PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ( COUNT( DISTINCT ?occupation ) AS ?count ) WHERE {
  wd:Q7245 wdt:P106 ?occupation .
}

Got 1 row and 1 column:
| count        |
| ------------ |
| 12 (xsd:int) |

Mark Twain had 12 distinct occupations according to Wikidata.

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

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

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

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

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

[User] How many occupations did Mark Twain have?

[Assistant]
To answer the question "How many occupations did Mark Twain have?", I need to:

1. Identify the entity for Mark Twain in Wikidata.
2. Find the property that represents "occupation" for this entity.
3. Count the number of distinct occupations associated with Mark Twain.

Step 1: Search for the entity "Mark Twain" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Mark Twain, also known as Samuel L. Clemens, Samuel Langhorne Clemens, Quintus Curtius Snodgrass, Samuel Clemens (wd:Q7245): American author and humorist (1835–1910), science fiction writer, opinion journalist, children's writer, autobiographer, travel writer, prose writer, journalist, humorist, novelist, aphorist, teacher, writer
2. 2362 Mark Twain, also known as Mark Twain (wd:Q959983): asteroid
3. Mark Twain (wd:Q6770075): crater on Mercury
4. Mark Twain (wd:Q6770076): 2001 documentary film on the life of Mark Twain directed by Ken Burns
5. Mark Twain (wd:Q66716403): 1873 article in Cartoon portraits and biographical sketches of men of the day
6. Mark Twain, also known as Mark Twain, St. Louis (wd:Q6770071): neighborhood of St. Louis, Missouri, United States
7. Rosa 'Mark Twain', also known as Mark Twain (wd:Q83668756): rose cultivar
8. Mark Twain (wd:Q116958637): bronze sculpture by unidentified artist
9. Mark Twain (wd:Q20174185): painting by Charles Noel Flagg
10. Mark Twain (wd:Q79493007): print by Samuel Johnson Woolf (American, 1880-1948) (1920.11)

[Assistant] The entity for Mark Twain in Wikidata is wd:Q7245. Next, I will find the occupations (property) associated with Mark Twain (wd:Q7245). The property for occupation in Wikidata is usually P106. I will list the occupations of Mark Twain using this property.

[Tool]
Got 12 rows and 2 columns, showing the first 5 and last 5 rows below:
| occupation                            | occupationLabel             |
| ------------------------------------- | --------------------------- |
| prose writer (wd:Q12144794)           | prose writer (en)           |
| humorist (wd:Q12406482)               | humorist (en)               |
| autobiographer (wd:Q18814623)         | autobiographer (en)         |
| science fiction writer (wd:Q18844224) | science fiction writer (en) |
| journalist (wd:Q1930187)              | journalist (en)             |
| ...                                   | ...                         |
| writer (wd:Q36180)                    | writer (en)                 |
| teacher (wd:Q37226)                   | teacher (en)                |
| children's writer (wd:Q4853732)       | children's writer (en)      |
| opinion journalist (wd:Q6051619)      | opinion journalist (en)     |
| novelist (wd:Q6625963)                | novelist (en)               |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly counts the distinct occupations of Mark Twain using the occupation property (wdt:P106). The query returns the count as 12, which matches the answer provided. The query is well-formed, uses the correct entity (wd:Q7245 for Mark Twain), and the property for occupation. The answer is clear and concise. No further refinement is needed.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?placeOfBirth ?placeOfBirthLabel WHERE {
  wd:Q79904 wdt:P19 ?placeOfBirth .
  OPTIONAL {
    ?placeOfBirth rdfs:label ?placeOfBirthLabel FILTER ( LANG( ?placeOfBirthLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| placeOfBirth           | placeOfBirthLabel  |
| ---------------------- | ------------------ |
| New York City (wd:Q60) | New York City (en) |

The author of The Catcher in the Rye, J. D. Salinger, was born in New York City.

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

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

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

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

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

[User] Where was the author of The Catcher in the Rye born ?

[Assistant]
Step 1: Identify the entity "The Catcher in the Rye" to find its author.
I will search for the entity "The Catcher in the Rye" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. The Catcher in the Rye, also known as Catcher in the Rye (wd:Q183883): 1951 novel by J. D. Salinger
2. Catcher in the Rye (wd:Q5051738): Chinese punk rock band
3. Catcher In the Rye (wd:Q16184712): 2011 EP by Datarock
4. Catcher in the Rye (wd:Q110065569): 2021 single by Ross Jennings
5. Catcher in the Rye (wd:Q10443835): song by Guns N' Roses
6. The Catcher in the Rye (wd:Q16689546): 2012 debut studio album by Ann
7. The Catcher in the Rye (wd:Q125291968): 2001 Back Bay edition
8. Catchers in the rye (wd:Q68693473): scientific article published on 01 January 1990
9. The Catcher in the Rye in popular culture (wd:Q7721703): Influence of J.D. Salinger's 1951 novel
10. The Catcher in the Rye in popular culture (wd:Q7721703): Influence of J.D. Salinger's 1951 novel

[Assistant]
The entity "The Catcher in the Rye" as a 1951 novel by J. D. Salinger is identified as wd:Q183883.

Step 2: Find the author of "The Catcher in the Rye" (wd:Q183883).
I will query the author property of this entity.

[Tool]
Got 1 row and 2 columns:
| author                     | authorLabel         |
| -------------------------- | ------------------- |
| J. D. Salinger (wd:Q79904) | J. D. Salinger (en) |

[Assistant]
The author of "The Catcher in the Rye" is J. D. Salinger (wd:Q79904).

