PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?director ?directorLabel WHERE {
  wd:Q28091065 wdt:P57 ?director .
  OPTIONAL {
    ?director rdfs:label ?directorLabel FILTER ( LANG( ?directorLabel ) = "en" )
  }
}

The director of the Canadian drama television series "Anne with an E" is Niki Caro.

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

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

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

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

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

[User] Who directed Anne with an E ?

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

[Tool]
Example 1:
Question:
Which companies work in the aerospace industry as well as in medicine?

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

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

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

Example 2:
Question:
What is the birth name of Angela Merkel?

SPARQL:
SELECT DISTINCT ?name WHERE {
  wd:Q567 wdt:P1477 ?name .
}

Using entities:
Angela Merkel, also known as Angela Dorothea Merkel, leader of the free world, Angela Kasner (wd:Q567): chancellor of Germany from 2005 to 2021, politician, physicist

Using properties:
birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as wdt): full name of a person at birth, if different from their current, generally used name, name

Example 3:
Question:
What is the largest state in the United States?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q35657 .
  ?uri wdt:P2046 ?area .
}
ORDER BY DESC ( ?area )
LIMIT 1

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

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

[Assistant] The examples did not directly relate to films or directors, so I will now search for the entity "Anne with an E" in Wikidata to identify the correct entity for the TV show or film. Then I will look for the property related to the director of that entity.

[Tool]
Top 10 entity alternatives:
1. Anne with an E (wd:Q28091065): Canadian drama television series
2. Anne Linda Chisa, also known as Anne with an E (wd:Q109236706): South African academic, podcaster
3. Anne with an E, season 1 (wd:Q30897460): Wikimedia list article
4. Anne with an E, season 2 (wd:Q56327877): season of Anne with an E
5. Anne with an E, season 3 (wd:Q97370516): season of Anne with an E
6. An Intimate Evening with Anne Murray (wd:Q4750087): live album
7. Annelid Phylogeny—Molecular Anal...th an Emphasis on Model Annelids (wd:Q57267390): article
8. Hat with Bird: Anne Estelle Rice (wd:Q119158898): painting by John Duncan Fergusson (1874–1961), Kelvingrove Art Gallery and Museum
9. Queery with Cameron Esposito: Anne McClain, also known as Anne McClain (wd:Q117712680): Queery with Cameron Esposito podcast episode
10. Live Body: An interview with Anne Emmanuelle Berger (wd:Q127594883): scholarly article

[Assistant] The entity "Anne with an E" corresponds to the Canadian drama television series with the identifier wd:Q28091065. Next, I will search for the property related to the director of this TV series.

[Tool]
Top 10 property alternatives:
1. director, also known as film director, movie director, game director, directed by (wd:P57 as wdt/p): director(s) of film, TV-series, stageplay, video game or similar, contributor to the creative work or subject, creator
2. cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as wdt/p): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
3. screenwriter, also known as story by, teleplay by, video game writer, writer (of screenplays), writing credits (wd:P58 as wdt/p): person(s) who wrote the script for subject item, film crew member, author
4. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as wdt/p): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
5. title, also known as name, titled, page name, original title, known as (wd:P1476 as wdt/p): published name of a work, such as a newspaper article, a literary work, piece of music, a website, or a performance work, name
6. logo image, also known as masthead, wordmark, trademark, trade mark, sign (wd:P154 as wdt/p): graphic mark or emblem commonly used by commercial enterprises, organizations and products, icon
7. Kinobox film ID, also known as www.kinobox.cz/film/, kinobox.cz/film/, https://www.kinobox.cz/film/ (wd:P12096 as wdt/p): identifier for a film on the Kinobox.cz website
8. IMDb ID, also known as IMDb identifier, Internet Movie Database identifier (wd:P345 as wdt/p): identifier for the IMDb (with prefix 'tt', 'nm', 'co', 'ev', 'ch' or 'ni')
9. Rotten Tomatoes ID, also known as RottenTomatoes ID, Rotten Tomatoes identifier, RottenTomatoes identifier (wd:P1258 as wdt/p): identifier on Rotten Tomatoes
10. country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as wdt/p): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country

No other items found

[Assistant] The property "director" (wdt:P57) is the relevant property for the director of the TV series. I will now write a SPARQL query to find the director(s) of "Anne with an E" (wd:Q28091065).

[Tool]
Got 1 row and 2 columns:
| director               | directorLabel  |
| ---------------------- | -------------- |
| Niki Caro (wd:Q449163) | Niki Caro (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the director of the TV series 'Anne with an E' using the property 'director' (wdt:P57). The query also optionally fetches the English label of the director, which is useful for readability. The answer 'Niki Caro' is accurate according to the query result. The query follows the rules by returning the identifier and label, and no further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?person ?personLabel WHERE {
  ?person wdt:P20 wd:Q934 .
  OPTIONAL {
    ?person rdfs:label ?personLabel FILTER ( LANG( ?personLabel ) = "en" )
  }
}

The person who died at the North Pole is Sigizmund Levanevsky.

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

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

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

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

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

[User] Who died at the North Pole?

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

[Tool]
Example 1:
Question:
When was the Titanic completed?

