PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ( COUNT( ?performer ) AS ?count ) WHERE {
  wd:Q79037 wdt:P175 ?performer .
  ?performer wdt:P27 wd:Q145 .
}

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

There is 1 Spider-Man performer who is a citizen of the United Kingdom.

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

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

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

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

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

[User] how many of spiderman perfomers are citizens of the united kingdom?

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

[Tool]
Example 1:
Question:
How large is the area of UK?

SPARQL:
SELECT ?area WHERE {
  wd:Q145 wdt:P2046 ?area .
}

Using entities:
United Kingdom, also known as U.K., UK, U. K., U K, United Kingdom of Great Britain and Northern Ireland (wd:Q145): country in north-west Europe

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

Example 2:
Question:
How many James Bond movies do exist?

SPARQL:
SELECT ( COUNT( ?s1 ) as ?c ) WHERE {
  ?s1 wdt:P31 wd:Q11424 .
  ?s1 ?p wd:Q2009573 .
  FILTER ( ?p = wdt:P144 || ?p = wdt:P674 )
}

Using entities:
film, also known as cinematic work, moving picture, movie, motion pictures, motion picture (wd:Q11424): sequence of images that give the impression of movement, stored on film stock
James Bond, also known as Agent 007, double o seven, 007 (wd:Q2009573): secret agent, invented by novellist Ian Fleming, 00 Agent, spy

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

Example 3:
Question:
In which UK city are the headquarters of the MI6?

SPARQL:
SELECT DISTINCT ?o1 WHERE {
  wd:Q184560 wdt:P159 ?o1 .
  ?o1 wdt:P31 wd:Q515 .
}

Using entities:
Secret Intelligence Service, also known as British intelligence agency, SIS, Secret Intelligence Service of the United Kingdom, Military Intelligence, Section 6, MI6 Secret Intelligence Service (wd:Q184560): British intelligence agency
city, also known as cities (wd:Q515): large human settlement

Using properties:
headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as wdt): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

[Assistant] Based on these examples, we need to identify the performers who played Spider-Man and then check their citizenship. Let's first find the entity for Spider-Man.

[Tool]
Top 10 entity alternatives:
1. Spider-Man, also known as Wallcrawler, The Amazing Spider-Man, The Human Spider, The Fantastic Spider-Man, Web-slinger (wd:Q79037): fictional character in Marvel Comics, photographer, scientist, superhero, inventor, teacher
2. Spider-Man (wd:Q484442): 2002 American film directed by Sam Raimi
3. Spider-Man, also known as Marvel's Spider-Man (wd:Q25340029): 2018 video game developed by Insomniac Games
4. Spider-Man, also known as Spider-Man: The Animated Series (wd:Q569934): American animated television series from 1994–1998
5. Miles Morales, also known as Ultimate Spider-Man, Spider-Man, Miles Gonzalo Morales (wd:Q59826): fictional character in Marvel Comics, superhero, student
6. Spider-Man, also known as Spider-Man 2000 (wd:Q288296): 2000 video game
7. Peter Parker, also known as Peter #1, Peter 1, Peter One, Peter-One, Spider-Man (wd:Q23991129): fictional character from the Marvel Cinematic Universe
8. Marvel's Spider-Man, also known as Spider-Man (wd:Q28207200): American animated television series
9. Spider-Man, also known as Supaidāman (wd:Q2087538): Japanese-US late 1970's television series
10. Spider-Man (wd:Q2333456): US late 1960s animated television series

[Assistant] The correct entity for the fictional character Spider-Man is `wd:Q79037`. Now, let's find the property that links actors to the characters they play.

[Tool]
Top 10 property alternatives:
1. performer, also known as actor, sung by, singer, recording by, recorded by (wd:P175 as wdt/p): actor, musician, band or other performer associated with this role or musical work, contributor to the creative work or subject
2. voice actor, also known as voice actors, voice dubber, voice actress, voice actresses, voiced by (wd:P725 as wdt/p): performer of a spoken role in a creative work such as animation,... (P453) as qualifier] [use "cast member" (P161) for live acting], film crew member, cast member
3. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt/p): most specific known birth location of a person, animal or fictional character, location
4. present in work, also known as is shown in, in work, in narrative, character in, from work (wd:P1441 as wdt/p): this (fictional or fictionalized) entity, place, or person appea...r works, P1343 for entities described in non-fictional accounts)
5. 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
6. 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)
7. 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
8. 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)
9. superhuman feature or ability, also known as has superpower, magic, magic ability, magical ability, supernatural abilities (wd:P2563 as wdt/p): superhuman, supernatural, or paranormal abilities that the fictional subject exhibits, uses
10. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as wdt/p): language(s) that a person or a people speaks, writes or signs, including the native language(s)

No other items found

[Assistant] The property `wdt:P175` (performer) links actors to the characters they play. Next, we need to find the property that indicates citizenship.

[Tool]
Top 10 property alternatives:
1. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): the object is a country that recognizes the subject as its citizen, country
2. country for sport, also known as sports nationality, sports country, sport nationality, sporting nationality, sport country (wd:P1532 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): country a person or a team represents when playing a sport, country
3. permanent resident of, also known as landed immigrant of, PR (wd:P5389 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): country or region where a person has the legal status of permanent resident
4. occupant, also known as tenant, resident, renter, occupiers, lessee (wd:P466 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): person or organization occupying property, used by
5. ethnic group, also known as ethnic or cultural origin, tribal affiliation, race, people, ethnicity (wd:P172 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): subject's ethnicity (consensus is that a VERY high standard of p...agreed on by scholars, or 3) is fictional and portrayed as such)
6. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): most specific known birth location of a person, animal or fictional character, location
7. residence, also known as living in, place of residence, resided at, resided in, resident in (wd:P551 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): the place where the person is or has been, resident, location
8. right to vote, also known as suffrage (wd:P2964 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): people who have right to vote at this election, referendum, etc.
9. category for people born here, also known as category for place of birth, category of people born here (wd:P1464 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): category item that groups people born in this place, related category
10. A New Nation Votes ID (wd:P12578 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): ID of a person in A New Nation Votes: American Electoral Returns, 1788-1825

[Assistant] The property `wdt:P27` (country of citizenship) indicates citizenship. Now, let's find the entity for the United Kingdom.

