PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?gender WHERE {
  wd:Q6711 wdt:P451 | wdt:P26 ?partner .
  ?partner wdt:P21 ?gender
}

male

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

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

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

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

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

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

[Assistant]
To answer this question, we need to identify the following:
1. The entity for Allen Ginsberg.
2. The property that represents a partner or spouse.
3. The entity for the partner of Allen Ginsberg.
4. The property that represents binary gender.
5. The value of the binary gender for the partner.

Let's start by searching for the entity for Allen Ginsberg.

[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 correct entity for Allen Ginsberg is `wd:Q6711`. Next, we need to find the property that represents a partner or spouse. Let's search for this property.

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

[Assistant]
The property for a partner or spouse is `wdt:P451` for an unmarried partner and `wdt:P26` for a spouse. Since Allen Ginsberg was known to have had both types of relationships, we will check both properties.

Let's find out who Allen Ginsberg's partner or spouse was.

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

[Assistant]
The partner of Allen Ginsberg is Peter Orlovsky (`wd:Q1983102`). Now, we need to find the binary gender of Peter Orlovsky. The property for binary gender is typically `wdt:P21`.

Let's find the binary gender of Peter Orlovsky.

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

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

Here is the final SPARQL query and answer:

```sparql
SELECT ?gender WHERE {
  wd:Q6711 wdt:P451|wdt:P26 ?partner .
  ?partner wdt:P21 ?gender
}
```

The answer is: male.

[Tool] Stopped generation process


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

The youngest member of G-IDLE is Shuhua.

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

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

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

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

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

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

[Assistant] To find the youngest member of the K-pop group G-IDLE, we need to identify the group and then look for its members along with their birth dates. We can start by searching for the entity representing G-IDLE in the knowledge graph.

[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 exact entity for the group G-IDLE. Let me try a more specific search to find the correct 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]
The correct entity for the K-pop group G-IDLE is `wd:Q51885404`. Now, we need to find the members of this group and their birth dates. We can start by listing the members of the group.

Let's list the members of G-IDLE:

[Tool]
Got 6 rows and 3 columns:
| subject                 | property               | object                     |
| ----------------------- | ---------------------- | -------------------------- |
| (G)I-dle (wd:Q51885404) | has part(s) (wdt:P527) | Jeon Soyeon (wd:Q26707915) |
| (G)I-dle (wd:Q51885404) | has part(s) (wdt:P527) | Cho Mi-yeon (wd:Q56259927) |
| (G)I-dle (wd:Q51885404) | has part(s) (wdt:P527) | Song Yuqi (wd:Q55287306)   |
| (G)I-dle (wd:Q51885404) | has part(s) (wdt:P527) | Soojin (wd:Q61100297)      |
| (G)I-dle (wd:Q51885404) | has part(s) (wdt:P527) | Minnie (wd:Q56761923)      |
| (G)I-dle (wd:Q51885404) | has part(s) (wdt:P527) | Shuhua (wd:Q55287305)      |

[Assistant]
We have identified the members of G-IDLE. Now, we need to find the birth dates of these members to determine who is the youngest. We can do this by querying the birth dates of each member.

Let's execute a SPARQL query to find the birth dates of the members and determine the youngest member.

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

[Assistant]
The youngest member of G-IDLE is Shuhua, born on January 6, 2000.

Here is the final SPARQL query and answer:

```sparql
SELECT ?member ?birthDate WHERE {
  wd:Q51885404 wdt:P527 ?member .
  ?member wdt:P569 ?birthDate
} ORDER BY DESC(?birthDate) LIMIT 1
```

The youngest member of G-IDLE is Shuhua.

[Tool] Stopped generation process


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

The author of The Hellbound Heart is Clive Barker.

