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 ?partner ?gender WHERE {
  VALUES ?ginsberg {
    wd:Q6711
  }
  VALUES ?genderBinary {
    wd:Q6581097 wd:Q6581072
  }
  ?ginsberg wdt:P451 ?partner .
  ?partner wdt:P21 ?gender .
  FILTER ( ?gender IN ( ?genderBinary ) ) OPTIONAL {
    ?partner rdfs:label ?partnerLabel FILTER ( lang( ?partnerLabel ) = "en" )
  }
  OPTIONAL {
    ?gender rdfs:label ?genderLabel FILTER ( lang( ?genderLabel ) = "en" )
  }
}

The binary gender of Allen Ginsberg's partner (Peter Orlovsky) is male.

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

You have access to the following knowledge graphs:
wikidata at http://amur:7001

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 break down the question:

1. We need to identify the entity for "Allen Ginsberg".
2. Then, we need to find the property that links Allen Ginsberg to his partner(s).
3. Next, we need to find the property that describes the gender of the partner(s).
4. Finally, we need to check if the gender is binary (male or female).

Let's start by searching for the entity "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 most relevant entity for "Allen Ginsberg" is wd:Q6711 (the American poet and writer).

Next, I need to find the property that links Allen Ginsberg to his partner(s). I'll search for properties related to "partner" for this entity.

[Tool]
Top 10 property alternatives:
1. unmarried partner, also known as romantic partner, partner of, partners, posslq, relationship (wd:P451 as wdt/p): 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 p): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative
3. 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
4. employer, also known as working at, working for, working place, works at, works for (wd:P108 as wdt/p): person or organization for which the subject works or worked, affiliation
5. occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt/p): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
6. father, also known as son of, child of, parent, is son of, is daughter of (wd:P22 as wdt/p): male parent of the subject. For stepfather, use "stepparent" (P3448), parent
7. ethnic group, also known as ethnic or cultural origin, tribal affiliation, race, people, ethnicity (wd:P172 as p): subject's ethnicity (consensus is that a VERY high standard of p...agreed on by scholars, or 3) is fictional and portrayed as such)
8. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdt/p): the object is a country that recognizes the subject as its citizen, country
9. field of work, also known as scientific discipline, scientific area, responsible for, research on, research fields (wd:P101 as wdt/p): specialization of a person or organization; see P106 for the occupation, interested in
10. notable work, also known as artwork, wrote, writer of, works, work (wd:P800 as wdt/p): notable scientific, artistic or literary work, or other work of significance among subject's works

No other items found

[Assistant]
The relevant properties for linking Allen Ginsberg to a partner are:
- "unmarried partner" (wdt:P451)
- "spouse" (wdt:P26)

Since the question asks about "partner", I should consider both properties to cover both married and unmarried partners.

Next, I need to find the property that describes the gender of the partner(s). I'll search for properties related to "gender".

[Tool]
Top 10 property alternatives:
1. grammatical gender, also known as gender (wd:P5185 as pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): grammatical gender of the word
2. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): 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 pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): grammatical features required or generally used with lexeme or form of lexeme
4. has grammatical gender, also known as grammatical genders, has genders (wd:P5109 as pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): specific form of noun class system of a language. Use qualifier ... subject of" (P805) to link to language specific item if present
5. personal pronoun, also known as gender pronoun, personal gender pronoun, personal pronouns, PGP, PGPs (wd:P6553 as pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): personal pronoun(s) this person goes by
6. semantic gender, also known as natural gender (wd:P10339 as pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): used when a word is only used to refer to people of this gender or to animals of this sex, independent of the grammatical gender
7. female form of label, also known as female form of label (string), female gender sense, feminine form of label (wd:P2521 as pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): female form of name or title (for male use P3321)
8. gender educated (wd:P7419 as pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): 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 pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): 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 pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): 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) is the correct one to use for describing the gender of a person.