[Tool]
Top 10 entity alternatives:
1. United Kingdom, also known as U.K., UK, U. K., U K, United Kingdom of Great Britain and Northern Ireland (wd:Q145): country in north-west Europe
2. United Kingdom, also known as U K, The United Kingdom of Great Britain and Northern Ireland, The UK, U. K., Great Britain and Northern Ireland (wd:Q145): country in north-west Europe
3. United Kingdom of Great Britain and Ireland, also known as Great Britain and Ireland, UK, UKGBI, United Kingdom (wd:Q174193): historical sovereign state (1801–1922)
4. A United Kingdom, also known as United Kingdom (wd:Q21528200): 2016 film by Amma Asante
5. United Kingdom in the Eurovision Song Contest 2010, also known as United Kingdom (wd:Q974636)
6. United Kingdom (wd:Q108280869): 1989 studio album by American Music Club
7. Pedlars Act 1871, also known as Pedlars Act 1881, United Kingdom, (wd:Q55629342): 1871 United Kingdom of Great Britain and Ireland Act of Parliament 34 & 35 Vic c. 96
8. United Kingdom (wd:Q110577800): Manny Montes's single
9. United Kingdom (wd:Q7887906): album by Manny Montes
10. United Kingdom (wd:Q96412324)

[Assistant]
The correct entity for the United Kingdom is `wd:Q145`. Now, let's construct a SPARQL query to find the number of Spider-Man performers who are citizens of the United Kingdom.

We will:
1. Find the performers of Spider-Man using `wdt:P175`.
2. Check their citizenship using `wdt:P27`.
3. Count the number of performers who are citizens of the United Kingdom.

Let's execute the query.

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

[Assistant]
The SPARQL query has returned that there is 1 Spider-Man performer who is a citizen of the United Kingdom.

Here is the final SPARQL query and answer:

```sparql
SELECT (COUNT(?performer) AS ?count) WHERE {
  wd:Q79037 wdt:P175 ?performer .
  ?performer wdt:P27 wd:Q145 .
}
```

Answer: There is 1 Spider-Man performer who is a citizen of the United Kingdom.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is well-formed and correctly answers the question. It returns the count of performers of Spider-Man who are citizens of the United Kingdom. The result is accurate and no further refinement is needed.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?song ?songLabel WHERE {
  {
    SELECT ?songLabel ( SAMPLE( ?songTemp ) AS ?song ) WHERE {
      ?songTemp wdt:P361 wd:Q828282 .
      OPTIONAL {
        ?songTemp rdfs:label ?songLabel .
        FILTER ( LANG( ?songLabel ) = "en" )
      }
    }
    GROUP BY ?songLabel
  }
}

Got 7 rows and 2 columns:
| song                              | songLabel                |
| --------------------------------- | ------------------------ |
| Día de Enero (wd:Q576798)         | Día de Enero (en)        |
| Día Especial (wd:Q3045530)        | Día Especial (en)        |
| La pared (wd:Q2713486)            | La pared (en)            |
| Las de la Intuición (wd:Q2265331) | Las de la Intuición (en) |
| La Tortura (wd:Q1784211)          | La Tortura (en)          |
| No (wd:Q3040253)                  | No (en)                  |
| Obtener un sí (wd:Q9051589)       | Obtener un sí (en)       |

The songs that made up the album 'Fijación Oral vol. 1' are: 1. Día de Enero, 2. Día Especial, 3. La pared, 4. Las de la Intuición, 5. La Tortura, 6. No, 7. Obtener un sí.

[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 songs made up the album Fijación Oral vol. 1 ?

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

[Tool]
Example 1:
Question:
What was the first Queen album?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q482994 .
  ?uri wdt:P175 wd:Q15862 .
  ?uri wdt:P577 ?date
}
ORDER BY ?date
LIMIT 1

Using entities:
Queen (wd:Q15862): British musical group; rock band
album, also known as full album, record album, music album, full-length album, audio album (wd:Q482994): grouping of album releases by an artist usually released at the ...racks but in different formats for consumption (digital, CD, LP)

Using properties:
performer, also known as actor, sung by, singer, recording by, recorded by (wd:P175 as wdt): actor, musician, band or other performer associated with this role or musical work, contributor to the creative work or subject
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
publication date, also known as launched, published, publication time, publication, pubdate (wd:P577 as wdt): date or point in time when a work was first published or released, point in time

[Assistant] None of the examples directly match our question, but we can use them as a starting point. We need to find the songs that are part of the album "Fijación Oral vol. 1". Let's start by searching for the album itself.

[Tool]
Top 10 entity alternatives:
1. Fijación Oral, Vol. 1, also known as Fijación Oral – vol. 1, Fijación Oral (Vol. 1), Fijación Oral Vol. 1 (wd:Q828282): 2005 studio album by Shakira
2. Oral Fixation Volumes 1 & 2, also known as Oral Fixation, Vols. 1-2 (wd:Q3278323): 2006 compilation box set by Shakira
3. Vol. 1 (wd:Q3284180): album by Hurt
4. 15 Vol. 1 (wd:Q9955140): 1997 compilation album by Arakain
5. Vol. 1, also known as Volume 1 (wd:Q2844005): 1965 debut studio album by Robert Charlebois
6. Vol. 1 (wd:Q96414091)
7. Vol. 1 (wd:Q9369071): 2008 studio album by Grzybowski Band
8. Vol. 1 (wd:Q7939947): album by We Are The Becoming
9. Vol. 1 (wd:Q7939946): 1999 extended play by Breed 77
10. Vol. 1 (wd:Q65054996): album by Samae Koskinen

[Assistant]
The correct entity for the album "Fijación Oral vol. 1" is `wd:Q828282`. Now, let's find out which songs are part of this album. We need to look for the property that links songs to albums.

