PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?series ?seriesLabel ?numSeasons WHERE {
  BIND( wd:Q30603704 AS ?series ) .
  ?series wdt:P2437 ?numSeasons .
  OPTIONAL {
    ?series rdfs:label ?seriesLabel FILTER ( LANG( ?seriesLabel ) = "en" )
  }
}

Using entities:
Pose (wd:Q30603704)

Using properties:
number of seasons (wd:P2437 as wdt), also known as no. of seasons, no. of series, number of series, seasons, P2437

Answer: Pose (wd:Q30603704) has 3 seasons.

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

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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

You have access to the following knowledge graphs:
wikidata at http://localhost:7001 without notes

You are provided with the following notes across all knowledge graphs:
No notes available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
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 these rules:
- Explain your thought process before and after each step and function call.
- Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
- 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.
- Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
- 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.
- 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.
- 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.
- For questions with a "True" or "False" answer the SPARQL query should be an ASK query.

[User] How many seasons does Pose have?

[Assistant] I will first search Wikidata for the TV series "Pose" to find its entity identifier. Then I'll look for the property that records the number of seasons (likely "number of seasons"). I'll verify the property and then build a SPARQL query to retrieve the number of seasons for the Pose TV series. I'll start by searching for the entity "Pose".

[Tool]
Top 10 entity alternatives:
1. television series (wd:Q5398426, matched via TV series), also known as television show, TV series, TV-series, TV show: connected set of television programme episodes under the same title / connected set of television program episodes under the same title / is instance of type of television program / is subclass of series of creative works / is subclass of television programme / is subclass of television program / is subclass of serial
2. miniseries (wd:Q1259759, matched via TV mini series), also known as event series, limited serial, limited series, mini-series, television mini-series, etc.: TV shows or series that have a predetermined number of episodes / is instance of type of television program / is subclass of serial drama
3. Halo (wd:Q55279915, matched via Halo (TV Series)), also known as Halo: The Television Series, Halo (TV Series): is instance of television series / is instance of serial / television series
4. children's television series (wd:Q1273568, matched via children's TV series), also known as children's TV series, kids tv, kids TV series: television programs designed for, and marketed to children / is subclass of children's television program / is subclass of family television series / is instance of television series genre
5. television series season (wd:Q3464665, matched via TV series season), also known as season, Season, season of a television series, season of a TV show, season of television series, etc.: set of episodes produced for a television series / set of episodes produced by a television series / is subclass of series of creative works / is subclass of television programme / is subclass of creative work season / is subclass of television program / is subclass of serial
6. Chinese television drama (wd:Q28195059, matched via Chinese tv series), also known as cdrama, C-drama, Chinese drama, Chinese drama serial, Chinese drama series, etc.: Chinese television drama series originating from Mainland China or the Greater China region / is subclass of drama television series / is subclass of dramatic programming / is instance of television genre
7. drama television series (wd:Q1366112, matched via drama TV series), also known as drama series, dramatic television series, drama TV series, television drama series, TV drama series: television programme content that is scripted and fictional along the lines of a traditional drama / is subclass of drama television program / is instance of television series genre / is subclass of television series / television series genre / is subclass of serial
8. Landman (wd:Q124447212, matched via Landman (TV series)), also known as Landman (TV series): is instance of television series / American television series / is instance of serial
9. Belgravia (wd:Q65120601, matched via Belgravia TV series), also known as Belgravia TV series: is instance of television series / American television series / is instance of serial
10. Disney Junior's Ariel (wd:Q121863673, matched via Ariel (TV series)), also known as Ariel (TV series), Disney Jr.'s Ariel: American animated television series / is instance of television series / is instance of animated series / is instance of serial

[Assistant] I'll search for entities matching "Pose" (shorter query) to find the TV series entry.

[Tool]
Top 10 entity alternatives:
1. Pose (wd:Q30603704): 2018 American drama television series / is instance of television series / is instance of serial
2. posture (wd:Q8514257, matched via pose), also known as attitude, human position, pose: physical configuration that a human or animal body can take / is subclass of spatial arrangement
3. Pose (wd:Q29966944): is instance of single / 2017 song by Rihanna
4. Pose (wd:Q432543): is instance of single / single
5. pose (wd:Q1671968): position and orientation of an object in an image / is instance of technical term
6. Pose (wd:Q108250580): 2021 song by Red Velvet / 2021 song by Red Velvet / is instance of song
7. pose (wd:Q2105738), also known as posing: sustained posture or positioning of the torso and limbs / is subclass of posture
8. Pose (wd:Q85794108): 2021 single by Yo Gotti featuring Lil Uzi Vert / is instance of musical work/composition
9. Pose (wd:Q10352082): Album by Engenheiros do Hawaii / is instance of album
10. Pose (wd:Q25213080): has occupation artist / is instance of human / American artist

[Assistant] I'll search for properties related to "number of seasons" to find the correct property identifier in Wikidata.

[Tool]
Top 10 property alternatives:
1. number of seasons (wd:P2437 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq), also known as no. of seasons, no. of series, number of series, seasons, P2437: number of seasons a television or radio series has had / number of series a television or radio show has had / is subproperty of number of parts of a work of art / is subproperty of number of parts of this work
2. number of episodes (wd:P1113 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via no. of episodes), also known as episode count, episodes, no. of episodes, series length, P1113: is subproperty of number of parts of a work of art / is subproperty of number of parts of this work / number of episodes in a film/TV/radio series / number of episodes in a film/TV/radio series / number of episodes in a film/TV/radio series
3. volume (wd:P478 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via number of series), also known as numbering in series, numbering of part, numbering of volume, number of part, number of series, etc.: volume of a book or music release in a collection/series or a published collection of journal issues in a serial publication / volume of a book in a collection/series, for reference
4. number of representations (wd:P5027 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via no. of shows), also known as concerts, no. of shows, number of concerts, number of performances, number of shows, etc.: number of shows (including the premiere) of a concert tour or a performing arts production
5. season (wd:P4908 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via television season), also known as series of television program, television season, television series, TV season, TV series, etc.: season of a series (televison, web, podcast) / Series of a television show / is subproperty of part of
6. number of parts of this work (wd:P2635 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via number of segments of anthology film), also known as acts count, acts number, acts quantity, chapter count, chapters quantity, etc.: the number of parts that a work of art consists of / the number of parts that a work comprises
7. number of seats (wd:P1342 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq), also known as membership quantity, number of seats (members), quantity of members, seats (members), P1342: total number of seats/members in an assembly (legislative house or similar) / number of seats/members in an assembly (legislative house or similar)
8. number of seats in assembly (wd:P1410 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via number of seats), also known as number of delegates, number of representatives, number of seats, seats, P1410: number of seats a political party, faction, or group has in a given assembly
9. maximum capacity (wd:P1083 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via number of seats), also known as capacity, complement, crew, number of seats, seating capacity, etc.: number of people allowed for a venue or vehicle / number of people allowed for a venue or vehicle
10. Douban film ID (wd:P4529 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via Douban television series season ID), also known as Douban Film ID, Douban ID, Douban Movie ID, Douban season ID, Douban Subject ID, etc.: identifier for a film (movie) at the website Douban

[Assistant] I found the entity wd:Q30603704 for the Pose TV series and the property wd:P2437 for the number of seasons. I'll verify that Pose (wd:Q30603704) has a statement using P2437. I'll list triples with that subject and property.

[Tool]
Got 1 row and 3 columns:
| subject             | property                      | object          |
| ------------------- | ----------------------------- | --------------- |
| Pose (wd:Q30603704) | number of seasons (wdt:P2437) | 3 (xsd:decimal) |

[Assistant] I'll now run a final SPARQL query that returns the TV series IRI for Pose and its number of seasons. This uses the verified entity wd:Q30603704 and property wdt:P2437 (number of seasons). The query also optionally retrieves the English label. After the query runs I'll provide the numeric answer.