Step 3: Find the place of birth of J. D. Salinger (wd:Q79904).
I will query the place of birth property for this author.

[Tool]
Got 1 row and 2 columns:
| placeOfBirth           | placeOfBirthLabel  |
| ---------------------- | ------------------ |
| New York City (wd:Q60) | New York City (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the place of birth of J. D. Salinger, the author of The Catcher in the Rye, from Wikidata. The query uses the appropriate entity (wd:Q79904) and property (wdt:P19) to get the birthplace, and it also optionally fetches the English label for readability. The answer provided is accurate and complete, matching the query result. No further refinement is necessary.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?inception ?endTime WHERE {
  wd:Q1361648 wdt:P571 ?inception .
  OPTIONAL {
    wd:Q1361648 wdt:P582 ?endTime
  }
}

The company Allegheny Technologies (ATI) has an inception date of January 1, 1996, and there is no end time or dissolution date recorded. This indicates that the ATI company still exists.

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

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

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

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

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

[User] Does the ATI Company still exist?

[Assistant] To answer this question, I first need to identify the entity corresponding to "ATI Company" in Wikidata. I will search for entities related to "ATI Company" to find the correct entity representing this company.

[Tool]
Top 10 entity alternatives:
1. company, also known as co., firm (wd:Q783794): legal entity representing an association of people, whether natural, legal or a mixture of both, with a specific objective
2. company, also known as company (military unit), military company (wd:Q102538): military unit size designation
3. enterprise, also known as business enterprise, firm, company (wd:Q6881511): organizational unit producing goods or services, which benefits ...n-making, especially for the allocation of its current resources
4. Ati (wd:Q755791): city
5. Aashaadha, also known as Ashadha, Āṭi (wd:Q1105198): month in Hindu calender
6. Artigas Airport, also known as ATI, SUAG (wd:Q1430852): airport
7. Company (wd:Q225093): 2002 film directed by Ram Gopal Varma
8. Company (wd:Q2915810): 1970 musical comedy by Stephen Sondheim
9. Company (wd:Q23723998): 2016 single by Justin Bieber
10. Ati, also known as Ati language, Ati (Philippines) (wd:Q3217458): Malayo-Polynesian language spoken and native to the Ati people of Panay

[Assistant] The search for "ATI Company" did not directly return a specific company entity named "ATI Company." It returned general entities related to companies and other unrelated entities. To refine the search, I will try searching for "ATI" as a company or organization to see if there is a specific company entity with the name "ATI."

[Tool]
Top 10 entity alternatives:
1. company, also known as co., firm (wd:Q783794): legal entity representing an association of people, whether natural, legal or a mixture of both, with a specific objective
2. company, also known as company (military unit), military company (wd:Q102538): military unit size designation
3. enterprise, also known as business enterprise, firm, company (wd:Q6881511): organizational unit producing goods or services, which benefits ...n-making, especially for the allocation of its current resources
4. Ati (wd:Q755791): city
5. Aashaadha, also known as Ashadha, Āṭi (wd:Q1105198): month in Hindu calender
6. Artigas Airport, also known as ATI, SUAG (wd:Q1430852): airport
7. Company (wd:Q225093): 2002 film directed by Ram Gopal Varma
8. Company (wd:Q2915810): 1970 musical comedy by Stephen Sondheim
9. Company (wd:Q23723998): 2016 single by Justin Bieber
10. Ati, also known as Ati language, Ati (Philippines) (wd:Q3217458): Malayo-Polynesian language spoken and native to the Ati people of Panay

[Assistant]
The search for "ATI company" still did not return a specific company entity named "ATI Company." It seems that the exact entity for "ATI Company" is not directly found in the search results.

To proceed, I will try a broader search for "ATI" to see if there is a company or organization with that name or abbreviation.

[Tool]
Top 10 entity alternatives:
1. Ati (wd:Q755791): city
2. Aashaadha, also known as Ashadha, Āṭi (wd:Q1105198): month in Hindu calender
3. Artigas Airport, also known as ATI, SUAG (wd:Q1430852): airport
4. Ati, also known as Ati language, Ati (Philippines) (wd:Q3217458): Malayo-Polynesian language spoken and native to the Ati people of Panay
5. The Alan Turing Institute, also known as Turing Institute, turing.ac.uk, ATI (wd:Q16826821): research institute in Britain
6. Boneh-ye Ati, also known as Boneh-ye ‘Āţī, ‘Āţī (wd:Q4941616): village in Iran
7. Allegheny Technologies, also known as Allegheny Technologies Incorporated, ATI, ATI Metals (wd:Q1361648): company
8. Computer Engineers Association of Spain, also known as ATI (wd:Q5709317): Spanish non-profit association
9. Aati, also known as Ati (wd:Q106432253): Ancient Egyptian judge of the dead
10. Ati (wd:Q32289862): river in Uganda

[Assistant]
Among the search results for "ATI," I found "Allegheny Technologies," also known as ATI, ATI Metals (wd:Q1361648), which is a company. This seems to be the most relevant entity for "ATI Company."

Next, I will check if this company still exists. To do this, I will look for a property related to the company's existence or dissolution status. Typically, the property "dissolved, abolished or demolished date" (P576) can indicate if a company no longer exists. If this property is absent, it may imply the company still exists.

I will query if the company Allegheny Technologies (wd:Q1361648) has a dissolution date.

