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

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

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

[Tool]
Example 1:
Question:
What languages are spoken in Pakistan?

SPARQL:
SELECT * {
  wd:Q843 wdt:P2936 ?uri .
}

Using entities:
Pakistan, also known as Islamic Republic of Pakistan, PAK, pk, Republic of Pakistan (wd:Q843): sovereign state in South Asia

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

Example 2:
Question:
Who wrote the book Les Piliers de la terre?

SPARQL:
SELECT DISTINCT ?res WHERE {
  wd:Q1163227 wdt:P50 ?res .
}

Using entities:
The Pillars of the Earth, also known as The Pillars of the Earth (Kingsbridge, #1) (wd:Q1163227): 1989 novel by Ken Follett

Using properties:
author, also known as writer, written by, poet, playwright, maker (wd:P50 as wdt): main creator(s) of a written work (use on works, not humans); us...hor name string) when Wikidata item is unknown or does not exist, creator

Example 3:
Question:
Who is the governor of Texas?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q1439 wdt:P1313 wd:Q5589725 .
  wd:Q5589725 wdt:P1308 ?uri .
}

Using entities:
Texas, also known as Lone Star State, US-TX, TX, Texas, United States, Tex. (wd:Q1439): state of the United States of America
Governor of Texas, also known as Governor of the State of Texas, Texas Governor (wd:Q5589725): head of state and of government of the U.S. state of Texas

Using properties:
position holder, also known as incumbent, noble title holder, office holder, position held by (wd:P1308 as wdt): persons who hold and/or held the position
office held by head of government, also known as title of head of government, position of head of government, office of head of government, head of government's office, position held by head of government (wd:P1313 as wdt): political office that is fulfilled by the head of the government of this item

[Assistant] Based on these examples, we need to identify the entity for Mark Twain and the property for occupation. Let's start by searching for the entity "Mark Twain".

[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 correct entity for Mark Twain is the first one, wd:Q7245. Now let's search for the property "occupation".

[Tool]
Top 10 property alternatives:
1. occupation, also known as job, work, vocation, profession, employment (wd:P106 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
2. field of this occupation, also known as practice, works in, profession's field, practices, field of this profession (wd:P425 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): field corresponding to this occupation or profession (use only f...fessions - for people use Property:P101, for companies use P452)
3. members have occupation, also known as profession of members, organization of, organization for, organisation of, organisation for (wd:P3989 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): some or all members of this group share the occupation
4. practiced by, also known as proponent, studied by, practitioners, practioner, occupation of this field (wd:P3095 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): type of agents that study this subject or work in this field
5. position held, also known as function, held position, holds position, job, office held (wd:P39 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): subject currently or formerly holds the object position or public office
6. employer, also known as working at, working for, working place, works at, works for (wd:P108 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): person or organization for which the subject works or worked, affiliation
7. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): the object is a country that recognizes the subject as its citizen, country
8. occupant, also known as tenant, resident, renter, occupiers, lessee (wd:P466 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): person or organization occupying property, used by
9. field of work, also known as scientific discipline, scientific area, responsible for, research on, research fields (wd:P101 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): specialization of a person or organization; see P106 for the occupation, interested in
10. work location, also known as work place, working from, working at, worked from, worked at (wd:P937 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): location where persons or organisations were actively participating in employment, business or other work, significant place, location

[Assistant]
The correct property for occupation is the first one, wd:P106. Now we can construct a simple SPARQL query to count the number of distinct occupations that Mark Twain had.

Let's try the following SPARQL query:

```sparql
SELECT (COUNT(DISTINCT ?occupation) AS ?count)
WHERE {
  wd:Q7245 wdt:P106 ?occupation .
}
```

This query selects the count of distinct occupations that Mark Twain had.

Let's execute this query.

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

[Assistant]
The SPARQL query has returned that Mark Twain had 12 distinct occupations.

Therefore, the answer to the question "How many occupations did Mark Twain have?" is 12.

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

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is correct and returns the expected result. It counts the distinct occupations of Mark Twain (Samuel L. Clemens) using the appropriate Wikidata property (P106). The answer provided, 12, matches the result of the query.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?birthPlace WHERE {
  wd:Q183883 wdt:P50 ?author .
  ?author wdt:P19 ?birthPlace .
}

Got 1 row and 1 column:
| birthPlace             |
| ---------------------- |
| New York City (wd:Q60) |

New York City (wd:Q60)

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

[Tool]
Example 1:
Question:
how big is the total area of North Rhine- Westphalia?