[Tool] Stopping


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ( COUNT( DISTINCT ?award ) AS ?goldenGlobeWins ) WHERE {
  wd:Q312674 wdt:P166 ?award .
  OPTIONAL {
    ?award rdfs:label ?awardLabel FILTER ( LANG( ?awardLabel ) = "en" )
  }
  FILTER ( CONTAINS( LCASE( COALESCE ( ?awardLabel , "" ) ) , "golden globe" ) )
}

Using entities:
Giorgio Moroder (wd:Q312674), also known as Giovanni Giorgio Moroder, Hansjörg Moroder

Using properties:
award received (wd:P166 as wdt), also known as award, awarded, awards, awards received, award won, etc.

Got 1 row and 1 column:
| goldenGlobeWins |
| --------------- |
| 2 (xsd:int)     |

Answer: Giorgio Moroder has won 2 Golden Globe Awards.

how many times has Giorgio Moroder won golden globe award?

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

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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

You have access to the following knowledge graphs:
wikidata at http://localhost:7001 without notes

You are provided with the following notes across all knowledge graphs:
No notes available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
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 these rules:
- Explain your thought process before and after each step and function call.
- Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
- 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.
- Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
- 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.
- 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.
- 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.
- For questions with a "True" or "False" answer the SPARQL query should be an ASK query.

[User] how many times has Giorgio Moroder won golden globe award?

[Assistant] Step 1: I'll search for the Wikidata item for Giorgio Moroder to find his identifier and relevant award properties. I'll query the knowledge graph for the entity.

[Tool]
Top 10 entity alternatives:
1. Giorgio Moroder (wd:Q312674), also known as Giovanni Giorgio Moroder, Hansjörg Moroder: Italian record producer and composer / has occupation film score composer / has occupation record producer / has occupation Film producer / has occupation film producer / has occupation disc jockey / has occupation songwriter / has occupation composer / is instance of human / has occupation DJ
2. Giorgio by Moroder (wd:Q15720519): is instance of musical work/composition / 2013 song by Daft Punk
3. Metropolis (wd:Q76367460, matched via Giorgio Moroder Presents Metropolis), also known as Giorgio Moroder Presents Metropolis: 1984 version by Giorgio Moroder / is instance of film
4. Philip Oakey & Giorgio Moroder (wd:Q7184164): 1989 self-titled studio album by Philip Oakey & Giorgio Moroder / is instance of album
5. Giorgio Napolitano (wd:Q1220): President of Italy from 2006 to 2015 / has occupation journalist / has occupation politician / is instance of human
6. Giorgio Vasari (wd:Q128027), also known as Aretino, Arettino, Dzhordzho Vazari, Georges Vasari, George Vasari, etc.: Italian painter, architect, writer and historian (1511-1574) / has occupation architectural draftsperson / has occupation art historian / has occupation visual artist / has occupation art theorist / has occupation aesthetician / has occupation biographer / has occupation architect / has occupation Architect / has occupation painter / has occupation writer / is instance of human
7. Georges Braque (wd:Q153793, matched via Giorgio Braque), also known as Braque, G. Braque, geo braque, geo. braque, George B., etc.: 20th-century French painter and sculptor / 20th-century French painter and sculptor / French painter and sculptor (1882-1963) / has occupation jewellery designer / has occupation jewelry designer / has occupation scenographer / has occupation draftsperson / has occupation lithographer / has occupation printmaker / has occupation collagist / has occupation designer / has occupation sculptor / has occupation painter / has occupation artist / has occupation drawer / is instance of human
8. Giorgio Chiellini (wd:Q80306): has occupation association football player / Italian association football player / has occupation sports commentator / has occupation soccer player / has occupation lawyer / is instance of human
9. Giorgione (wd:Q8459, matched via Giorgio), also known as Barbarella Giorgio detto il Giorgione, Cavaglier Georgione, Dzhordzhone, G. Barbarelli, genannt Giorgione Georgius Parbarelli, etc.: Venetian Renaissance painter (1478–1510) / has occupation visual artist / has occupation painter / is instance of human

[Assistant] Now I'll search for the Wikidata item for the Golden Globe Award to identify the correct item(s) to match against Giorgio Moroder's awards.

[Tool]
Top 10 entity alternatives:
1. Golden Globe Awards (wd:Q1011547), also known as Golden Globes: award of the Hollywood Foreign Press Association / is subclass of television award / is instance of group of awards / is subclass of film award / is instance of award
2. Golden Globe Award ceremony (wd:Q19311591): is instance of television programme / is instance of television program / is instance of award ceremony / is subclass of award ceremony / is instance of annual event
3. 73rd Golden Globe Awards (wd:Q21094897): is instance of Golden Globe Award ceremony / Golden Globe Award ceremony
4. 72nd Golden Globe Awards (wd:Q17278465), also known as Golden Globe Awards 2015: is instance of Golden Globe Award ceremony / award ceremony
5. 74th Golden Globe Awards (wd:Q26212578), also known as Golden Globe 2017: is instance of Golden Globe Award ceremony / Golden Globe Award ceremony
6. 70th Golden Globe Awards (wd:Q490861): is instance of Golden Globe Award ceremony / award ceremony
7. 69th Golden Globe Awards (wd:Q8671): award for best in film and television of 2011 / is instance of Golden Globe Award ceremony
8. 68th Golden Globe Awards (wd:Q180813): is instance of Golden Globe Award ceremony / award ceremony
9. 67th Golden Globe Awards (wd:Q249397): is instance of Golden Globe Award ceremony / 2010 ceremony honoring film and TV in 2009
10. 71st Golden Globe Awards (wd:Q15139147): is instance of Golden Globe Award ceremony / award ceremony

[Assistant] I'll list Giorgio Moroder's values for the "award received" property (P166) to see which awards he received and to identify which ones are Golden Globes. I'll call the list function to fetch triples with subject wd:Q312674 and property wdt:P166.

[Tool]
Got 11 rows and 3 columns, showing the first 10 rows below:
| subject                      | property                  | object                                                                 |
| ---------------------------- | ------------------------- | ---------------------------------------------------------------------- |
| Giorgio Moroder (wd:Q312674) | award received (wdt:P166) | Academy Award for Best Original Song (wd:Q112243)                      |
| Giorgio Moroder (wd:Q312674) | award received (wdt:P166) | David di Donatello Award for Lifetime Achievement (wd:Q13634272)       |
| Giorgio Moroder (wd:Q312674) | award received (wdt:P166) | Grammy Award for Best Instrumental Composition (wd:Q13635451)          |
| Giorgio Moroder (wd:Q312674) | award received (wdt:P166) | Golden Globe Award for Best Original Score (wd:Q1422140)               |
| Giorgio Moroder (wd:Q312674) | award received (wdt:P166) | Commander of the Order of Merit of the Italian Republic (wd:Q14539729) |
| Giorgio Moroder (wd:Q312674) | award received (wdt:P166) | Golden Globe Award for Best Original Song (wd:Q1472235)                |
| Giorgio Moroder (wd:Q312674) | award received (wdt:P166) | Grammy Award for Best Score Soundtrack for Visual Media (wd:Q4376972)  |
| Giorgio Moroder (wd:Q312674) | award received (wdt:P166) | Academy Award for Best Original Score (wd:Q488651)                     |
| Giorgio Moroder (wd:Q312674) | award received (wdt:P166) | Bambi Award (wd:Q630018)                                               |
| Giorgio Moroder (wd:Q312674) | award received (wdt:P166) | Grammy Award for Best Dance/Electronic Recording (wd:Q740968)          |
| ...                          | ...                       | ...                                                                    |

[Assistant] I'll query the awards Giorgio Moroder received and retrieve their instance-of (P31) and subclass-of (P279) values to identify which are Golden Globes.

[Tool]
SPARQL execution failed:
HTTPConnectionPool(host='localhost', port=7001): Read timed out.

[Assistant] I'll list all triples for Giorgio Moroder to find all award-related statements and confirm which awards are Golden Globes.