[Tool] Got no rows and 1 columns

[Assistant]
The company Allegheny Technologies (ATI) does not have a dissolution date property in Wikidata, which suggests that it has not been marked as dissolved or abolished.

To further confirm if the company still exists, I will check if it has a "inception" date (P571) and no "end time" (P582) for its existence. This can help confirm it is still active.

I will query for the inception date and any end time for the company Allegheny Technologies (wd:Q1361648).

[Tool]
Got 1 row and 2 columns:
| inception                           | endTime |
| ----------------------------------- | ------- |
| 1996-01-01T00:00:00Z (xsd:dateTime) |         |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the inception date and checks for an end time (dissolution date) of the ATI company (Allegheny Technologies). Since there is no end time recorded, the conclusion that the company still exists is valid. The query follows best practices by returning the actual identifiers and optional properties. The answer is complete and accurate based on the data retrieved from Wikidata.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?instrument ?instrumentLabel WHERE {
  wd:Q1779 wdt:P1303 ?instrument .
  OPTIONAL {
    ?instrument rdfs:label ?instrumentLabel FILTER ( LANG( ?instrumentLabel ) = "en" )
  }
}

Got 3 rows and 2 columns:
| instrument           | instrumentLabel |
| -------------------- | --------------- |
| voice (wd:Q17172850) | voice (en)      |
| cornet (wd:Q202027)  | cornet (en)     |
| trumpet (wd:Q8338)   | trumpet (en)    |

Louis Armstrong played the following instruments: voice, cornet, and trumpet.

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

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

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

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

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

[User] What instruments did Louis Armstrong play?

[Assistant] To answer the question about which instruments Louis Armstrong played, I will first search for the entity "Louis Armstrong" in Wikidata to get his identifier. Then, I will look for properties related to musical instruments played by him.

[Tool]
Top 10 entity alternatives:
1. Louis Armstrong, also known as Satchelmouth, Satch, Satchmo, Louis Daniel Armstrong, Dipper (wd:Q1779): American jazz musician, trumpeter and singer (1901–1971), film score composer, radio personality, recording artist, jazz musician, street artist, film actor, songwriter, bandleader, trumpeter, conductor, writer, singer, actor
2. Louis Armstrong (wd:Q98823980): photograph by Lisette Model (MET, 2019.33)
3. Louis Armstrong (wd:Q132754304): online exhibition from Louis Armstrong House and Archives, Queens College, City University of New York
4. Louis Armstrong (wd:Q100721665): college basketball player (1991–1992) Northern Iowa, basketball player
5. Louis Armstrong Stadium (wd:Q1029132): tennis venue in New York City from 1978 to 2016
6. Louis Armstrong Park (wd:Q931042): park in New Orleans, Louisiana, U.S.
7. Louis Armstrong House, also known as Louis Armstrong House Museum (wd:Q6686652): NY location listed on National Register of Historic Places
8. Louise Armstrong (wd:Q6688616): American writer and feminist, human rights activist, children's writer, writer
9. Louis Armstrong Stadium (wd:Q47487977): tennis stadium opened in 2018, replacing a 1978 venue of the same name
10. Louis Armstrong Jazzfesztivál (wd:Q65218436)

[Assistant] The entity for Louis Armstrong as an American jazz musician is wd:Q1779. Next, I will search for properties related to the instruments he played. I will look for properties related to "instrument" or "musical instrument" for this entity.

[Tool]
Top 10 property alternatives:
1. instrument, also known as uses this instrument, teaches instrument, instruments, plays this instrument, plays instrument (wd:P1303 as p/wdt): musical instrument that a person plays or teaches or used in a music occupation, uses
2. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as p/wdt): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
3. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
4. voice type, also known as range of voice, register, tessitura, type of voice, vocal type (wd:P412 as p/wdt): person's voice type. expected values: soprano, mezzo-soprano, contralto, countertenor, tenor, baritone, bass (and derivatives)
5. member of, also known as band member of, membership, member of musical group, in musical group, be member of (wd:P463 as p/wdt): organization, club or musical group to which the subject belongs...ical position, such as a member of parliament (use P39 for that), part of
6. Pitchfork artist ID, also known as Pitchfork, Pitchfork ID (wd:P8819 as p/wdt): identifier for musical artists on the Pitchfork website
7. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as p/wdt): the object is a country that recognizes the subject as its citizen, country
8. signature, also known as signature image, image of signature, facsimiles, autograph (wd:P109 as p/wdt): image of a person's signature, image
9. occupation, also known as job, work, vocation, profession, employment (wd:P106 as p/wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
10. part of, also known as of, within, system of, subsystem of, subgroup of (wd:P361 as p/wdt): object of which the subject is a part (if this subject is alread... of "has part" (P527, see also "has parts of the class" (P2670))

No other items found

[Assistant] The property "instrument" (wdt:P1303) is the relevant property that indicates the musical instrument a person plays. I will now query which instruments Louis Armstrong (wd:Q1779) played using this property.

[Tool]
Got 3 rows and 2 columns:
| instrument           | instrumentLabel |
| -------------------- | --------------- |
| voice (wd:Q17172850) | voice (en)      |
| cornet (wd:Q202027)  | cornet (en)     |
| trumpet (wd:Q8338)   | trumpet (en)    |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the instruments Louis Armstrong played using the property P1303 (instrument). The results include voice, cornet, and trumpet, which matches the known information about him. The query also optionally retrieves English labels for the instruments, which is helpful for readability. The answer is complete and accurate based on the data from Wikidata. No further refinement is necessary.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ( COUNT( DISTINCT ?scale ) AS ?count ) WHERE {
  ?scale wdt:P279 wd:Q179651 .
}

Got 1 row and 1 column:
| count        |
| ------------ |
| 26 (xsd:int) |

There are 26 distinct types of musical scales recorded in Wikidata.