Now, I need to identify the IRIs for "male" and "female" in Wikidata, as these represent binary genders. I'll search for these entities.

[Tool]
Top 10 entity alternatives:
1. Malé, also known as Malé City (wd:Q9347): capital of the Maldives
2. Malé, also known as Malè (wd:Q295126): Italian comune
3. Mâle, also known as Male (wd:Q1347276): former commune in Orne, France
4. male, also known as guy, m, male character, male gender, male human (wd:Q6581097): to be used in "sex or gender" (P21) to indicate that the human s...gender" (P10339) to indicate that a word refers to a male person
5. Male (wd:Q4278140): village in Dachne rural hromada (municipality), Odesa Raion (district), Odesa Oblast, Ukraine
6. Enrique Ossorio, also known as Male, Enrique Matías Ossorio Crespo (wd:Q5833669): Spanish politician, politician
7. Male, also known as Male language, Male (Papua New Guinea) (wd:Q6742927): language
8. Male (wd:Q1887100): suburb of Bruges, West Flanders, Belgium
9. Malerzowice Małe (wd:Q1754889): village in Opole, Poland
10. Males, also known as Male (wd:Q6743117): village in Greece

[Tool]
Top 10 entity alternatives:
1. female organism, also known as ♀, female, female animal, female creature, sex — female (wd:Q43445): organism of the female sex
2. Female (wd:Q639354): 1933 Warner Bros. pre-code film
3. female, also known as female human, women, woman, lady, human female (wd:Q6581072): to be used in "sex or gender" (P21) to indicate that the human s...nder" (P10339) to indicate that a word refers to a female person
4. Female, also known as Fîmeiru ,(Female) (wd:Q5442715): 2005 film directed by Shinya Tsukamoto
5. The Female, also known as Female (wd:Q18708947): 1924 film by Sam Wood
6. female connector, also known as female contact, female fastener, female (wd:Q11659367): gender of connectors and fasteners
7. Female (wd:Q47128284): song by Keith Urban
8. Female (wd:Q5442717): 1933 novel by Donald Henderson Clarke
9. Female (wd:Q130232348): enemy type in the 2023 video game World of Horror
10. Female (wd:Q63650079): theatrical character in the play "Yerma"

[Assistant]
The relevant entities for binary gender are:
- male: wd:Q6581097
- female: wd:Q6581072

Now, I will construct a SPARQL query that:
- Finds Allen Ginsberg's partners (using both wdt:P451 and wdt:P26)
- Gets the partner's gender (wdt:P21)
- Returns the partner and their gender, but only if the gender is "male" or "female" (binary)

I will also include optional labels for clarity.

[Tool]
Failed to call function execute:
The following knowledge graph items are used in the SPARQL query without being known from previous function calls:
wdt:P26

[Tool]
Top 10 property alternatives:
1. spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as p): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative
2. unmarried partner, also known as romantic partner, partner of, partners, posslq, relationship (wd:P451 as wdt/p): someone with whom the person is in a relationship without being married. Use "spouse" (P26) for married couples, significant person
3. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as wdt/p): full name of a person at birth, if different from their current, generally used name, name
4. occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt/p): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
5. given name, also known as name, proper name, personal name, middle name, forename (wd:P735 as wdt/p): first name or another given name of this person; values used with the property should not link disambiguations nor family names, name
6. father, also known as son of, child of, parent, is son of, is daughter of (wd:P22 as wdt/p): male parent of the subject. For stepfather, use "stepparent" (P3448), parent
7. ethnic group, also known as ethnic or cultural origin, tribal affiliation, race, people, ethnicity (wd:P172 as p): subject's ethnicity (consensus is that a VERY high standard of p...agreed on by scholars, or 3) is fictional and portrayed as such)
8. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as wdt/p): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)
9. family name, also known as clan name, last name, surname (wd:P734 as wdt/p): part of full name of person, name
10. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdt/p): the object is a country that recognizes the subject as its citizen, country

No other items found

[Assistant]
The property for "spouse" is indeed wd:P26, and for "unmarried partner" is wd:P451. Both can be used as direct properties (wdt:P26, wdt:P451).