I will search for the property that connects songs to albums.

[Tool]
Top 10 property alternatives:
1. number of parts of this work, also known as number of movements, number of parts of this work of art, number of pictures, number of scenes, number of segments of anthology film (wd:P2635 as wdt/p): the number of parts that a work comprises
2. 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
3. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as wdt/p): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
4. distribution format, also known as book format, type of media, publication format, method of distribution, medium (wd:P437 as wdt/p): method (or type) of distribution for the subject
5. title, also known as name, titled, page name, original title, known as (wd:P1476 as wdt/p): published name of a work, such as a newspaper article, a literary work, piece of music, a website, or a performance work, name
6. language of work or name, also known as language of the reference, language of URL, language of website, language of work, named in language (wd:P407 as wdt/p): language associated with this creative work (such as books, show...guage" (P103) and "languages spoken, written or signed" (P1412))
7. 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)
8. performer, also known as actor, sung by, singer, recording by, recorded by (wd:P175 as wdt/p): actor, musician, band or other performer associated with this role or musical work, contributor to the creative work or subject
9. Freebase ID, also known as Freebase, MID, Freebase identifier, FID (wd:P646 as wdt/p): identifier for a page in the Freebase database. Format: "/m/0" f...r IDs starting with "/g/", use Google Knowledge Graph ID (P2671)
10. review score, also known as rating (score), review rating (wd:P444 as wdt/p): review score received by a creative work or other entity

No other items found

[Assistant]
It seems that the property we are looking for is not among the top 10 results. However, the property `track list` (P2131) is commonly used to link songs to albums. Let's check if this property is used for the album "Fijación Oral vol. 1".

I will search for the property `track list` and see if it is used for the album.

[Tool]
Top 10 property alternatives:
1. tracklist, also known as tracks, track listing, track list, songs, list of tracks (wd:P658 as ps/pq/pqv/prn/psn/prv/wdtn/psv/wdt/pqn/pr/p): audio tracks contained in this release, has part(s)
2. published in, also known as song on album, tome of the book, tome of, track of, track on (wd:P1433 as ps/pq/pqv/prn/psn/prv/wdtn/psv/wdt/pqn/pr/p): larger work that a given work was published in, like a book, journal or music album, part of
3. featured track(s), also known as songs, soundtrack, OST, music tracks, music track (wd:P10664 as ps/pq/pqv/prn/psn/prv/wdtn/psv/wdt/pqn/pr/p): soundtrack of this audiovisual work
4. setlist, also known as set list, works performed, songs performed, performances, performance list (wd:P9793 as ps/pq/pqv/prn/psn/prv/wdtn/psv/wdt/pqn/pr/p): performances of songs or other music at an event; concert program, presented works
5. soundtrack release, also known as soundtrack single, soundtrack extended play, soundtrack album, has soundtrack album, OST (wd:P406 as ps/pq/pqv/prn/psn/prv/wdtn/psv/wdt/pqn/pr/p): music release that incorporates music directly recorded from the soundtrack of an audiovisual work
6. number of parts of this work, also known as number of movements, number of parts of this work of art, number of pictures, number of scenes, number of segments of anthology film (wd:P2635 as ps/pq/pqv/prn/psn/prv/wdtn/psv/wdt/pqn/pr/p): the number of parts that a work comprises
7. AllMusic song ID, also known as AllMusic recording ID, AllMusic track ID, recording ID (AllMusic), track ID (AllMusic) (wd:P1730 as ps/pq/pqv/prn/psn/prv/wdtn/psv/wdt/pqn/pr/p): identifier for a song in AllMusic database
8. music created for, also known as music for, music for work, music made for, music made for work, music written for (wd:P9899 as ps/pq/pqv/prn/psn/prv/wdtn/psv/wdt/pqn/pr/p): a work, event, etc. for which a musical composition was created ... was written; a film for which motion picture music was created), created for
9. Discogs track ID, also known as Discogs recording ID, recording ID (Discogs), track ID (Discogs) (wd:P6079 as ps/pq/pqv/prn/psn/prv/wdtn/psv/wdt/pqn/pr/p): identifier for a music track in Discogs
10. number of platform tracks, also known as platform tracks, Tracks (wd:P1103 as ps/pq/pqv/prn/psn/prv/wdtn/psv/wdt/pqn/pr/p): number of tracks served by the platforms at a railway station

[Assistant]
The property `tracklist` (P658) is the one we need to use to find the songs that are part of the album "Fijación Oral vol. 1". Let's construct a SPARQL query to retrieve the songs.

I will execute the SPARQL query to get the songs from the album "Fijación Oral vol. 1".

```sparql
SELECT ?song ?songLabel
WHERE {
  wd:Q828282 p:P658 ?statement.
  ?statement ps:P658 ?song.
  OPTIONAL { ?song rdfs:label ?songLabel . FILTER(LANG(?songLabel) = "en") }
}
```

This query will retrieve the songs that are part of the album "Fijación Oral vol. 1" and their English labels.

Let's execute the query.

[Tool] Got no rows and 2 columns

[Assistant]
It seems that the query did not return any results. This might be because the album "Fijación Oral vol. 1" does not have the `tracklist` property (P658) or the data is structured differently.

Let's try another approach. We can look for the songs that are part of the album by checking if they have the album as their `part of` property (P179).

I will execute the SPARQL query to get the songs from the album "Fijación Oral vol. 1" using the `part of` property.

```sparql
SELECT ?song ?songLabel
WHERE {
  ?song wdt:P179 wd:Q828282.
  OPTIONAL { ?song rdfs:label ?songLabel . FILTER(LANG(?songLabel) = "en") }
}
```

This query will retrieve the songs that are part of the album "Fijación Oral vol. 1" and their English labels.

Let's execute the query.

[Tool] Got no rows and 2 columns

[Assistant]
It seems that the `part of` property (P179) also did not yield any results. This suggests that the data structure for the album "Fijación Oral vol. 1" might be different from what we expected.