[Tool]
Got 1,023 rows and 3 columns, showing the first 10 rows below:
| subject                      | property                         | object                                                                               |
| ---------------------------- | -------------------------------- | ------------------------------------------------------------------------------------ |
| Giorgio Moroder (wd:Q312674) | instance of (wdt:P31)            | human (wd:Q5)                                                                        |
| Giorgio Moroder (wd:Q312674) | occupation (wdt:P106)            | composer (wd:Q36834)                                                                 |
| Giorgio Moroder (wd:Q312674) | sex or gender (wdt:P21)          | male (wd:Q6581097)                                                                   |
| Giorgio Moroder (wd:Q312674) | given name (wdt:P735)            | Giorgio (wd:Q12900074)                                                               |
| Giorgio Moroder (wd:Q312674) | date of birth (wdt:P569)         | 1940-04-26T00:00:00Z (xsd:dateTime)                                                  |
| Giorgio Moroder (wd:Q312674) | Commons category (wdt:P373)      | Giorgio Moroder                                                                      |
| Giorgio Moroder (wd:Q312674) | image (wdt:P18)                  | <http://commons.wikimedia.org/wiki/Special:FilePath/Giorgio%20Moroder%20%282%29.jpg> |
| Giorgio Moroder (wd:Q312674) | family name (wdt:P734)           | Moroder (wd:Q18288660)                                                               |
| Giorgio Moroder (wd:Q312674) | country of citizenship (wdt:P27) | Italy (wd:Q38)                                                                       |
| Giorgio Moroder (wd:Q312674) | Freebase ID (wdt:P646)           | /m/019x62                                                                            |
| ...                          | ...                              | ...                                                                                |

[Assistant] I'll filter the award received (P166) statements specifically to see all awards and their labels.

[Tool]
Got 11 rows and 2 columns, showing the first 5 and last 5 rows below:
| award                                                                  | awardLabel                                                   |
| ---------------------------------------------------------------------- | ------------------------------------------------------------ |
| Academy Award for Best Original Song (wd:Q112243)                      | Academy Award for Best Original Song (en)                    |
| David di Donatello Award for Lifetime Achievement (wd:Q13634272)       | David di Donatello Award for Lifetime Achievement (en)       |
| Grammy Award for Best Instrumental Composition (wd:Q13635451)          | Grammy Award for Best Instrumental Composition (en)          |
| Golden Globe Award for Best Original Score (wd:Q1422140)               | Golden Globe Award for Best Original Score (en)              |
| Commander of the Order of Merit of the Italian Republic (wd:Q14539729) | Commander of the Order of Merit of the Italian Republic (en) |
| ...                                                                    | ...                                                          |
| Grammy Award for Best Score Soundtrack for Visual Media (wd:Q4376972)  | Grammy Award for Best Score Soundtrack for Visual Media (en) |
| Academy Award for Best Original Score (wd:Q488651)                     | Academy Award for Best Original Score (en)                   |
| Bambi Award (wd:Q630018)                                               | Bambi Award (en)                                             |
| Grammy Award for Best Dance/Electronic Recording (wd:Q740968)          | Grammy Award for Best Dance/Electronic Recording (en)        |
| Grammy Award for Album of the Year (wd:Q904528)                        | Grammy Award for Album of the Year (en)                      |

[Assistant] I see two Golden Globe-related awards in the list earlier: wd:Q1422140 (Golden Globe Award for Best Original Score) and wd:Q1472235 (Golden Globe Award for Best Original Song). I'll verify Giorgio Moroder has award received statements for those two items. I'll run a query checking for P166 with those specific awards.

[Tool]
Got 2 rows and 2 columns:
| award                                                    | awardLabel                                      |
| -------------------------------------------------------- | ----------------------------------------------- |
| Golden Globe Award for Best Original Score (wd:Q1422140) | Golden Globe Award for Best Original Score (en) |
| Golden Globe Award for Best Original Song (wd:Q1472235)  | Golden Globe Award for Best Original Song (en)  |

[Assistant] This shows two Golden Globe award items are directly listed as awards received by Giorgio Moroder. The user's question asks: "how many times has Giorgio Moroder won golden globe award?" They likely mean the number of Golden Globe awards he has won. I need to count how many awards he received that are instances or subclasses of Golden Globe Awards (wd:Q1011547), or whose label contains "Golden Globe". Better to count awards that are instance of or subclass of wd:Q1011547. I'll construct a SPARQL COUNT query: find distinct ?award such that wd:Q312674 wdt:P166 ?award and (?award wdt:P31/wdt:P279* wd:Q1011547) OR ?award rdfs:label contains "Golden Globe" as fallback. Use PATH wdt:P31/wdt:P279* to handle instance-of and subclass hierarchy. I will execute the COUNT query.

[Tool]
SPARQL execution failed:
HTTPConnectionPool(host='localhost', port=7001): Read timed out. (read timeout=30)

[Assistant] The endpoint timed out for that query. I'll run a simpler query: list the awards received with labels and filter labels containing "Golden Globe" to count them.

[Tool]
Got 2 rows and 2 columns:
| award                                                    | awardLabel                                      |
| -------------------------------------------------------- | ----------------------------------------------- |
| Golden Globe Award for Best Original Score (wd:Q1422140) | Golden Globe Award for Best Original Score (en) |
| Golden Globe Award for Best Original Song (wd:Q1472235)  | Golden Globe Award for Best Original Song (en)  |

[Assistant] The results show two Golden Globe awards. I'll produce a final SPARQL query that returns the count and the awards (their IRIs). The query should return identifiers; also include labels optionally. Then execute it to ensure it returns the expected result before answering. I'll prepare a COUNT query that selects distinct awards where the label contains "Golden Globe" OR the award is instance/subclass of wd:Q1011547. To reduce complexity and avoid timeouts, I'll primarily use label matching (since we verified the two awards have labels containing "Golden Globe"). Then run the query to get the count and list.

[Tool]
Got 1 row and 2 columns:
| goldenGlobeWins | awards |
| --------------- | ------ |
| 2 (xsd:int)     |        |

[Assistant] The query returned count 2, but the GROUP_CONCAT of awards was empty because I used OPTIONAL and then FILTER on label; but award variable should be present. It's okay since we have the count. I'll finalize by returning the SPARQL query used and the answer: Giorgio Moroder has won 2 Golden Globe Awards. I'll use the same COUNT query as final.

[Tool] Stopping


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?creator ?creatorLabel WHERE {
  wd:Q2394280 wdt:P170 ?creator .
  OPTIONAL {
    ?creator rdfs:label ?creatorLabel FILTER ( LANG( ?creatorLabel ) = "en" )
  }
}

Using entities:
Boo-Boo Bear (wd:Q2394280), also known as Boo Boo

Using properties:
creator (wd:P170 as wdt), also known as art by, artist (non-musical), art work by, artwork by, by, etc.

Answer: I will execute the query to get the creator and then report the result.

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

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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

You have access to the following knowledge graphs:
wikidata at http://localhost:7001 without notes

You are provided with the following notes across all knowledge graphs:
No notes available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
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 these rules:
- Explain your thought process before and after each step and function call.
- Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
- 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.
- Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
- 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.
- 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.
- 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.
- For questions with a "True" or "False" answer the SPARQL query should be an ASK query.

[User] Who was the creator of Boo-Boo Bear ?

[Assistant] I will search Wikidata for the entity "Boo-Boo Bear" to find its Q-id and then look for a property that indicates its creator (often P170, "creator", or possibly "created by"). I'll first search for the entity.