I will now retry the query, ensuring that both properties are used correctly to find all partners of Allen Ginsberg and their binary gender.

[Tool]
Failed to call function execute:
The following knowledge graph items are used in the SPARQL query without being known from previous function calls:
wdt:P26

[Tool]
Got 65,536 rows and 3 columns, showing the first 10 rows below:
| subject                                       | property         | object                             |
| --------------------------------------------- | ---------------- | ---------------------------------- |
| Evelyn Mase (wd:Q10492742)                    | spouse (wdt:P26) | Nelson Mandela (wd:Q8023)          |
| Julius Caesar (wd:Q1048)                      | spouse (wdt:P26) | Pompeia (wd:Q234825)               |
| Mahatma Gandhi (wd:Q1001)                     | spouse (wdt:P26) | Kasturba Gandhi (wd:Q264908)       |
| Charles Darwin (wd:Q1035)                     | spouse (wdt:P26) | Emma Darwin (wd:Q242147)           |
| Memorial Museum of Sarı Ashig (wd:Q110104295) | spouse (wdt:P26) | human (wd:Q5)                      |
| Dante Alighieri (wd:Q1067)                    | spouse (wdt:P26) | Gemma Donati (wd:Q3759380)         |
| James Thomas Sprinkle (wd:Q107571083)         | spouse (wdt:P26) | year (wd:Q577)                     |
| Zakaria A. Yakubu (wd:Q106170755)             | spouse (wdt:P26) | marriage (wd:Q8445)                |
| Bill Clinton (wd:Q1124)                       | spouse (wdt:P26) | Hillary Clinton (wd:Q6294)         |
| Carl Linnaeus (wd:Q1043)                      | spouse (wdt:P26) | Sara Elisabeth Moræa (wd:Q3473264) |
| ...                                           | ...              | ...                                |

[Tool]
Got 990 rows and 3 columns, showing the first 10 rows below:
| subject                   | property                         | object                                                                                |
| ------------------------- | -------------------------------- | ---------------------------------------------------------------------------------------------- |
| Allen Ginsberg (wd:Q6711) | instance of (wdt:P31)            | human (wd:Q5)                                                                                |
| Allen Ginsberg (wd:Q6711) | occupation (wdt:P106)            | writer (wd:Q36180)                                                                             |
| Allen Ginsberg (wd:Q6711) | sex or gender (wdt:P21)          | male (wd:Q6581097)                                                                             |
| Allen Ginsberg (wd:Q6711) | given name (wdt:P735)            | Irwin (wd:Q16277131)                                                                           |
| Allen Ginsberg (wd:Q6711) | date of birth (wdt:P569)         | 1926-06-03T00:00:00Z (xsd:dateTime)                                                            |
| Allen Ginsberg (wd:Q6711) | Commons category (wdt:P373)      | Allen Ginsberg                                                                                |
| Allen Ginsberg (wd:Q6711) | image (wdt:P18)                  | <http://commons.wikimedia.org/wiki/Special:FilePath/Allen%20Ginsberg%201979%20-%20cropped.jpg> |
| Allen Ginsberg (wd:Q6711) | country of citizenship (wdt:P27) | United States (wd:Q30)                                                                         |
| Allen Ginsberg (wd:Q6711) | family name (wdt:P734)           | Ginsberg (wd:Q21484848)                                                                        |
| Allen Ginsberg (wd:Q6711) | place of birth (wdt:P19)         | Newark (wd:Q25395)                                                                             |
| ...                       | ...                              | ...                                                                                |

[Tool]
Got 1 row and 3 columns:
| subject                   | property                     | object                       |
| ------------------------- | ---------------------------- | ---------------------------- |
| Allen Ginsberg (wd:Q6711) | unmarried partner (wdt:P451) | Peter Orlovsky (wd:Q1983102) |