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

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

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

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

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

[User] How many musical scales are there?

[Assistant]
To answer the question "How many musical scales are there?" I need to clarify what is meant by "musical scales." Typically, in music theory, a musical scale is a set of musical notes ordered by pitch. There are many types of scales, such as major scales, minor scales, pentatonic scales, chromatic scales, and various modes.

I will start by searching for the entity "musical scale" in Wikidata to understand how it is represented and if there is a property or classification that enumerates different musical scales. Then, I will try to find how many instances or subclasses of musical scales exist in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. scale, also known as gamut, musical scale (wd:Q179651): set of musical notes ordered by pitch
2. musical scale (wd:L490906-S1)
3. Japanese musical scale (wd:Q1683319): Scales used in Japanese traditional music
4. minor scale; musical scale (wd:L739761-S2)
5. A Perfect Musical Scale (wd:Q60136008): scientific article published in Nature
6. Synthetic Musical Scales (wd:Q58123356)
7. type of musical scale (wd:L640378-S8)
8. MUSICAL INTELLIGENCE AND SCALE PREFERENCE. (wd:Q30335517): scientific article
9. sixth note in musical scale (wd:L739149-S1)
10. sixth note of musical scale (wd:L1405299-S1)

[Assistant]
The entity "scale" also known as "musical scale" is represented by wd:Q179651 in Wikidata. This entity corresponds to the concept of a set of musical notes ordered by pitch.

Next, I will check if there are subclasses or instances of this entity that represent different types of musical scales. This will help to determine how many musical scales are recorded in Wikidata.

[Tool]
Got 1 row and 1 column:
| count        |
| ------------ |
| 26 (xsd:int) |

[Assistant]
There are 26 distinct subclasses of the musical scale (wd:Q179651) recorded in Wikidata. This gives us a count of different types of musical scales as classified in the knowledge graph.

I will now provide the final answer with this information.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly counts the number of distinct musical scales (items that are subclasses of the musical scale class Q179651) in Wikidata. The query returns 26, which matches the provided answer. The query follows the rules by returning the actual identifiers (count of scales) and uses the appropriate property (wdt:P279) to find subclasses. No further refinement is necessary.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?gender ?genderLabel WHERE {
  wd:Q1983102 wdt:P21 ?gender .
  OPTIONAL {
    ?gender rdfs:label ?genderLabel FILTER ( LANG( ?genderLabel ) = "en" )
  }
}

The binary gender of the partner of Allen Ginsberg, Peter Orlovsky, is male.

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

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

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

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

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

[User] What is the binary gender of the partner of Allen Ginsberg ?

[Assistant]
To answer the question "What is the binary gender of the partner of Allen Ginsberg?", I will follow these steps:

1. Identify the entity for Allen Ginsberg in Wikidata.
2. Identify the property for "partner" or equivalent in Wikidata.
3. Retrieve the partner(s) of Allen Ginsberg.
4. Identify the property for "binary gender" or "sex or gender" in Wikidata.
5. Retrieve the binary gender of the partner(s) of Allen Ginsberg.

First, I will search for the entity "Allen Ginsberg" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Allen Ginsberg, also known as Irwin Allen Ginsberg (wd:Q6711): American poet and writer (1926–1997), autobiographer, photographer, screenwriter, playwright, musician, diarist, teacher, writer, poet
2. Allen Ginsberg (wd:Q102249265): Ph.D. Rutgers University, New Brunswick 1986
3. Allen Ginsberg Library (wd:Q117833470): this entity is a library in the state of colorado. it was identified and verified by the chr task force
4. Untitled (Allen Ginsberg) (wd:Q76558858): print in the National Gallery of Art (NGA 155538)
5. Allen Ginsberg no number (wd:Q64163104): photograph in the National Gallery of Art (NGA 88333)
6. Allen Ginsberg no number (wd:Q64163625): photograph in the National Gallery of Art (NGA 88331)
7. Allen Ginsberg no number (wd:Q64163102): photograph in the National Gallery of Art (NGA 88336)
8. Allen Ginsberg no number (wd:Q64163079): photograph in the National Gallery of Art (NGA 88334)
9. Allen Ginsberg no number (wd:Q64162725): photograph in the National Gallery of Art (NGA 88330)
10. Allen Ginsberg no number (wd:Q64162264): photograph in the National Gallery of Art (NGA 88332)

[Assistant] The entity for Allen Ginsberg is wd:Q6711. Next, I will search for the property that represents "partner" in Wikidata.