[Tool]
Top 10 entity alternatives:
1. Boo-Boo Bear (wd:Q2394280), also known as Boo Boo: is instance of Hanna-Barbera character / is instance of video game character / is instance of anthropomorphic bear / is instance of television character / is instance of animated character / fictional character in Yogi Bear / is instance of film character / is instance of CGI character
2. Yogi Bear and Boo-Boo Bear (wd:Q132184386), also known as Boo Boo and Yogi, Boo-Boo Bear and Yogi Bear, Yogi and Boo Boo: fictional characters from Yogi Bear / is instance of fictional duo
3. Ursidae (wd:Q11788, matched via bear), also known as bear, bear family, ursid, ursids: is subclass of carnivora / is subclass of Carnivora / is instance of taxon / family of mammals / family of mammals
4. Ursus maritimus (wd:Q33609, matched via ice bear), also known as ice bear, polar bear, white bear: species of bear native largely within the Arctic Circle / species of bear native largely within the Arctic Circle / species of bear native largely within the Arctic Circle / is instance of apex predator / is instance of Apex predator / is instance of taxon / is subclass of bear
5. Giant panda (wd:Q33602, matched via panda bear), also known as Ailuropoda melanoleuca, panda, panda bear: is instance of taxon / species of mammal / species of mammal
6. Ursus arctos (wd:Q36341, matched via brown bear), also known as brown bear, grizzly bear: is instance of taxon / is subclass of bear / species of mammal / species of mammal / species of mammal / species of mammal
7. Phascolarctos cinereus (wd:Q36101, matched via koala bear), also known as coala, koala, koala bear, koolah: arboreal herbivorous marsupial native to Australia / is instance of taxon
8. Ursa Major (wd:Q8918, matched via Great Bear), also known as Arctus, Arktos, Charles's Wain, Great Bear, Larger Bear, etc.: constellation visible throughout the year in most of the northern hemisphere / constellation visible throughout the year in most of the northern hemisphere / is instance of constellation
9. Ursa Minor (wd:Q10478, matched via Little Bear), also known as Little Bear, Little Dipper, UMi, Ursae Minoris: constellation in the northern celestial hemisphere, containing the northern celestial pole / is instance of constellation
10. wolverine (wd:Q14334, matched via skunk bear), also known as beaver eater, carcajou, glutton, Gulo gulo, quickhatch, etc.: largest land-dwelling species of the family Mustelidae / largest land-dwelling species of the family Mustelidae / is instance of taxon

[Assistant] I'll list the triples for the Boo-Boo Bear item to find properties that indicate its creator. I'll fetch all triples with Boo-Boo Bear as subject.

[Tool]
Got 199 rows and 3 columns, showing the first 10 rows below:
| subject                    | property                                        | object                                                                                |
| -------------------------- | ----------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| Boo-Boo Bear (wd:Q2394280) | instance of (wdt:P31)                           | Hanna-Barbera character (wd:Q113374319)                                                                                |
| Boo-Boo Bear (wd:Q2394280) | sex or gender (wdt:P21)                         | male (wd:Q6581097)                                                                                |
| Boo-Boo Bear (wd:Q2394280) | given name (wdt:P735)                           | Boo Boo (wd:Q4942729)                                                                                |
| Boo-Boo Bear (wd:Q2394280) | Commons category (wdt:P373)                     | Boo-Boo Bear                                                                                |
| Boo-Boo Bear (wd:Q2394280) | image (wdt:P18)                                 | <http://commons.wikimedia.org/wiki/Special:FilePath/Yogi%20Bear%20and%20son%2C%20Storybook%20Land%20Park%2C%20Aberdeen%2C%20South%20Dakota%20%28LOC%29%20-%20Flickr%20-%20The%20Library%20of%20Congress.jpg> |
| Boo-Boo Bear (wd:Q2394280) | country of citizenship (wdt:P27)                | United States (wd:Q30)                                                                                |
| Boo-Boo Bear (wd:Q2394280) | part of (wdt:P361)                              | Yogi Bear and Boo-Boo Bear (wd:Q132184386)                                                                                |
| Boo-Boo Bear (wd:Q2394280) | Freebase ID (wdt:P646)                          | /m/02z0j87                                                                                |
| Boo-Boo Bear (wd:Q2394280) | languages spoken, written or signed (wdt:P1412) | English (wd:Q1860)                                                                                |
| Boo-Boo Bear (wd:Q2394280) | country of origin (wdt:P495)                    | United States (wd:Q30)                                                                                |
| ...                        | ...                                             | ...                                                                                |

[Assistant] I'll check whether Boo-Boo Bear (wd:Q2394280) has a creator (wdt:P170) or related properties like "creator" or "creator of work". I'll list triples filtered by property P170.

[Tool]
Got 1 row and 3 columns:
| subject                    | property           | object                     |
| -------------------------- | ------------------ | -------------------------- |
| Boo-Boo Bear (wd:Q2394280) | creator (wdt:P170) | William Hanna (wd:Q263324) |

[Assistant] I'll run a final SPARQL query that retrieves the creator (P170) of the Boo-Boo Bear item (wd:Q2394280), returning the creator's IRI and English label. This verifies the result I observed earlier.

[Tool] Stopping


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX schema: <http://schema.org/>
SELECT ?player ( COUNT( DISTINCT ?award ) AS ?nbAwards ) WHERE {
  VALUES ?player {
    wd:Q41421 wd:Q25369
  }
  ?player wdt:P166 ?award .
  OPTIONAL {
    ?award rdfs:label ?al FILTER ( LANG( ?al ) = "en" )
  }
  OPTIONAL {
    ?award schema:description ?desc FILTER ( LANG( ?desc ) = "en" )
  }
  BIND( LCASE( COALESCE ( ?al , ?desc , "" ) ) AS ?text ) FILTER ( CONTAINS( ?text , "nba" ) || CONTAINS( ?text , "national basketball" ) )
}
GROUP BY ?player
ORDER BY DESC ( ?nbAwards )

Using entities:
Kobe Bryant (wd:Q25369), also known as Black Mamba, KB24, Kobe, Kobe B. Bryant, Kobe Bean Bryant
Michael Jordan (wd:Q41421), also known as Air Jordan, His Airness

Using properties:
award received (wd:P166 as wdt), also known as award, awarded, awards, awards received, award won, etc.

Answer: Michael Jordan has won more NBA awards (10) than Kobe Bryant (6) according to the query results.

who has won more NBA awards, Michael Jordan or Kobe Bean Bryant？

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

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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

You have access to the following knowledge graphs:
wikidata at http://localhost:7001 without notes

You are provided with the following notes across all knowledge graphs:
No notes available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
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 these rules:
- Explain your thought process before and after each step and function call.
- Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
- 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.
- Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
- 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.
- 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.
- 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.
- For questions with a "True" or "False" answer the SPARQL query should be an ASK query.

[User] who has won more NBA awards, Michael Jordan or Kobe Bean Bryant？

[Assistant] I will first find the Wikidata entities for "Michael Jordan" and "Kobe Bean Bryant", then check how awards are represented (property for "award received" is likely P166). I'll search for the players and then search for properties and awards related to basketball/NBA. I'll start by searching for Michael Jordan's Wikidata item.

[Tool]
Top 10 entity alternatives:
1. Michael Jordan (wd:Q41421), also known as Air Jordan, His Airness: American basketball player and businessman (born 1963) / American basketball player and businessman / American basketball player and businessman / has occupation basketball player / has occupation baseball player / has occupation autobiographer / has occupation spokesperson / has occupation Entrepreneur / has occupation entrepreneur / is instance of human
2. Michael I. Jordan (wd:Q3308285, matched via Michael Jordan), also known as Michael Irwin Jordan, Michael Jordan: American computer scientist, University of California, Berkeley / has occupation artificial intelligence researcher / has occupation university teacher / has occupation computer scientist / has occupation statistician / is instance of human
3. Michael Jordan (wd:Q6831716), also known as Michael William Jordan: has occupation association football player / English footballer (born 1984) / has occupation soccer player / is instance of human
4. Michael Jordan (wd:Q65029442): has occupation American football player / American football offensive lineman / has occupation football player / is instance of human
5. Mike Jordan (wd:Q6847437, matched via Michael Jordan), also known as M. H. Jordan, Michael Henry Jordan, Michael H. Jordan, Michael Jordan: American baseball player and politician (1863-1940) / has occupation baseball player / has occupation politician / is instance of human
6. Michael Jordan (wd:Q27069141), also known as Mike Jordan: has occupation American football player / has occupation football player / American football cornerback / is instance of human
7. Michael Jordan (wd:Q6831715): has occupation politician / has occupation farmer / is instance of human / Irish politician / Irish politician / Irish politician
8. Michael Jordan (wd:Q1928047): German draughtsperson, artist and comics artist / has occupation university teacher / has occupation comics artist / has occupation draftsperson / has occupation drawer / has occupation artist / is instance of human
9. Michael Jordan (wd:Q6831719): British mycologist, writer, and television presenter / has occupation television presenter / has occupation mushroom gatherer / has occupation mycologist / has occupation announcer / has occupation writer / is instance of human
10. Michael Jordan (wd:Q126207492): has occupation botanist / is instance of human / 1941--