[Tool]
Got 314 rows and 3 columns, showing the first 10 rows below:
| subject                      | property                         | object                                                                                |
| ---------------------------- | -------------------------------- | -------------------------------------------------------------------------------------------------------- |
| Peter Orlovsky (wd:Q1983102) | instance of (wdt:P31)            | human (wd:Q5)                                                                                |
| Peter Orlovsky (wd:Q1983102) | occupation (wdt:P106)            | actor (wd:Q33999)                                                                                |
| Peter Orlovsky (wd:Q1983102) | sex or gender (wdt:P21)          | male (wd:Q6581097)                                                                                |
| Peter Orlovsky (wd:Q1983102) | given name (wdt:P735)            | Peter (wd:Q2793400)                                                                                |
| Peter Orlovsky (wd:Q1983102) | date of birth (wdt:P569)         | 1933-07-08T00:00:00Z (xsd:dateTime)                                                                      |
| Peter Orlovsky (wd:Q1983102) | Commons category (wdt:P373)      | Peter Orlowski                                                                                |
| Peter Orlovsky (wd:Q1983102) | image (wdt:P18)                  | <http://commons.wikimedia.org/wiki/Special:FilePath/Allen%20Ginsberg%20und%20Peter%20Orlowski%20ArM.jpg> |
| Peter Orlovsky (wd:Q1983102) | country of citizenship (wdt:P27) | United States (wd:Q30)                                                                                |
| Peter Orlovsky (wd:Q1983102) | family name (wdt:P734)           | Orlovsky (wd:Q37029218)                                                                                |
| Peter Orlovsky (wd:Q1983102) | place of birth (wdt:P19)         | Manhattan (wd:Q11299)                                                                                |
| ...                          | ...                              | ...                                                                                |

[Tool]
Got 1 row and 3 columns:
| subject                      | property                | object             |
| ---------------------------- | ----------------------- | ------------------ |
| Peter Orlovsky (wd:Q1983102) | sex or gender (wdt:P21) | male (wd:Q6581097) |

[Tool] Got no rows and 3 columns

[Assistant]
Allen Ginsberg's partner (using the "unmarried partner" property) is Peter Orlovsky (wd:Q1983102). Peter Orlovsky's gender is "male" (wd:Q6581097), which is one of the binary genders.

I will now provide the final SPARQL query and answer.

[Tool] Stopped generation process


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

The youngest member of (G)I-dle is Shuhua (wd:Q55287305).

[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 http://amur:7001

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 break down the question:

1. The question asks for the youngest member of (G)I-dle, a K-pop group.
2. We need to:
   - Identify the Wikidata entity for (G)I-dle.
   - Find its members.
   - For each member, get their date of birth.
   - Determine which member has the most recent date of birth (i.e., is the youngest).

First, I'll search for the entity for (G)I-dle.

[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 (G)I-dle, the South Korean girl group, is wd:Q51885404.

Next, I need to find the members of this group. I'll look for properties related to "member" or "has member" for this entity.

[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) is often used to indicate members of a group. I'll use this property to find the members of (G)I-dle (wd:Q51885404).

Next, I'll write a query to get all entities that are "parts" (members) of (G)I-dle. Then, for each member, I'll try to get their date of birth to determine who is the youngest.

[Tool]
Got 6 rows and 1 column:
| member                     |
| -------------------------- |
| Jeon Soyeon (wd:Q26707915) |
| Shuhua (wd:Q55287305)      |
| Song Yuqi (wd:Q55287306)   |
| Cho Mi-yeon (wd:Q56259927) |
| Minnie (wd:Q56761923)      |
| Soojin (wd:Q61100297)      |

[Assistant]
I have found the following members of (G)I-dle:
- Jeon Soyeon (wd:Q26707915)
- Shuhua (wd:Q55287305)
- Song Yuqi (wd:Q55287306)
- Cho Mi-yeon (wd:Q56259927)
- Minnie (wd:Q56761923)
- Soojin (wd:Q61100297)

Next, I need to get the date of birth for each member. I'll search for the relevant property for "date of birth" to ensure I use the correct one.

