyler Jr, John Tyler, Jr (wd:Q11881): president of the United States from 1841 to 1845, statesperson, politician, lawyer

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

Example 3:
Question:
who was sam houston answers?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q216547 wdt:P106 ?x .
}

Using entities:
Sam Houston, also known as Samuel Houston, Samuel "Sam" Houston (wd:Q216547): American statesman, politician, and soldier (1793-1863), politician, lawyer

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]
The question "what was John Tyler?" is likely asking about John Tyler's occupation or role. From the similar examples, we see that the property "occupation" (wdt:P106) is used to find what a person was or did. John Tyler is identified as wd:Q11881 in Wikidata.

I will now write a SPARQL query to find the occupation(s) of John Tyler using the property wdt:P106.

[Tool]
Got 3 rows and 2 columns:
| occupation                | occupationLabel   |
| ------------------------- | ----------------- |
| statesperson (wd:Q372436) | statesperson (en) |
| lawyer (wd:Q40348)        | lawyer (en)       |
| politician (wd:Q82955)    | politician (en)   |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the occupations of John Tyler using the property wdt:P106. The query returns the expected occupations: statesperson, lawyer, and politician, which matches the provided answer. The query also includes labels for readability, which is helpful. The answer is accurate and complete based on the data retrieved. 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 ?notableWork ?notableWorkLabel ?occupation ?occupationLabel WHERE {
  wd:Q307 wdt:P800 ?notableWork .
  wd:Q307 wdt:P106 ?occupation .
  OPTIONAL {
    ?notableWork rdfs:label ?notableWorkLabel FILTER ( LANG( ?notableWorkLabel ) = "en" )
  }
  OPTIONAL {
    ?occupation rdfs:label ?occupationLabel FILTER ( LANG( ?occupationLabel ) = "en" )
  }
}

Got 18 rows and 4 columns, showing the first 5 and last 5 rows below:
| notableWork                                | notableWorkLabel                  | occupation                       | occupationLabel         |
| ------------------------------------------ | --------------------------------- | -------------------------------- | ----------------------- |
| equations for a falling body (wd:Q1132975) | equations for a falling body (en) | astronomer (wd:Q11063)           | astronomer (en)         |
| equations for a falling body (wd:Q1132975) | equations for a falling body (en) | astrologer (wd:Q155647)          | astrologer (en)         |
| equations for a falling body (wd:Q1132975) | equations for a falling body (en) | university teacher (wd:Q1622272) | university teacher (en) |
| equations for a falling body (wd:Q1132975) | equations for a falling body (en) | physicist (wd:Q169470)           | physicist (en)          |
| equations for a falling body (wd:Q1132975) | equations for a falling body (en) | mathematician (wd:Q170790)       | mathematician (en)      |
| ...                                        | ...                               | ...                              | ...                     |
| Galilean transformation (wd:Q219207)       | Galilean transformation (en)      | mathematician (wd:Q170790)       | mathematician (en)      |
| Galilean transformation (wd:Q219207)       | Galilean transformation (en)      | inventor (wd:Q205375)            | inventor (en)           |
| Galilean transformation (wd:Q219207)       | Galilean transformation (en)      | philosopher (wd:Q4964182)        | philosopher (en)        |
| Galilean transformation (wd:Q219207)       | Galilean transformation (en)      | engineer (wd:Q81096)             | engineer (en)           |
| Galilean transformation (wd:Q219207)       | Galilean transformation (en)      | scientist (wd:Q901)              | scientist (en)          |

Galileo Galilei was famous for his notable works such as "equations for a falling body" and "Galilean transformation." He was also known for his occupations as an astronomer, astrologer, university teacher, physicist, mathematician, inventor, philosopher, engineer, and scientist.

[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 galileo galilei was famous for?