SPARQL:
SELECT DISTINCT ?val WHERE {
  wd:Q1198 wdt:P2046 ?val .
}

Using entities:
North Rhine-Westphalia, also known as Nordrhein-Westfalen, NRW (wd:Q1198): state in Germany

Using properties:
area, also known as total area, surface area, surface, size, resolution (wd:P2046 as wdt): area occupied by an object

Example 2:
Question:
Which companies work in the aerospace industry as well as in medicine?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?type wdt:P279 * wd:Q4830453 .
  ?aerospace wdt:P279 * wd:Q3477363 .
  ?healthcare wdt:P279 * wd:Q15067276 .
  ?pharma wdt:P279 * wd:Q507443 .
  ?uri wdt:P452 ?aerospace ; wdt:P452 ?healthcare .
}

Using entities:
health care industry, also known as healthcare industry, health industry, medical care industry, medical industry (wd:Q15067276): industry dedicated to providing health care services and products
aerospace industry, also known as aircraft industry (wd:Q3477363): industrial sector
business (wd:Q4830453): organization undertaking commercial, industrial, or professional activity
pharmaceutical industry, also known as drug industry, pharma, pharmaceutical wholesaler, pharma industry (wd:Q507443): develops, produces, and markets drugs or pharmaceuticals licensed for use as medications

Using properties:
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
industry, also known as branch, economic branch, field of action, field of exercise, sector (wd:P452 as wdt): specific industry of company or organization, part of

Example 3:
Question:
In which films did Julia Roberts as well as Richard Gere play?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q11424 .
  ?uri wdt:P161 wd:Q48410 .
  ?uri wdt:P161 wd:Q40523 .
}

Using entities:
film, also known as cinematic work, moving picture, movie, motion pictures, motion picture (wd:Q11424): sequence of images that give the impression of movement, stored on film stock
Julia Roberts, also known as Julia Fiona Roberts (wd:Q40523): American actress (born 1967), television actor, film producer, voice actor, stage actor, film actor, actor, model
Richard Gere, also known as Richard Tiffany Gere (wd:Q48410): American actor (born 1949), human rights activist, television actor, film director, film producer, photographer, voice actor, stage actor, film actor, actor

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

[Assistant] Based on the examples, we need to identify the author of "The Catcher in the Rye" and then find where they were born. Let's first search for the book "The Catcher in the Rye".

[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 correct entity for "The Catcher in the Rye" is the first one, `wd:Q183883`. Now let's find out who the author of this book is.

[Tool]
Got 1 row and 3 columns:
| subject                             | property         | object                     |
| ----------------------------------- | ---------------- | -------------------------- |
| The Catcher in the Rye (wd:Q183883) | author (wdt:P50) | J. D. Salinger (wd:Q79904) |

[Assistant] The author of "The Catcher in the Rye" is J. D. Salinger (`wd:Q79904`). Next, we need to find where J. D. Salinger was born. We will look for the property "place of birth" for this entity.

[Tool]
Got 1 row and 3 columns:
| subject                    | property                 | object                 |
| -------------------------- | ------------------------ | ---------------------- |
| J. D. Salinger (wd:Q79904) | place of birth (wdt:P19) | New York City (wd:Q60) |

[Assistant]
J. D. Salinger was born in New York City (`wd:Q60`).

Now, let's construct the final SPARQL query to confirm this information and provide the answer to the user's question.

```sparql
SELECT ?birthPlace WHERE {
  wd:Q183883 wdt:P50 ?author .
  ?author wdt:P19 ?birthPlace .
}
```

This query will return the birthplace of the author of "The Catcher in the Rye". Let's execute it to verify the result.

[Tool]
Got 1 row and 1 column:
| birthPlace             |
| ---------------------- |
| New York City (wd:Q60) |

[Assistant]
The SPARQL query confirms that the author of "The Catcher in the Rye," J. D. Salinger, was born in New York City.

Here is the final SPARQL query and the answer:

```sparql
SELECT ?birthPlace WHERE {
  wd:Q183883 wdt:P50 ?author .
  ?author wdt:P19 ?birthPlace .
}
```

Answer: New York City (wd:Q60)

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

[Tool] Stopped generation process

[User]
Feedback (status=done):
The output is correct and complete. The SPARQL query correctly identifies the birthplace of the author of The Catcher in the Rye, which is New York City.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
ASK WHERE {
  wd:Q213849 wdt:P576 ?dissolvedDate .
}

The ATI Company no longer 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] Let's start by looking at some examples.

[Tool]
Example 1:
Question:
Where was JFK assassinated?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q9696 wdt:P20 ?uri .
}

Using entities:
John F. Kennedy, also known as John Kennedy, John Fitzgerald Kennedy, John F Kennedy, Kennedy, President Kennedy (wd:Q9696): President of the United States from 1961 to 1963, anti-communist, naval officer, statesperson, journalist, politician, writer

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

Example 2:
Question:
Who wrote The Hunger Games?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q11679 wdt:P50 ?uri .
}

Using entities:
The Hunger Games, also known as Hunger Games Saga, The Hunger Games Saga (wd:Q11679): three books by Suzanne Collins (2008–2010)

Using properties:
author, also known as writer, written by, poet, playwright, maker (wd:P50 as wdt): main creator(s) of a written work (use on works, not humans); us...hor name string) when Wikidata item is unknown or does not exist, creator