[Tool]
Top 10 property alternatives:
1. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): date on which the subject was born, inception
2. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): most specific known birth location of a person, animal or fictional character, location
3. birthday, also known as b-day, bday, birth day (wd:P3150 as pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): item for day and month on which the subject was born. Used when full "date of birth" (P569) isn't known., date of birth
4. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): the object is a country that recognizes the subject as its citizen, country
5. commemorates, also known as monument to, memorial to, memorializes, marks, in memory of (wd:P547 as pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): what the place, monument, memorial, or holiday, commemorates, main subject
6. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): full name of a person at birth, if different from their current, generally used name, name
7. date of death, also known as DOD, deathdate, died, died on, year of death (wd:P570 as pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): dissolved, abolished or demolished date, date on which the subject died, end time
8. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): time when an entity begins to exist; for date of official opening use P1619, start time
9. website username or ID, also known as user name, website username, website ID, username in social media, username (wd:P554 as pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): username or identifier on a website that the person or movement ... account on, for use as qualifier of "website account on" (P553)
10. pseudonym, also known as nom de plume, nom-de-plume, nome de guerre, pen name, ring name (wd:P742 as pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): alias used by someone (for nickname use P1449), name

[Assistant]
The property for "date of birth" is wdt:P569.

Now, I'll write a query to get the date of birth for each member of (G)I-dle, and then select the member with the most recent date of birth (i.e., the youngest member). I'll also try to get their label for clarity.

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

[Tool] Stopped generation process


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

The author of The Hellbound Heart is Clive Barker (wd:Q298761).

[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 http://amur:7001

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 break down the question:

1. The entity we need is "The Hellbound Heart", which is likely a book or novel.
2. The property we need is "author".

First, I'll search for the entity "The Hellbound Heart" in Wikidata.

[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 most relevant entity is "The Hellbound Heart" (wd:Q3521239), described as a novella by Clive Barker.

Next, I need to find the property for "author" in Wikidata.

[Tool]
Top 10 property alternatives:
1. theorized by, also known as author, supported by, suggested by, proposer, proposed by (wd:P8403 as pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): 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 pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): author of song lyrics, author
3. author, also known as writer, written by, poet, playwright, maker (wd:P50 as pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/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
4. notable work, also known as artwork, wrote, writer of, works, work (wd:P800 as pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): 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 pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): 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 pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): 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 pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): 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 pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): 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 pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): 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 pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): use as qualifier to indicate how the object's value was given in the source, name

[Assistant]
The most relevant property for "author" is wd:P50 ("author").

Now, I will construct a SPARQL query to find the author(s) of "The Hellbound Heart" (wd:Q3521239) using the property "author" (wd:P50). I will also optionally retrieve the label of the author for readability.

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

[Tool] Stopped generation process


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

No, After Eight is not manufactured by Unilever. It is manufactured by Nestlé.

[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 http://amur:7001

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]
Let's break down the question:

- "After Eight" is likely a product or brand.
- "manufactured by" implies a relationship between a product and a company, specifically Unilever.

Step 1: Identify the entity for "After Eight".
Step 2: Identify the property for "manufacturer".
Step 3: Identify the entity for "Unilever".
Step 4: Construct an ASK query to check if After Eight is manufactured by Unilever.

Let's start by searching for "After Eight" in Wikidata.