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

[Tool]
Example 1:
Question:
who was galileo galilei?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q307 wdt:P106 ?x .
}

Using entities:
Galileo Galilei (wd:Q307): Italian polymath (1564–1642), university teacher, mathematician, philosopher, astronomer, astrologer, scientist, physicist, engineer, inventor

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 is isaac newton famous for?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q935 wdt:P800 ?x .
}

Using entities:
Isaac Newton (wd:Q935): English mathematician and physicist (1642–1727), mathematician, philosopher

Using properties:
notable work, also known as artwork, wrote, writer of, works, work (wd:P800 as wdt): notable scientific, artistic or literary work, or other work of significance among subject's works

Example 3:
Question:
where did galileo go to school?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q307 wdt:P69 ?x .
}

Using entities:
Galileo Galilei (wd:Q307): Italian polymath (1564–1642), university teacher, mathematician, philosopher, astronomer, astrologer, scientist, physicist, engineer, inventor

Using properties:
educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as wdt): educational institution attended by subject, affiliation

[Assistant]
From the similar examples, we see two main approaches to answer what Galileo Galilei was famous for:
1. Querying his occupations (wdt:P106) to show what he was known as professionally.
2. Querying his notable works (wdt:P800) to show what significant works he is known for.

I will first query the notable works of Galileo Galilei (wd:Q307) to see what he was famous for.

[Tool]
Got 2 rows and 2 columns:
| notableWork                                | notableWorkLabel                  |
| ------------------------------------------ | --------------------------------- |
| equations for a falling body (wd:Q1132975) | equations for a falling body (en) |
| Galilean transformation (wd:Q219207)       | Galilean transformation (en)      |

[Assistant] Galileo Galilei was famous for notable works such as "equations for a falling body" and "Galilean transformation." To provide a more complete answer, I will also query his occupations to show the fields he was known for.

[Tool]
Got 9 rows and 2 columns:
| occupation                       | occupationLabel         |
| -------------------------------- | ----------------------- |
| astronomer (wd:Q11063)           | astronomer (en)         |
| astrologer (wd:Q155647)          | astrologer (en)         |
| university teacher (wd:Q1622272) | university teacher (en) |
| physicist (wd:Q169470)           | physicist (en)          |
| mathematician (wd:Q170790)       | mathematician (en)      |
| inventor (wd:Q205375)            | inventor (en)           |
| philosopher (wd:Q4964182)        | philosopher (en)        |
| engineer (wd:Q81096)             | engineer (en)           |
| scientist (wd:Q901)              | scientist (en)          |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves Galileo Galilei's notable works and occupations, which directly answer the question about what he was famous for. The answer includes relevant notable works such as "equations for a falling body" and "Galilean transformation," as well as his various occupations, providing a comprehensive and accurate response. The query follows best practices by returning identifiers and labels, and the answer is clear and informative. 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 ?timeZone ?timeZoneLabel WHERE {
  wd:Q8646 wdt:P421 ?timeZone .
  OPTIONAL {
    ?timeZone rdfs:label ?timeZoneLabel FILTER ( LANG( ?timeZoneLabel ) = "en" )
  }
}

The time zone of Hong Kong, China is UTC+08:00. The current time in Hong Kong can be calculated based on this time zone.

[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 time in china hong kong?

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

[Tool]
Example 1:
Question:
where is hong kong china?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q8646 wdt:P30 ?x .
}

Using entities:
Hong Kong, also known as Hong Kong SAR, Hong Kong Special Administrative...f the People's Republic of China, Hong Kong Special Administrative Region, Hong Kong SAR, China, Hong Kong, China (wd:Q8646): city and special administrative region of China

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

Example 2:
Question:
what time is in london heathrow?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q8691 wdt:P421 ?x .
}

Using entities:
Heathrow Airport, also known as EGLL, Heathrow, LHR, London Heathrow, London Heathrow Airport (wd:Q8691): main airport serving London, England, United Kingdom

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

Example 3:
Question:
what time zone is it in london england?

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

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

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

[Assistant]
From the examples, it seems the property "located in time zone" (wdt:P421) is used to find the time zone of a place. To answer the question "what time in China Hong Kong?", we need to find the time zone of Hong Kong and then get the current time in that time zone.

Step 1: Find the time zone of Hong Kong using the property wdt:P421.
Step 2: Get the current time in that time zone.

I will start with step 1 and find the time zone of Hong Kong.