[Tool]
Top 10 entity alternatives:
1. Kobe Bryant (wd:Q25369, matched via Kobe Bean Bryant), also known as Black Mamba, KB24, Kobe, Kobe B. Bryant, Kobe Bean Bryant: American basketball player (1978–2020) / has occupation professional athlete / has occupation basketball player / has occupation screenwriter / is instance of human
2. Kobe Bryant Day (wd:Q98969272): proposed Federal Holiday / is instance of holiday
3. Kobe Bryant Boulevard (wd:Q107299206): proposed street renaming in Los Angeles / is instance of thoroughfare
4. death of Kobe Bryant (wd:Q83737550, matched via Kobe Bryant death), also known as Kobe Bryant death, Kobe Bryant's death: 26 January 2020 death of Kobe Bryant in helicopter crash / is instance of death
5. NBA All-Star Game Kobe Bryant Most Valuable Player Award (wd:Q31391, matched via Kobe Bryant MVP Award), also known as Kobe Bryant Most Valuable Player Award, Kobe Bryant MVP Award, NBA All-Star Game Kobe Bryant MVP Award: basketball award of the National Basketball Association (NBA) / is instance of most valuable player award
6. Statue of Kobe Bryant (wd:Q125101336): sculpture in Los Angeles, California, U.S
7. Kobe Bryant China Fund (wd:Q6424297): for education, sports, and culture programs for children from China and the United States / is instance of fund
8. Kobe Bryant/Ice Cube (wd:Q125446155): is instance of television series episode / episode of All That (S4 E19)
9. Kobe Bryant sexual assault case (wd:Q6424298): is instance of legal case / legal case
10. Kobe Bryant in NBA Courtside (wd:Q3198120): is instance of video game / 1998 video game / 1998 video game / 1998 video game

[Assistant] I'll search for properties and awards: first I'll list the awards Michael Jordan has received (P166) to inspect their types and see which are NBA awards.

[Tool]
Got 24 rows and 3 columns, showing the first 10 rows below:
| subject                    | property                  | object                                                    |
| -------------------------- | ------------------------- | --------------------------------------------------------- |
| Michael Jordan (wd:Q41421) | award received (wdt:P166) | L'Équipe Champion of Champions (wd:Q1061233)              |
| Michael Jordan (wd:Q41421) | award received (wdt:P166) | wd:Q137003                                                |
| Michael Jordan (wd:Q41421) | award received (wdt:P166) | NBA All-Rookie Team (wd:Q1418009)                         |
| Michael Jordan (wd:Q41421) | award received (wdt:P166) | NBA All-Defensive Team (wd:Q1465181)                      |
| Michael Jordan (wd:Q41421) | award received (wdt:P166) | John R. Wooden Award (wd:Q1641970)                        |
| Michael Jordan (wd:Q41421) | award received (wdt:P166) | Sports Illustrated Sportsperson of the Year (wd:Q1653207) |
| Michael Jordan (wd:Q41421) | award received (wdt:P166) | Presidential Medal of Freedom (wd:Q17144)                 |
| Michael Jordan (wd:Q41421) | award received (wdt:P166) | NBA Most Valuable Player Award (wd:Q222047)               |
| Michael Jordan (wd:Q41421) | award received (wdt:P166) | Oscar Robertson Trophy (wd:Q2404133)                      |
| Michael Jordan (wd:Q41421) | award received (wdt:P166) | Naismith College Player of the Year (wd:Q2666769)         |
| ...                        | ...                       | ...                                                       |

[Assistant] I'll search for properties that link awards to organizations, like "presented by", "award received" qualifiers, or "manufacturer/presented by". I'll search properties related to "presented by" and "presented".

[Tool]
Top 10 property alternatives:
1. conferred by (wd:P1027 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via presented by), also known as awarded by, bestowed by, by, conceded by, degree awarded by, etc.: person or organisation who awards a prize to or bestows an honour upon a recipient / person or organization who grants an award, certification, grant, or role
2. presenter (wd:P371 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via presented by), also known as host, hosted by, hostess, presented by, TV host, etc.: someone who takes a main role in presenting a radio or television programme or a performing arts show / main role in presenting a radio or television program or a performing arts show / is subproperty of significant person / is subproperty of cast member
3. presented in (wd:P5072 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq), also known as held at meeting, presented at, screened at, P5072: event at which a talk, film, paper, or poster was presented
4. depicts (wd:P180 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via presents), also known as conveys, depicting, depiction of, displays, features, etc.: entity visually depicted in an image, literarily described in ... audiovisual or other medium; see also P921,  'main subject' / depicted entity (see also P921: main subject) / depicted entity (see also P921: main subject) / is subproperty of has part(s) / is subproperty of has part / place
5. organizer (wd:P664 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via presenter), also known as event organiser, event organizer, event producer, organised by, organiser, etc.: person or institution organizing an event / person or institution organizing an event
6. participant in (wd:P1344 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via present at), also known as attended, competed in, competes in, participant of, participant of event, etc.: event in which a person or organisation was/is a participant; inverse of P710 or P1923 / event in which a person or organization was/is a participant; inverse of P710 or P1923 / is subproperty of significant event / is subproperty of part of
7. manufacturer (wd:P176 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via provided by), also known as assembled by, assembler, brewed by, brewer, builder, etc.: (main or final) manufacturer or producer of this product / manufacturer or producer of this product
8. operator (wd:P137 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via provided by), also known as administrator, controlled by, facility operator, in use by, item operator, etc.: person, profession, or organization that operates the equipment, facility, or service; use country for diplomatic missions / person, profession, organization or entity that operates the equipment, facility, or service / organization that operates the service, facility, ship, aircraft, missile / is subproperty of used by
9. unveiled by (wd:P1656 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq), also known as P1656: person who unveils a statue, sculpture, memorial or plaque, etc. / person who unveils a statue, sculpture, memorial or plaque, etc. / is subproperty of significant person
10. first performance by (wd:P11849 as p/wdtn/pqn/pqv/wdt/prv/pr/ps/psn/prn/psv/pq, matched via premiered by), also known as first performed by, premiered by, world premiere by, world premiere performed by, world premier performance by, etc.: performer or performing group for the first performance of a work

[Assistant] I will inspect Kobe Bryant's award received (P166) list to count awards.

[Tool]
Got 9 rows and 3 columns:
| subject                 | property                  | object                                                               |
| ----------------------- | ------------------------- | -------------------------------------------------------------------- |
| Kobe Bryant (wd:Q25369) | award received (wdt:P166) | NBA All-Defensive Team (wd:Q1465181)                                 |
| Kobe Bryant (wd:Q25369) | award received (wdt:P166) | NBA Most Valuable Player Award (wd:Q222047)                          |
| Kobe Bryant (wd:Q25369) | award received (wdt:P166) | NBA All-Star Game Kobe Bryant Most Valuable Player Award (wd:Q31391) |
| Kobe Bryant (wd:Q25369) | award received (wdt:P166) | BET Award for Athlete of the Century (wd:Q4835465)                   |
| Kobe Bryant (wd:Q25369) | award received (wdt:P166) | All-NBA Team (wd:Q674359)                                            |
| Kobe Bryant (wd:Q25369) | award received (wdt:P166) | Bill Russell NBA Finals Most Valuable Player Award (wd:Q739499)      |
| Kobe Bryant (wd:Q25369) | award received (wdt:P166) | Under Armour Undeniable Performance ESPY Award (wd:Q7883073)         |
| Kobe Bryant (wd:Q25369) | award received (wdt:P166) | Academy Award for Best Animated Short Film (wd:Q917808)              |
| Kobe Bryant (wd:Q25369) | award received (wdt:P166) | Best NBA Player ESPY Award (wd:Q943106)                              |

[Assistant] Next I'll identify how awards are linked to the NBA in Wikidata. I will search for the NBA entity and then inspect an award like "NBA Most Valuable Player Award" to see its properties (like 'presented by' or 'sport'). I'll search for the NBA entity first.

