PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?industry WHERE {
  wd:Q806191 wdt:P31 ?industry
}

The House of Medici owns a business in the banking industry.

[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] In which industry does the House of Medici own a business?

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

[Tool]
Example 1:
Question:
Who is the owner of Rolls-Royce?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q243278 wdt:P127 ?uri .
}

Using entities:
Rolls-Royce, also known as Rolls-Royce Holdings plc (wd:Q243278): British multinational public holding company

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

Example 2:
Question:
Who owns Aldi?

SPARQL:
SELECT ?uri WHERE {
  wd:Q125054 wdt:P355 ?uri
}

Using entities:
Aldi, also known as Aldi Stores (wd:Q125054): brand name of two global discount supermarket chains

Using properties:
has subsidiary, also known as subordinate body, subsidiary body, subordinate unit, subsidiary, subsidiary company (wd:P355 as wdt): subsidiary of a company or organization; generally a fully owned...siness division" (P199). Opposite of parent organization (P749)., has part(s), owner of

Example 3:
Question:
What is Donald Trump's main business?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P488 wd:Q22686 ; wdt:P31 / wdt:P279 * wd:Q4830453 . MINUS {
    ?uri wdt:P576 ?closed
  }
}

Using entities:
Donald Trump, also known as President Donald Trump, President Donald J. Trump, President Trump, President Donald J Trump, Trump (wd:Q22686): president of the United States (2017–2021, 2025–present), real estate entrepreneur, chief executive officer, television producer, business magnate, businessperson, game show host, film producer, entrepreneur, politician, merchant, investor, writer, actor
business (wd:Q4830453): organization undertaking commercial, industrial, or professional activity

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)
chairperson, also known as dean, headed by, leader, president, chairwoman (wd:P488 as wdt): presiding member of an organization, group or body, director / manager, significant person
dissolved, abolished or demolished date, also known as ended, publication end date, final issue, date repealed, final year (wd:P576 as wdt): point in time at which the subject (organisation, building) ceas...g equipment,  "discontinued date" (P2669) for stopping a product, end time

[Assistant] Based on these examples, we can infer that we need to find the entity for the House of Medici and then look for its subsidiaries or businesses. Let's first search for the House of Medici entity.

[Tool]
Top 10 entity alternatives:
1. House of Medici, also known as Medici, Medici family (wd:Q170022): royal family
2. Xtian de Medici, also known as House of Medici, Medici (wd:Q67090917): Luxury brand fashion house
3. House of Medici of Ottajano, also known as Medici di Ottaiano, Medici di Ottajano, Princes of Ottajano (wd:Q3922038): Italian noble family
4. House of Medici-Tornaquinci, also known as House of Medici Tornaquinci (wd:Q124362845): Tuscan noble family
5. Genius of House of Medici, also known as Genio di Casa Medici (wd:Q126003839): statue in Palazzo Pitti, Florence, Italy, by Bartolomeo Ammannati
6. House of Medici di Melegnano, also known as Medici di Marignano, Medici di Melegnano (wd:Q65127246): Italian noble family
7. coat of arms of the House of Medici, also known as the House of Medici coat of arms, House of Medici coat of arms (wd:Q3972987)
8. House of Medici del Vascello (wd:Q97160588): Italian noble family
9. The House of Medicine (wd:Q35655376): scientific article published on July 1967
10. The house of medicine (wd:Q70468758): scientific article published on 01 July 1972

[Assistant]
The correct entity for the House of Medici is `wd:Q170022`. Now, let's find out what businesses or industries the House of Medici is associated with. We can use the property `P127` (owned by) or `P355` (has subsidiary) to find this information.

Let's start with `P127` (owned by).

[Tool]
Got 7 rows and 1 column:
| business                               |
| -------------------------------------- |
| Villa Banci (wd:Q111416431)            |
| Villa Vittoria (wd:Q111570993)         |
| Barchetto della Pineta (wd:Q111634204) |
| wd:Q3634898                            |
| Villa Panna (wd:Q4012389)              |
| Rocca di Fucecchio (wd:Q66371018)      |
| Medici Bank (wd:Q806191)               |

[Assistant]
The results include several villas and the Medici Bank. To determine the industry, we need to find out what these entities represent. Let's focus on the Medici Bank first, as it is likely to be the most relevant.