SPARQL:
SELECT DISTINCT ?date WHERE {
  wd:Q25173 wdt:P729 ?date .
}

Using entities:
Titanic, also known as RMS Titanic, The Titanic, Royal Mail Steamship Titanic, SS Titanic (wd:Q25173): British transatlantic passenger liner, launched and foundered in 1912

Using properties:
service entry, also known as commissioned, time of service entry, service introduction, launch date, in service (wd:P729 as wdt): date or point in time on which a piece or class of equipment entered operational service, start time

Example 2:
Question:
Which scientist is known for the Manhattan Project and the Nobel Peace Prize?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P1344 wd:Q127050 .
  ?scientist wdt:P279 * wd:Q901 .
  ?uri wdt:P106 ?scientist .
  ?uri wdt:P166 wd:Q35637 .
}

Using entities:
Manhattan Project, also known as Development of Substitute Materials (wd:Q127050): World War 2 American R&D program that produced the first nuclear weapons
Nobel Peace Prize, also known as Nobel Prize for Peace, Noble Peace Prize, Nobel Prize in Peace (wd:Q35637): one of five Nobel Prizes
scientist, also known as natural philosopher (wd:Q901): person who use scientific methods to study in an area of interest

Using properties:
occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
participant in, also known as participated in, present at, takes part, took part, took part in (wd:P1344 as wdt): event in which a person or organization was/is a participant; inverse of P710 or P1923, significant event, part of
award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as wdt): award or recognition received by a person, organization or creative work
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain

Example 3:
Question:
Who is the owner of Universal Studios?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q168383 wdt:P127 ?uri .
}

Using entities:
Universal Pictures, also known as Universal City Studios LLC, Universal Film Manufacturing Company, Universal-International Pictures Inc., Universal Studios (wd:Q168383): American film studio

Using properties:
owned by, also known as belongs to, stockholders, stockholder, shareholders, shareholder (wd:P127 as wdt): owner of the subject

[Assistant]
The question "Who died at the North Pole?" is asking for people who have the place of death as the North Pole.

Step 1: Identify the entity for "North Pole."
Step 2: Identify the property for "place of death."
Step 3: Query for people who have the place of death as the North Pole.

I will start by searching for the entity "North Pole" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. North Pole, also known as terrestrial North Pole, geographic North Pole (wd:Q934): one of the two points where the Earth's axis of rotation intersects its surface
2. North Pole, also known as North Pole, Alaska (wd:Q79494): city in Alaska, USA
3. North Pole, also known as North Pole, ID, North Pole, Idaho (wd:Q7056392): unincorporated community in Idaho
4. North Pole, also known as North Pole, New York, North Pole, NY (wd:Q4327488): human settlement in United States of America
5. North Pole (wd:Q130803558): pub in Wateringbury, Tonbridge and Malling, Kent, England
6. North Pole (wd:Q21958071): mine in Western Australia
7. North Pole (wd:Q21983876): mountain in Australia
8. North Pole (wd:Q31972103): mine in Masvingo Province, Zimbabwe
9. North Pole (wd:Q34886291): mountain in United States of America
10. North Pole (wd:Q49057483): mountain in Idaho, United States of America

[Assistant] The entity for the geographic North Pole is wd:Q934. Next, I will search for the property that represents "place of death" to find people who died at the North Pole.

[Tool]
Top 10 property alternatives:
1. place of death, also known as POD, location of death, killed in, deathplace, died in (wd:P20 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): most specific known (e.g. city instead of country, or hospital i... city) death location of a person, animal or fictional character, location
2. place of burial, also known as interment, interment location, interment place, interred at, location of burial (wd:P119 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): location of grave, resting place, place of ash-scattering, etc. ...veral places: e.g., re-burials, parts of body buried separately., location
3. date of death, also known as DOD, deathdate, died, died on, year of death (wd:P570 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): dissolved, abolished or demolished date, date on which the subject died, end time
4. category for people who died here, also known as category for place of death, category of people who died here (wd:P1465 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): category item for people who died in this location, related category
5. manner of death, also known as type of death, nature of death, death manner, death type, circumstance of death (wd:P1196 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): general circumstances of a person's death; e.g. natural causes, ...ysiological mechanism, e.g. heart attack, trauma, pneumonia etc.
6. number of deaths, also known as dead, qty fatalities, qty deaths, number of fatalities, fatalities (wd:P1120 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): total (cumulative) number of people who died since start as a direct result of an event or cause
7. category for people buried here, also known as buried here: Wikimedia category for, category of people buried here, category for place of burial, category for burials (wd:P1791 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): Wikimedia category for people with a burial site within this area, related category
8. cause of death, also known as death cause, murder method, method of murder, die of, die from (wd:P509 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): underlying or immediate cause of death.  Underlying cause (e.g. ...adest category, e.g. natural causes, accident, homicide, suicide
9. date of burial or cremation, also known as burial date, cremation date, date of cremation, funeral date (wd:P4602 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): date on which the person was buried or cremated soon after death, point in time
10. commemorates, also known as monument to, memorial to, memorializes, marks, in memory of (wd:P547 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): what the place, monument, memorial, or holiday, commemorates, main subject

[Assistant] The property for "place of death" is wd:P20. Now I will write a SPARQL query to find people who have the place of death as the North Pole (wd:Q934). I will also include their names as labels.

[Tool]
Got 1 row and 2 columns:
| person                             | personLabel               |
| ---------------------------------- | ------------------------- |
| Sigizmund Levanevsky (wd:Q1333099) | Sigizmund Levanevsky (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves persons who died at the North Pole (wd:Q934) using the property place of death (wdt:P20). The result includes Sigizmund Levanevsky, which matches the answer provided. The query also optionally retrieves English labels for readability. The query and answer are accurate and complete for the question asked.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?character ?characterLabel WHERE {
  wd:Q696071 wdt:P674 ?character .
  ?character wdt:P21 wd:Q6581072 .
  OPTIONAL {
    ?character rdfs:label ?characterLabel FILTER ( LANG( ?characterLabel ) = "en" )
  }
}
LIMIT 50

There are no female characters listed as characters in the Hunter × Hunter series in Wikidata. Therefore, based on the available data, there is no female main character in Hunter × Hunter.