Example 3:
Question:
Give me all Australian nonprofit organizations.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q163740 .
  {
    ?uri wdt:P159 | wdt:P17 wd:Q408 .
  } UNION {
    ?uri wdt:P159 | wdt:P17 ?city .
    ?city wdt:P159 wd:Q408
  }
}

Using entities:
nonprofit organization, also known as Organizations, Nonprofit, np organization, NPO, NPI, not-for-profit organization (wd:Q163740): organization operated for a collective benefit
Australia, also known as AU, The Commonwealth of Australia, Stria, Straya, Stralia (wd:Q408): country in Oceania

Using properties:
headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as wdt): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place
country, also known as sovereign state, state, land, host country (wd:P17 as wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

[Assistant] Based on the examples, we need to identify the entity for ATI Company and then check if it has a property indicating its current status. Let's first search for the entity "ATI 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] None of these results seem to match the ATI Company we are looking for. Let's try searching again with a more specific query, such as "ATI Technologies".

[Tool]
Top 10 entity alternatives:
1. ATI Technologies, also known as Array Technologies Incorporated (wd:Q213849): Canadian technology corporation
2. Atipa Technologies (wd:Q67904906): American hardware manufacturer
3. technology, also known as technologies, technological sciences, technicology, tech, technological science (wd:Q11016): making, modification, usage, and knowledge of tools, machines, t... and methods of organization, or tools and techniques so created
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. Ati, also known as Ati language, Ati (Philippines) (wd:Q3217458): Malayo-Polynesian language spoken and native to the Ati people of Panay
8. The Alan Turing Institute, also known as Turing Institute, turing.ac.uk, ATI (wd:Q16826821): research institute in Britain
9. Boneh-ye Ati, also known as Boneh-ye ‘Āţī, ‘Āţī (wd:Q4941616): village in Iran
10. Allegheny Technologies, also known as Allegheny Technologies Incorporated, ATI, ATI Metals (wd:Q1361648): company

[Assistant]
The top result, "ATI Technologies" (wd:Q213849), seems to be the correct entity. Now, let's check if there is a property that indicates the current status of the company. We can look for properties like "dissolved" or "status" to see if the company is still active.

Let's search for relevant properties of this entity.

[Tool]
Top 10 property alternatives:
1. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
2. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as wdt/p): time when an entity begins to exist; for date of official opening use P1619, start time
3. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
4. product, material, or service produced or provided, also known as products, product or service provided, product, material, or service produced or provided, product, output (wd:P1056 as wdt/p): material or product produced or sold by an organization, industry, facility, or process, material or product produced by an organization, industry, facility, or process, immediate cause of
5. official name, also known as long title, name, official title, registered name, full title (wd:P1448 as wdt/p): official name of the subject in its official language(s), name
6. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as wdt/p): URL of the official page of an item (current or former). Usage: ...but see the "Hijacked or dead websites" section of the Talk page, URL
7. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
8. parent organization, also known as parent company, parent institution, parent organisation, parent unit, part of (wd:P749 as wdt/p): parent organization of an organization, opposite of subsidiaries (P355), owned by, part of
9. dissolved, abolished or demolished date, also known as ended, publication end date, final issue, date repealed, final year (wd:P576 as wdt/p): point in time at which the subject (organisation, building) ceas...g equipment,  "discontinued date" (P2669) for stopping a product, end time
10. stock exchange, also known as listed on, listed on stock exchange, listed on exchange, exchange (wd:P414 as p): exchange on which this company is traded

No other items found

[Assistant]
The property "dissolved, abolished or demolished date" (wd:P576) is relevant to check if the company has been dissolved. Let's run a SPARQL query to see if ATI Technologies has a value for this property.

If the property is present, it means the company has been dissolved. If it is not present, it suggests that the company is still active.

Let's execute the query:

```sparql
ASK WHERE {
  wd:Q213849 wdt:P576 ?dissolvedDate .
}
```

This ASK query will return `true` if the company has a dissolved date and `false` otherwise.

[Tool] True

[Assistant]
The ASK query returned `True`, which means that ATI Technologies has a dissolved date. Therefore, the company no longer exists.

Here is the final SPARQL query and answer:

```sparql
ASK WHERE {
  wd:Q213849 wdt:P576 ?dissolvedDate .
}
```

Answer: The ATI Company no longer exists.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is correct and follows all the rules. It checks if the ATI Company has a dissolved date, which would indicate that the company no longer exists. The result is True, meaning the company does have a dissolved date and therefore no longer exists. The answer provided is accurate and complete.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
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)    |

The instruments that Louis Armstrong played are: 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] Let's start by looking at some examples.

[Tool]
Example 1:
Question:
Which ingredients do I need for carrot cake?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q656071 wdt:P527 ?uri .
}

Using entities:
carrot cake (wd:Q656071): sweet cake that contains grated carrots as an ingredient

Using properties:
has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as wdt): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).

Example 2:
Question:
Who is the founder of Penguin Books?