We can check the type of the Medici Bank to understand its industry.

[Tool]
Got 2 rows and 1 column:
| industry               |
| ---------------------- |
| bank (wd:Q22687)       |
| business (wd:Q4830453) |

[Assistant]
The Medici Bank is classified as a bank and a business. Therefore, the House of Medici owns a business in the banking industry.

Let's confirm this with a final SPARQL query that directly answers the user's question.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?island WHERE {
  wd:Q252 wdt:P36 ?capital .
  ?capital wdt:P706 ?island .
}

Java (wd:Q3757)

[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] On which island is the Indonesian capital located?

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

[Tool]
Example 1:
Question:
What is the capital of Cameroon?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q1009 wdt:P36 ?uri
}

Using entities:
Cameroon, also known as CAM, CM, CMR, Republic of Cameroon (wd:Q1009): sovereign state in West-Central Africa

Using properties:
capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as wdt): seat of government of a country, province, state or other type of administrative territorial entity

Example 2:
Question:
Who is the mayor of the capital of French Polynesia?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q30971 wdt:P36 ?capital .
  ?capital wdt:P6 ?uri .
}

Using entities:
French Polynesia, also known as 🇵🇫, Territory of French Polynesia, pf, French Oceania, French Settlements in Oceania (wd:Q30971): French overseas country in the southern Pacific Ocean

Using properties:
capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as wdt): seat of government of a country, province, state or other type of administrative territorial entity
head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as wdt): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson

Example 3:
Question:
How many people live in the capital of Australia?

SPARQL:
SELECT DISTINCT ?number WHERE {
  wd:Q408 wdt:P36 ?uri .
  ?uri wdt:P1082 ?number .
}

Using entities:
Australia, also known as AU, The Commonwealth of Australia, Stria, Straya, Stralia (wd:Q408): country in Oceania

Using properties:
population, also known as inhabitants, human population (wd:P1082 as wdt): number of people inhabiting the place; number of people of subject
capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as wdt): seat of government of a country, province, state or other type of administrative territorial entity

[Assistant] From the examples, we can see that the property `capital` (P36) is used to link a country to its capital city. We need to find the capital of Indonesia and then determine which island it is located on. Let's first identify the entity for Indonesia.

[Tool]
Top 10 entity alternatives:
1. Indonesia, also known as id, ID, IDN, INA, Republic of Indonesia (wd:Q252): island country in Southeast Asia and Oceania
2. Nusantara, also known as Indonesian Islands, Old Javanese name for Indonesia, Nusantara Islands, Nusantara Archipelago, Indonesian Archipelago (wd:Q49332): Old Javanese term for the archipelagic Majapahit territory
3. Indonesia, also known as Indonesia Raya (wd:Q6025895): song
4. Indonesia, also known as Kota Palopo, Palopo (wd:Q12497996): village in Palopo Kota Palopo Sulawesi Selatan, South Sulawesi, Indonesia
5. indonesia (wd:Q97375377)
6. Indonesia (wd:Q20203516): 1981 single by Sandra Reemer
7. Indonesia at the 1982 Asian Games, also known as Indonesia (wd:Q16927493): sporting event delegation
8. Indonesia (wd:Q43379569): board game
9. INDONESIA (wd:Q127048047): hymn tune
10. Indonesia. (wd:Q30744720): scientific article

[Assistant] The correct entity for Indonesia is `wd:Q252`. Now, let's find the capital of Indonesia using the `capital` property (P36).

[Tool]
Got 1 row and 1 column:
| capital            |
| ------------------ |
| Jakarta (wd:Q3630) |

[Assistant] The capital of Indonesia is Jakarta (`wd:Q3630`). Next, we need to determine which island Jakarta is located on. To do this, we will look for a property that links cities to islands.