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

[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

[Tool]
Top 10 property alternatives:
1. manufacturer, also known as manufactured by, provider, provided by, product of, producer (wd:P176 as pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): (main or final) manufacturer or producer of this product
2. 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 pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): 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
3. 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 pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): 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. location of creation, also known as manufactured in, manufacturing location, mint, minted at, photographed at (wd:P1071 as pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): place where the item was conceived or made; where applicable, location of final assembly, significant place
5. made from material, also known as material used, manufactured out of, manufactured from, made of material, made of (wd:P186 as pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): material the subject or the object is made of or derived from (do not confuse with P10672 which is used for processes), uses
6. creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): maker of this creative work or other object (where no more specific property exists)
7. fabrication method, also known as process used, method of cooking, preparation method, obtained by, method used (wd:P2079 as pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): method, process or technique used to grow, cook, weave, build, assemble, manufacture the item, uses
8. brand, also known as main brand (wd:P1716 as pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): commercial brand associated with the item
9. author, also known as writer, written by, poet, playwright, maker (wd:P50 as pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/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
10. serial number, also known as s/n, serial code, MSN, manufacturer serial number, construction number (wd:P2598 as pq/psv/pqn/pqv/psn/wdtn/ps/prn/p/pr/prv/wdt): an identifier for a specific object among the same product. Not a product code or model number

[Tool] False

[Tool]
Got 125 rows and 3 columns, showing the first 10 rows below:
| subject                  | property                                 | object                                                                            |
| ------------------------ | ---------------------------------------- | --------------------------------------------------------------------------------- |
| After Eight (wd:Q388973) | instance of (wdt:P31)                    | trademark (wd:Q167270)                                                            |
| After Eight (wd:Q388973) | Commons category (wdt:P373)              | After Eight                                                                       |
| After Eight (wd:Q388973) | image (wdt:P18)                          | <http://commons.wikimedia.org/wiki/Special:FilePath/Aftereightchocolatethins.jpg> |
| After Eight (wd:Q388973) | subclass of (wdt:P279)                   | confection (wd:Q5159627)                                                          |
| After Eight (wd:Q388973) | inception (wdt:P571)                     | 1962-01-01T00:00:00Z (xsd:dateTime)                                               |
| After Eight (wd:Q388973) | official website (wdt:P856)              | <https://www.nestle.co.uk/en-gb/brands/chocolate_and_confectionery/boxed>         |
| After Eight (wd:Q388973) | creator (wdt:P170)                       | Rowntree's (wd:Q695070)                                                           |
| After Eight (wd:Q388973) | manufacturer (wdt:P176)                  | Nestlé (wd:Q160746)                                                               |
| After Eight (wd:Q388973) | Freebase ID (wdt:P646)                   | /m/05987f                                                                         |
| After Eight (wd:Q388973) | Wolfram Language entity code (wdt:P4839) | Entity["Food", "AfterEightChocolateMint::563w2"]                                  |
| ...                      | ...                                      | ...                                                                               |

[Tool]
Got 17 rows and 3 columns, showing the first 10 rows below:
| subject                 | property                | object                |
| ----------------------- | ----------------------- | --------------------- |
| Lipton (wd:Q874407)     | manufacturer (wdt:P176) | Unilever (wd:Q157062) |
| Marmite (wd:Q1331998)   | manufacturer (wdt:P176) | Unilever (wd:Q157062) |
| Dove (wd:Q962709)       | manufacturer (wdt:P176) | Unilever (wd:Q157062) |
| Axe (wd:Q791930)        | manufacturer (wdt:P176) | Unilever (wd:Q157062) |
| Rexona (wd:Q1183694)    | manufacturer (wdt:P176) | Unilever (wd:Q157062) |
| Viennetta (wd:Q2348879) | manufacturer (wdt:P176) | Unilever (wd:Q157062) |
| Sunsilk (wd:Q596546)    | manufacturer (wdt:P176) | Unilever (wd:Q157062) |
| Timotei (wd:Q1997791)   | manufacturer (wdt:P176) | Unilever (wd:Q157062) |
| Zendium (wd:Q2743513)   | manufacturer (wdt:P176) | Unilever (wd:Q157062) |
| TRESemmé (wd:Q7671316)  | manufacturer (wdt:P176) | Unilever (wd:Q157062) |
| ...                     | ...                     | ...                   |