SPARQL:
SELECT ?o1 WHERE {
  wd:Q1336200 wdt:P112 ?o1 .
}

Using entities:
Penguin Books, also known as Penguin Books, Limited (wd:Q1336200): British publishing house

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

Example 3:
Question:
Which countries have places with more than two caves?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?cave wdt:P31 wd:Q35509 ; wdt:P17 ?uri .
}
GROUP BY ?uri
HAVING ( COUNT( ?cave ) > 2 )

Using entities:
cave, also known as cavern (wd:Q35509): natural void under the Earth's surface

Using properties:
country, also known as sovereign state, state, land, host country (wd:P17 as wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

[Assistant]
Based on the examples, we can see that the SPARQL queries are structured around specific entities and their properties. For our question about the instruments played by Louis Armstrong, we'll need to identify:

1. The entity representing Louis Armstrong.
2. The property that indicates the instruments he played.

Let's start by searching for the entity representing Louis Armstrong.

[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 top result, `wd:Q1779`, represents Louis Armstrong, the American jazz musician. Now, let's find the property that indicates the instruments he played. We can search for properties related to "instruments" or "played" 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 wdt/p): musical instrument that a person plays or teaches or used in a music occupation, uses
2. has works in the collection, also known as has items in the collection, works in collection, work in collection, museum housing this person's work, items in the collection (wd:P6379 as wdt/p): collection that has works of this person or organisation (use archives at [P485] for archives)
3. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as wdt/p): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
4. discography, also known as discography link, recording catalog (wd:P358 as wdt/p): item for list pages with discography of artist or band, list of works
5. has list, also known as list, topic's list, topic list, related list, list for this topic (wd:P2354 as wdt/p): Wikimedia list related to this subject
6. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
7. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as wdt/p): main Wikimedia category
8. member of, also known as band member of, membership, member of musical group, in musical group, be member of (wd:P463 as wdt/p): organization, club or musical group to which the subject belongs...ical position, such as a member of parliament (use P39 for that), part of
9. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as wdt/p): award or recognition received by a person, organization or creative work
10. record label, also known as label, labels (wd:P264 as wdt/p): brand and trademark associated with the marketing of subject music recordings and music videos

No other items found

[Assistant]
The property `wd:P1303` (instrument) seems to be the most relevant for indicating the instruments that Louis Armstrong played. Let's construct a SPARQL query to retrieve the instruments associated with Louis Armstrong using this property.

Here is the initial SPARQL query:

```sparql
SELECT ?instrument WHERE {
  wd:Q1779 wdt:P1303 ?instrument .
}
```

Let's execute this query to see the results.

[Tool]
Got 3 rows and 1 column:
| instrument           |
| -------------------- |
| voice (wd:Q17172850) |
| cornet (wd:Q202027)  |
| trumpet (wd:Q8338)   |

[Assistant]
The SPARQL query has returned the instruments that Louis Armstrong played:

- Voice (wd:Q17172850)
- Cornet (wd:Q202027)
- Trumpet (wd:Q8338)

To provide a more user-friendly response, we can include the labels of these instruments. However, since the labels are optional, we will use an `OPTIONAL` clause to fetch them.

Here is the refined SPARQL query:

```sparql
SELECT ?instrument ?instrumentLabel WHERE {
  wd:Q1779 wdt:P1303 ?instrument .
  OPTIONAL { ?instrument rdfs:label ?instrumentLabel . FILTER(LANG(?instrumentLabel) = "en") }
}
```

Let's execute this query to get the labels as well.

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

[Assistant]
The refined SPARQL query has successfully retrieved the instruments that Louis Armstrong played along with their labels:

- Voice (wd:Q17172850)
- Cornet (wd:Q202027)
- Trumpet (wd:Q8338)

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

```sparql
SELECT ?instrument ?instrumentLabel WHERE {
  wd:Q1779 wdt:P1303 ?instrument .
  OPTIONAL { ?instrument rdfs:label ?instrumentLabel . FILTER(LANG(?instrumentLabel) = "en") }
}
```

The instruments that Louis Armstrong played are:
- Voice
- Cornet
- Trumpet

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is well-formed and returns the correct and complete information about the instruments Louis Armstrong played. The query follows all the rules and guidelines provided. The human-readable answer is accurate and matches the execution result.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( DISTINCT ?instance ) AS ?count ) WHERE {
  {
    ?instance wdt:P31 wd:Q179651 .
  } UNION {
    ?instance wdt:P31 ?subclass .
    ?subclass wdt:P279 * wd:Q179651 .
  } UNION {
    VALUES ?specificScale {
      wd:Q1058106 wd:Q1325245 wd:Q1343138 wd:Q6902033 wd:Q3424018 wd:Q781861 wd:Q20640663 wd:Q1919626
    }
    .
    ?instance wdt:P31 ?specificScale .
  }
}

Got 1 row and 1 column:
| count        |
| ------------ |
| 77 (xsd:int) |

There are 77 musical scales.

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

[Tool]
Example 1:
Question:
How many awards has Bertrand Russell?