Let's try one more approach. We can look for the songs that are part of the album by checking if they have the album as their `recorded in` property (P175) or any other relevant property.

I will execute the SPARQL query to get the songs from the album "Fijación Oral vol. 1" using the `recorded in` property (P175).

```sparql
SELECT ?song ?songLabel
WHERE {
  ?song wdt:P175 wd:Q828282.
  OPTIONAL { ?song rdfs:label ?songLabel . FILTER(LANG(?songLabel) = "en") }
}
```

This query will retrieve the songs that are part of the album "Fijación Oral vol. 1" and their English labels.

Let's execute the query.

[Tool] Got no rows and 2 columns

[Assistant]
It seems that the `recorded in` property (P175) also did not yield any results. This indicates that the data structure for the album "Fijación Oral vol. 1" might be more complex or different from what we initially assumed.

Given that the direct approaches have not worked, let's try a more general approach by looking for songs that are linked to the album through any property. We can then filter out the relevant ones.

I will execute a more general SPARQL query to find any songs that are linked to the album "Fijación Oral vol. 1" through any property.

```sparql
SELECT ?song ?songLabel ?property
WHERE {
  ?song ?property wd:Q828282.
  OPTIONAL { ?song rdfs:label ?songLabel . FILTER(LANG(?songLabel) = "en") }
}
```

This query will retrieve any songs that are linked to the album "Fijación Oral vol. 1" and their English labels, along with the property that links them.

Let's execute the query.

[Tool]
Got 63 rows and 3 columns, showing the first 5 and last 5 rows below:
| song                                                       | songLabel | property                  |
| ---------------------------------------------------------- | --------- | ------------------------- |
| <https://bg.wikipedia.org/wiki/Fijaci%C3%B3n_Oral_Vol._1>  |           | schema:about              |
| <https://cs.wikipedia.org/wiki/Fijaci%C3%B3n_Oral_vol._1>  |           | schema:about              |
| <https://de.wikipedia.org/wiki/Fijaci%C3%B3n_oral_vol._1>  |           | schema:about              |
| <https://en.wikipedia.org/wiki/Fijaci%C3%B3n_Oral,_Vol._1> |           | schema:about              |
| <https://es.wikipedia.org/wiki/Fijaci%C3%B3n_oral_vol._1>  |           | schema:about              |
| ...                                                        | ...       | ...                       |
| s:Q65516009-addc19a4-483b-3715-995e-7d74b9fc70fd           |           | has part(s) (ps:P527)     |
| s:Q732900-aeed1ba5-46b7-b343-55a3-33a8d0beaff1             |           | follows (pq:P155)         |
| s:Q8961651-f7f06b84-40b6-f18b-9ccf-9656125dcd73            |           | different from (ps:P1889) |
| s:Q9051589-6c8904b5-4ccd-d4a6-cc87-5af478b9a882            |           | part of (ps:P361)         |
| s:Q923178-132649d6-4cd3-e2e9-4728-27214dc5b077             |           | followed by (pq:P156)     |

[Assistant]
The results show that there are several properties linking songs to the album "Fijación Oral vol. 1". The most relevant property appears to be `part of` (P361), which indicates that the song is part of the album.

Let's refine our query to specifically use the `part of` property (P361) and retrieve the songs and their labels.

```sparql
SELECT ?song ?songLabel
WHERE {
  ?song wdt:P361 wd:Q828282.
  OPTIONAL { ?song rdfs:label ?songLabel . FILTER(LANG(?songLabel) = "en") }
}
```

This query will retrieve the songs that are part of the album "Fijación Oral vol. 1" and their English labels.

Let's execute the query.

[Tool]
Got 8 rows and 2 columns:
| song                              | songLabel                |
| --------------------------------- | ------------------------ |
| La Tortura (wd:Q1784211)          | La Tortura (en)          |
| Las de la Intuición (wd:Q2265331) | Las de la Intuición (en) |
| La pared (wd:Q2713486)            | La pared (en)            |
| No (wd:Q3040253)                  | No (en)                  |
| Día Especial (wd:Q3045530)        | Día Especial (en)        |
| Día de Enero (wd:Q576798)         | Día de Enero (en)        |
| Día de Enero (wd:Q62063330)       | Día de Enero (en)        |
| Obtener un sí (wd:Q9051589)       | Obtener un sí (en)       |

[Assistant]
The query has successfully retrieved the songs that are part of the album "Fijación Oral vol. 1" along with their English labels. Here are the songs:

1. **La Tortura** (wd:Q1784211)
2. **Las de la Intuición** (wd:Q2265331)
3. **La pared** (wd:Q2713486)
4. **No** (wd:Q3040253)
5. **Día Especial** (wd:Q3045530)
6. **Día de Enero** (wd:Q576798)
7. **Día de Enero** (wd:Q62063330)
8. **Obtener un sí** (wd:Q9051589)

Note that there are two entries for "Día de Enero," which might indicate a duplicate or a different version of the same song.

Here is the final SPARQL query and the answer:

```sparql
SELECT ?song ?songLabel
WHERE {
  ?song wdt:P361 wd:Q828282.
  OPTIONAL { ?song rdfs:label ?songLabel . FILTER(LANG(?songLabel) = "en") }
}
```

The songs that made up the album "Fijación Oral vol. 1" are:

1. La Tortura
2. Las de la Intuición
3. La pared
4. No
5. Día Especial
6. Día de Enero
7. Día de Enero
8. Obtener un sí

I will now provide the final answer.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query is mostly correct, but there is a duplicate entry for 'Día de Enero'. This could be due to different versions or recordings of the same song being listed separately. To refine the query, consider adding a DISTINCT keyword to ensure each song is only returned once.

[Assistant]
Thank you for the feedback. To address the issue of the duplicate entry for "Día de Enero," I will add the `DISTINCT` keyword to the SPARQL query to ensure that each song is only returned once.