[Tool]
Top 10 property alternatives:
1. located in/on physical feature, also known as located on the terrain feature, location (terrain feature), loc (terr), on, on geographical feature (wd:P706 as p/wdt): located on the specified (geo)physical feature. Should not be us...nly political/administrative (P131) or a mountain range (P4552)., location, part of
2. located in or next to body of water, also known as located on body of water, ocean, on bay, next to lake, on coast of (wd:P206 as p/wdt): body of water on or next to which a place is located, location
3. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
4. located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as p/wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
5. contains the administrative territorial entity, also known as has shires, has rural cities, has regions, has municipalities, has members (wd:P150 as p/wdt): (list of) direct subdivisions of an administrative territorial entity, has part(s)
6. elevation above sea level, also known as MAMSL, MASL, height, elevation above mean sea level, elevation (wd:P2044 as p/wdt): height of the item (geographical object) as measured relative to sea level
7. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as p/wdt): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
8. continent (wd:P30 as p/wdt): continent of which the subject is a part, located in/on physical feature
9. population, also known as inhabitants, human population (wd:P1082 as p/wdt): number of people inhabiting the place; number of people of subject
10. area, also known as total area, surface area, surface, size, resolution (wd:P2046 as p/wdt): area occupied by an object

No other items found

[Assistant] The property `located in/on physical feature` (P706) seems to be the most relevant for determining the island on which Jakarta is located. Let's use this property to find the island.

[Tool]
Got 1 row and 1 column:
| island          |
| --------------- |
| Java (wd:Q3757) |

[Assistant]
The Indonesian capital, Jakarta, is located on the island of Java (`wd:Q3757`).

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

```sparql
SELECT ?island WHERE {
  wd:Q252 wdt:P36 ?capital .
  ?capital wdt:P706 ?island .
}
```

This query will return the island on which the Indonesian capital is located.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
SELECT ( COUNT( DISTINCT ?year ) AS ?count ) WHERE {
  wd:Q169452 wdt:P166 wd:Q674359 ; p:P166 [ ps:P166 wd:Q674359 ; pq:P585 ?year ] .
  wd:Q25369 wdt:P166 wd:Q674359 ; p:P166 [ ps:P166 wd:Q674359 ; pq:P585 ?year ] .
}

Got 1 row and 1 column:
| count       |
| ----------- |
| 4 (xsd:int) |

[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 All-NBA Team awards have Shaquille O'Neal and Kobe Bryant received in the same year?

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

[Tool]
Example 1:
Question:
Who are the four youngest MVP basketball players?

SPARQL:
SELECT ?uri WHERE {
  ?uri wdt:P106 wd:Q3665646 ; wdt:P569 ?birthDate ; wdt:P166 ?award .
  ?award rdfs:label ?awardLabel
  FILTER ( CONTAINS( STR( ?awardLabel ) , "MVP" ) || CONTAINS( STR( ?awardLabel ) , "Most Valuable Player" ) ) .
  FILTER ( LANGMATCHES( LANG( ?awardLabel ) , "EN" ) )
}
ORDER BY DESC ( ?birthDate )
LIMIT 4

Using entities:
basketball player, also known as basketballer, basketeer, cager, hoopster, professional basketball player (wd:Q3665646): person who plays in basketball

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)
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
date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as wdt): date on which the subject was born, inception

Example 2:
Question:
Who is the tallest basketball player?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P106 wd:Q3665646 ; wdt:P2048 ?height .
}
ORDER BY DESC ( ?height )
LIMIT 1

Using entities:
basketball player, also known as basketballer, basketeer, cager, hoopster, professional basketball player (wd:Q3665646): person who plays in basketball

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)
height, also known as heighth, size, depth over terrain (wd:P2048 as wdt): vertical length of an entity, length

Example 3:
Question:
Show me all basketball players that are higher than 2 meters.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P106 wd:Q3665646 .
  ?uri wdt:P2048 ?height .
  FILTER ( ?height > 200 )
}

Using entities:
basketball player, also known as basketballer, basketeer, cager, hoopster, professional basketball player (wd:Q3665646): person who plays in basketball

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)
height, also known as heighth, size, depth over terrain (wd:P2048 as wdt): vertical length of an entity, length

[Assistant] None of these examples directly address the question about All-NBA Team awards for Shaquille O'Neal and Kobe Bryant, but they provide useful guidance on how to structure the query. We need to identify the entities for Shaquille O'Neal and Kobe Bryant, and the property for the All-NBA Team award. Let's start by searching for the entities.