SPARQL:
SELECT ( COUNT( DISTINCT ?o1 ) as ?count ) WHERE {
  wd:Q33760 wdt:P166 ?o1 .
}

Using entities:
Bertrand Russell, also known as Bertrand Russell, Earl Russell, Bertrand Russell, 3rd Earl Russell, Russell, Bertrand Arthur William Russell, Bertrand Arthur William Russell, 3rd Earl Russell (wd:Q33760): British philosopher and logician (1872–1970), philosopher of language, science fiction writer, philosopher of science, analytic philosopher, university teacher, political activist, peace activist, autobiographer, epistemologist, social critic, mathematician, metaphysician, philosopher, journalist, politician, essayist, logician, writer

Using properties:
award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as wdt): award or recognition received by a person, organization or creative work

Example 2:
Question:
Who produced films starring Natalie Portman?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?film wdt:P31 wd:Q11424 .
  ?film wdt:P161 wd:Q37876 .
  ?film wdt:P162 ?uri .
}

Using entities:
film, also known as cinematic work, moving picture, movie, motion pictures, motion picture (wd:Q11424): sequence of images that give the impression of movement, stored on film stock
Natalie Portman, also known as Natalie Hershlag, Neta-Lee Herschlag, Natalie Herschlag, Nat (wd:Q37876): Israeli-American actress, television actor, film director, film producer, screenwriter, stage actor, film actor, actor

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as wdt): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
producer, also known as music producer, record producer, produced by, film producer, creative producer (wd:P162 as wdt): person(s) who produced the film, musical work, theatrical produc...etc.) [for production company, use P272, video games - use P178]
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 3:
Question:
Where did Abraham Lincoln die?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q91 wdt:P20 ?uri
}

Using entities:
Abraham Lincoln, also known as President Lincoln, Uncle Abe, Honest Abe, Abe Lincoln (wd:Q91): president of the United States from 1861 to 1865, military officer, statesperson, postmaster, politician, farmer, writer, lawyer

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

[Assistant] Based on the examples, we can see that to count something, we use the COUNT function in SPARQL. We need to identify the entity representing 'musical scale' and then count the number of instances of this entity. Let's first search for the entity 'musical scale'.

[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 top result, 'scale' (wd:Q179651), seems to be the correct entity for 'musical scale'. Now, let's check if there is a property that indicates that something is an instance of a musical scale. We can use the 'instance of' property (wdt:P31) to find all instances of the musical scale entity.

Let's construct a SPARQL query to count the number of instances of the musical scale entity.

[Tool]
Got 1 row and 1 column:
| count        |
| ------------ |
| 22 (xsd:int) |

[Assistant]
The SPARQL query returned a count of 22 musical scales.

Therefore, the answer to the question "How many musical scales are there?" is 22.

I will now provide the final answer using the `answer` function.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query is on the right track, but it only counts instances of 'musical scale' (wd:Q179651). However, there are different types of musical scales, such as diatonic, chromatic, pentatonic, etc., which might not all be directly classified as 'musical scale'. To ensure we capture all relevant scales, we should consider using a broader approach, such as finding all subclasses of 'musical scale' and counting their instances as well.

[Assistant]
Thank you for the feedback. To ensure we capture all relevant musical scales, including those that are subclasses of 'musical scale', we need to find all subclasses of 'musical scale' and then count the instances of these subclasses as well.

First, let's find all subclasses of 'musical scale' (wd:Q179651).

### Step 1: Find all subclasses of 'musical scale'
We will use the property 'subclass of' (wdt:P279) to find all subclasses of 'musical scale'.

### Step 2: Count instances of 'musical scale' and its subclasses
We will then count the instances of 'musical scale' and all its subclasses.

Let's start by finding all subclasses of 'musical scale'.

[Tool]
Got 39 rows and 1 column, showing the first 5 and last 5 rows below:
| subclass                              |
| ------------------------------------- |
| Gregorian mode (wd:Q1058106)          |
| wd:Q11919698                          |
| octatonic scale (wd:Q1325245)         |
| Enigmatic scale (wd:Q1343138)         |
| wd:Q16182817                          |
| ...                                   |
| monotonic scale (wd:Q6902033)         |
| relative major (wd:Q3424018)          |
| Chinese pentatonic scale (wd:Q781861) |
| natural minor scale (wd:Q20640663)    |
| jazz minor scale (wd:Q1919626)        |

[Assistant]
The query returned 39 subclasses of 'musical scale' (wd:Q179651). Now, we need to count the instances of 'musical scale' and all its subclasses.

### Step 3: Count instances of 'musical scale' and its subclasses
We will use a UNION to combine the instances of 'musical scale' and its subclasses and then count them.

Let's construct the SPARQL query to achieve this.

[Tool]
Got 1 row and 1 column:
| count        |
| ------------ |
| 77 (xsd:int) |

[Assistant]
The SPARQL query returned a count of 77 instances of 'musical scale' and its subclasses.

Therefore, the answer to the question "How many musical scales are there?" is 77.