Here is the refined SPARQL query:

```sparql
SELECT DISTINCT ?song ?songLabel
WHERE {
  ?song wdt:P361 wd:Q828282.
  OPTIONAL { ?song rdfs:label ?songLabel . FILTER(LANG(?songLabel) = "en") }
}
```

Let's execute this refined query to ensure it returns the correct and unique songs.

[Tool]
Got 8 rows and 2 columns:
| song                              | songLabel                |
| --------------------------------- | ------------------------ |
| La Tortura (wd:Q1784211)          | La Tortura (en)          |
| Las de la Intuición (wd:Q2265331) | Las de la Intuición (en) |
| La pared (wd:Q2713486)            | La pared (en)            |
| No (wd:Q3040253)                  | No (en)                  |
| Día Especial (wd:Q3045530)        | Día Especial (en)        |
| Día de Enero (wd:Q576798)         | Día de Enero (en)        |
| Día de Enero (wd:Q62063330)       | Día de Enero (en)        |
| Obtener un sí (wd:Q9051589)       | Obtener un sí (en)       |

[Assistant]
The refined query with the `DISTINCT` keyword has been executed, but it still returns both entries for "Día de Enero." This suggests that the two entries are indeed distinct in the knowledge graph, possibly representing different versions or recordings of the same song.

To further refine the query, we can try to filter out duplicates based on the song labels. However, since the labels are the same, we need to ensure that we are not losing any important information.

Let's try to filter out duplicates by ensuring that we only keep one entry for each unique song label. We can use a subquery to achieve this.

Here is the refined SPARQL query:

```sparql
SELECT ?song ?songLabel
WHERE {
  {
    SELECT ?songLabel (SAMPLE(?song) AS ?song)
    WHERE {
      ?song wdt:P361 wd:Q828282.
      OPTIONAL { ?song rdfs:label ?songLabel . FILTER(LANG(?songLabel) = "en") }
    }
    GROUP BY ?songLabel
  }
}
```

This query will group the results by the song label and select one representative song for each label.

Let's execute this refined query.

[Tool]
SPARQL execution failed:
Invalid SPARQL query: The target ?song of an AS clause was already used in the query body.

[Assistant]
It looks like the query failed because the variable `?song` was already used in the query body. To resolve this, we can use a different variable for the subquery. Let's use `?songTemp` in the subquery and then map it back to `?song` in the outer query.

Here is the revised SPARQL query:

```sparql
SELECT ?song ?songLabel
WHERE {
  {
    SELECT ?songLabel (SAMPLE(?songTemp) AS ?song)
    WHERE {
      ?songTemp wdt:P361 wd:Q828282.
      OPTIONAL { ?songTemp rdfs:label ?songLabel . FILTER(LANG(?songLabel) = "en") }
    }
    GROUP BY ?songLabel
  }
}
```

This query will group the results by the song label and select one representative song for each label.

Let's execute this revised query.

[Tool]
Got 7 rows and 2 columns:
| song                              | songLabel                |
| --------------------------------- | ------------------------ |
| Día de Enero (wd:Q576798)         | Día de Enero (en)        |
| Día Especial (wd:Q3045530)        | Día Especial (en)        |
| La pared (wd:Q2713486)            | La pared (en)            |
| Las de la Intuición (wd:Q2265331) | Las de la Intuición (en) |
| La Tortura (wd:Q1784211)          | La Tortura (en)          |
| No (wd:Q3040253)                  | No (en)                  |
| Obtener un sí (wd:Q9051589)       | Obtener un sí (en)       |

[Assistant]
The revised query has successfully removed the duplicate entry for "Día de Enero" and returned the unique songs that are part of the album "Fijación Oral vol. 1."

Here are the songs:

1. **Día de Enero** (wd:Q576798)
2. **Día Especial** (wd:Q3045530)
3. **La pared** (wd:Q2713486)
4. **Las de la Intuición** (wd:Q2265331)
5. **La Tortura** (wd:Q1784211)
6. **No** (wd:Q3040253)
7. **Obtener un sí** (wd:Q9051589)

Here is the final SPARQL query and the answer:

```sparql
SELECT ?song ?songLabel
WHERE {
  {
    SELECT ?songLabel (SAMPLE(?songTemp) AS ?song)
    WHERE {
      ?songTemp wdt:P361 wd:Q828282.
      OPTIONAL { ?songTemp rdfs:label ?songLabel . FILTER(LANG(?songLabel) = "en") }
    }
    GROUP BY ?songLabel
  }
}
```

The songs that made up the album "Fijación Oral vol. 1" are:

1. Día de Enero
2. Día Especial
3. La pared
4. Las de la Intuición
5. La Tortura
6. No
7. Obtener un sí

I will now provide the final answer.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is correct and returns the expected results. It retrieves the songs that are part of the album 'Fijación Oral vol. 1' and provides their labels in English. The query follows the rules and does not include unnecessary computations or filters. Well done!


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?composer ?nativeName WHERE {
  wd:Q81534 wdt:P86 ?composer .
  ?composer wdt:P1559 ?nativeName .
}

The native name of the composer of the Japanese national anthem is 林廣守.

[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 native name of the composer of the Japanese national anthem?

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

[Tool]
Example 1:
Question:
In which countries do people speak Japanese?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q6256 .
  ?uri wdt:P37 wd:Q5287 .
}

Using entities:
Japanese, also known as Japanese language, Japanesic (wd:Q5287): language spoken in East Asia
country, also known as countries (wd:Q6256): distinct territorial body or political entity

Using properties:
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as wdt): language designated as official by this item, language used

Example 2:
Question:
Which country does the creator of Miffy come from?