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

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

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

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

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

[User] is there female main character in hunter x hunter?

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

[Tool]
Example 1:
Question:
Which electronics companies were founded in Beijing?

SPARQL:
SELECT DISTINCT ?company WHERE {
  ?company wdt:P452 wd:Q581105 ; wdt:P740 wd:Q956 .
}

Using entities:
consumer electronics, also known as home electronics, household electronics (wd:Q581105): electronic equipment intended for everyday use, typically in private homes
Beijing, also known as Pei-ping, Peip'ing, Peiping, Pekin, Pe-king (wd:Q956): capital city of China

Using properties:
industry, also known as branch, economic branch, field of action, field of exercise, sector (wd:P452 as wdt): specific industry of company or organization, part of
location of formation, also known as place of incorporation, originates from, place of establishment, place of formation, place of foundation (wd:P740 as wdt): location where a group or organization was formed, location of creation

Example 2:
Question:
What is Angela Merkel’s birth name?

SPARQL:
SELECT ?o1 WHERE {
  wd:Q567 wdt:P1477 ?o1 .
}

Using entities:
Angela Merkel, also known as Angela Dorothea Merkel, leader of the free world, Angela Kasner (wd:Q567): chancellor of Germany from 2005 to 2021, politician, physicist

Using properties:
birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as wdt): full name of a person at birth, if different from their current, generally used name, name

Example 3:
Question:
What is the biggest stadium in Spain?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  {
    ?uri wdt:P31 wd:Q483110 .
  } UNION {
    ?uri wdt:P31 ?type .
    ?type wdt:P279 wd:Q483110
  }
  ?uri wdt:P17 wd:Q29 .
  ?uri wdt:P1083 ?num .
}
ORDER BY DESC ( ?num )
LIMIT 1

Using entities:
Spain, also known as Kingdom of Spain (wd:Q29): country in southwestern Europe with territories in Africa
stadium, also known as sports arena, sports stadium, sport stadium, stadiums, 🏟 (wd:Q483110): place or venue for (mostly) outdoor sports, concerts, or other events

Using properties:
maximum capacity, also known as capacity, complement, crew, number of seats, seating capacity (wd:P1083 as wdt): number of people allowed for a venue or vehicle
country, also known as sovereign state, state, land, host country (wd:P17 as wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

[Assistant]
The question is whether there is a female main character in the anime/manga "Hunter x Hunter." To answer this, I need to:

1. Identify the entity for "Hunter x Hunter."
2. Identify the property that relates to main characters of a work.
3. Check if any of the main characters of "Hunter x Hunter" are female.

I will start by searching for the entity "Hunter x Hunter" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Hunter × Hunter, also known as HUNTER × HUNTER, Hunter x Hunter, HXH (wd:Q696071): Japanese manga series
2. Hunter × Hunter, also known as H×H, Hunter x Hunter, HxH (wd:Q70209136): 2011 Japanese anime television series
3. Hunter × Hunter, also known as Hunter x Hunter, HxH (wd:Q21232458): 1999 Japanese anime television series
4. Monster Hunter Generations, also known as Monster Hunter X (wd:Q20856979): 2015 Japanese video game
5. Hunter Xcite (wd:Q60767092): sailboat class
6. Xavier Hunter (wd:Q100806788): basketball player
7. Hunter × Hunter: Phantom Rouge, also known as Hunter X Hunter: Phantom Rouge (wd:Q11398237): 2013 film by Yūzō Satō
8. City Hunter XYZ (wd:Q97170832): fan film by Filip Wong
9. Monster Hunter Generations Ultimate, also known as Monster Hunter XX (wd:Q30302563): 2017 video game
10. XX: Beautiful Hunter (wd:Q8042573): 1994 film by Masaru Konuma

[Assistant] The entity "Hunter × Hunter" as a Japanese manga series is wd:Q696071. Now I need to find the property that relates to main characters of a work. I will search for properties related to "main character" or "character" for this entity.

[Tool]
Top 10 property alternatives:
1. characters, also known as appears in this work (wd:P674 as wdt/p): characters which appear in this item (like plays, operas, operettas, books, comics, films, TV series, video games)
2. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
3. author, also known as writer, written by, poet, playwright, maker (wd:P50 as wdt/p): main creator(s) of a written work (use on works, not humans); us...hor name string) when Wikidata item is unknown or does not exist, creator
4. title, also known as name, titled, page name, original title, known as (wd:P1476 as wdt/p): published name of a work, such as a newspaper article, a literary work, piece of music, a website, or a performance work, name
5. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as wdt/p): main Wikimedia category
6. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as wdt/p): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
7. language of work or name, also known as language of the reference, language of URL, language of website, language of work, named in language (wd:P407 as wdt/p): language associated with this creative work (such as books, show...guage" (P103) and "languages spoken, written or signed" (P1412))
8. MyAnimeList manga ID, also known as Manga ID MAL, MAL manga ID (wd:P4087 as wdt/p): identifier for a manga or novel on MyAnimeList
9. start time, also known as start date, since, valid, join time, joined (wd:P580 as wdt/p): time an entity begins to exist or a statement starts being valid, point in time
10. topic's main template, also known as topic has template, topic's main module, topic's main infobox, topic infobox, main template (wd:P1424 as wdt/p): the main template relating to a topic

No other items found

[Assistant] The property "characters" (wdt:P674) relates to characters which appear in the work. Now I will query the characters of "Hunter × Hunter" (wd:Q696071) and check if any of them are female main characters. To do this, I will get the characters and check their gender. I will limit the results to characters that are female (wd:Q6581072).