I will now provide the final answer using the `answer` function.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query is on the right track, but it only counts direct instances and subclasses of 'musical scale'. However, there might be more specific types of scales (like modes or exotic scales) that are not directly classified as musical scales but are still relevant. Consider adding more specific types of scales to the query to ensure a comprehensive count.

[Assistant]
Thank you for the feedback. To ensure a more comprehensive count, we should include more specific types of scales that might not be directly classified as 'musical scale' but are still relevant. We can do this by explicitly listing some of these specific types and including them in our query.

### Step 1: Identify specific types of scales
Let's list some specific types of scales that are commonly recognized and might not be directly classified as 'musical scale'. We can use the subclasses we found earlier as a starting point and add any additional specific types.

### Step 2: Construct the SPARQL query
We will use a UNION to combine the instances of 'musical scale', its subclasses, and any additional specific types of scales.

Let's start by identifying some specific types of scales and then construct the query.

### Step 3: Execute the query
We will execute the query to count the instances of 'musical scale', its subclasses, and the additional specific types of scales.

Let's proceed with this approach.

[Tool]
Got 1 row and 1 column:
| count        |
| ------------ |
| 77 (xsd:int) |

[Assistant]
The SPARQL query returned a count of 77 instances of 'musical scale', its subclasses, and the additional specific types of scales. Since the count remains the same, it suggests that the additional specific types of scales we included are already covered by the subclasses of 'musical scale'.

Therefore, the answer to the question "How many musical scales are there?" is 77.

I will now provide the final answer using the `answer` function.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?gender WHERE {
  wd:Q1983102 wdt:P21 ?gender
}

The binary gender of the partner of Allen Ginsberg 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] Let's start by looking at some examples.

[Tool]
Example 1:
Question:
How many airlines are there?

SPARQL:
SELECT ( COUNT( DISTINCT ?uri ) AS ?uriCount ) WHERE {
  ?uri wdt:P31 wd:Q46970
}

Using entities:
airline, also known as air company, air carrier (wd:Q46970): company that provides air transport services for traveling passengers and freight

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

Example 2:
Question:
In which country does the Ganges start?

SPARQL:
SELECT ?o2 WHERE {
  wd:Q5089 wdt:P885 ?o1 .
  ?o1 wdt:P17 ?o2 .
}

Using entities:
Ganges, also known as Ganga, River Ganges, Ganges River (wd:Q5089): major river in India

Using properties:
country, also known as sovereign state, state, land, host country (wd:P17 as wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
origin of the watercourse, also known as headwaters, water source, water origin, water body origin, stream source (wd:P885 as wdt): main source of a river, stream or lake

Example 3:
Question:
How many students does the Free University of Amsterdam have?

SPARQL:
SELECT ?o1 WHERE {
  wd:Q214341 wdt:P2196 ?o1 .
}

Using entities:
University of Amsterdam, also known as GUA, uva.nl, UvA, Univ. of Amsterdam, G.U.A. (wd:Q214341): public university in Amsterdam, Netherlands

Using properties:
count of students, also known as count of pupils, count of students, enrollment, number of pupils, number of pupils or students (wd:P2196 as wdt): number of pupils or students of any type in an educational organ...evious years normal rank (not deprecated rank). Don't overwrite.

[Assistant] Based on the examples, we need to identify the relevant entities and properties for our question. We need to find the partner of Allen Ginsberg and then determine their binary gender. Let's start by searching for Allen Ginsberg in the knowledge graph.

[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 first result, Allen Ginsberg (wd:Q6711), seems to be the correct entity for the American poet and writer. Now, let's find out who his partner was. We can search for the property "partner" or "spouse" to find this information.

[Tool]
Top 10 property alternatives:
1. unmarried partner, also known as romantic partner, partner of, partners, posslq, relationship (wd:P451 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): 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/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): 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/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): professional collaborator, significant person
4. partnership with, also known as works with, collaborates with, collaboration with (wd:P2652 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): 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/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): 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/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): 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/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): 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/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): organization or individual that sponsors this item
9. commissioned by, also known as client, orderer, made for, commissioner, built for (wd:P88 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): 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/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): two or more astronomic bodies of the same type relating to each other

[Assistant] The property "spouse" (wd:P26) seems to be the most appropriate for finding Allen Ginsberg's partner. Let's use this property to find out who his partner was.

[Tool] Got no rows and 1 columns

[Assistant] It appears that Allen Ginsberg does not have a recorded spouse in the knowledge graph. However, he might have had an unmarried partner. Let's try the property "unmarried partner" (wd:P451) to see if we can find any information about his partner.

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

[Assistant] We found that Peter Orlovsky (wd:Q1983102) was Allen Ginsberg's unmarried partner. Now, let's determine Peter Orlovsky's binary gender. We can search for the property "gender" or "sex" to find this information.