[Tool]
Got 1 row and 2 columns:
| timeZone             | timeZoneLabel  |
| -------------------- | -------------- |
| UTC+08:00 (wd:Q6985) | UTC+08:00 (en) |

[Assistant]
Hong Kong is in the time zone UTC+08:00. Now I will construct a SPARQL query to get the current time in the UTC+08:00 time zone. However, note that Wikidata itself does not provide real-time data such as the current time. It only provides static data like time zones.

So, the best I can do is provide the time zone information for Hong Kong, which is UTC+08:00. The current time would need to be calculated externally based on this time zone.

I will provide the final answer with this information.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the time zone of Hong Kong (wd:Q8646) using the property 'located in time zone' (wdt:P421). The result includes the time zone identifier and its English label, which is UTC+08:00. The answer correctly states the time zone and explains that the current time can be calculated based on this. The query and answer meet the requirements and provide a clear, accurate response to the user's question.


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 ?venue ?venueLabel WHERE {
  wd:Q204623 wdt:P115 ?venue .
  OPTIONAL {
    ?venue rdfs:label ?venueLabel FILTER ( LANG( ?venueLabel ) = "en" )
  }
}

The Florida Panthers play at the Amerant Bank Arena.

[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 florida panthers play?

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

[Tool]
Example 1:
Question:
where do the fla marlins play?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q652879 wdt:P115 ?x .
}

Using entities:
Miami Marlins, also known as Florida Marlins, Marlins (wd:Q652879): baseball team and Major League Baseball franchise in Miami, Florida, United States

Using properties:
home venue, also known as home water, venue, stadium, home ground, home field (wd:P115 as wdt): home stadium or venue of a sports team or applicable performing arts organization, location

Example 2:
Question:
where does the atlanta braves play?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q461595 wdt:P115 ?x .
}

Using entities:
Atlanta Braves, also known as Beaneaters, Rustlers, Milwaukee Braves, Doves, Braves (wd:Q461595): Major League Baseball team in Cumberland, Georgia

Using properties:
home venue, also known as home water, venue, stadium, home ground, home field (wd:P115 as wdt): home stadium or venue of a sports team or applicable performing arts organization, location

Example 3:
Question:
where are the florida marlins from?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q652879 wdt:P115 ?y .
  ?y wdt:P131 ?x .
}

Using entities:
Miami Marlins, also known as Florida Marlins, Marlins (wd:Q652879): baseball team and Major League Baseball franchise in Miami, Florida, United States

Using properties:
home venue, also known as home water, venue, stadium, home ground, home field (wd:P115 as wdt): home stadium or venue of a sports team or applicable performing arts organization, location
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

[Assistant] From the similar examples, it seems that the property "home venue" (wdt:P115) is used to indicate where a sports team plays. Now, I will search for the entity "Florida Panthers" to find its identifier in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Florida Panthers (wd:Q204623): National Hockey League team in Sunrise, Florida
2. FIU Panthers, also known as FIU Golden Panthers, Florida International Golden Panthers, Florida International Panthers (wd:Q3110096): intercollegiate sports teams of Florida International University
3. FIU Panthers men's basketball, also known as FIU Golden Panthers men's basketball, FIU Panthers basketball, Florida International Golden Panthers men's basketball, Florida International Panthers, Florida International Panthers basketball (wd:Q5425988): men's college basketball team
4. Florida Panthers IceDen (wd:Q124007705)
5. Florida Tech Panthers (wd:Q16155409): collegiate sports club in the United States
6. 2010–11 Florida Panthers season (wd:Q3467872): national Hockey League team season
7. 2007–08 Florida Panthers season (wd:Q4610005): national Hockey League team season
8. 2009–10 Florida Panthers season (wd:Q4615762): national Hockey League team season
9. 2008–09 Florida Panthers season (wd:Q4612635): national Hockey League team season
10. 2013–14 Florida Panthers season (wd:Q16245182): national Hockey League team season

[Assistant] The Florida Panthers NHL team is identified as wd:Q204623 in Wikidata. Based on the similar examples, the property for the home venue is wdt:P115. I will now query the home venue of the Florida Panthers.