[Tool]
Top 10 property alternatives:
1. unmarried partner, also known as romantic partner, partner of, partners, posslq, relationship (wd:P451 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): someone with whom the person is in a relationship without being married. Use "spouse" (P26) for married couples, significant person
2. spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative
3. partner in business or sport, also known as professional partner, sport partner, sports partner, team mate, team-mate (wd:P1327 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): professional collaborator, significant person
4. partnership with, also known as works with, collaborates with, collaboration with (wd:P2652 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): partnership (commercial or/and non-commercial) between this organization and another organization or institution
5. twinned administrative body, also known as twin cities, twin town, twin city, sister town, sister city (wd:P190 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): twin towns, sister cities, twinned municipalities and other loca..., either legally or informally acknowledged by their governments
6. contributor to the creative work or subject, also known as assistant, collaborator, contributor, contributor(s) to the subject, creative contributor (wd:P767 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): person or organization that contributed to a subject: co-creator of a creative work or subject, participant
7. funder, also known as benefactor, sponsored by, sponsor, has funder, has donor (wd:P8324 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): entity that gives money to a person, organization, or project for a specific purpose, sponsor
8. sponsor, also known as benefactor, endorsed by, patron, sponsored by (wd:P859 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): organization or individual that sponsors this item
9. commissioned by, also known as client, orderer, made for, commissioner, built for (wd:P88 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): person or organization that commissioned this work
10. companion of, also known as has astronomical companion, has companion, companion, astronomic companion of, astronomic companion (wd:P399 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): two or more astronomic bodies of the same type relating to each other

[Assistant]
The property for "partner" is wd:P451 (unmarried partner) and wd:P26 (spouse) for married partner. Since the question is about the partner of Allen Ginsberg, I will check both properties to cover all possibilities.

Next, I will retrieve the partner(s) of Allen Ginsberg using these properties.

[Tool]
Got 1 row and 1 column:
| partner                      |
| ---------------------------- |
| Peter Orlovsky (wd:Q1983102) |

[Assistant] Allen Ginsberg's partner is Peter Orlovsky (wd:Q1983102). Now, I will search for the property that represents "binary gender" or "sex or gender" in Wikidata.

[Tool]
Top 10 property alternatives:
1. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)
2. grammatical gender, also known as gender (wd:P5185 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): grammatical gender of the word
3. requires grammatical feature, also known as grammatical feature required, required grammatical feature, requires case, requires mood, uses case (wd:P5713 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): grammatical features required or generally used with lexeme or form of lexeme
4. has grammatical gender, also known as grammatical genders, has genders (wd:P5109 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): specific form of noun class system of a language. Use qualifier ... subject of" (P805) to link to language specific item if present
5. personal pronoun, also known as gender pronoun, personal gender pronoun, personal pronouns, PGP, PGPs (wd:P6553 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): personal pronoun(s) this person goes by
6. semantic gender, also known as natural gender (wd:P10339 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): used when a word is only used to refer to people of this gender or to animals of this sex, independent of the grammatical gender
7. sexual orientation, also known as sexuality (wd:P91 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): the sexual orientation of the person relative to their declared ...r it has been widely agreed upon by historians after their death
8. female form of label, also known as female form of label (string), female gender sense, feminine form of label (wd:P2521 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): female form of name or title (for male use P3321)
9. male form of label, also known as male form of label (string), male gender sense, masculine form of label (wd:P3321 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): male form of name or title (for female use P2521)
10. GSSO ID, also known as Gender, Sex, and Sexual Orientation Ontology ID, GSSO identifier, Gender, Sex, and Sexual Orientation Ontology identifier (wd:P9827 as pqn/ps/psv/p/pq/psn/prv/prn/pqv/pr/wdtn/wdt): identifier for controlled vocabulary in the GSSO (Gender, Sex, and Sexual Orientation) ontology

[Assistant] The property for "sex or gender" is wd:P21. Now, I will retrieve the binary gender of Peter Orlovsky using this property.

[Tool]
Got 1 row and 2 columns:
| gender             | genderLabel |
| ------------------ | ----------- |
| male (wd:Q6581097) | male (en)   |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The system correctly identified the partner of Allen Ginsberg as Peter Orlovsky and retrieved his binary gender using the property 'sex or gender' (wdt:P21). The SPARQL query is appropriate and returns the correct gender entity and label. The answer is accurate and complete, providing the binary gender as male. No further refinement is necessary.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?member ?memberLabel ?birthDate WHERE {
  wd:Q51885404 wdt:P527 ?member .
  ?member wdt:P569 ?birthDate .
  OPTIONAL {
    ?member rdfs:label ?memberLabel FILTER ( LANG( ?memberLabel ) = "en" )
  }
}
ORDER BY DESC ( ?birthDate )
LIMIT 1

The youngest member of (G)I-DLE is Shuhua, born on January 6, 2000.

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

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

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

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

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

[User] who is the youngested member in g-idle?

[Assistant] To answer the question "Who is the youngest member in (G)I-DLE?", I will first search for the entity representing the music group "(G)I-DLE" in Wikidata. Then, I will find the members of this group and their birth dates to determine the youngest member.

[Tool]
Top 10 entity alternatives:
1. (G)I-dle, also known as (G)I-DLE (wd:Q51885404): South Korean girl group
2. (G)I-DLE: I-TALK, also known as I-Talk (wd:Q98844809): original program made by Cube Entertainment, showing behind-the-scenes footage of MVs as series
3. Hwaa, also known as Hwaa ((G)I-dle song), Hwaa (song) (wd:Q104600483): 2021 single by (G)I-dle
4. Moon, also known as Moon ((G)I-dle song), Moon (G-Idle song) (wd:Q104969991): 2021 single by (G)I-dle
5. Last Dance, also known as Last Dance ((G)I-dle song), Last Dance (G-Idle song) (wd:Q106584541): song written and composed by Kriz and Soyeon, adapted by GroovyRoom; recorded 2021 by (G)I-dle
6. I-Land: Who Am I, also known as 2020 (G)I-dle Online Concert 'I-Land: Who Am I' (wd:Q96381600): 2020 (G)I-dle online concert
7. (G)I-dle Just Me ( )I-dle in Seoul, June 2022 (wd:Q124058812)
8. (G)I-dle Just Me ( )I-dle in Monterrey, 14 August 2022 (wd:Q124058808)
9. (G)I-dle at 2020 Tainan Christmas & New Year Eve Party (wd:Q124058809)
10. (G)I-dle Just Me ( )I-dle in San Francisco, 24 July 2022 (wd:Q124058817)

[Assistant] The entity for the South Korean girl group (G)I-DLE is wd:Q51885404. Next, I will find the members of this group and their birth dates to determine the youngest member.