[Tool]
Top 10 property alternatives:
1. grammatical gender, also known as gender (wd:P5185 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): grammatical gender of the word
2. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)
3. requires grammatical feature, also known as grammatical feature required, required grammatical feature, requires case, requires mood, uses case (wd:P5713 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): 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/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): 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/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): personal pronoun(s) this person goes by
6. semantic gender, also known as natural gender (wd:P10339 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): 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. female form of label, also known as female form of label (string), female gender sense, feminine form of label (wd:P2521 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): female form of name or title (for male use P3321)
8. gender educated (wd:P7419 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): genders educated at this educational institution
9. male form of label, also known as male form of label (string), male gender sense, masculine form of label (wd:P3321 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): male form of name or title (for female use P2521)
10. given name version for other gender, also known as personal name version for other gender, other genders given name, male version of this female given name, gender inflection of given name, female version of this male given name (wd:P1560 as pqn/prv/pq/wdt/ps/prn/psv/p/wdtn/pqv/psn/pr): equivalent name (with respect to the meaning of the name) in the...n of a female first name. Add primarily the closest matching one

[Assistant] The property "sex or gender" (wd:P21) seems to be the most appropriate for determining Peter Orlovsky's binary gender. Let's use this property to find out his gender.

[Tool]
Got 1 row and 1 column:
| gender             |
| ------------------ |
| male (wd:Q6581097) |

[Assistant]
Peter Orlovsky, the partner of Allen Ginsberg, has a binary gender of male (wd:Q6581097).

Here is the final SPARQL query and answer:

```sparql
SELECT ?gender WHERE {
  wd:Q1983102 wdt:P21 ?gender
}
```

Answer: The binary gender of the partner of Allen Ginsberg is male.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The output is correct and complete. The SPARQL query correctly identifies the binary gender of Peter Orlovsky, who was the partner of Allen Ginsberg.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?member ?birthDate WHERE {
  wd:Q51885404 wdt:P527 ?member .
  ?member wdt:P569 ?birthDate
}
ORDER BY DESC ( ?birthDate )
LIMIT 1

Shuhua (wd:Q55287305) is the youngest member of G-IDLE.

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

[Tool]
Example 1:
Question:
Who is the mayor of Tel Aviv?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q33935 wdt:P6 ?uri .
}

Using entities:
Tel Aviv, also known as Tel Aviv City, TLV, Tel Aviv-Jafo, Tel-Aviv Jaffa, Tel Aviv-Jaffa (wd:Q33935): city in Israel

Using properties:
head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as wdt): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson

Example 2:
Question:
Which U.S. state has the highest population density?

SPARQL:
SELECT ?uri {
  ?uri wdt:P31 wd:Q35657 .
  ?uri wdt:P1082 ?population .
  ?uri wdt:P2046 ?area .
  BIND( ( ?population / ?area ) AS ?density )
}
ORDER BY DESC ( ?density )
LIMIT 1

Using entities:
U.S. state, also known as U.S. states, US state, USA state, U.S.A. state, United States states (wd:Q35657): constituent political entity of the United States of America

Using properties:
population, also known as inhabitants, human population (wd:P1082 as wdt): number of people inhabiting the place; number of people of subject
area, also known as total area, surface area, surface, size, resolution (wd:P2046 as wdt): area occupied by an object
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 3:
Question:
How many languages are spoken in Turkmenistan?

SPARQL:
SELECT ( COUNT( DISTINCT ?uri ) as ?c ) WHERE {
  wd:Q874 wdt:P2936 ?uri .
}

Using entities:
Turkmenistan, also known as TKM, tm, Turkmenia (wd:Q874): country in Central Asia

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

[Assistant] Based on the examples, we need to identify the relevant entities and properties for our question. We need to find the youngest member of the K-pop group G-IDLE. Let's start by searching for the entity representing G-IDLE.

[Tool]
Top 10 entity alternatives:
1. Neverland, also known as Neverland (fandom), Neverland (G-Idle) (wd:Q99515216): Neverland are the fanbase of (G)I-DLE.
2. Moon, also known as Moon ((G)I-dle song), Moon (G-Idle song) (wd:Q104969991): 2021 single by (G)I-dle
3. Lost, also known as Lost (G-Idle song) (wd:Q105132486): 2021 song by (G)I-DLE
4. 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

[Assistant] It seems that the search did not return the correct entity for the K-pop group G-IDLE. Let me try another search with a different query to ensure we get the right entity.

[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] We found the correct entity for the K-pop group G-IDLE, which is `wd:Q51885404`. Next, we need to find the members of this group and their birth dates to determine who is the youngest. Let's search for the property that links group members to the group.