[Tool]
Got 1 row and 2 columns:
| venue                           | venueLabel              |
| ------------------------------- | ----------------------- |
| Amerant Bank Arena (wd:Q795526) | Amerant Bank Arena (en) |

[Assistant] The Florida Panthers play at the Amerant Bank Arena. I will now provide the final answer with the SPARQL query.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the home venue of the Florida Panthers using the property 'home venue' (wdt:P115). The query also optionally fetches the English label of the venue, which is 'Amerant Bank Arena'. The answer is accurate and complete, matching the known home arena of the Florida Panthers. 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 ?country ?countryLabel WHERE {
  wd:Q1215310 wdt:P276 ?location .
  ?location wdt:P17 ?country .
  OPTIONAL {
    ?country rdfs:label ?countryLabel FILTER ( LANG( ?countryLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| country        | countryLabel |
| -------------- | ------------ |
| Cuba (wd:Q241) | Cuba (en)    |

The Battle of San Juan Hill took place in the country Cuba.

[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 country did the battle of san juan hill take place?

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

[Tool]
Example 1:
Question:
in what state did the bloody battle of antietam take place?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q719252 wdt:P276 ?p .
  ?p wdt:P131 + ?x .
  ?x wdt:P31 wd:Q107390 .
}

Using entities:
federated state, also known as state in a federation, state of a federation, state, federal state, constituent state (wd:Q107390): territorial and constitutional community forming part of a federal union
Battle of Antietam, also known as Battle of Sharpsburg (wd:Q719252): 1862 major battle of the American Civil War

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

Example 2:
Question:
where did chancellorsville battle take place?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q745979 wdt:P276 ?x .
}

Using entities:
Battle of Chancellorsville (wd:Q745979): 1863 major battle of the American Civil War

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:
where was the gettysburg war located?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q33132 wdt:P276 ?x .
}

Using entities:
Battle of Gettysburg (wd:Q33132): 1863 battle of the American Civil War

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

[Assistant]
From the similar examples, it is clear that the property "location" (wdt:P276) is used to find the place where a battle took place. We should first find the entity for "Battle of San Juan Hill" and then query its location. After that, we can find the country of that location.

I will start by searching for the entity "Battle of San Juan Hill".

[Tool]
Top 10 entity alternatives:
1. Battle of San Juan Hill, also known as Battle for the San Juan Heights (wd:Q1215310): 1898 decisive battle of the Spanish–American War
2. The Battle of San Juan Hill (wd:Q3985806): 1913 film by Francis Ford
3. San Juan Hill order of battle (wd:Q7414586)
4. Battle of San Juan and Chorrillos, also known as Battle of Chorrillos, Battle of San Juan (wd:Q3772977): 1881 battle of the War of the Pacific
5. Battle of San Juan (wd:Q656046): 1797 battle
6. Battle of San Juan (wd:Q4872281): Spanish victory during the Anglo–Spanish War
7. Battle of San Juan (wd:Q4872279): 1625 battle in Puerto Rico
8. Battle of San Juan (wd:Q4872278): 1598 English force of 20 ships took San Juan from Spain for 65 days
9. Battle of San Juan Bautista (wd:Q4872282): 1864 battle
10. Second Battle of San Juan (wd:Q7443113): naval battle during the Spanish-American War (1898)

[Assistant] The entity "Battle of San Juan Hill" corresponds to wd:Q1215310. Now I will query the location (wdt:P276) of this battle.

[Tool]
Got 1 row and 2 columns:
| location                    | locationLabel      |
| --------------------------- | ------------------ |
| San Juan Hill (wd:Q7414587) | San Juan Hill (en) |

[Assistant] The Battle of San Juan Hill took place at the location "San Juan Hill" (wd:Q7414587). Now I will find the country where this location is situated. Typically, the property "country" (wdt:P17) is used for this. I will query the country of the location "San Juan Hill".