[Tool] Got no rows and 2 columns

[Assistant] There are no characters explicitly marked as female in the characters property of Hunter × Hunter (wd:Q696071). I will try to find main characters of Hunter × Hunter by searching for "main character" and "Hunter x Hunter" to see if there is a specific property or qualifier for main characters.

[Tool]
Top 10 property alternatives:
1. character role, also known as role, plays, performer of, as, acting role (wd:P453 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)
2. present in work, also known as is shown in, in work, in narrative, character in, from work (wd:P1441 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): this (fictional or fictionalized) entity, place, or person appea...r works, P1343 for entities described in non-fictional accounts)
3. name of the character role, also known as character named as, role named as, role name, name of the role, name of the character (wd:P4633 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): name by which a character role is recorded in a database or ment...ably a specific performance of a theatrical production of a play, name
4. performer, also known as actor, sung by, singer, recording by, recorded by (wd:P175 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): actor, musician, band or other performer associated with this role or musical work, contributor to the creative work or subject
5. depicted by, also known as acted by, shown in, seen in, portrayed by, played by (wd:P1299 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): object depicting this subject (object being creative works such as books, films, paintings)
6. characters, also known as appears in this work (wd:P674 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): characters which appear in this item (like plays, operas, operettas, books, comics, films, TV series, video games)
7. personality trait of fictional character, also known as personality trait, personality trait of fictitious character, personal quality of fictional character, fictitious character personality trait, personal quality of fictitious character (wd:P9652 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): particular personality trait which applies to this fictional character
8. notable role, also known as notable character role, notable for character role, notable for role (wd:P10606 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): role in a theatrical, motion picture, television, or other work that a performer is particularly known for, notable work
9. used by, also known as armiger, user, played by, of (wd:P1535 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): item or concept that makes use of the subject (use sub-properties when appropriate)
10. character type, also known as -dere, stock character, stereotype, dere, character stereotype (wd:P9071 as ps/pqv/prv/psn/wdt/pqn/psv/wdtn/prn/pq/pr/p): generic character type that this fictional character represents, manifestation of

[Assistant] There is no direct property for "main character," but the property "characters" (wdt:P674) is used for characters appearing in the work. I will now try to get a list of characters of Hunter × Hunter and check their gender to see if any are female. I will also try to get their roles or descriptions to identify if they are main characters.

[Tool]
Got 6 rows and 3 columns:
| character                         | characterLabel           | genderLabel |
| --------------------------------- | ------------------------ | ----------- |
| Ging Freecss (wd:Q20381047)       | Ging Freecss (en)        | male (en)   |
| Hisoka (wd:Q2280812)              | Hisoka (en)              | male (en)   |
| Kurapika (wd:Q2537895)            | Kurapika (en)            | male (en)   |
| Leorio Paladiknight (wd:Q2611418) | Leorio Paladiknight (en) | male (en)   |
| Gon Freecss (wd:Q2717608)         | Gon Freecss (en)         | male (en)   |
| Killua Zoldyck (wd:Q2717625)      | Killua Zoldyck (en)      | male (en)   |

[Assistant] The characters listed for Hunter × Hunter are all male according to the data retrieved. I will check if there are any other characters in the series that might be female by expanding the query to include more characters and filtering for female gender explicitly.

[Tool] Got no rows and 2 columns

[Assistant] There are no female characters listed as characters in the Hunter × Hunter series in Wikidata. Based on this data, it appears there is no female main character in Hunter × Hunter. I will now provide the final answer.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves characters from the Hunter × Hunter series who are female by filtering on the gender property. The query returned no results, which supports the answer that there are no female main characters listed in Wikidata for this series. The query is well-formed and follows the rules, and the answer is consistent with the query result. Therefore, the output is correct and complete.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?numberOfSeasons WHERE {
  wd:Q30603704 wdt:P2437 ?numberOfSeasons .
}

Got 1 row and 1 column:
| numberOfSeasons |
| --------------- |
| 3 (xsd:decimal) |

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

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

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

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

[User] How many seasons does Pose have?

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

[Tool]
Example 1:
Question:
What is the name of the university where Obama's wife studied?

SPARQL:
SELECT DISTINCT ?uri ?institute WHERE {
  wd:Q76 wdt:P26 / wdt:P69 / wdt:P361 * ?uri .
  ?uri wdt:P31 * / wdt:P279 * wd:Q3918 .
}

Using entities:
university, also known as uni, universities (wd:Q3918): academic institution for further education
Barack Obama, also known as Honorable Barack Obama, BHO, Obama, Barry O Bomber, President Obama (wd:Q76): president of the United States from 2009 to 2017, community organizer, political writer, statesperson, politician, podcaster, memoirist, academic, lawyer, jurist

Using properties:
spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as wdt): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
part of, also known as of, within, system of, subsystem of, subgroup of (wd:P361 as wdt): object of which the subject is a part (if this subject is alread... of "has part" (P527, see also "has parts of the class" (P2670))
educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as wdt): educational institution attended by subject, affiliation

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

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

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

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

Example 3:
Question:
What is the highest place of the Urals?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q35600 wdt:P610 ?uri .
}

Using entities:
Ural Mountains, also known as the Urals, Urals (wd:Q35600): mountain range in Russia

Using properties:
highest point, also known as tallest point, zenith, summit, pinnacle, highest peak (wd:P610 as wdt): point with highest elevation in a region or path, has part(s)

[Assistant]
The question is about the TV show "Pose" and how many seasons it has. We need to find the entity for the TV show "Pose" and then find the property that indicates the number of seasons.