[Tool]
Got 31 rows and 3 columns, showing the first 10 rows below:
| subject                      | property                | object              |
| ---------------------------- | ----------------------- | ------------------- |
| Nescafé (wd:Q503191)         | manufacturer (wdt:P176) | Nestlé (wd:Q160746) |
| Kit Kat (wd:Q367251)         | manufacturer (wdt:P176) | Nestlé (wd:Q160746) |
| Maggi (wd:Q688424)           | manufacturer (wdt:P176) | Nestlé (wd:Q160746) |
| Nesquik (wd:Q1150326)        | manufacturer (wdt:P176) | Nestlé (wd:Q160746) |
| Smarties (wd:Q1400476)       | manufacturer (wdt:P176) | Nestlé (wd:Q160746) |
| After Eight (wd:Q388973)     | manufacturer (wdt:P176) | Nestlé (wd:Q160746) |
| Dolce Gusto (wd:Q1235370)    | manufacturer (wdt:P176) | Nestlé (wd:Q160746) |
| Lion Bar (wd:Q1827229)       | manufacturer (wdt:P176) | Nestlé (wd:Q160746) |
| Quality Street (wd:Q1307165) | manufacturer (wdt:P176) | Nestlé (wd:Q160746) |
| Aero chocolate (wd:Q2989610) | manufacturer (wdt:P176) | Nestlé (wd:Q160746) |
| ...                          | ...                     | ...                 |

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

[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 ?business ?businessLabel WHERE {
  ?business wdt:P112 wd:Q317521 .
  OPTIONAL {
    ?business rdfs:label ?businessLabel .
    FILTER ( LANG( ?businessLabel ) = "en" )
  }
}

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

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

[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 http://amur:7001

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]
Let's break down the question:

1. We need to identify the person in charge of Tesla (likely the CEO or a similar role).
2. Then, we need to find businesses (companies) that this person has founded.

Step 1: Find the entity for Tesla and the property for "person in charge" (CEO or similar).
Step 2: Find the property for "founded by" or "founder".
Step 3: Combine these to get the businesses founded by the person in charge of Tesla.

Let's start by searching for the entity "Tesla" in Wikidata.

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

[Assistant]
The correct entity for Tesla, the company, is wd:Q478214 (Tesla, Inc.).

Next, I need to find the property that links Tesla, Inc. to its "person in charge" (such as CEO or similar roles). I'll search for properties related to "CEO" or "head" for this entity.

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

No other items found

[Assistant]
The property for "chief executive officer" (CEO) is wd:P169.

Now, I need to find out who is the current CEO of Tesla, Inc. (wd:Q478214) using this property.

[Tool]
Got 1 row and 3 columns:
| subject                  | property                           | object                 |
| ------------------------ | ---------------------------------- | ---------------------- |
| Tesla, Inc. (wd:Q478214) | chief executive officer (wdt:P169) | Elon Musk (wd:Q317521) |

[Assistant]
The current CEO of Tesla, Inc. is Elon Musk (wd:Q317521).

Next, I need to find businesses (companies) that were founded by Elon Musk. For this, I will use the property "founded by" (wd:P112) and look for companies where Elon Musk is the founder.

[Tool]
Got 14 rows and 3 columns, showing the first 10 rows below:
| subject                           | property              | object                 |
| --------------------------------- | --------------------- | ---------------------- |
| SpaceX (wd:Q193701)               | founded by (wdt:P112) | Elon Musk (wd:Q317521) |
| PayPal (wd:Q483959)               | founded by (wdt:P112) | Elon Musk (wd:Q317521) |
| OpenAI (wd:Q21708200)             | founded by (wdt:P112) | Elon Musk (wd:Q317521) |
| Neuralink (wd:Q29043471)          | founded by (wdt:P112) | Elon Musk (wd:Q317521) |
| The Boring Company (wd:Q28874479) | founded by (wdt:P112) | Elon Musk (wd:Q317521) |
| X Corp. (wd:Q117617480)           | founded by (wdt:P112) | Elon Musk (wd:Q317521) |
| X.com (wd:Q30686532)              | founded by (wdt:P112) | Elon Musk (wd:Q317521) |
| xAI (wd:Q120599684)               | founded by (wdt:P112) | Elon Musk (wd:Q317521) |
| Zip2 (wd:Q28222602)               | founded by (wdt:P112) | Elon Musk (wd:Q317521) |
| Thud (wd:Q115815194)              | founded by (wdt:P112) | Elon Musk (wd:Q317521) |
| ...                               | ...                   | ...                    |