[Tool]
Got 1 row and 2 columns:
| country        | countryLabel |
| -------------- | ------------ |
| Cuba (wd:Q241) | Cuba (en)    |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly identifies the country where the Battle of San Juan Hill took place by using the location property (wdt:P276) of the battle and then retrieving the country (wdt:P17) of that location. The query also optionally retrieves the English label of the country. The result correctly returns Cuba as the country. The answer is accurate and the query follows best practices, including returning the actual identifier and label optionally. No further refinement is needed.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX p: <http://www.wikidata.org/prop/>
SELECT DISTINCT ?coach ?coachLabel WHERE {
  wd:Q330120 p:P286 ?statement .
  ?statement ps:P286 ?coach .
  OPTIONAL {
    ?coach rdfs:label ?coachLabel FILTER ( LANG( ?coachLabel ) = "en" )
  }
}
ORDER BY ?coachLabel

Got 8 rows and 2 columns:
| coach                       | coachLabel        |
| --------------------------- | ----------------- |
| Chris Tabor (wd:Q57242442)  | Chris Tabor (en)  |
| Dave Canales (wd:Q47456134) | Dave Canales (en) |
| Frank Reich (wd:Q5489177)   | Frank Reich (en)  |
| John Fox (wd:Q719030)       | John Fox (en)     |
| Matt Rhule (wd:Q14950994)   | Matt Rhule (en)   |
| Perry Fewell (wd:Q7169776)  | Perry Fewell (en) |
| Ron Rivera (wd:Q1991889)    | Ron Rivera (en)   |
| Steven Wilks (wd:Q7615391)  | Steven Wilks (en) |

The coaches who have coached the Carolina Panthers are Chris Tabor, Dave Canales, Frank Reich, John Fox, Matt Rhule, Perry Fewell, Ron Rivera, and Steven Wilks.

[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 has coached the carolina panthers?

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

[Tool]
Example 1:
Question:
who has coached the baltimore ravens?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q276539 wdt:P286 ?x .
}

Using entities:
Baltimore Ravens (wd:Q276539): National Football League franchise in Baltimore, Maryland

Using properties:
head coach, also known as team manager, trainer, senior coach, manager, coached by (wd:P286 as wdt): on-field manager or head coach of a sports club (not to be confu...eneral manager P505, which is not a coaching position) or person

Example 2:
Question:
who has coached the minnesota vikings?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q221150 wdt:P286 ?x .
}

Using entities:
Minnesota Vikings, also known as Vikings, Vikes (wd:Q221150): National Football League team

Using properties:
head coach, also known as team manager, trainer, senior coach, manager, coached by (wd:P286 as wdt): on-field manager or head coach of a sports club (not to be confu...eneral manager P505, which is not a coaching position) or person

Example 3:
Question:
what is the name of the pittsburgh steelers head coach?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q191477 wdt:P286 ?x .
}

Using entities:
Pittsburgh Steelers, also known as Pittsburgh Pirates, Rooneymen, Steelers (wd:Q191477): professional American football team based in Pittsburgh, Pennsylvania

Using properties:
head coach, also known as team manager, trainer, senior coach, manager, coached by (wd:P286 as wdt): on-field manager or head coach of a sports club (not to be confu...eneral manager P505, which is not a coaching position) or person

[Assistant] From the similar examples, it appears that the property "head coach" or "coached by" (wdt:P286) is used to indicate the coach of a sports team. The Carolina Panthers is likely represented by an entity in Wikidata. I will first search for the entity representing the Carolina Panthers.

[Tool]
Top 10 entity alternatives:
1. Carolina Panthers (wd:Q330120): American football team
2. history of the Carolina Panthers, also known as Carolina Panthers history, the Carolina Panthers history (wd:Q5869201): aspect of history
3. Carolina Panthers Cheerleaders (wd:Q130385213): cheerleading squad of the Carolina Panthers
4. 2021 Carolina Panthers season (wd:Q104869609): 27th season in franchise history
5. 2022 Carolina Panthers season (wd:Q110445399): 28th season in franchise history
6. 2020 Carolina Panthers season (wd:Q80995958): 26th season in franchise history
7. 2018 Carolina Panthers season (wd:Q48843395): 24th season in franchise history
8. 2015 Carolina Panthers season (wd:Q18701993): NFL team 21st season(lost Super Bowl)
9. 2019 Carolina Panthers season (wd:Q60525825): 25th season in franchise history
10. 2023 Carolina Panthers season (wd:Q116170055): 29th season in franchise history

[Assistant] The Carolina Panthers as an American football team is represented by the entity wd:Q330120. Based on the similar examples, the property for head coach or coached by is wdt:P286. I will now write a query to find all the coaches of the Carolina Panthers using this property.