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

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

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

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

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

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

[Assistant] To find the author of "The Hellbound Heart," we need to first identify the entity representing the book in the knowledge graph and then find the property that links it to its author. 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 top result for "The Hellbound Heart" is wd:Q3521239, which is described as a novella by Clive Barker. This seems to be the correct entity for the book. Next, we need to find the property that links the book to its author. A common property for this relationship is "author" or "creator." Let's search for the relevant property.

[Tool]
Top 10 property alternatives:
1. theorized by, also known as author, supported by, suggested by, proposer, proposed by (wd:P8403 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): subject who suggested or proposed this concept or immaterial invention
2. lyricist, also known as text poet, writer (of song lyrics), words by, text writer, text by (wd:P676 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): author of song lyrics, author
3. author, also known as writer, written by, poet, playwright, maker (wd:P50 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): 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
4. notable work, also known as artwork, wrote, writer of, works, work (wd:P800 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): notable scientific, artistic or literary work, or other work of significance among subject's works
5. author given names, also known as given name, given names, first name, author first names, author first name (wd:P9687 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): qualifier for string representation of given or secondary sortin...presented in a bibliographic reference file (for example BibTeX), given name
6. used by, also known as armiger, user, played by, of (wd:P1535 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): item or concept that makes use of the subject (use sub-properties when appropriate)
7. operator, also known as offered by, operated by, provided by, run by, service operator (wd:P137 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): person, profession, organization or entity that operates the equipment, facility, or service, used by
8. creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): maker of this creative work or other object (where no more specific property exists)
9. author last names, also known as author last name, surnames, surname, last names, last name (wd:P9688 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): qualifier to provide string representation of family or primary ...presented in a bibliographic reference file (for example BibTeX), family name
10. object named as, also known as original wording, place name string, printed as, reference wording, [sic] (wd:P1932 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): use as qualifier to indicate how the object's value was given in the source, name

[Assistant]
The property "author" (wd:P50) is the most relevant for linking a book to its author. Now, let's construct a SPARQL query to find the author of "The Hellbound Heart" (wd:Q3521239).

Here is the initial SPARQL query:

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

Let's execute this query to see the results.

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

[Assistant]
The author of "The Hellbound Heart" is Clive Barker (wd:Q298761).

To provide a more complete answer, we can include the label of the author in the query. Here is the refined SPARQL query:

```sparql
SELECT ?author ?authorLabel WHERE {
  wd:Q3521239 wdt:P50 ?author .
  OPTIONAL { ?author rdfs:label ?authorLabel . }
}
```

Let's execute this refined query to get the label of the author.

[Tool]
Got 55 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?author                   | ?authorLabel       |
| ------------------------- | ------------------ |
| Clive Barker (wd:Q298761) | "Clive Barker"@ast |
| Clive Barker (wd:Q298761) | "Clive Barker"@br  |
| Clive Barker (wd:Q298761) | "Clive Barker"@bs  |
| Clive Barker (wd:Q298761) | "Clive Barker"@ca  |
| Clive Barker (wd:Q298761) | "Clive Barker"@cs  |
| ...                       | ...                |
| Clive Barker (wd:Q298761) | "克里夫·巴克"@zh-hans   |
| Clive Barker (wd:Q298761) | "克里夫·巴克"@zh-hant   |
| Clive Barker (wd:Q298761) | "克里夫·巴克"@zh-hk     |
| Clive Barker (wd:Q298761) | "克里夫·巴克"@zh-sg     |
| Clive Barker (wd:Q298761) | "克里夫·巴克"@zh-tw     |

[Assistant]
The query returned multiple rows with different language labels for Clive Barker. To simplify the result, we can limit the query to return only the English label. Here is the updated SPARQL query:

```sparql
SELECT ?author ?authorLabel WHERE {
  wd:Q3521239 wdt:P50 ?author .
  OPTIONAL { ?author rdfs:label ?authorLabel . FILTER(LANG(?authorLabel) = "en") }
}
```

Let's execute this query to get the English label of the author.

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

[Assistant]
The author of "The Hellbound Heart" is Clive Barker (wd:Q298761).