[Tool]
SPARQL execution failed:
Error while executing a SERVICE request to <http://wikiba.se:80/ontology#label>: SERVICE responded with HTTP status code: 301, Moved Permanently. First 100 bytes of the response: '<html>
<head><title>301 Moved Permanently</title></head>
<body>
<center><h1>301 Moved Permanently'

[Assistant] The query failed due to the use of the SERVICE wikibase:label which is not supported by the endpoint. I will rewrite the query without using SERVICE wikibase:label and instead use optional rdfs:label to get the member's label.

[Tool]
Got 1 row and 3 columns:
| member                | memberLabel | birthDate                           |
| --------------------- | ----------- | ----------------------------------- |
| Shuhua (wd:Q55287305) | Shuhua (en) | 2000-01-06T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves all members of (G)I-DLE along with their birth dates, orders them by birth date in descending order, and limits the result to the youngest member. The answer identifies Shuhua as the youngest member with the correct birth date. The query and answer are accurate and complete for the user's question.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?author ?authorLabel WHERE {
  wd:Q3521239 wdt:P50 ?author .
  OPTIONAL {
    ?author rdfs:label ?authorLabel FILTER ( LANG( ?authorLabel ) = "en" )
  }
}

The author of The Hellbound Heart is Clive Barker.

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

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

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

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

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

[User] Who's the author of The Hellbound Heart ?

[Assistant] First, I will search for the entity "The Hellbound Heart" in Wikidata to identify its unique identifier. This will help me to find the author of this work.

[Tool]
Top 10 entity alternatives:
1. The Hellbound Heart (wd:Q3521239): novella by Clive Barker
2. The Hellbound Heart (wd:Q131862610): 2008 HarperVoyager edition
3. Holiday Peak, also known as The Heart (wd:Q5880456): mountain in the Antarctic
4. The Heart, also known as Heart, Kokoro (wd:Q19567789): 1955 Japanese film directed by Kon Ichikawa
5. Das Herz, also known as The Heart (wd:Q49139357): opera by Hans Pfitzner
6. The Heart (wd:Q110895729): film by Kaneto Shindo
7. The Heart (wd:Q124421885): work by Hippocrates
8. The Heart, also known as Hjärtat (wd:Q10524935): 1987 film
9. The Heart, also known as Srdce (wd:Q12055804): opera by Josef Bohuslav Foerster
10. The Heart, also known as Hjärtat (wd:Q61672477): 2018 film

[Assistant] I found the entity "The Hellbound Heart" as a novella by Clive Barker with the identifier wd:Q3521239. Now I will query for the author of this novella.

[Tool]
Got 1 row and 2 columns:
| author                    | authorLabel       |
| ------------------------- | ----------------- |
| Clive Barker (wd:Q298761) | Clive Barker (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the author of 'The Hellbound Heart' using the property wdt:P50 (author). It returns both the author's identifier and English label, which is appropriate. The answer 'Clive Barker' matches the expected author of the novella. The query is well-formed and the result is accurate and complete. No further refinement is needed.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?manufacturer ?manufacturerLabel WHERE {
  wd:Q388973 wdt:P176 ?manufacturer .
  OPTIONAL {
    ?manufacturer rdfs:label ?manufacturerLabel FILTER ( LANG( ?manufacturerLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| manufacturer        | manufacturerLabel |
| ------------------- | ----------------- |
| Nestlé (wd:Q160746) | Nestlé (en)       |

After Eight is manufactured by Nestlé, not Unilever. So the answer is No.

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

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

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

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

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

[User] Is After Eight manufactured by Unilever?

[Assistant]
To answer the question "Is After Eight manufactured by Unilever?", I need to identify the entity for "After Eight" and check its manufacturer property to see if it is Unilever.

Step 1: Search for the entity "After Eight" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. After Eight, also known as After Eight mint chocolate (wd:Q388973): chocolate brand of Nestle
2. Polar Bear, also known as After Eight, Peppermint Paddy (wd:Q7209010): mint chocolate cocktail
3. After Eight (wd:Q60786577): 1982 debut studio album by Taco
4. Dahlia 'Twyning's After Eight', also known as Twyning's After Eight (wd:Q83544826): Dahlia cultivar
5. 8 Man After, also known as Eightman After (wd:Q115948406): 1993 original video animation series
6. DeltaD, also known as after eight protein, delta-like protein D, dld, aei (wd:Q29825141): protein found in Danio rerio
7. Quarter After Eight (wd:Q15762559): journal
8. Twelve after Eight (wd:Q131628059): journal article from 'Journal of Medical Humanities' published in 2015
9. Chernobyl: eight years after (wd:Q56608399): scientific article published on 01 October 1994
10. After Eighty Study (wd:Q63818230): clinical trial

[Assistant] The entity "After Eight" that refers to the chocolate brand is wd:Q388973. It is described as a chocolate brand of Nestle. Now I will check the manufacturer of this entity to see if it is Unilever.