[Tool]
Got 1 row and 2 columns:
| coach                       | coachLabel        |
| --------------------------- | ----------------- |
| Dave Canales (wd:Q47456134) | Dave Canales (en) |

[Assistant] The query returned only one coach, Dave Canales, who is likely the current coach. To get a comprehensive list of all coaches who have coached the Carolina Panthers, I will check if there is a property for former head coaches or if the property P286 has qualifiers indicating the time period. I will list the statements for the Carolina Panthers with property P286 to see if there are qualifiers.

[Tool]
Got 1 row and 3 columns:
| subject                        | property              | object                      |
| ------------------------------ | --------------------- | --------------------------- |
| Carolina Panthers (wd:Q330120) | head coach (wdt:P286) | Dave Canales (wd:Q47456134) |

[Assistant] The direct property wdt:P286 only shows the current head coach Dave Canales. I will now try to find statements (not direct properties) about the Carolina Panthers with property P286 to see if there are historical coaches with qualifiers.

[Tool]
Got 8 rows and 3 columns:
| subject                        | property            | object                                         |
| ------------------------------ | ------------------- | ---------------------------------------------- |
| Carolina Panthers (wd:Q330120) | head coach (p:P286) | s:Q330120-2f5b688c-4701-ae35-ef29-51ef69c9de92 |
| Carolina Panthers (wd:Q330120) | head coach (p:P286) | s:Q330120-48e97c3f-4363-828d-db0f-94a68ca39086 |
| Carolina Panthers (wd:Q330120) | head coach (p:P286) | s:Q330120-736700dd-49fa-7abe-2a02-a38de36334ad |
| Carolina Panthers (wd:Q330120) | head coach (p:P286) | s:Q330120-901db853-45eb-301d-3bb0-b14edb6a9c88 |
| Carolina Panthers (wd:Q330120) | head coach (p:P286) | s:Q330120-997ea6c1-4d3d-292e-addd-bbd89937d2c0 |
| Carolina Panthers (wd:Q330120) | head coach (p:P286) | s:Q330120-9f179107-47e5-69c1-ce60-3ecf15100852 |
| Carolina Panthers (wd:Q330120) | head coach (p:P286) | s:Q330120-c511c1f0-48ea-054e-a3bc-89f44d9ff9cc |
| Carolina Panthers (wd:Q330120) | head coach (p:P286) | s:Q330120-eb409d3a-4f10-6ae9-925d-a730cc610f68 |

[Assistant] There are 8 statements about the Carolina Panthers with property P286 (head coach). I will now retrieve the coaches from these statements along with their labels.

[Tool]
Got 8 rows and 2 columns:
| coach                       | coachLabel        |
| --------------------------- | ----------------- |
| Chris Tabor (wd:Q57242442)  | Chris Tabor (en)  |
| Dave Canales (wd:Q47456134) | Dave Canales (en) |
| Frank Reich (wd:Q5489177)   | Frank Reich (en)  |
| John Fox (wd:Q719030)       | John Fox (en)     |
| Matt Rhule (wd:Q14950994)   | Matt Rhule (en)   |
| Perry Fewell (wd:Q7169776)  | Perry Fewell (en) |
| Ron Rivera (wd:Q1991889)    | Ron Rivera (en)   |
| Steven Wilks (wd:Q7615391)  | Steven Wilks (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves all individuals who have coached the Carolina Panthers using the property 'head coach' (wd:P286). The query returns the identifiers and English labels of the coaches, which matches the user's question. The answer lists all coaches found in the query result, and the query is well-formed and complete. No further refinement is needed.


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:Q794 wdt:P37 ?language .
  OPTIONAL {
    ?language rdfs:label ?languageLabel FILTER ( LANG( ?languageLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| language           | languageLabel |
| ------------------ | ------------- |
| Persian (wd:Q9168) | Persian (en)  |

The language spoken in Iran is Persian.

[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 language do they speak in iran?