[Tool]
Top 10 property alternatives:
1. has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as wdt/p): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).
2. member count, also known as total members, number of members, count of members, amount of members, membership (wd:P2124 as wdt/p): number of entities that are part of an organization at a particular time
3. member category, also known as category for members (wd:P6365 as wdt/p): category item for members of the organization
4. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
5. country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as wdt/p): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country
6. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as wdt/p): URL of the official page of an item (current or former). Usage: ...but see the "Hijacked or dead websites" section of the Talk page, URL
7. name, also known as also known as, referred to as, label, known as, be known as (wd:P2561 as wdt/p): name the subject is known by; preferably use a more specific subproperty if available
8. YouTube channel ID, also known as YouTube account, YouTube channel, YouTube channel identifier, official YouTube channel, youtube.com/channel/ (wd:P2397 as wdt/p): ID of the YouTube channel of a person or organisation (not to be...f the channel) The ID can also be used for music.youtube.com IDs, website username or ID
9. X (Twitter) username, also known as twitter.com/, X username, X handle, x.com/, X account (wd:P2002 as wdt/p): username on X (formerly Twitter); do not include the '@' symbol, website username or ID
10. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as wdt/p): time when an entity begins to exist; for date of official opening use P1619, start time

No other items found

[Assistant] The property `has part(s)` (`wdt:P527`) seems to be the most appropriate for linking group members to the group. Now, let's find the members of G-IDLE using this property and then retrieve their birth dates to determine who is the youngest.

[Tool]
Got 6 rows and 2 columns:
| member                     | birthDate                           |
| -------------------------- | ----------------------------------- |
| Cho Mi-yeon (wd:Q56259927) | 1997-01-31T00:00:00Z (xsd:dateTime) |
| Minnie (wd:Q56761923)      | 1997-10-23T00:00:00Z (xsd:dateTime) |
| Soojin (wd:Q61100297)      | 1998-03-09T00:00:00Z (xsd:dateTime) |
| Jeon Soyeon (wd:Q26707915) | 1998-08-26T00:00:00Z (xsd:dateTime) |
| Song Yuqi (wd:Q55287306)   | 1999-09-23T00:00:00Z (xsd:dateTime) |
| Shuhua (wd:Q55287305)      | 2000-01-06T00:00:00Z (xsd:dateTime) |

[Assistant]
From the results, we can see that the youngest member of G-IDLE is Shuhua, born on January 6, 2000.

Let's confirm this by providing the final SPARQL query and the answer.

[Tool] Stopped generation process

[User]
Feedback (status=retry):
The SPARQL query is almost correct, but the result returned is not the youngest member. The query should order the members by their birth dates in ascending order and limit the result to the first one, which it does, but the result shows Cho Mi-yeon who is not the youngest member. Please check the data and ensure that the correct member is being selected.

[Assistant]
I see the issue now. The query is ordering the members by their birth dates in ascending order, which means the oldest member is listed first. To find the youngest member, we need to order the members by their birth dates in descending order and limit the result to the first one.

Let's correct the query.

[Tool]
Got 1 row and 2 columns:
| member                | birthDate                           |
| --------------------- | ----------------------------------- |
| Shuhua (wd:Q55287305) | 2000-01-06T00:00:00Z (xsd:dateTime) |

[Assistant]
The corrected query now correctly identifies Shuhua as the youngest member of G-IDLE, born on January 6, 2000.

Let's provide the final SPARQL query and the answer.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is correct and returns the expected result. It identifies Shuhua as the youngest member of G-IDLE based on their birth dates. The query follows all the rules and guidelines provided.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?author WHERE {
  wd:Q3521239 wdt:P50 ?author .
}

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] Let's start by looking at some examples.

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

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

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

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

Example 2:
Question:
Give me the runtime of Toy Story.

SPARQL:
SELECT ?val WHERE {
  wd:Q171048 wdt:P2047 ?val .
}

Using entities:
Toy Story, also known as Toy Story 1 (wd:Q171048): 1995 American animated film

Using properties:
duration, also known as time length, timespan, time span, time interval, runtime (wd:P2047 as wdt): length of time of an event or process

Example 3:
Question:
How many languages are spoken in Turkmenistan?

SPARQL:
SELECT ( COUNT( DISTINCT ?uri ) as ?c ) WHERE {
  wd:Q874 wdt:P2936 ?uri .
}

Using entities:
Turkmenistan, also known as TKM, tm, Turkmenia (wd:Q874): country in Central Asia

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

[Assistant] Based on the examples, we need to identify the entity for "The Hellbound Heart" and then find the author of this work. Let's start by searching for the entity "The Hellbound Heart".

[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]
The correct entity for "The Hellbound Heart" is `wd:Q3521239`. Now, let's find the author of this work. We need to look for a property that indicates the author of a literary work. A common property for this is `wdt:P50` (author).

Let's execute a SPARQL query to find the author of "The Hellbound Heart".

[Tool]
Got 1 row and 1 column:
| author                    |
| ------------------------- |
| Clive Barker (wd:Q298761) |

[Assistant]
The author of "The Hellbound Heart" is Clive Barker.

Here is the final SPARQL query and answer:

```sparql
SELECT ?author WHERE {
  wd:Q3521239 wdt:P50 ?author .
}
```

Answer: Clive Barker

[Tool] Stopped generation process

[User]
Feedback (status=done):
The output is correct and complete. The SPARQL query correctly identifies the author of 'The Hellbound Heart' as Clive Barker, and the result includes the IRI of the author.