[Tool]
Top 10 entity alternatives:
1. Shaquille O'Neal, also known as Shaquille O’Neal, Shaquille Rashaun O'Neal, Shaq O'Neal, Shaquille Rashaun O’Neal, Shaq (wd:Q169452): American basketball player, real estate entrepreneur, television producer, sports commentator, basketball player, businessperson, film producer, screenwriter, film actor, Thai boxer, podcaster, singer, rapper, actor
2. Shaquille O'Neal (wd:Q125446160): episode of All That (S5 E3)
3. Shaquille Cleare, also known as Shaquille O'Neal Cleare (wd:Q61953486): college basketball player (2013–2017) Maryland; Texas, basketball player
4. Shaquille O'Neal Motors (wd:Q114535400): episode of Fresh Off the Boat (S2 E3)
5. Shaq Belson, also known as Shaquille Belson, Shaquille O'Neal Belson (wd:Q106725566): American American football player, American football player
6. Shaquille Allen, also known as Shaquille O'Neal Allen (wd:Q106725550): American football player
7. Upload with Shaquille O'Neal (wd:Q7898386): American comedy television series
8. Statue of Shaquille O'Neal (wd:Q114363921): sculpture in Los Angeles, California, U.S
9. The Best of Shaquille O'Neal (wd:Q7717219): album by Shaquille O'Neal
10. A Message from Shaquille O'Neal (wd:Q110058550): sketch from Saturday Night Live

[Assistant] The correct entity for Shaquille O'Neal is `wd:Q169452`. Now let's search for the entity for Kobe Bryant.

[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] The correct entity for Kobe Bryant is `wd:Q25369`. Next, we need to find the property for the All-NBA Team award. Let's search for it.

[Tool]
Top 10 property alternatives:
1. Basketball Reference international player ID, also known as BRCIP, Basketball Reference player ID, Basketball-Reference.com Europe player ID, Basketball-Reference.com international player ID (wd:P4790 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): identifier for a basketball player in a non-U.S. league on Basketball-Reference.com
2. Basketball Reference NBA player ID, also known as Basketball-Reference.com NBA player ID, BRCNBA (wd:P2685 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): identifier for a NBA player on the Basketball Reference website
3. NBA.com player ID (wd:P3647 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): identifier for a basketball player on the National Basketball Association's website
4. Hoopla artist ID, also known as hoopladigital.com (wd:P6868 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): identifier for an individual on Hoopla
5. Eurobasket.com player ID, also known as Eurobasket.com ID, eurobasket.com identifier (wd:P3527 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): ID for a basketball player at Eurobasket.com
6. Basketball Reference NBA coach ID, also known as Basketball-Reference.com NBA coach ID (wd:P4718 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): identifier for a NBA coach on the Basketball Reference website
7. ESPN.com NBA player ID, also known as ESPN NBA player ID (wd:P3685 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): identifier for a National Basketball Association player at ESPN.com
8. Basketball Reference NBA G League player ID, also known as Basketball-Reference.com NBA G League player ID, Basketball-Reference.com NBDL player ID, BRCNBAG (wd:P4744 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): identifier for an NBA G League (formerly NBDL) player on the Basketball Reference website
9. FIBA.com player ID (archived), also known as FIBA.com player ID, FIBA ID, FIBA identifier, FIBA player ID (wd:P3542 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): identifier for a basketball player at archive.FIBA.com
10. FIBA.basketball player ID, also known as FIBA.basketball ID, FIBA player ID, FIBA identifier, FIBA ID (wd:P12338 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): identifier for a basketball player at www.FIBA.basketball

[Assistant] It seems that the specific property for the All-NBA Team award is not listed among the top 10 results. Let's try a different approach by searching for the award itself as an entity and then finding the property that links players to this award.