Here is the final SPARQL query and the answer:

```sparql
SELECT ?author ?authorLabel WHERE {
  wd:Q3521239 wdt:P50 ?author .
  OPTIONAL { ?author rdfs:label ?authorLabel . FILTER(LANG(?authorLabel) = "en") }
}
```

Answer: The author of "The Hellbound Heart" is Clive Barker.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
ASK WHERE {
  wd:Q388973 wdt:P176 wd:Q157062 .
}

False

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

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

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

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

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

[User] Is After Eight manufactured by Unilever?

[Assistant]
To answer this question, we need to identify the entities "After Eight" and "Unilever" and check if there is a relationship indicating that Unilever manufactures After Eight. Let's start by searching for these entities in the knowledge graph.

First, I will search for "After Eight" and "Unilever".

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

[Tool]
Top 10 entity alternatives:
1. Unilever (wd:Q157062): British multinational consumer goods company
2. Unilever, also known as UNVR, Unilever Tbk, Lever Zeepfabrieken N.V., PT Unilever  Tbk (wd:Q7885208): British company in
3. Unilever Headquarters, also known as Unilever, Weena 455 (wd:Q125679337): office building at Weena 455, Centrum, Rotterdam, the Netherlands
4. T.H. Estabrooks Co. Ltd., also known as Brooke Bond, Unilever (wd:Q116708935): Canadian business.
5. Hindustan Unilever, also known as Unilever (India), HUL, Hindustan Unilever Limited (wd:Q1619376): Indian consumer goods company
6. Unilever House (wd:Q2494434): grade II listed office building in City of London, United kingdom
7. Unilever Philippines, also known as Unilever (Philippines) (wd:Q18159894): Philippine subsidiary of Unilever
8. Unilever Pakistan, also known as Unilever Pakistan Limited (wd:Q7885211): Pakistani subsidiary of a foreign company
9. Unilever Gloucester, also known as Walls Ice Cream Factory (wd:Q96412295): food manufacturing site in Gloucester, England, UK
10. Unilever (Bydgoszcz) (wd:Q25415517): business enterprise

[Assistant]
From the search results, it appears that "After Eight" (chocolate brand of Nestle) is represented by `wd:Q388973`, and "Unilever" is represented by `wd:Q157062`.

Next, we need to check if there is a relationship indicating that Unilever manufactures After Eight. We can look for a property that indicates manufacturing or production. Let's search for such a property.

I will search for properties related to "manufactured by" or "produced by".

[Tool]
Top 10 property alternatives:
1. manufacturer, also known as manufactured by, provider, provided by, product of, producer (wd:P176 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): (main or final) manufacturer or producer of this product
2. made from material, also known as material used, manufactured out of, manufactured from, made of material, made of (wd:P186 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): material the subject or the object is made of or derived from (do not confuse with P10672 which is used for processes), uses
3. product or material produced, also known as products, product or service provided, product, material, or service produced or provided, product, producer of (wd:P1056 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): 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
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/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): 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. fabrication method, also known as process used, method of cooking, preparation method, obtained by, method used (wd:P2079 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): method, process or technique used to grow, cook, weave, build, assemble, manufacture the item, uses
6. creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): maker of this creative work or other object (where no more specific property exists)
7. location of creation, also known as manufactured in, manufacturing location, mint, minted at, photographed at (wd:P1071 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): place where the item was conceived or made; where applicable, location of final assembly, significant place
8. natural product of taxon, also known as produced by taxon, product of taxon, made from, fruit of (taxon), derived from (wd:P1582 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): links a natural product with its source (animal, plant, fungal, algal, etc.)
9. main building contractor, also known as contractor, general contractor, main contractor, prime contractor, constructed by (wd:P193 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): the main organization (or person) responsible for construction of this structure or building, manufacturer
10. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): time when an entity begins to exist; for date of official opening use P1619, start time