SPARQL:
SELECT ?uri WHERE {
  wd:Q1501505 wdt:P170 ?creator .
  ?creator wdt:P27 ?uri .
}

Using entities:
Miffy (wd:Q1501505): female rabbit character in a series of picture books drawn and written by Dick Bruna

Using properties:
creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as wdt): maker of this creative work or other object (where no more specific property exists)
country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdt): the object is a country that recognizes the subject as its citizen, country

Example 3:
Question:
Give me all islands that belong to Japan.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q23442 ; wdt:P17 wd:Q17 .
}

Using entities:
Japan, also known as State of Japan, Nippon-koku, Nippon, Nihon-koku, Nihon (wd:Q17): island country in East Asia
island, also known as islands, isle (wd:Q23442): piece of sub-continental land completely surrounded by water

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

[Assistant] From these examples, we can see that we need to identify the composer of the Japanese national anthem and then find their native name. Let's first search for the Japanese national anthem.

[Tool]
Top 10 entity alternatives:
1. national anthem, also known as national hymn, state anthem (wd:Q23691): song that represents a country or sovereign state
2. National Anthem of Chile, also known as Canción Nacional, National Anthem (wd:Q484161): National Anthem of Chile
3. National Anthem (wd:Q2697331): Lana Del Rey song
4. National Anthem (wd:Q116945688): 2023 film directed by Luke Gilford
5. The National Anthem, also known as National Anthem (wd:Q19573235): 1999 film by Wu Ziniu
6. National Anthem (wd:Q16955069): album by The Away Team
7. National Anthem (wd:Q39078564): 2003 film
8. America, also known as National Anthem, National Hymn (wd:Q109781686): melody often used for national anthems; first published in 1744
9. National Anthem (wd:Q110059383): sketch from Saturday Night Live
10. anthem, also known as club anthem, march, national anthem, official hymn, official song (wd:P85): subject's official anthem

[Assistant] The correct entity for the Japanese national anthem is not listed in the top 10 results. Let's try a more specific search.

[Tool]
Top 10 entity alternatives:
1. Kimigayo, also known as national anthem of Japan (wd:Q81534): national anthem of Japan
2. Kimigayo (wd:Q130240831): edition in ''The National Anthems of the Allies'' (1917)
3. Kimigayo March, also known as Kimigayo Kōshinkyoku (wd:Q24887361)
4. Kimigayo boy (wd:Q10926866)
5. National Anthem,  Kimigayo, also known as Kokka Kimigayo (wd:Q106398988): short film by Noburo Ofuji
6. Music and Politics: Japanese Composer Mayuzumi Toshiro and Kimigayo (wd:Q127824960): scholarly article

[Assistant] The correct entity for the Japanese national anthem, "Kimigayo," is the first result. Now, let's find the composer of "Kimigayo."

[Tool]
Top 10 property alternatives:
1. composer, also known as music by, written by, songwriter, musical score by, film score by (wd:P86 as wdt/p): person(s) who wrote the music [for lyricist, use "lyrics by" (P676)], creator
2. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as wdt/p): time when an entity begins to exist; for date of official opening use P1619, start time
3. lyricist, also known as text poet, writer (of song lyrics), words by, text writer, text by (wd:P676 as wdt/p): author of song lyrics, author
4. MusicBrainz work ID, also known as composition ID (MusicBrainz), MBID work, MBW, MB work ID, MusicBrainz composition ID (wd:P435 as wdtn/p/wdt): identifier for a work per the MusicBrainz open music encyclopedia
5. tonality, also known as in key, key, key of musical composition, key used, musical key (wd:P826 as wdt/p): key of a musical composition
6. sheet music, also known as musical score (wd:P3030 as wdt/p): media file containing the musical score (sheet music) for this item
7. derivative work, also known as is source work of, is adapted as, is the basis for, iteration, reboot (wd:P4969 as wdt/p): new work of art (film, book, software, etc.) derived from major part of this work
8. audio, also known as audio file, audio recording, audio sample, recording, song (wd:P51 as wdt/p): relevant sound. If available, use a more specific property. Samples: "spoken text audio" (P989), "pronunciation audio" (P443)
9. depicts, also known as portrays, presents, preserves, quotes, represents (wd:P180 as wdt/p): entity visually depicted in an image, literarily described in a ...o an audiovisual or other medium; see also P921,  'main subject', has part(s)
10. copyright status, also known as copyrighted, copyright restriction (wd:P6216 as wdt/p): copyright status for intellectual creations like works of art, publications, software, etc.

No other items found

[Assistant] The property "composer" (wdt:P86) is the correct one to use for finding the composer of "Kimigayo." Let's execute a SPARQL query to find the composer of the Japanese national anthem, "Kimigayo."

[Tool]
Got 1 row and 1 column:
| composer                       |
| ------------------------------ |
| Hiromori Hayashi (wd:Q3783782) |

[Assistant] The composer of the Japanese national anthem, "Kimigayo," is Hiromori Hayashi. Now, let's find the native name of Hiromori Hayashi.

[Tool]
No property items found

No other items found

[Assistant]
It seems that the property "native name" is not directly associated with Hiromori Hayashi. However, we can try using the property "name in native language" (wdt:P1705) or look for the label in the native language.

Let's check if there is a property for the name in the native language.

[Tool]
Top 10 property alternatives:
1. name in native language, also known as native name (wd:P1559 as wdt/p): name of a person in their native language, name
2. name in kana, also known as kana reading, reading in kana, yomigana, kana name, kana (wd:P1814 as wdt/p): the reading of a Japanese name in kana, transliteration or transcription, name
3. family name, also known as clan name, last name, surname (wd:P734 as wdt/p): part of full name of person, name
4. 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
5. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt/p): most specific known birth location of a person, animal or fictional character, location
6. ISNI, also known as International Standard Name Identifier, ISO 27729 (wd:P213 as wdt/p): International Standard Name Identifier for an identity. Starting with 0000.
7. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as wdt/p): date on which the subject was born, inception
8. child, also known as has son, kids, mother of, kid, issue (wd:P40 as wdt/p): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative
9. 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)
10. National Library of Poland Descriptor, also known as Polish National Library ID, PLWABN ID, PLWABN, National Library of Poland ID, NLP identifier (wd:P7293 as wdt/p): National Library of Poland record no. identifier. Format: "98", followed by 10 digits, then ending with "5606"

No other items found

[Assistant] The property "name in native language" (wdt:P1559) is the correct one to use for finding the native name of Hiromori Hayashi. Let's execute a SPARQL query to find the native name of Hiromori Hayashi.