[Tool]
Top 10 entity alternatives:
1. National Basketball Association (wd:Q155223), also known as BAA, Basketball Association of America, National Basketball Assn., Nat'l Basketball Assn., NBA: North American professional men's basketball league / is instance of professional sports league / is instance of basketball association / is instance of basketball league / is instance of online database
2. Women's National Basketball Association (wd:Q2593221), also known as WNBA: professional women's basketball league in the United States / is instance of basketball association / is instance of basketball league
3. National Basketball Association draft (wd:Q622521), also known as NBA draft: National Basketball Association annual event / is instance of recurring event / is subclass of draft
4. NBA Playoffs (wd:Q2265397, matched via National Basketball Association Playoffs), also known as National Basketball Association Playoffs: best-of-seven elimination tournament annually held after the NBA / is subclass of best-of-seven elimination tournament
5. National Basketball Players Association (wd:Q1627222), also known as NBPA: is instance of labour union / is instance of labor union / is instance of trade union / trade union
6. National Wheelchair Basketball Association (wd:Q12811067): organization in Colorado Springs, United States / is instance of non-profit organisation / is instance of non-profit organization / is instance of nonprofit organization / is instance of sports league
7. The League (wd:Q48851136, matched via Mongolian National Basketball Association), also known as Mongolian Basketball League, Mongolian National Basketball Association: Basketball league in Mongolia
8. WikiProject National Basketball Association (wd:Q8256083): Wikimedia subject-area collaboration / is instance of WikiProject
9. National Women's Basketball Association (wd:Q125470215): 1986 basketball league in the United States
10. National Basketball Referees Association (wd:Q15213691)

[Assistant] I'll inspect the item for "NBA Most Valuable Player Award" to see how it's characterized and whether it's an NBA award (likely 'presented by' or 'award for').

[Tool]
Call to function list returned an error:
Constraint "?" for property position is not a valid IRI. IRIs can be given in prefixed form, like "wd:Q937", as URIs, like "http://www.wikidata.org/entity/Q937", or in full form, like "<http://www.wikidata.org/entity/Q937>".

[Assistant] I'll list all properties (triples) for the MVP award item.

[Tool]
Got 346 rows and 3 columns, showing the first 10 rows below:
| subject                                     | property                         | object                              |
| ------------------------------------------- | -------------------------------- | ----------------------------------- |
| NBA Most Valuable Player Award (wd:Q222047) | instance of (wdt:P31)            | wd:Q652965                          |
| NBA Most Valuable Player Award (wd:Q222047) | country (wdt:P17)                | United States (wd:Q30)              |
| NBA Most Valuable Player Award (wd:Q222047) | Freebase ID (wdt:P646)           | /m/02yqk8                           |
| NBA Most Valuable Player Award (wd:Q222047) | inception (wdt:P571)             | 1956-01-01T00:00:00Z (xsd:dateTime) |
| NBA Most Valuable Player Award (wd:Q222047) | sport (wdt:P641)                 | basketball (wd:Q5372)               |
| NBA Most Valuable Player Award (wd:Q222047) | topic's main category (wdt:P910) | wd:Q9630219                         |
| NBA Most Valuable Player Award (wd:Q222047) | winner (wdt:P1346)               | Michael Jordan (wd:Q41421)          |
| NBA Most Valuable Player Award (wd:Q222047) | name in kana (wdt:P1814)         | さいゆうしゅうせんしゅしょう                      |
| NBA Most Valuable Player Award (wd:Q222047) | Lex ID (wdt:P8313)               | NBA_Most_Valuable_Player            |
| NBA Most Valuable Player Award (wd:Q222047) | wdt:P31279                       | award (wd:Q618779)                  |
| ...                                         | ...                              | ...                                 |

[Assistant] The awards list for each player is present via P166. The user asked "who has won more NBA awards, Michael Jordan or Kobe Bean Bryant?" We need to count NBA awards for each. Define "NBA awards" as awards that are related to the NBA. How to filter P166 items to those that are "NBA awards"? We can check whether the award's 'sport' is basketball (P641) and maybe 'country' United States and has 'presented by' the NBA (presented by is P1027 'conferred by' might be used) or maybe awards that have 'instance of' such as 'NBA award' items. Let's search for awards like "NBA All-Star MVP", "All-NBA Team", "NBA All-Defensive Team" — these items may have "presented by" or "award given by". I'll search for the property 'conferred by' usage on one award like NBA All-Defensive Team.

[Tool]
Got 135 rows and 3 columns, showing the first 10 rows below:
| subject                              | property                    | object                                                                  |
| ------------------------------------ | --------------------------- | ----------------------------------------------------------------------- |
| NBA All-Defensive Team (wd:Q1465181) | instance of (wdt:P31)       | award (wd:Q618779)                                                      |
| NBA All-Defensive Team (wd:Q1465181) | Freebase ID (wdt:P646)      | /m/027c6xm                                                              |
| NBA All-Defensive Team (wd:Q1465181) | inception (wdt:P571)        | 1968-01-01T00:00:00Z (xsd:dateTime)                                     |
| NBA All-Defensive Team (wd:Q1465181) | described at URL (wdt:P973) | <https://newspapers.com/clip/5862454/1993_nba_alldefensive_team_voting> |
| NBA All-Defensive Team (wd:Q1465181) | sport (wdt:P641)            | basketball (wd:Q5372)                                                   |
| NBA All-Defensive Team (wd:Q1465181) | wdt:P31279                  | award (wd:Q618779)                                                      |
| NBA All-Defensive Team (wd:Q1465181) | schema:description          | annual National Basketball Association honor (en)                       |
| NBA All-Defensive Team (wd:Q1465181) | schema:name                 | Mejor quinteto defensivo de la NBA (es)                                 |
| NBA All-Defensive Team (wd:Q1465181) | rdf:type                    | wikibase:Item                                                           |
| NBA All-Defensive Team (wd:Q1465181) | rdfs:label                  | Mejor quinteto defensivo de la NBA (es)                                 |
| ...                                  | ...                         | ...                                                                     |

[Assistant] The award items often have schema:description mentioning "National Basketball Association". But for machine filtering, we can use properties: sport (P641) = basketball, and maybe 'presented by' (P1027) linking to NBA (wd:Q155223) or 'award given by' maybe 'presented by' property is P1470? Let's search for properties that indicate 'award by' relationships. We saw 'conferred by' P1027 earlier. I'll check whether the NBA All-Defensive Team has a 'conferred by' property.

[Tool]
Top 10 property alternatives:
1. inception (wd:P571 as p/wdt, matched via constructed), also known as broke ground, built, commenced on date, commencement date, completed, etc.: time when an entity begins to exist; for date of official opening use P1619 / time when an entity begins to exist; for date of official opening use P1619 / date or point in time when the organisation / object was founded / created / is subproperty of start time
2. instance of (wd:P31 as p/wdt, matched via is a), also known as example of, has type, is a, is an, is of type, etc.: type to which this subject corresponds/belongs. Different ... and the volcano is a type (instance) of volcanic landform / that class of which this subject is a particular example and ... a subclass of mountain (and an instance of volcanic landform)
3. Freebase ID (wd:P646 as p/wdt, matched via Freebase), also known as FID, Freebase, Freebase identifier, MID, P646: identifier for a page in the Freebase database. Format: ... with "/g/", use Google Knowledge Graph identifier (P2671) / identifier for a page in the Freebase database. Format: ... with "/g/", use Google Knowledge Graph identifier (P2671) / identifier for a page in the Freebase database. Format: ... starting with "/g/", use Google Knowledge Graph ID (P2671)
4. sport (wd:P641 as p/wdt, matched via plays), also known as play, plays, sport played, sports, P641: sport that the subject participates or participated in or is associated with / sport or discipline in which the entity participates or belongs to
5. described at URL (wd:P973 as p/wdt, matched via rdfs:isDefinedBy), also known as about page, described at Uniform Resource Locator, described at webpage, described at website, described by URL, etc.: item is described at the following URL / is subproperty of URL

No other items found

[Assistant]
It doesn't show 'conferred by'. But many award items might not have 'presented by'. Another approach: define NBA awards as awards whose label or description contains 'National Basketball Association' or 'NBA'. We can filter award items where rdfs:label or schema:description contains "National Basketball Association" or "NBA". SPARQL can use FILTER(CONTAINS(LCASE(STR(?desc)),"national basketball")) or label contains "NBA". The rules allow rdfs:label usage. We must ensure the query returns actual IRIs of awards for each player and count them per player. The question asks who has won more NBA awards, Michael Jordan or Kobe. So we need to count number of award items (P166) per player where award item has description or label indicating NBA. Better to check both: description contains 'National Basketball Association' OR label contains 'NBA' or label contains 'National Basketball Association'. Also some awards like 'All-NBA Team' might have label 'All-NBA Team' which includes 'NBA' in label. Good.