[Tool]
Got 14 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)                                     |

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

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?genre ?label ( STRLEN( ?label ) AS ?length ) WHERE {
  VALUES ?genre {
    wd:Q9759 wd:Q3071 wd:Q11366 wd:Q183504 wd:Q206159 wd:Q211573
  }
  ?genre rdfs:label ?label .
  FILTER ( LANG( ?label ) = "en" )
}
ORDER BY ?length
LIMIT 1

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

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

You have access to the following knowledge graphs:
wikidata at http://amur:7001

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]
Let's break down the question:

1. We need to identify the entity "Cage the Elephant" in Wikidata.
2. We need to find all genres ("genre" property) that "Cage the Elephant" belongs to.
3. For each genre, we need to get its English label.
4. We need to count the number of English characters in each genre label.
5. Finally, we need to select the genre with the fewest English characters.

Let's proceed step by step.

First, let's search for the entity "Cage the Elephant" in Wikidata.

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

[Assistant]
The correct entity for the band "Cage the Elephant" is wd:Q68061.

Next, I need to find the genres that "Cage the Elephant" belongs to. The property for genre is likely "genre" or similar. I'll search for properties related to "genre" for this entity.

[Tool]
Top 10 property alternatives:
1. 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
2. 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
3. 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
4. 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)
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. AllMusic artist ID, also known as AllMusic, AllMusic ID, amg artist (wd:P1728 as wdt/p): identifier for an artist, musical group, or record label in the AllMusic database (record labels are listed as "artists")
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. 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).
9. work period (start), also known as start working, flourished (start), start time for work, start date of activity, fl. (start) (wd:P2031 as wdt/p): start of period during which a person or group flourished (fl. = "floruit") in their professional activity, start time, floruit
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 for genre is wd:P136.

Now, I will list the genres (wdt:P136) for "Cage the Elephant" (wd:Q68061).

[Tool]
Got 6 rows and 3 columns:
| subject                       | property         | object                        |
| ----------------------------- | ---------------- | ----------------------------- |
| Cage the Elephant (wd:Q68061) | genre (wdt:P136) | blues (wd:Q9759)              |
| Cage the Elephant (wd:Q68061) | genre (wdt:P136) | punk rock (wd:Q3071)          |
| Cage the Elephant (wd:Q68061) | genre (wdt:P136) | alternative rock (wd:Q11366)  |
| Cage the Elephant (wd:Q68061) | genre (wdt:P136) | indie rock (wd:Q183504)       |
| Cage the Elephant (wd:Q68061) | genre (wdt:P136) | psychedelic rock (wd:Q206159) |
| Cage the Elephant (wd:Q68061) | genre (wdt:P136) | garage rock (wd:Q211573)      |

[Assistant]
Cage the Elephant belongs to the following genres:
- blues (wd:Q9759)
- punk rock (wd:Q3071)
- alternative rock (wd:Q11366)
- indie rock (wd:Q183504)
- psychedelic rock (wd:Q206159)
- garage rock (wd:Q211573)

Next, I need to get the English labels for these genres and count the number of English characters in each label. Then, I will select the genre with the fewest English characters.

I will write a SPARQL query to retrieve the English labels for these genres, count their length, and select the one with the fewest characters.

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

[Tool] Stopped generation process