Step 1: Search for the entity "Pose" in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Pose (wd:Q30603704): 2018 American drama television series
2. posture, also known as attitude, human position, pose (wd:Q8514257): physical configuration that a human or animal body can take
3. Pose (wd:Q29966944): 2017 song by Rihanna
4. pose (wd:Q1671968): position and orientation of an object in an image
5. Pose (wd:Q432543): single
6. Pose (wd:Q108250580): 2021 song by Red Velvet
7. Pose (wd:Q85794108): 2021 single by Yo Gotti featuring Lil Uzi Vert
8. pose, also known as posing (wd:Q2105738): sustained posture or positioning of the torso and limbs
9. Pose (wd:Q6083341): Album by Second
10. Pose (wd:Q36886624): family name

[Assistant] The entity "Pose" as a 2018 American drama television series is wd:Q30603704. Next, I will search for properties related to the number of seasons for this TV show.

[Tool]
Top 10 property alternatives:
1. number of seasons, also known as no. of seasons, no. of series, number of series, seasons (wd:P2437 as wdt/p): number of seasons a television or radio series has had, number of parts of this work
2. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as wdt/p): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
3. main subject, also known as primary topic, primary subject, primary keyword, plot keyword, of (wd:P921 as wdt/p): primary topic of a work (see also P180: depicts), depicts
4. number of episodes, also known as series length, no. of episodes, episodes, episode count (wd:P1113 as wdt/p): number of episodes in a film/TV/radio series, number of parts of this work
5. end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as wdt/p): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time
6. narrative location, also known as set in location, set in, setting, setting location, setting of work (wd:P840 as wdt/p): the narrative of the work is set in this location, significant place, depicts
7. producer, also known as music producer, record producer, produced by, film producer, creative producer (wd:P162 as wdt/p): person(s) who produced the film, musical work, theatrical produc...etc.) [for production company, use P272, video games - use P178]
8. distribution format, also known as book format, type of media, publication format, method of distribution, medium (wd:P437 as wdt/p): method (or type) of distribution for the subject
9. start time, also known as start date, since, valid, join time, joined (wd:P580 as wdt/p): time an entity begins to exist or a statement starts being valid, point in time
10. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as wdt/p): award or recognition received by a person, organization or creative work

No other items found

[Assistant] The property "number of seasons" (wdt:P2437) is the correct property to find how many seasons the TV show "Pose" has. Now I will write a SPARQL query to get the number of seasons for the TV show "Pose" (wd:Q30603704).

[Tool]
Got 1 row and 1 column:
| numberOfSeasons |
| --------------- |
| 3 (xsd:decimal) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the number of seasons for the TV show Pose using the property 'number of seasons' (wdt:P2437). The query returns the expected result of 3 seasons, which matches the answer provided. The query is simple, direct, and follows the rules for returning identifiers and values. No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?award ?awardLabel ( COUNT( ?award ) AS ?count ) WHERE {
  wd:Q312674 wdt:P166 ?award .
  FILTER ( ?award IN ( wd:Q1422140 , wd:Q1472235 ) ) .
  ?award rdfs:label ?awardLabel FILTER ( LANG( ?awardLabel ) = "en" )
}
GROUP BY ?award ?awardLabel

Got 2 rows and 3 columns:
| award                                                    | awardLabel                                      | count       |
| -------------------------------------------------------- | ----------------------------------------------- | ----------- |
| Golden Globe Award for Best Original Score (wd:Q1422140) | Golden Globe Award for Best Original Score (en) | 1 (xsd:int) |
| Golden Globe Award for Best Original Song (wd:Q1472235)  | Golden Globe Award for Best Original Song (en)  | 1 (xsd:int) |

Giorgio Moroder has won the Golden Globe Award twice: once for Best Original Score and once for Best Original Song.

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

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

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

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

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

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

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

[Tool]
Example 1:
Question:
Give me all breeds of the German Shepherd dog.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P279 * wd:Q38280 FILTER ( ?uri != wd:Q38280 )
}

Using entities:
German Shepherd, also known as GSD, Alsatian dog, Alsatian, Alsatian wolf dog (wd:Q38280): German breed of dog

Using properties:
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain

Example 2:
Question:
What airlines are part of the SkyTeam alliance?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P114 wd:Q212282 .
}

Using entities:
SkyTeam, also known as Sky Team (wd:Q212282): global airline alliance

Using properties:
airline alliance (wd:P114 as wdt): alliance the airline belongs to, member of

Example 3:
Question:
How many seats does the home stadium of FC Porto have?

SPARQL:
SELECT DISTINCT ?num WHERE {
  wd:Q128446 wdt:P115 / wdt:P1083 ?num
}

Using entities:
FC Porto, also known as Porto, Futebol Clube do Porto, Football Club of Porto, FCPorto, F.C. Porto (wd:Q128446): professional association football club based in Porto, Portugal

Using properties:
maximum capacity, also known as capacity, complement, crew, number of seats, seating capacity (wd:P1083 as wdt): number of people allowed for a venue or vehicle
home venue, also known as home water, venue, stadium, home ground, home field (wd:P115 as wdt): home stadium or venue of a sports team or applicable performing arts organization, location

[Assistant]
The question is about how many times Giorgio Moroder has won the Golden Globe Award.

Step 1: Identify the entity "Giorgio Moroder" in Wikidata.
Step 2: Identify the property related to winning the Golden Globe Award.
Step 3: Query how many times Giorgio Moroder has won the Golden Globe Award.