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

[Tool]
Example 1:
Question:
what do they speak in iran?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q794 wdt:P37 ?x .
}

Using entities:
Iran, also known as ir, IRI, IRN, Islamic Rep. Iran, Islamic Republic of Iran (wd:Q794): country in Western 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 language do people speak in iran?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q794 wdt:P37 ?x .
}

Using entities:
Iran, also known as ir, IRI, IRN, Islamic Rep. Iran, Islamic Republic of Iran (wd:Q794): country in Western 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 language do you speak in iran?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q794 wdt:P37 ?x .
}

Using entities:
Iran, also known as ir, IRI, IRN, Islamic Rep. Iran, Islamic Republic of Iran (wd:Q794): country in Western 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 property for the language spoken in a country is wdt:P37 (official language). The entity for Iran is wd:Q794. I will now write a SPARQL query to get the languages spoken in Iran using this property and entity.

[Tool]
Got 1 row and 2 columns:
| language           | languageLabel |
| ------------------ | ------------- |
| Persian (wd:Q9168) | Persian (en)  |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the official language spoken in Iran using the property wdt:P37 (official language). It returns the identifier and the English label for the language, which is Persian. The answer is accurate and complete for the user's question. 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 ?college ?collegeLabel WHERE {
  wd:Q134262 wdt:P69 ?college .
  ?college wdt:P31 / wdt:P279 * wd:Q38723 .
  OPTIONAL {
    ?college rdfs:label ?collegeLabel FILTER ( LANG( ?collegeLabel ) = "en" )
  }
}

Got 4 rows and 2 columns:
| college                                         | collegeLabel                            |
| ----------------------------------------------- | --------------------------------------- |
| University of Iowa (wd:Q182973)                 | University of Iowa (en)                 |
| University of Missouri (wd:Q579968)             | University of Missouri (en)             |
| The New School (wd:Q599316)                     | The New School (en)                     |
| Washington University in St. Louis (wd:Q777403) | Washington University in St. Louis (en) |

Tennessee Williams went to the University of Iowa, University of Missouri, The New School, and Washington University in St. Louis.

[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 did tennessee williams go to college?

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

[Tool]
Example 1:
Question:
where did tennessee williams live?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q134262 wdt:P551 ?x .
}

Using entities:
Tennessee Williams, also known as Thomas Lanier Williams III, Thomas Williams (wd:Q134262): American playwright (1911–1983), screenwriter, playwright, novelist, writer, poet

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

Example 2:
Question:
where did brian williams go to college?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q459695 wdt:P69 ?x .
  ?x wdt:P31 / wdt:P279 * wd:Q38723 .
}

Using entities:
higher education institution, also known as HEI, Higher Education school, institution of higher education, Superior Institute (wd:Q38723): institution that provides higher education (e.g., universities, ...es, liberal arts colleges, institutes of technology, and others)
Brian Williams (wd:Q459695): American TV news anchor, television presenter, editor-in-chief, news presenter, editing staff, journalist, blogger

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

Example 3:
Question:
where did buzz williams go to college?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q5003559 wdt:P69 ?x .
  ?x wdt:P31 / wdt:P279 * wd:Q38723 .
}

Using entities:
higher education institution, also known as HEI, Higher Education school, institution of higher education, Superior Institute (wd:Q38723): institution that provides higher education (e.g., universities, ...es, liberal arts colleges, institutes of technology, and others)
Buzz Williams (wd:Q5003559): American basketball coach, basketball coach

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] From the examples, the property "educated at" (wdt:P69) is used to find the college or higher education institution someone attended. The entity for Tennessee Williams is wd:Q134262. I will now write a query to find where Tennessee Williams went to college using this property.

[Tool]
Got 4 rows and 2 columns:
| college                                         | collegeLabel                            |
| ----------------------------------------------- | --------------------------------------- |
| University of Iowa (wd:Q182973)                 | University of Iowa (en)                 |
| University of Missouri (wd:Q579968)             | University of Missouri (en)             |
| The New School (wd:Q599316)                     | The New School (en)                     |
| Washington University in St. Louis (wd:Q777403) | Washington University in St. Louis (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves all higher education institutions where Tennessee Williams studied, using the property 'educated at' (wdt:P69) and filtering for institutions that are subclasses of higher education institutions (wd:Q38723). The answer lists all four institutions found in the query result, which matches the user's question about where Tennessee Williams went to college. The query also includes English labels for readability, which is helpful. The output is correct and complete.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?coordinate WHERE {
  wd:Q8321 wdt:P625 ?coordinate .
}

The Illinois River (wd:Q8321) is located in Illinois (wd:Q1204). Its coordinates on the map are approximately POINT(-90.454200 38.970300) and POINT(-88.260300 41.393600), which represent points along the river.