Plan:
- For each player ?player (wd:Q41421 and wd:Q25369), find ?award via wdt:P166 ?award.
- Optional get rdfs:label and schema:description for ?award (we can use rdfs:label@en and schema:description@en).
- Filter to awards where either contains 'nba' in label or description, or contains 'national basketball' in description/label, case-insensitive.
- Count distinct ?award per player.
- Return counts and maybe player IRIs.

Construct SELECT with GROUP BY ?player and ?playerLabel optionally. But must avoid wikibase:label service. We can include rdfs:label for player using OPTIONAL { wd:Q41421 rdfs:label ?playerLabel filter(lang(?playerLabel)="en") } but since players are fixed, we can include their labels as literals. But requirement: The SPARQL query should return actual identifiers / IRIs of the items. So include ?player and ?count. Also can include optional labels for awards? Not necessary.

We must execute final query to ensure results. Let's build the query.

SPARQL:

SELECT ?player (COUNT(DISTINCT ?award) AS ?nbAwards) WHERE {
VALUES ?player { wd:Q41421 wd:Q25369 }
?player wdt:P166 ?award.
OPTIONAL { ?award rdfs:label ?al FILTER(LANG(?al)="en") }
OPTIONAL { ?award schema:description ?desc FILTER(LANG(?desc)="en") }
BIND(LCASE(COALESCE(?al,?desc, "")) AS ?text)
FILTER(
CONTAINS(?text, "nba") || CONTAINS(?text, "national basketball")
)
}
GROUP BY ?player
ORDER BY DESC(?nbAwards)

This should count awards whose label or description mentions 'nba' or 'national basketball'. Edge cases: some NBA awards might not have English label or description containing 'NBA' but likely they do. Execute.

We must explain thought process before and after each function call and each step. Ensure to comply with developer instructions: explain thought process before and after each step and function call. So we need to narrate each search/list call we already did — we included explanations above. But the tool calls we've made were: search_entity, search_entity, list, search_property, list, search_entity, list, search_property_of_entity, list. We already provided thought processes earlier. For the remaining function call execute, we must explain before calling. Then call functions.execute with query.

Let's prepare the final query, then call execute. Then after execution, analyze results and produce final answer and call functions.answer with final SPARQL query and answer string. Also requirement: Always execute your final SPARQL query before giving an answer.

We must include explanation before and after the final execute call. Then use functions.answer to finalize.

Let's craft the execute call.

I'll run a SPARQL query that, for each of the two players (Michael Jordan wd:Q41421 and Kobe Bryant wd:Q25369), counts the distinct awards (wdt:P166) whose English label or English description mentions "NBA" or "National Basketball" (case-insensitive). This approximates "NBA awards" by text matching on award items. I'll execute the query now.

[Tool]
Got 2 rows and 2 columns:
| player                     | nbAwards     |
| -------------------------- | ------------ |
| Michael Jordan (wd:Q41421) | 10 (xsd:int) |
| Kobe Bryant (wd:Q25369)    | 6 (xsd:int)  |

[Assistant] The query returned counts: Michael Jordan 10, Kobe Bryant 6. This answers who has won more NBA awards. I will now provide the final SPARQL query and the answer.

[Tool] Stopping


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?work ?workLabel WHERE {
  wd:Q550311 wdt:P800 ?work .
  FILTER ( ?work != wd:Q696071 ) ?work wdt:P921 wd:Q16003532 .
  OPTIONAL {
    ?work rdfs:label ?workLabel FILTER ( LANG( ?workLabel ) = "en" )
  }
}

Using entities:
middle school student (wd:Q16003532), also known as middle school pupil
Yoshihiro Togashi (wd:Q550311), also known as Togashi Yoshihiro
Hunter × Hunter (wd:Q696071), also known as HUNTER × HUNTER, Hunter x Hunter, HXH

Using properties:
notable work (wd:P800 as wdt), also known as artwork, author of, bibliography, books by, creator of, etc.
main subject (wd:P921 as wdt), also known as about, artistic theme, /common/topic/subject, content deals with, content describes, etc.

Answer: The representative work of Yoshihiro Togashi (other than Hunter × Hunter) that is about a middle school student is Yu Yu Hakusho (wd:Q18225473).

among the other representative work of the author of hunter x hunter, which one is talking about middle school student?

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

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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

You have access to the following knowledge graphs:
wikidata at http://localhost:7001 without notes

You are provided with the following notes across all knowledge graphs:
No notes available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
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 these rules:
- Explain your thought process before and after each step and function call.
- Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
- 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.
- Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
- 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.
- 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.
- 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.
- For questions with a "True" or "False" answer the SPARQL query should be an ASK query.

[User] among the other representative work of the author of hunter x hunter, which one is talking about middle school student?

[Assistant] I'll first find the Wikidata item for "Hunter × Hunter" so I can get its author. Then I'll look up that author's notable/representative works and among them find which one has a description or property indicating it's about a "middle school student". I'll run searches and simple queries step by step and explain each call.

[Tool]
Top 10 entity alternatives:
1. Hunter × Hunter (wd:Q696071), also known as HUNTER × HUNTER, Hunter x Hunter, HXH: is instance of manga series / Japanese manga series
2. Hunter × Hunter (wd:Q70209136), also known as H×H, Hunter x Hunter, HxH: is instance of anime television series / 2011 Japanese anime television series
3. Hunter × Hunter (wd:Q21232458), also known as Hunter x Hunter, HxH: is instance of anime television series / 1999 Japanese anime television series
4. Hunter × Hunter (wd:Q132542678), also known as Hunter×Hunter: is instance of media franchise / media franchise
5. Hunter × Hunter (wd:Q132543073), also known as Hunter×Hunter: is instance of video game series / video game series
6. Combination × And × Evolution (wd:Q116849879, matched via Hunter × Hunter ep99), also known as Combination × to × Evolution, Hunter × Hunter ep 99, Hunter × Hunter ep. 99, Hunter × Hunter ep99, Hunter × Hunter Episode 99: is instance of anime television series episode / Episode 99 of Hunter × Hunter
7. Knov × And × Morel (wd:Q116849888, matched via Hunter × Hunter ep6), also known as Hunter × Hunter ep 6, Hunter × Hunter ep. 6, Hunter × Hunter ep6, Hunter × Hunter Episode 6, Knov × to × Morel: is instance of anime television series episode / Episode 6 of Hunter × Hunter
8. Resolve × And × Awakening (wd:Q116849887, matched via Hunter × Hunter ep5), also known as Hunter × Hunter ep 5, Hunter × Hunter ep. 5, Hunter × Hunter ep5, Hunter × Hunter Episode 5, Kakugo × to × Kakusei: is instance of anime television series episode / Episode 5 of Hunter × Hunter
9. Doubt × And × Hesitation (wd:Q116849886, matched via Hunter × Hunter ep4), also known as Hunter × Hunter ep 4, Hunter × Hunter ep. 4, Hunter × Hunter ep4, Hunter × Hunter Episode 4, Mayoi × to × Tomadoi: is instance of anime television series episode / Episode 4 of Hunter × Hunter
10. Check × And × Mate (wd:Q116849884, matched via Hunter × Hunter ep3), also known as Hunter × Hunter ep 3, Hunter × Hunter ep. 3, Hunter × Hunter ep3, Hunter × Hunter Episode 3, Tsumi × to × Yomi: is instance of anime television series episode / Episode 3 of Hunter × Hunter

[Assistant] I'll get the author/creator of the Hunter × Hunter Wikidata item to identify the author. Then I'll list that author's "notable works" or "representative works" and check which of those is about a middle school student. I'll first query the author of wd:Q696071.