[Tool]
Got 1 row and 2 columns:
| manufacturer        | manufacturerLabel |
| ------------------- | ----------------- |
| Nestlé (wd:Q160746) | Nestlé (en)       |

[Assistant] After Eight (wd:Q388973) is manufactured by Nestlé (wd:Q160746), not Unilever. Therefore, the answer to the question is "No." I will now provide the final answer with the SPARQL query.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The system correctly identified the manufacturer of After Eight as Nestlé using the property 'manufacturer' (wdt:P176) on the entity After Eight (wd:Q388973). The SPARQL query is well-formed and returns the expected manufacturer entity and label. The answer correctly states that After Eight is not manufactured by Unilever, which directly answers the user's question. No further refinement is needed.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?business ?businessLabel WHERE {
  ?business wdt:P112 wd:Q317521 .
  OPTIONAL {
    ?business rdfs:label ?businessLabel FILTER ( LANG( ?businessLabel ) = "en" )
  }
}

Got 14 rows and 2 columns, showing the first 5 and last 5 rows below:
| business                                                | businessLabel                                |
| ------------------------------------------------------- | -------------------------------------------- |
| Texas Institute of Technology & Science (wd:Q109332244) | Texas Institute of Technology & Science (en) |
| Thud (wd:Q115815194)                                    | Thud (en)                                    |
| X Corp. (wd:Q117617480)                                 | X Corp. (en)                                 |
| X Holdings Corp (wd:Q117705742)                         | X Holdings Corp (en)                         |
| xAI (wd:Q120599684)                                     | xAI (en)                                     |
| ...                                                     | ...                                          |
| Zip2 (wd:Q28222602)                                     | Zip2 (en)                                    |
| The Boring Company (wd:Q28874479)                       | The Boring Company (en)                      |
| Neuralink (wd:Q29043471)                                | Neuralink (en)                               |
| X.com (wd:Q30686532)                                    | X.com (en)                                   |
| PayPal (wd:Q483959)                                     | PayPal (en)                                  |

The businesses founded by the person in charge of Tesla (Elon Musk) are: Texas Institute of Technology & Science, Thud, X Corp., X Holdings Corp, xAI, Zip2, The Boring Company, Neuralink, X.com, and PayPal, among others.

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

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

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

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

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

[User] Which businesses are founded by the person in charge of Tesla?

[Assistant]
To answer the question "Which businesses are founded by the person in charge of Tesla?", I will follow these steps:

1. Identify the entity for "Tesla" in Wikidata.
2. Identify the person in charge of Tesla (likely the CEO or similar role).
3. Identify the businesses founded by that person.

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

[Tool]
Top 10 entity alternatives:
1. Nikola Tesla, also known as Tesla, Nicola Tesla (wd:Q9036): Serbian-American inventor (1856–1943), mechanical engineer, electrical engineer, electrician, physicist, futurist, inventor
2. Tesla, Inc., also known as Tesla, Tesla Inc. (wd:Q478214): American automotive, energy storage and solar power company
3. tesla, also known as T (wd:Q163343): SI unit of magnetic flux density
4. Tesla (wd:Q1428953): American hard rock band
5. Nvidia Tesla, also known as NVidia Tesla, NVIDIA Tesla, Tesla (wd:Q16258100): Nvidia's brand name for their products targeting stream processing and/or general purpose GPU
6. Tesla (wd:Q88053410): 2020 film directed by Michael Almereyda
7. Tesla (wd:Q2406220): lunar crater
8. Tesla, also known as TESLA, Tesla (Czech Republic) (wd:Q1548225): Czech manufacturer of electronical and electrical equipment (est.1991)
9. Tesla, also known as NVIDIA Tesla, Nvidia Tesla, NVidia Tesla (wd:Q1050485): GPU microarchitecture designed by NVIDIA
10. Tesla, also known as Tesla, West Virginia, Tesla, WV (wd:Q7705502): unincorporated community in Braxton County, West Virginia

[Assistant]
The entity for Tesla, the American automotive, energy storage, and solar power company, is wd:Q478214.

Step 2: Identify the person in charge of Tesla (likely the CEO or similar role). I will look for the CEO or similar leadership position of Tesla (wd:Q478214).

[Tool]
Top 10 property alternatives:
1. chief executive officer, also known as executive director, CEO, chief executive (wd:P169 as p/wdt): highest-ranking corporate officer appointed as the CEO within an organization, director / manager, corporate officer
2. chairperson, also known as dean, headed by, leader, president, chairwoman (wd:P488 as p/wdt): presiding member of an organization, group or body, director / manager, significant person
3. founded by, also known as starter, co-founded by, started by, institutor, instituted by (wd:P112 as p/wdt): founder or co-founder of this organization, religion, place or entity, creator
4. board member, also known as member of the board, member of the board of directors (wd:P3320 as p/wdt): member(s) of the board for the organization
5. headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as p/wdt): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place
6. owned by, also known as belongs to, stockholders, stockholder, shareholders, shareholder (wd:P127 as p/wdt): owner of the subject
7. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as p/wdt): time when an entity begins to exist; for date of official opening use P1619, start time
8. owner of, also known as owns, owns property, shareholder of (wd:P1830 as p/wdt): entities owned by the subject
9. country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as p/wdt): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country
10. has subsidiary, also known as subordinate body, subsidiary body, subordinate unit, subsidiary, subsidiary company (wd:P355 as p/wdt): subsidiary of a company or organization; generally a fully owned...siness division" (P199). Opposite of parent organization (P749)., has part(s), owner of

No other items found

[Assistant]
The property for the CEO or chief executive officer is wd:P169.