[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 is the illinois river on a map?

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

[Tool]
Example 1:
Question:
what are the biggest cities in illinois?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P31 / wdt:P279 * wd:Q515 ; wdt:P131 + wd:Q1204 ; wdt:P1082 ?y .
}
ORDER BY DESC ( ?y )
LIMIT 1

Using entities:
Illinois, also known as The Prairie State, Illinois, United States, The Land of Lincoln, US-IL, Prairie State (wd:Q1204): state of the United States of America
city, also known as cities (wd:Q515): large human settlement

Using properties:
population, also known as inhabitants, human population (wd:P1082 as wdt): number of people inhabiting the place; number of people of subject
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)

Example 2:
Question:
where's the hudson river?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q3140 wdt:P131 ?x .
}

Using entities:
Hudson River, also known as Hudson (wd:Q3140): river in New York State, United States

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

Example 3:
Question:
what states does the missouri river touch?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q5419 wdt:P131 + ?x .
  ?x wdt:P31 / wdt:P279 * wd:Q107390 .
}

Using entities:
federated state, also known as state in a federation, state of a federation, state, federal state, constituent state (wd:Q107390): territorial and constitutional community forming part of a federal union
Missouri River, also known as Missouri, The Missouri (wd:Q5419): major river in central United States

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]
From the examples, it is clear that the Illinois River is an entity we need to identify first. Then we can look for its location or the administrative territorial entity it is located in. This will help us understand where the Illinois River is on a map.

Step 1: Search for the Illinois River entity in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Illinois River (wd:Q8321): Illinois tributary of the Mississippi River in the United States
2. Illinois River (wd:Q1309881): tributary of the Rogue River in Curry and Josephine counties in Oregon, United States
3. Illinois River (wd:Q5999628): Colorado tributary of the Michigan River
4. Illinois River (wd:Q5999623): river in Arkansas and Oklahoma
5. Chicago River, also known as Chicago river, Chicago (river, Illinois), Chicago River main stem, Chicago River (United States) (wd:Q643284): river in Chicago, Illinois, United States
6. Wood River, also known as Wood River, IL, Wood River (Illinois), Wood River, Illinois (wd:Q185601): city in Illinois, United States
7. River Forest, also known as River Forest, IL, River Forest, Illinois (wd:Q2299339): village in Cook County, Illinois, United States
8. River Grove, also known as River Grove, IL, River Grove, Illinois (wd:Q783421): village in Cook County, Illinois, United States of America
9. Apple River, also known as Apple River, Illinois (wd:Q621346): human settlement in Illinois, United States of America
10. Riverside, also known as Riverside, Illinois, Riverside IL, Riverside, IL (wd:Q2462183): village in Cook County, Illinois, United States

[Assistant]
The Illinois River we are interested in is most likely the first entity: Illinois River (wd:Q8321), which is an Illinois tributary of the Mississippi River in the United States.

Step 2: Now, let's find the location or the administrative territorial entity where this Illinois River (wd:Q8321) is located. This will help us understand where it is on a map.

[Tool]
Got 1 row and 2 columns:
| location            | locationLabel |
| ------------------- | ------------- |
| Illinois (wd:Q1204) | Illinois (en) |

[Assistant] The Illinois River (wd:Q8321) is located in Illinois (wd:Q1204). To provide a more complete answer, I can also retrieve the coordinates of the Illinois River to indicate its position on a map.

[Tool]
Got 2 rows and 1 column:
| coordinate                                   |
| -------------------------------------------- |
| POINT(-90.454200 38.970300) (geo:wktLiteral) |
| POINT(-88.260300 41.393600) (geo:wktLiteral) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The system correctly identified the Illinois River (wd:Q8321) and retrieved its geocoordinates using the property wdt:P625. The SPARQL query is appropriate and returns the coordinates as POINT literals, which represent locations on a map. The answer clearly states the river's location in Illinois and provides the coordinates found. This output is correct and complete for the user's question about where the Illinois River is on a map.