[Tool]
Got 1 row and 1 column:
| nativeName |
| ---------- |
| 林廣守 (ja)   |

[Assistant]
The native name of Hiromori Hayashi, the composer of the Japanese national anthem "Kimigayo," is 林廣守.

Now, let's finalize the answer with the SPARQL query and the result.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The output is correct and complete. The SPARQL query correctly identifies the composer of the Japanese national anthem and retrieves his native name.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?animal ?lifespan WHERE {
  VALUES ?animal {
    wd:Q174199 wd:Q36341
  }
  ?animal wdt:P4214 ?lifespan .
}

The common bottlenose dolphin has a higher observed lifespan.

[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 has a higher observed lifespan out of the common bottlenose dolphin and the brown bear?

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

[Tool] No examples found

[Assistant] Since no examples were found, let's start by searching for the entities "common bottlenose dolphin" and "brown bear".

[Tool]
Top 10 entity alternatives:
1. common bottlenose dolphin, also known as Atlantic bottlenose dolphin, Bottle-Nosed Dolphin, bottlenose dolphin, Bottlenose dolphin, Tursiops truncatus (wd:Q174199): best-known species of the dolphin family
2. bottlenose dolphin, also known as Tursiops (wd:Q149069): genus of dolphin
3. Common Dolphin (wd:Q84262742): ship built in 2012
4. Fetal omphalocele in a common bo...se dolphin (Tursiops truncatus). (wd:Q46363505): scientific article
5. Short-beaked Common Dolphin, also known as Delphinus delphis (wd:Q207114): species of mammal
6. mahi-mahi, also known as dorado, mahi mahi, Coryphaena hippurus, common dolphinfish (wd:Q14443): species of fish
7. Delphinus, also known as Common dolphin genus (wd:Q312257): genus of mammals
8. Indo-Pacific bottlenose dolphin, also known as Tursiops aduncus, Indian Ocean bottlenose dolphin (wd:Q370597): species of mammal
9. Delphinus capensis, also known as Long-beaked common dolphin (wd:Q604326): species of mammal
10. Tursiops erebennus, also known as Tamanend's bottlenose dolphin (wd:Q121222034): species of dolphin

[Assistant] The first result seems to be the correct one for the common bottlenose dolphin. Let's now search for the brown bear.

[Tool]
Top 10 entity alternatives:
1. Ursus arctos, also known as brown bear, grizzly bear (wd:Q36341): species of mammal
2. Ursus arctos, also known as brown bear, grizzly bear (wd:Q36341): species of mammal
3. Brown Bear, also known as Brown Bear Public House, Brown Bear, Whitechapel, The Brown Bear, Whitechapel (wd:Q26318258): pub in Whitechapel, London
4. Brown bear (wd:Q57080481): sculpture by François Pompon on display at Musée de Grenoble
5. Brown Bear, also known as Beube (wd:Q124961726): South Korean online streamer
6. Brown Bear, also known as The Brown Bear (wd:Q79684102): pub in Berwick-Upon-Tweed, Northumberland, UK
7. The Brown Bear Public House, also known as Brown Bear, The Brown Bear, Ware (wd:Q17554255): pub in Braughing, Ware, UK
8. brown bear, also known as grizzly bear (wd:Q113488817): fictional monster from Dungeons & Dragons
9. Brown bear (wd:Q117481410): sculpture by Georg Wrba in Tierpark Berlin, Germany
10. Brown Bear, also known as Brown Bear, Devonport, Plymouth (wd:Q80476278): pub in Plymouth, Devon, UK

[Assistant] The first result seems to be the correct one for the brown bear. Now we need to find the property for observed lifespan. Let's search for it.

[Tool]
Top 10 property alternatives:
1. life expectancy, also known as life span, lifespan (wd:P2250 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): average life expectancy for this group or species, duration
2. longest observed lifespan, also known as maximum age, oldest recorded individual, oldest observed, maximum life span, highest observed lifespan (wd:P4214 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): age of the oldest specimen of a taxon for which the age can be verified
3. mean lifetime (wd:P2645 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): inverse of exponential decay rate; half-life is ln(2) times this value, duration
4. practiced by, also known as proponent, studied by, practitioners, practioner, occupation of this field (wd:P3095 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): type of agents that study this subject or work in this field
5. state of transmission, also known as state of preservation, survival status (wd:P12020 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): state in which a work is transmitted or its existence; for the state of its material witnesses, use P5816
6. service life (wd:P5069 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): product's total life in use from the point of sale to the point of discard
7. discontinued date, also known as EOL date, product discontinued, EOL, end-of-life date, end-of-life (wd:P2669 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): date that the availability of a product or service was discontin...d "service retirement" (P730) for pieces or classes of equipment, end time
8. medical examination, also known as prognostic method, diagnostic method, possible examinations, medical examinations, examinations (wd:P923 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): examinations that might be used to diagnose and/or prognose the medical condition, test method
9. observed in (wd:P6531 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): to be used as reference to location, condition, variant where upon the subject property object statement is based
10. mean age, also known as average age (wd:P4442 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): mean age in a given place

[Assistant]
The second result, "longest observed lifespan" (wd:P4214), seems to be the correct property for our query. Now let's construct a SPARQL query to compare the longest observed lifespans of the common bottlenose dolphin and the brown bear.

Here is the initial SPARQL query:

```sparql
SELECT ?animal ?lifespan
WHERE {
  VALUES ?animal { wd:Q174199 wd:Q36341 }
  ?animal wdt:P4214 ?lifespan .
}
```

Let's execute this query to see the results.