Step 3: Find the person who is the CEO (wd:P169) of Tesla (wd:Q478214).

[Tool]
Got 1 row and 2 columns:
| person                 | personLabel    |
| ---------------------- | -------------- |
| Elon Musk (wd:Q317521) | Elon Musk (en) |

[Assistant]
The person in charge of Tesla (CEO) is Elon Musk (wd:Q317521).

Step 4: Identify the businesses founded by Elon Musk. I will look for the "founded by" property (wdt:P112) for businesses founded by Elon Musk.

[Tool]
Got 14 rows and 2 columns, showing the first 5 and last 5 rows below:
| business                                                | businessLabel                                |
| ------------------------------------------------------- | -------------------------------------------- |
| Texas Institute of Technology & Science (wd:Q109332244) | Texas Institute of Technology & Science (en) |
| Thud (wd:Q115815194)                                    | Thud (en)                                    |
| X Corp. (wd:Q117617480)                                 | X Corp. (en)                                 |
| X Holdings Corp (wd:Q117705742)                         | X Holdings Corp (en)                         |
| xAI (wd:Q120599684)                                     | xAI (en)                                     |
| ...                                                     | ...                                          |
| Zip2 (wd:Q28222602)                                     | Zip2 (en)                                    |
| The Boring Company (wd:Q28874479)                       | The Boring Company (en)                      |
| Neuralink (wd:Q29043471)                                | Neuralink (en)                               |
| X.com (wd:Q30686532)                                    | X.com (en)                                   |
| PayPal (wd:Q483959)                                     | PayPal (en)                                  |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves businesses founded by Elon Musk, the person in charge of Tesla, using the property 'founded by' (wdt:P112). The query includes optional English labels for readability, which is helpful. The answer lists relevant businesses founded by Elon Musk, matching the query results. The query and answer are accurate and complete for the user's question.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?genre ?genreLabel ( STRLEN( ?genreLabel ) AS ?length ) WHERE {
  wd:Q68061 wdt:P136 ?genre .
  ?genre rdfs:label ?genreLabel .
  FILTER ( LANG( ?genreLabel ) = "en" )
}
ORDER BY ?length
LIMIT 1

The genre that Cage the Elephant belongs to with the fewest English characters is 'blues' with 5 characters.

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

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

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

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

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

[User] Which genre that Cage the Elephant belongs to has the fewest english characters?

[Assistant]
To answer this question, I need to follow these steps:
1. Identify the entity "Cage the Elephant" in Wikidata.
2. Find the genres that "Cage the Elephant" belongs to.
3. Retrieve the English labels of these genres.
4. Determine the genre with the fewest English characters in its label.

I will start by searching for the entity "Cage the Elephant" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Cage the Elephant (wd:Q68061): American rock band from Bowling Green, Kentucky
2. Cage the Elephant (wd:Q1950243): debut album by the American rock band Cage the Elephant
3. The Cage, also known as Cage, Cage, The, Pilot: The Cage (wd:Q20909): 1986 episode of Star Trek: The Original Series directed by Robert Butler
4. The Cage, also known as La Cage (wd:Q3206978): 1975 film by Pierre Granier-Deferre
5. The Cage, also known as Cage (wd:Q41016691): 2017 film by Akram Khan
6. The Cage, also known as Cage, La Cage (wd:Q7720935): 1963 film by Robert Darène
7. West Fourth Street Courts, also known as West 4th Street Courts, The Cage (wd:Q7985184): athletic venue in Manhattan, New York
8. The Cage (wd:Q3520180): album by Tygers of Pan Tang
9. The Elephant (wd:Q31645050): hill in New Zealand
10. The Cage, also known as Colivia (wd:Q29581150): Romanian film

[Assistant] I found the entity "Cage the Elephant" with the identifier wd:Q68061, which is an American rock band. Now I will find the genres that this band belongs to.

[Tool]
Got 6 rows and 2 columns:
| genre                         | genreLabel            |
| ----------------------------- | --------------------- |
| alternative rock (wd:Q11366)  | alternative rock (en) |
| indie rock (wd:Q183504)       | indie rock (en)       |
| psychedelic rock (wd:Q206159) | psychedelic rock (en) |
| garage rock (wd:Q211573)      | garage rock (en)      |
| punk rock (wd:Q3071)          | punk rock (en)        |
| blues (wd:Q9759)              | blues (en)            |

[Assistant] The genres that Cage the Elephant belongs to are: alternative rock, indie rock, psychedelic rock, garage rock, punk rock, and blues. Now I will find the genre with the fewest English characters in its label. I will write a query to order these genres by the length of their English labels and get the one with the fewest characters.

[Tool]
Got 1 row and 3 columns:
| genre            | genreLabel | length      |
| ---------------- | ---------- | ----------- |
| blues (wd:Q9759) | blues (en) | 5 (xsd:int) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the genres associated with Cage the Elephant and orders them by the length of their English labels, returning the genre with the fewest characters. The answer 'blues' with 5 characters is accurate based on the query result. The query follows the rules by returning the genre identifier and its label, filtering for English labels, and ordering by string length. No further refinement is necessary.