I will start by searching for the entity "Giorgio Moroder" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Giorgio Moroder, also known as Hansjörg Moroder, Giovanni Giorgio Moroder (wd:Q312674): Italian record producer and composer, film score composer, record producer, film producer, disc jockey, songwriter, composer
2. Giorgio by Moroder (wd:Q15720519): 2013 song by Daft Punk
3. Metropolis, also known as Giorgio Moroder Presents Metropolis (wd:Q76367460): 1984 version by Giorgio Moroder
4. Philip Oakey & Giorgio Moroder (wd:Q7184164): 1989 self-titled studio album by Philip Oakey & Giorgio Moroder
5. Giorgione, also known as Giorgon, Giorgioni di Castelfranco, Giorgioni da Castel Franco, Giorgioni, Giorgione of Castel Franco (wd:Q8459): Venetian Renaissance painter (1478–1510), visual artist, painter
6. Rubén Omar Romano, also known as Rubén Romano, Rubén Omar Romano Cachía, Ruben Omar Romano, Giorgio (wd:Q322982): Argentine footballer and manager, association football manager, association football player
7. Giorgio (wd:Q5563455): 1958 single by Lys Assia
8. Giorgio, also known as Giorgio (first name), Giorgio (given name) (wd:Q12900074): male given name
9. Moroder (wd:Q18288660): family name
10. Giorgio (wd:Q37251262): family name

[Assistant] The entity for Giorgio Moroder is wd:Q312674. Now I will search for properties related to winning the Golden Globe Award for this entity.

[Tool]
Top 10 property alternatives:
1. nominated for, also known as nominee for, shortlisted for, selected for award, selected for, nominee for award (wd:P1411 as wdt/p): award nomination received by a person, organisation or creative work (inspired from "award received" (Property:P166))
2. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as wdt/p): award or recognition received by a person, organization or creative work
3. Academy Awards Database nominee ID, also known as Oscar nominee ID (wd:P6150 as wdt/p): identifier for nominees in the official Academy Awards database
4. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as wdt/p): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
5. Grammy Awards artist ID (wd:P7303 as wdt/p): identifier for an artist on the Grammy Awards website
6. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt/p): most specific known birth location of a person, animal or fictional character, location
7. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
8. AllMusic artist ID, also known as AllMusic, AllMusic ID, amg artist (wd:P1728 as wdt/p): identifier for an artist, musical group, or record label in the AllMusic database (record labels are listed as "artists")
9. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdt/p): the object is a country that recognizes the subject as its citizen, country
10. Douban movie celebrity ID, also known as https://movie.douban.com/celebrity, https://movie.douban.com, https://m.douban.com, Douban person ID, douban.com person ID (wd:P5284 as wdt/p): identifier for a celebrity at the Douban movie website

No other items found

[Assistant] The property "award received" (wdt:P166) is the most relevant for finding awards won by Giorgio Moroder. Now I will find the awards Giorgio Moroder has received using this property and check if any of them are Golden Globe Awards.

[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] Giorgio Moroder has won the "Golden Globe Award for Best Original Score" (wd:Q1422140). Now I will count how many times he has won this Golden Globe Award.

[Tool]
Got 1 row and 1 column:
| count       |
| ----------- |
| 0 (xsd:int) |

[Assistant] The query returned 0, which means the approach to count the awards by checking if the award instance is the Golden Globe Award for Best Original Score is not correct. Instead, I will count how many times Giorgio Moroder has received any award that is a subclass or instance of the Golden Globe Award. I will try to find the correct property or qualifier to count the number of times he won the Golden Globe Award.

[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) | Academy Award for Best Original Score (wd:Q488651)                     |
| Giorgio Moroder (wd:Q312674) | award received (wdt:P166) | Grammy Award for Album of the Year (wd:Q904528)                        |
| 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) | Golden Globe Award for Best Original Song (wd:Q1472235)                |
| 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)          |
| 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) | Grammy Award for Best Instrumental Composition (wd:Q13635451)          |
| Giorgio Moroder (wd:Q312674) | award received (wdt:P166) | Commander of the Order of Merit of the Italian Republic (wd:Q14539729) |
| ...                          | ...                       | ...                                                                    |

[Assistant] Giorgio Moroder has received two different Golden Globe Awards: "Golden Globe Award for Best Original Score" (wd:Q1422140) and "Golden Globe Award for Best Original Song" (wd:Q1472235). I will count how many times he has received each of these awards.

[Tool]
Got 2 rows and 2 columns:
| award                                                    | count       |
| -------------------------------------------------------- | ----------- |
| Golden Globe Award for Best Original Score (wd:Q1422140) | 1 (xsd:int) |
| Golden Globe Award for Best Original Song (wd:Q1472235)  | 1 (xsd:int) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly identifies the two specific Golden Globe Awards that Giorgio Moroder has won: Best Original Score and Best Original Song. It counts each award once, matching the answer that he has won twice in total. The query uses the correct entity for Giorgio Moroder and the correct properties and award items. The answer is accurate and complete based on the query results. No further refinement is necessary.


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

The creator of Boo-Boo Bear is William Hanna.

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

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

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

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

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

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

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

[Tool]
Example 1:
Question:
How big is the earth's diameter?

SPARQL:
SELECT ?c WHERE {
  wd:Q2 wdt:P2386 ?c .
}

Using entities:
Earth, also known as World, The Blue Planet, Planet Earth, Mother Earth (wd:Q2): third planet from the Sun in the Solar System

Using properties:
diameter, also known as ⌀, diametre (wd:P2386 as wdt): diameter of a circular or spherical object

Example 2:
Question:
How many programming languages are there?