[Tool]
Top 10 entity alternatives:
1. All-NBA Team (wd:Q674359): National Basketball Association honor
2. All-NBA Development League Team (wd:Q4728301): American baseball honor
3. team (wd:Q327245): group linked in a common purpose
4. Team (wd:Q15054311): Lorde song
5. TEAM (wd:Q528227): Slovak rock music group
6. &TEAM, also known as andTeam (wd:Q112834233): Japanese boy band
7. Team (wd:Q23084914): 2016 song by Iggy Azalea
8. .team (wd:Q20577252): top-level domain
9. The Evangelical Alliance Mission, also known as TEAM (wd:Q7732630): Evangelical Christian mission organization
10. Transmission Electron Aberration-Corrected Microscope, also known as TEAM (wd:Q7834620): aberration-correction microscopes in the Lawrence Berkeley National Laboratory

[Assistant] The correct entity for the All-NBA Team is `wd:Q674359`. Now, let's find the property that links players to this award. We can use the `search_property_of_entity` function to find properties related to this award for Shaquille O'Neal or Kobe Bryant.

[Tool]
Top 10 property alternatives:
1. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as p/wdt): 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 p/wdt): award nomination received by a person, organisation or creative work (inspired from "award received" (Property:P166))
3. competition won, also known as won event, won, winner of, victory (wd:P2522 as p/wdt): competition or sports event won by the subject, participant in
4. instrument, also known as uses this instrument, teaches instrument, instruments, plays this instrument, plays instrument (wd:P1303 as p/wdt): musical instrument that a person plays or teaches or used in a music occupation, uses
5. member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as p/wdt): sports teams or clubs that the subject represents or represented, member of
6. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as p/wdt): 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 p/wdt): 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 p/wdt): 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 p/wdt): 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 p/wdt): 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` (wd:P166) is the most relevant for linking players to awards. Now, let's construct a SPARQL query to find the years in which both Shaquille O'Neal and Kobe Bryant received the All-NBA Team award.

We will start by finding the years when Shaquille O'Neal received the All-NBA Team award and then check if Kobe Bryant received the same award in those years.

[Tool]
Got 8 rows and 1 column:
| year                                |
| ----------------------------------- |
| 2006-01-01T00:00:00Z (xsd:dateTime) |
| 2002-01-01T00:00:00Z (xsd:dateTime) |
| 1998-01-01T00:00:00Z (xsd:dateTime) |
| 2004-01-01T00:00:00Z (xsd:dateTime) |
| 2003-01-01T00:00:00Z (xsd:dateTime) |
| 2000-01-01T00:00:00Z (xsd:dateTime) |
| 2005-01-01T00:00:00Z (xsd:dateTime) |
| 2001-01-01T00:00:00Z (xsd:dateTime) |

[Assistant] Shaquille O'Neal received the All-NBA Team award in the years 1998, 2000, 2001, 2002, 2003, 2004, 2005, and 2006. Now, let's find out if Kobe Bryant received the All-NBA Team award in any of these years.

[Tool]
Got 4 rows and 1 column:
| year                                |
| ----------------------------------- |
| 2004-01-01T00:00:00Z (xsd:dateTime) |
| 2003-01-01T00:00:00Z (xsd:dateTime) |
| 2006-01-01T00:00:00Z (xsd:dateTime) |
| 2002-01-01T00:00:00Z (xsd:dateTime) |

[Assistant]
Kobe Bryant received the All-NBA Team award in the years 2002, 2003, 2004, and 2006. These are the years in which both Shaquille O'Neal and Kobe Bryant received the All-NBA Team award.

Now, let's count the number of such years using a single SPARQL query.

[Tool]
Got 1 row and 1 column:
| count       |
| ----------- |
| 4 (xsd:int) |

[Assistant]
Both Shaquille O'Neal and Kobe Bryant received the All-NBA Team award in the same year 4 times.

Here is the final SPARQL query:

```sparql
SELECT (COUNT(DISTINCT ?year) AS ?count) WHERE {
  wd:Q169452 wdt:P166 wd:Q674359 ; p:P166 [ ps:P166 wd:Q674359 ; pq:P585 ?year ].
  wd:Q25369 wdt:P166 wd:Q674359 ; p:P166 [ ps:P166 wd:Q674359 ; pq:P585 ?year ].
}
```

The answer to the question is 4.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?prize ?prizeLabel WHERE {
  wd:Q7197 wdt:P1411 ?prize .
  OPTIONAL {
    ?prize rdfs:label ?prizeLabel .
    FILTER ( LANG( ?prizeLabel ) = 'en' )
  }
}

Simone de Beauvoir was nominated for the Nobel Prize in Literature.