[Tool] Got no rows and 2 columns

[Assistant] I'll query the author/creator using known properties P50 (author) and P170 (creator) for Hunter × Hunter (wd:Q696071).

[Tool]
Got 1 row and 4 columns:
| prop             | propLabel | author                         | authorLabel            |
| ---------------- | --------- | ------------------------------ | ---------------------- |
| author (wdt:P50) |           | Yoshihiro Togashi (wd:Q550311) | Yoshihiro Togashi (en) |

[Tool]
Top 10 property alternatives:
1. notable work (wd:P800 as p/wdt), also known as artwork, author of, bibliography, books by, creator of, etc.: notable scientific, artistic or literary work, or other work of significance among subject's works / notable scientific, artistic or literary work, or other work of significance among subject's works
2. occupation (wd:P106 as p/wdt, matched via work), also known as avocation, career, craft, employ, employment, etc.: occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39) / occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39) / occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
3. sibling (wd:P3373 as p/wdt, matched via sis), also known as bro, brother, brother of, brother or sister, brothers, etc.: the subject and the object have at least one common parent ... etc.) and step-siblings (step-brothers, step-sisters, etc.) / the subject has the object as their sibling (brother, sister, ... etc.) and step-siblings (step-brothers, step-sisters, etc.) / is subproperty of relative
4. instance of (wd:P31 as p/wdt, matched via is a), also known as example of, has type, is a, is an, is of type, etc.: type to which this subject corresponds/belongs. Different ... and the volcano is a type (instance) of volcanic landform / that class of which this subject is a particular example and ... a subclass of mountain (and an instance of volcanic landform)
5. NDL Authority ID (wd:P349 as p/wdtn/wdt, matched via ndl), also known as National Diet Library Auth ID, National Diet Library ID, National Diet Library of Japan authority control ID, National Diet Library of Japan ID, ndl, etc.: identifier for authority control per the National Diet Library of Japan
6. given name (wd:P735 as p/wdt, matched via name), also known as Christian name, first name, forename, middle name, name, etc.: first name or another given name of this person; values used with the property should not link disambiguations nor family names / first name or another given name of this person; values used with the property shouldn't link disambiguations nor family names / first name or another given name of this person; values used with the property shouldn't link disambiguations nor family names / is subproperty of name
7. topic's main category (wd:P910 as p/wdt, matched via category), also known as article's main category, category, category for this topic, catmain, has category, etc.: main category of this topic / main Wikimedia category
8. spouse (wd:P26 as p/wdt, matched via partner), also known as common-law husband, common-law spouse, common-law wife, husband, husbands, etc.: the subject has the object as their spouse (husband, wife, ... Use "unmarried partner" (P451) for non-married companions / the subject has the object as their spouse (husband, wife, ... Use "unmarried partner" (P451) for non-married companions / the subject has the object as their spouse (husband, wife, ... Use "unmarried partner" (P451) for non-married companions / is subproperty of significant person / is subproperty of relative
9. educated at (wd:P69 as p/wdt, matched via graduate of), also known as alma mater, alumna of, alumni of, alumnus of, attended, etc.: educational institution attended by the subject / educational institution attended by the subject / educational institution attended by subject / is subproperty of affiliation
10. related image (wd:P6802 as p/wdt), also known as alternate image, ancillary image, backup image, decorative image, image related to topic, etc.: less fitting image, used only because a better alternative is ... use P18 instead. Value should not be a generic placeholder. / is subproperty of image

No other items found

[Assistant] I'll list the notable works (P800) of Yoshihiro Togashi (wd:Q550311). Then I will check each for whether it's about a middle school student. Likely works: YuYu Hakusho, Level E, etc. I'll retrieve the notable works with labels and descriptions.

[Tool]
Got 3 rows and 3 columns:
| work                         | workLabel            | workDescription            |
| ---------------------------- | -------------------- | -------------------------- |
| Yu Yu Hakusho (wd:Q18225473) | Yu Yu Hakusho (en)   | Japanese manga series (en) |
| Level E (wd:Q483557)         | Level E (en)         | Japanese manga series (en) |
| Hunter × Hunter (wd:Q696071) | Hunter × Hunter (en) | Japanese manga series (en) |

[Assistant] I'll search Wikidata for an item matching "middle school student" to see if there's a canonical entity I can use to check topics of works.

[Tool]
Top 10 entity alternatives:
1. middle school student (wd:Q16003532), also known as middle school pupil: student in late primary or early secondary education / is instance of demographic profile / is subclass of schoolchild / is instance of occupation / is subclass of student
2. Middlesex Middle School (wd:Q6841932): public secondary school in Darien, Connecticut, United States / is instance of middle school
3. Middle school students’self-concept and mental health (wd:Q120364046): scholarly article in Journal of Anhui Normal University (Hum.& Soc.Sci.), no. 1, 2006 / is instance of scholarly article / is instance of academic article
4. Additional Incentive for Middle School Students (wd:Q126270572): is instance of scholarly article / is instance of academic article / scholarly article
5. Reading Preferences of Middle School Students (wd:Q129963064): scholarly article published on 17 April 2018 / is instance of scholarly article / is instance of academic article
6. Doremi's Boyfriend is a Middle School Student! (wd:Q117319259), also known as Doremi no Kare wa Chuugakusei!, Ojamajo Doremi ep 39, Ojamajo Doremi ep. 39, Ojamajo Doremi ep39, Ojamajo Doremi Episode 39, etc.: is instance of anime television series episode / Episode 39 of Ojamajo Doremi Season 1
7. Recruiting middle school students into nursing (wd:Q37192510): scientific article published on June 2008 / is instance of scholarly article / is instance of academic article
8. Electronic bullying among middle school students (wd:Q39823864): is instance of scholarly article / is instance of academic article / scientific article
9. Middle school students' knowledge of autism. (wd:Q46354310): scientific article published in June 2011 / scientific article published in June 2011 / scientific article published in June 2011 / is instance of scholarly article / is instance of academic article
10. Measuring Middle School Students’ Algebra Readiness (wd:Q99717858): is instance of scholarly article / is instance of academic article

[Assistant] I'll check the characters (property P674) of Yu Yu Hakusho and Level E, then check whether any of those characters are instances of or have an occupation corresponding to "middle school student" (wd:Q16003532). I'll query both works for their characters and each character's instance-of/occupations.

[Tool]
SPARQL execution failed:
HTTPConnectionPool(host='localhost', port=7001): Read timed out. (read timeout=30)

[Assistant] Now I'll run a SPARQL query to find Yoshihiro Togashi's notable works (excluding Hunter × Hunter) that have main subject (P921) equal to "middle school student" (wd:Q16003532). This checks whether the work is explicitly tagged as being about middle school students. I'll run that query next.

[Tool]
Got 1 row and 2 columns:
| work                         | workLabel          |
| ---------------------------- | ------------------ |
| Yu Yu Hakusho (wd:Q18225473) | Yu Yu Hakusho (en) |

[Assistant] I'll run the final SPARQL query to confirm which of Yoshihiro Togashi's notable works (P800) other than Hunter × Hunter is about "middle school student" (wd:Q16003532). This final check ensures the result is correct. Then I'll return the query and the answer. Now I'll execute the query.

[Tool]
Got 1 row and 2 columns:
| work                         | workLabel          |
| ---------------------------- | ------------------ |
| Yu Yu Hakusho (wd:Q18225473) | Yu Yu Hakusho (en) |

[Assistant] I will now provide the final answer including the SPARQL query I used and the result.

[Tool] Stopping