SPARQL:
SELECT ( COUNT( DISTINCT ?sub ) AS ?count ) WHERE {
  ?sub wdt:P31 / wdt:P279 * wd:Q9143 .
}

Using entities:
programming language, also known as coding language, computer language, computer programming, computer programming language (wd:Q9143): language for communicating instructions to a machine

Using properties:
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 3:
Question:
Who created Family Guy?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q5930 wdt:P170 ?uri
}

Using entities:
Family Guy (wd:Q5930): American adult animated sitcom

Using properties:
creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as wdt): maker of this creative work or other object (where no more specific property exists)

[Assistant] From the examples, I see that the property "creator" (wdt:P170) is used to find the creator of a work. Now I need to find the entity for "Boo-Boo Bear" in Wikidata. I will search for the entity "Boo-Boo Bear" first.

[Tool]
Top 10 entity alternatives:
1. Boo-Boo Bear, also known as Boo Boo (wd:Q2394280): fictional character in Yogi Bear
2. Yogi Bear and Boo-Boo Bear, also known as Boo Boo and Yogi, Boo-Boo Bear and Yogi Bear, Yogi and Boo Boo (wd:Q132184386): fictional characters from Yogi Bear
3. Ursidae, also known as bear, bear family, ursid, ursids (wd:Q11788): family of mammals
4. Ursus, also known as 🐻 (wd:Q243359): genus of mammals
5. Tu-95, also known as Bear, Tu-95 Bear (wd:Q181815): bomber aircraft family by Tupolev
6. Bégard, also known as Bear (wd:Q217002): commune in Côtes-d'Armor, France
7. short, also known as bear, going short, selling short, shorting, short position (wd:Q106526): practice of selling securities or other financial instruments that are not currently owned
8. Jack Nicklaus, also known as Golden Bear, William Nicklaus, Karnak, Jack William Nicklaus, Bear (wd:Q9424): golf course designer, American golfer, golfer
9. Bear, also known as Bear, DE (wd:Q755632): census-designated place in Delaware, United States
10. bear, also known as bear community, gay bears, gay bear community, bear culture, gay bear (wd:Q618804): term in gay culture for heavily hairy, and usually muscular and bearded men

[Assistant] The entity "Boo-Boo Bear" (wd:Q2394280) is the fictional character in Yogi Bear. Now I will search for the property "creator" (wdt:P170) for this entity to find the creator of Boo-Boo Bear.

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

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly identifies the creator of Boo-Boo Bear using the property P170 (creator) and the entity Q2394280 for Boo-Boo Bear. It also retrieves the English label for the creator. The answer 'William Hanna' is accurate and matches the query result. The query follows the rules by returning the identifier and label, and the answer is complete and correct.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?player ?playerLabel ( COUNT( ?award ) AS ?nbaAwardCount ) WHERE {
  VALUES ?player {
    wd:Q41421 wd:Q25369
  }
  ?player wdt:P166 ?award .
  ?award rdfs:label ?awardLabel .
  FILTER ( LANG( ?awardLabel ) = "en" ) FILTER ( CONTAINS( LCASE( ?awardLabel ) , "nba" ) || CONTAINS( LCASE( ?awardLabel ) , "national basketball association" ) ) OPTIONAL {
    ?player rdfs:label ?playerLabel .
    FILTER ( LANG( ?playerLabel ) = "en" )
  }
}
GROUP BY ?player ?playerLabel

Got 2 rows and 3 columns:
| player                     | playerLabel         | nbaAwardCount |
| -------------------------- | ------------------- | ------------- |
| Kobe Bryant (wd:Q25369)    | Kobe Bryant (en)    | 6 (xsd:int)   |
| Michael Jordan (wd:Q41421) | Michael Jordan (en) | 10 (xsd:int)  |

Michael Jordan has won more NBA awards (10) compared to Kobe Bryant (6).

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

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

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

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

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

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

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

[Tool]
Example 1:
Question:
Give me all spacecrafts that flew to Mars.

SPARQL:
SELECT ?s1 where {
  ?s1 wdt:P31 wd:Q389459
}

Using entities:
Mars rover, also known as Mars rovers (wd:Q389459): space exploration vehicle designed to move across the surface of Mars

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

Example 2:
Question:
For which label did Elvis record his first album?

SPARQL:
SELECT DISTINCT ?label WHERE {
  wd:Q59150527 wdt:P527 ?uri .
  ?uri wdt:P577 ?date .
  ?uri wdt:P264 ?label .
}
ORDER BY ?date
LIMIT 1

Using properties:
record label, also known as label, labels (wd:P264 as wdt): brand and trademark associated with the marketing of subject music recordings and music videos
has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as wdt): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).
publication date, also known as launched, published, publication time, publication, pubdate (wd:P577 as wdt): date or point in time when a work was first published or released, point in time

Example 3:
Question:
What is the profession of Frank Herbert?

SPARQL:
SELECT ?o1 WHERE {
  wd:Q7934 wdt:P106 ?o1 .
}

Using entities:
Frank Herbert, also known as Jr. Franklin Patrick Herbert, Jr. Franklin Herbert, Frank Patrick Herbert, Jr. Frank Patrick Herbert, Franklin Herbert (wd:Q7934): American writer (1920–1986), science fiction writer, prose writer, photographer, journalist, novelist, writer

Using properties:
occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)

[Assistant] The examples do not directly relate to NBA awards or sports awards. Next, I will search for the entities "Michael Jordan" and "Kobe Bean Bryant" in Wikidata to get their identifiers. Then I will search for properties related to awards or honors for these entities.