[Tool]
Top 10 property alternatives:
1. produced by, also known as secreted by (wd:P2849 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): links a class of biological features (such as a biochemical compound) with another class of biological entities known to produce it, has immediate cause
2. manufacturer, also known as manufactured by, provider, provided by, product of, producer (wd:P176 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): (main or final) manufacturer or producer of this product
3. fabrication method, also known as process used, method of cooking, preparation method, obtained by, method used (wd:P2079 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): method, process or technique used to grow, cook, weave, build, assemble, manufacture the item, uses
4. producer, also known as music producer, record producer, produced by, film producer, creative producer (wd:P162 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): person(s) who produced the film, musical work, theatrical produc...etc.) [for production company, use P272, video games - use P178]
5. product or material produced, also known as products, product or service provided, product, material, or service produced or provided, product, producer of (wd:P1056 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): 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
6. 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/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): 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
7. created for, also known as cause of creation, commissioned for, made for, occasion, on the occasion of (wd:P9883 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): a work, event, etc. for which the subject work was created (e.g.... play was created for; a film that a screenplay was written for)
8. production company, also known as broadcasting company, theatrical troupe, theatre company, theater company, studio (wd:P272 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): company that produced this film, audio or performing arts work
9. working title, also known as code name, codename, production name, production title, working name (wd:P1638 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): temporary name of a product or project used during its development
10. creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): maker of this creative work or other object (where no more specific property exists)

[Assistant]
From the search results, the property `manufacturer` (P176) seems to be the most appropriate for checking if Unilever manufactures After Eight.

Now, let's construct a SPARQL query to check if Unilever (wd:Q157062) is the manufacturer of After Eight (wd:Q388973).

I will execute the following SPARQL query:

```sparql
ASK WHERE {
  wd:Q388973 wdt:P176 wd:Q157062 .
}
```

This query will return `true` if Unilever is the manufacturer of After Eight, and `false` otherwise.

Let's execute this query.

[Tool] False

[Assistant]
The SPARQL query returned `False`, which means that Unilever is not the manufacturer of After Eight.

To provide a complete answer, I will also check if there is any other manufacturer listed for After Eight. This will help us confirm the manufacturer and ensure our answer is accurate.

Let's execute a query to find the manufacturer of After Eight.

```sparql
SELECT ?manufacturer WHERE {
  wd:Q388973 wdt:P176 ?manufacturer .
  OPTIONAL { ?manufacturer rdfs:label ?label . FILTER(LANG(?label) = 'en') }
}
```

This query will return the manufacturer of After Eight along with its label (if available).

Let's execute this query.

[Tool]
Got 1 row and 1 column:
| ?manufacturer       |
| ------------------- |
| Nestlé (wd:Q160746) |

[Assistant]
The query results show that the manufacturer of After Eight is Nestlé (wd:Q160746).

Therefore, the answer to the question "Is After Eight manufactured by Unilever?" is **False**.

Here is the final SPARQL query and answer:

```sparql
ASK WHERE {
  wd:Q388973 wdt:P176 wd:Q157062 .
}
```

The answer is **False**.

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

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?business WHERE {
  ?business wdt:P112 wd:Q317521
}

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

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

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

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

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

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

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

[Assistant] To answer this question, we need to identify the person in charge of Tesla and then find the businesses they have founded. Let's start by finding the person in charge of Tesla. This could be the CEO or another high-ranking executive. We'll search for Tesla and then look for the relevant property that indicates leadership.

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

[Assistant] From the search results, the correct entity for Tesla, Inc. is `wd:Q478214`. Now, let's find out who is in charge of Tesla, Inc. We will look for properties such as "CEO" or "founder" to identify the person in charge.