[Tool]
Got 2 rows and 2 columns:
| animal                                 | lifespan           |
| -------------------------------------- | ------------------ |
| common bottlenose dolphin (wd:Q174199) | 51.6 (xsd:decimal) |
| Ursus arctos (wd:Q36341)               | 40 (xsd:decimal)   |

[Assistant]
The SPARQL query returned the longest observed lifespans for both the common bottlenose dolphin and the brown bear. The common bottlenose dolphin has a longer observed lifespan of 51.6 years compared to the brown bear's 40 years.

Therefore, the common bottlenose dolphin has a higher observed lifespan.

Here is the final SPARQL query and answer:

```sparql
SELECT ?animal ?lifespan
WHERE {
  VALUES ?animal { wd:Q174199 wd:Q36341 }
  ?animal wdt:P4214 ?lifespan .
}
```

Answer: The common bottlenose dolphin has a higher observed lifespan.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is correct and returns the necessary information to answer the question. The common bottlenose dolphin indeed has a higher observed lifespan compared to the brown bear.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?inception WHERE {
  wd:Q27706 wdt:P571 ?inception .
}

January 1, 1911

[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] When was the Hamburg Airport inaugurated?

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

[Tool] No examples found

[Assistant] Since no examples were found, let's proceed by searching for the entity "Hamburg Airport".

[Tool]
Top 10 entity alternatives:
1. Hamburg Airport, also known as Hamburg-Fuhlsbüttel Airport, Hamburg Airport “Helmut Schmidt”, EDDH, HAM (wd:Q27706): airport in Fuhlsbüttel, Hamburg, Germany
2. Hamburg Finkenwerder Airport, also known as Airbus Hamburg-Finkenwerder, EDHI, Finkenwerder Airport, XFW (wd:Q663819): aircraft manufacturing plant and associated private airport in the Finkenwerder quarter of southwest Hamburg, Germany
3. Hamburg Airport station (wd:Q5644290): railway station in Germany
4. Hamburg Airport Classics (wd:Q1572874)
5. Hamburg Inc Airport, also known as 4G2, Hamburg Inc Aerodrome (wd:Q34959585)
6. Hamburg : Airport, also known as A9 n35_Sm2 (wd:Q104725193): folder of the 20th Century Press Archives
7. Hamburg Airport S-Bahn line (wd:Q1430696): railway line in Germany
8. Novo Hamburgo Airport, also known as SSNH (wd:Q12694211): Brazilian airport
9. Hamburg : Airport, individual, also known as A9 n35_Sm2.II (wd:Q104725196): folder of the 20th Century Press Archives
10. Hamburg : Airport, general, also known as A9 n35_Sm2.I (wd:Q104725195): folder of the 20th Century Press Archives

[Assistant] The first result, "Hamburg Airport, also known as Hamburg-Fuhlsbüttel Airport, Hamburg Airport “Helmut Schmidt”, EDDH, HAM (wd:Q27706)", seems to be the correct entity we're looking for. Now, let's check what properties are associated with this entity to see if there is a property related to inauguration or opening date.

[Tool]
Got 402 rows and 3 columns, showing the first 10 rows below:
| subject                     | property                                                    | object                                                                                |
| --------------------------- | ----------------------------------------------------------- | -------------------------------------------------------------------------------------- |
| Hamburg Airport (wd:Q27706) | instance of (wdt:P31)                                       | international airport (wd:Q644371)                                                     |
| Hamburg Airport (wd:Q27706) | country (wdt:P17)                                           | Germany (wd:Q183)                                                                      |
| Hamburg Airport (wd:Q27706) | located in the administrative territorial entity (wdt:P131) | Hamburg-Nord (wd:Q1627)                                                                |
| Hamburg Airport (wd:Q27706) | coordinate location (wdt:P625)                              | POINT(9.988228 53.630389) (geo:wktLiteral)                                             |
| Hamburg Airport (wd:Q27706) | Commons category (wdt:P373)                                 | Hamburg Airport                                                                        |
| Hamburg Airport (wd:Q27706) | image (wdt:P18)                                             | <http://commons.wikimedia.org/wiki/Special:FilePath/Hamburg%20airport%20terminals.jpg> |
| Hamburg Airport (wd:Q27706) | location (wdt:P276)                                         | Fuhlsbüttel (wd:Q1163)                                                                 |
| Hamburg Airport (wd:Q27706) | inception (wdt:P571)                                        | 1911-01-01T00:00:00Z (xsd:dateTime)                                                    |
| Hamburg Airport (wd:Q27706) | official name (wdt:P1448)                                   | Hamburg Airport Helmut Schmidt (de)                                                    |
| Hamburg Airport (wd:Q27706) | official website (wdt:P856)                                 | <https://www.hamburg-airport.de/>                                                      |
| ...                         | ...                                                         | ...                                                                                |

[Assistant]
From the list of properties, we can see that the property `inception` (P571) has a value of "1911-01-01T00:00:00Z". This likely refers to the inauguration or opening date of the airport. Let's confirm this by constructing a simple SPARQL query to retrieve the inception date of Hamburg Airport.

Here is the SPARQL query:

```sparql
SELECT ?inception WHERE {
  wd:Q27706 wdt:P571 ?inception .
}
```

Let's execute this query to get the inception date.

[Tool]
Got 1 row and 1 column:
| inception                           |
| ----------------------------------- |
| 1911-01-01T00:00:00Z (xsd:dateTime) |

[Assistant]
The inception date of Hamburg Airport is "1911-01-01T00:00:00Z". This date likely represents the inauguration or opening of the airport.

Therefore, the answer to the question "When was the Hamburg Airport inaugurated?" is January 1, 1911.

Here is the final SPARQL query and answer:

```sparql
SELECT ?inception WHERE {
  wd:Q27706 wdt:P571 ?inception .
}
```

Answer: January 1, 1911

[Tool] Stopped generation process

[User]
Feedback (status=done):
The output is correct and complete. The SPARQL query correctly retrieves the inception date of Hamburg Airport, which is January 1, 1911. The query follows all the rules and returns the actual IRI of the item in its result, along with the human-readable date.