[Tool]
Top 10 entity alternatives:
1. Michael Jordan, also known as His Airness, Air Jordan (wd:Q41421): American basketball player and businessman (born 1963), basketball player, baseball player, autobiographer, spokesperson, entrepreneur
2. Michael I. Jordan, also known as Michael Irwin Jordan, Michael Jordan (wd:Q3308285): American computer scientist, University of California, Berkeley, artificial intelligence researcher, computer scientist, university teacher, statistician
3. Michael Jordan, also known as Michael William Jordan (wd:Q6831716): English footballer (born 1984), association football player
4. Michael Jordan (wd:Q65029442): American football offensive lineman, American football player
5. Mike Jordan, also known as Michael Jordan, Michael H. Jordan, Michael Henry Jordan, M. H. Jordan (wd:Q6847437): American baseball player and politician (1863-1940), baseball player, politician
6. Michael Jordan, also known as Mike Jordan (wd:Q27069141): American football cornerback, American football player
7. Michael Jordan (wd:Q6831715): Irish politician, politician, farmer
8. Michael Jordan (wd:Q6831719): British mycologist, writer, and television presenter, television presenter, mushroom gatherer, mycologist, announcer, writer
9. Michael Jordan (wd:Q1928047): German draughtsperson, artist and comics artist, university teacher, comics artist, draftsperson, artist
10. Michael Jordan (wd:Q100983906): college basketball player (2001–2001) New Mexico, basketball player

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

[Assistant] I found the entities for Michael Jordan (wd:Q41421) and Kobe Bryant (wd:Q25369). Next, I will search for properties related to awards or honors for Michael Jordan. Then I will do the same for Kobe Bryant. This will help identify the relevant properties to count the number of NBA awards won by each.

[Tool]
Top 10 property alternatives:
1. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as wdt/p): award or recognition received by a person, organization or creative work
2. nominated for, also known as nominee for, shortlisted for, selected for award, selected for, nominee for award (wd:P1411 as wdt/p): award nomination received by a person, organisation or creative work (inspired from "award received" (Property:P166))
3. member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as wdt/p): sports teams or clubs that the subject represents or represented, member of
4. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdt/p): the object is a country that recognizes the subject as its citizen, country
5. participant in, also known as participated in, present at, takes part, took part, took part in (wd:P1344 as wdt/p): event in which a person or organization was/is a participant; inverse of P710 or P1923, significant event, part of
6. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
7. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as wdt/p): work where this item is described, attested in
8. league or competition, also known as tournament, sports league, division, cup, competition (wd:P118 as wdt/p): league or competition in which team or player has played, or in which an event occurs, participant in
9. given name, also known as name, proper name, personal name, middle name, forename (wd:P735 as wdt/p): first name or another given name of this person; values used with the property should not link disambiguations nor family names, name
10. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

No other items found

[Tool]
Top 10 property alternatives:
1. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as wdt/p): award or recognition received by a person, organization or creative work
2. nominated for, also known as nominee for, shortlisted for, selected for award, selected for, nominee for award (wd:P1411 as wdt/p): award nomination received by a person, organisation or creative work (inspired from "award received" (Property:P166))
3. member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as wdt/p): sports teams or clubs that the subject represents or represented, member of
4. significant event, also known as significant occurrence, significant incident, significant achievment, sign. event, outcome (wd:P793 as wdt/p): significant or notable events associated with the subject
5. Academy Awards Database nominee ID, also known as Oscar nominee ID (wd:P6150 as wdt/p): identifier for nominees in the official Academy Awards database
6. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdt/p): the object is a country that recognizes the subject as its citizen, country
7. participant in, also known as participated in, present at, takes part, took part, took part in (wd:P1344 as wdt/p): event in which a person or organization was/is a participant; inverse of P710 or P1923, significant event, part of
8. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
9. league or competition, also known as tournament, sports league, division, cup, competition (wd:P118 as wdt/p): league or competition in which team or player has played, or in which an event occurs, participant in
10. given name, also known as name, proper name, personal name, middle name, forename (wd:P735 as wdt/p): first name or another given name of this person; values used with the property should not link disambiguations nor family names, name

No other items found

[Assistant]
The property "award received" (wdt:P166) is used for both Michael Jordan and Kobe Bryant to indicate awards or recognitions they have received. To answer the question "who has won more NBA awards," I will count the number of awards related to the NBA for each player using this property.

I will write a SPARQL query that counts the number of awards received by Michael Jordan and Kobe Bryant, filtering for awards related to the NBA. I will check the labels of the awards to see if they contain "NBA" or "National Basketball Association" as a keyword to identify NBA awards.

[Tool]
SPARQL execution failed:
Error while executing a SERVICE request to <http://wikiba.se:80/ontology#label>: SERVICE responded with HTTP status code: 301, Moved Permanently. First 100 bytes of the response: '<html>
<head><title>301 Moved Permanently</title></head>
<body>
<center><h1>301 Moved Permanently'

[Assistant] The query failed because the SERVICE wikibase:label is not supported by the endpoint. I will rewrite the query without using SERVICE wikibase:label and instead use optional clauses to get the labels. I will also remove the ordering and just return the counts for both players.

[Tool]
Got 2 rows and 3 columns:
| player                     | playerLabel         | nbaAwardCount |
| -------------------------- | ------------------- | ------------- |
| Kobe Bryant (wd:Q25369)    | Kobe Bryant (en)    | 6 (xsd:int)   |
| Michael Jordan (wd:Q41421) | Michael Jordan (en) | 10 (xsd:int)  |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the count of NBA-related awards for both Michael Jordan and Kobe Bryant by filtering awards with labels containing 'nba' or 'national basketball association'. The query returns the expected results showing Michael Jordan with 10 awards and Kobe Bryant with 6 awards. The answer is accurate and complete based on the data retrieved. No further refinement is necessary.