[Tool]
Top 10 property alternatives:
1. chief executive officer, also known as executive director, CEO, chief executive (wd:P169 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): highest-ranking corporate officer appointed as the CEO within an organization, director / manager, corporate officer
2. chief operating officer, also known as COO (wd:P1789 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): the chief operating officer of an organization
3. position held by head of the organization, also known as position held by head of the organisation, secretary's position, president's position, position held by head of the organization, office held by head of the organisation (wd:P2388 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): position of the head of this item
4. chairperson, also known as dean, headed by, leader, president, chairwoman (wd:P488 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): presiding member of an organization, group or body, director / manager, significant person
5. director / manager, also known as leader, manager, manager/director, managing director, Officer-in-Charge (wd:P1037 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): person who manages any kind of group, significant person
6. corporate officer, also known as executive officer (wd:P2828 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): person who holds a specific position, director / manager
7. founded by, also known as starter, co-founded by, started by, institutor, instituted by (wd:P112 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): founder or co-founder of this organization, religion, place or entity, creator
8. organization directed by the office or position, also known as leader of, head of, leads, organization directed by, organization directed from the office (wd:P2389 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): organization which is directed by this office
9. head of state, also known as leader, state headed by, monarch, president, queen (wd:P35 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): official with the highest formal authority in a country/state, director / manager, chairperson
10. rector, also known as chancellor, university president, Rector (academia), president (wd:P1075 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): senior official in an educational institution., director / manager, chairperson

[Assistant] The property for "chief executive officer" is `wdt:P169`. We will use this property to find the CEO of Tesla, Inc. Let's execute a SPARQL query to find the CEO of Tesla, Inc.

[Tool]
Got 1 row and 1 column:
| ?ceo                   |
| ---------------------- |
| Elon Musk (wd:Q317521) |

[Assistant] The CEO of Tesla, Inc. is Elon Musk, represented by the entity `wd:Q317521`. Next, we need to find the businesses that Elon Musk has founded. We will use the property "founded by" (`wdt:P112`) to find these businesses.

[Tool]
Got 13 rows and 1 column, showing the first 5 and last 5 rows below:
| ?business                                               |
| ------------------------------------------------------- |
| Texas Institute of Technology & Science (wd:Q109332244) |
| Thud (wd:Q115815194)                                    |
| X Corp. (wd:Q117617480)                                 |
| X Holdings Corp (wd:Q117705742)                         |
| xAI (wd:Q120599684)                                     |
| ...                                                     |
| Zip2 (wd:Q28222602)                                     |
| The Boring Company (wd:Q28874479)                       |
| Neuralink (wd:Q29043471)                                |
| X.com (wd:Q30686532)                                    |
| PayPal (wd:Q483959)                                     |

[Assistant]
Elon Musk has founded several businesses. Here are the businesses he has founded:

1. Texas Institute of Technology & Science (wd:Q109332244)
2. Thud (wd:Q115815194)
3. X Corp. (wd:Q117617480)
4. X Holdings Corp (wd:Q117705742)
5. xAI (wd:Q120599684)
6. Zip2 (wd:Q28222602)
7. The Boring Company (wd:Q28874479)
8. Neuralink (wd:Q29043471)
9. X.com (wd:Q30686532)
10. PayPal (wd:Q483959)

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

[Tool] Stopped generation process


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

blues

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

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

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

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

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

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

[Assistant]
To answer this question, we need to identify the genres associated with the band Cage the Elephant and then determine which of these genres has the fewest English characters. Let's start by finding the entity for Cage the Elephant and the property for genre.

### Step 1: Find the entity for Cage the Elephant
I will use the `search_entity` function to find the entity for Cage the Elephant.

```json
{
  "name": "search_entity",
  "arguments": {
    "kg": "wikidata",
    "query": "Cage the Elephant"
  }
}
```

### Step 2: Find the property for genre
I will use the `search_property` function to find the property for genre.

```json
{
  "name": "search_property",
  "arguments": {
    "kg": "wikidata",
    "query": "genre"
  }
}
```

### Step 3: Build the initial SPARQL query
Once we have the entity and property, we can build an initial SPARQL query to list the genres associated with Cage the Elephant.

### Step 4: Refine the SPARQL query to find the genre with the fewest characters
We will then refine the query to count the number of characters in each genre label and find the one with the fewest characters.

Let's start with the first step.

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

[Assistant]
The top result for "Cage the Elephant" is the American rock band with the identifier `wd:Q68061`. Next, let's find the property for genre.

I will use the `search_property` function to find the property for genre.

```json
{
  "name": "search_property",
  "arguments": {
    "kg": "wikidata",
    "query": "genre"
  }
}
```

Let's proceed with this step.

[Tool]
Top 10 property alternatives:
1. radio format, also known as format, radio station format, genre (wd:P415 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): describes the overall content broadcast on a radio station
2. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
3. subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
4. form of creative work, also known as work type, work form, type of work, artform, type of reference work (wd:P7937 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): structure of a creative work
5. Every Noise at Once ID, also known as Spotify genre, Every Noise at Once identifier, everynoise.com identifier (wd:P9881 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): identifier of a music genre, style, or scene on the Every Noise at Once website
6. MusicBrainz genre ID, also known as MB genre ID (wd:P8052 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): identifier for a genre on the MusicBrainz open music encyclopedia
7. for color scheme, also known as color mode, uses colour scheme, uses color scheme, theme, prefers colour scheme (wd:P8798 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): which color scheme this statement is designed for
8. based on, also known as modelled after, inspired by, iteration of, modeled after, fork of (wd:P144 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): the work(s) or inputs used as the basis for subject item; for fictional analog use P1074, references work, tradition or theory, inspired by
9. main subject, also known as primary topic, primary subject, primary keyword, plot keyword, of (wd:P921 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): primary topic of a work (see also P180: depicts), depicts
10. AllMusic genre/style ID, also known as AllMusic style identifier, AllMusic theme identifier, AllMusic theme ID, AllMusic style ID, AllMusic style/genre ID (wd:P9185 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): ID of a music genre or style in AllMusic

[Assistant]
The most relevant property for genre is `wd:P136`, which is used to describe the genre of a creative work or an artist's field of work.

Now, let's build an initial SPARQL query to list the genres associated with Cage the Elephant (wd:Q68061).

### Initial SPARQL Query
```sparql
SELECT ?genre ?genreLabel
WHERE {
  wd:Q68061 wdt:P136 ?genre.
  OPTIONAL { ?genre rdfs:label ?genreLabel . FILTER(LANG(?genreLabel) = "en") }
}
```

This query will return the genres associated with Cage the Elephant along with their English labels. We will then refine this query to find the genre with the fewest characters.

Let's execute this initial query.

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

[Assistant]
The initial query returned the genres associated with Cage the Elephant along with their English labels. Now, we need to refine the query to find the genre with the fewest characters.

### Refined SPARQL Query
We will use the `STRLEN` function to calculate the length of the genre labels and then use `ORDER BY` to sort the results by the length of the labels in ascending order. Finally, we will use `LIMIT 1` to get the genre with the fewest characters.

```sparql
SELECT ?genre ?genreLabel (STRLEN(?genreLabel) AS ?length)
WHERE {
  wd:Q68061 wdt:P136 ?genre.
  OPTIONAL { ?genre rdfs:label ?genreLabel . FILTER(LANG(?genreLabel) = "en") }
}
ORDER BY ASC(?length)
LIMIT 1
```

Let's execute this refined query.

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

[Assistant]
The genre with the fewest English characters associated with Cage the Elephant is "blues" with 5 characters.

### Final SPARQL Query and Answer
```sparql
SELECT ?genre ?genreLabel (STRLEN(?genreLabel) AS ?length)
WHERE {
  wd:Q68061 wdt:P136 ?genre.
  OPTIONAL { ?genre rdfs:label ?genreLabel . FILTER(LANG(?genreLabel) = "en") }
}
ORDER BY ASC(?length)
LIMIT 1
```

The answer to the question is "blues".

Let's provide the final answer.

[Tool] Stopped generation process