[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] For what literature prize was Simone de Beauvoir nominated?

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

[Tool]
Example 1:
Question:
Give me all writers that won the Nobel Prize in literature.

SPARQL:
SELECT ?uri WHERE {
  ?uri wdt:P106 wd:Q36180 .
  ?uri wdt:P166 wd:Q37922 .
}

Using entities:
writer, also known as penwoman, writers, penwomen, penmen, penman (wd:Q36180): person who uses written words to communicate ideas and to produce literary works
Nobel Prize in Literature, also known as Nobel Literature Prize (wd:Q37922): one of five prizes established by Alfred Nobel

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)
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

Example 2:
Question:
Give me all writers that won the Nobel Prize in literature.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P106 wd:Q36180 ; wdt:P166 wd:Q37922 .
}

Using entities:
writer, also known as penwoman, writers, penwomen, penmen, penman (wd:Q36180): person who uses written words to communicate ideas and to produce literary works
Nobel Prize in Literature, also known as Nobel Literature Prize (wd:Q37922): one of five prizes established by Alfred Nobel

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)
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

[Assistant] From the examples, we can see that the property `award received` (wdt:P166) is used to represent awards and prizes that a person has received. We can use this property to find out for what literature prize Simone de Beauvoir was nominated. Let's first search for the entity representing Simone de Beauvoir.

[Tool]
Top 10 entity alternatives:
1. Simone de Beauvoir (wd:Q7197): French philosopher, social theorist and activist (1908–1986), political philosopher, women letter writer, philosophy teacher, political activist, literary critic, autobiographer, philosopher, journalist, novelist, feminist, essayist, diarist, author, writer
2. Simone de Beauvoir (wd:Q66049034): 1979 documentary film directed by Josée Dayan
3. Simone de Beauvoir (wd:Q87280632): episode of In Our Time
4. Simone de Beauvoir Prize (wd:Q2316171)
5. Simone de Beauvoir Park, also known as Fontainas Park (wd:Q23796565): park in Brussels, Belgium
6. allée Simone de Beauvoir (wd:Q111916916): alley in Arcueil, France
7. mail Simone de Beauvoir (wd:Q113391499): street in Bobigny, France
8. place Simone de Beauvoir (wd:Q113414051): square in Stains, en Seine-Saint-Denis
9. rue Simone de Beauvoir (wd:Q111302129): street in Bondy, France
10. rue Simone de Beauvoir (wd:Q111847967): street in Limeil-Brévannes, France

[Assistant] The first result, `Simone de Beauvoir (wd:Q7197)`, is the correct entity for the French philosopher and writer. Now let's look for the property that represents nominations for awards or prizes. We can use the `search_property` function to find a suitable property.

[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 pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): award nomination received by a person, organisation or creative work (inspired from "award received" (Property:P166))
2. nominated by (wd:P4353 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): who nominated a person for an office or award; can be used as a qualifier
3. for work, also known as awarded for work, citation for award, for their work on, nominated for work (wd:P1686 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): qualifier of award received (P166) to specify the work that an award was given to the creator for
4. nominee, also known as award nominee (wd:P2453 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): qualifier used with “nominated for” to specify which person or organization was nominated
5. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): award or recognition received by a person, organization or creative work
6. conferred by, also known as presented by, officiated by, issued by, granted by, given by (wd:P1027 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): person or organization who grants an award, certification, grant, or role
7. winner, also known as nominee, prizewinner, titleholder, top dog, victor (wd:P1346 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): winner of a competition or similar event, not to be used for awa...ssibly qualified with "for work" (P1686)) or for wars or battles, participating team, participant
8. eligible recipient, also known as eligible recipient for award, type of recipient who is eligible for this award (wd:P8115 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): party that is eligible to receive something, like an award, grant or prize
9. Academy Awards Database nominee ID, also known as Oscar nominee ID (wd:P6150 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): identifier for nominees in the official Academy Awards database
10. award rationale, also known as award citation, rationale, award reason (wd:P6208 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): qualifier to add short citation explaining the official reason f... or add comments about a person's award. No quote marked needed.

[Assistant]
The property `nominated for` (wdt:P1411) seems to be the most appropriate for our purpose. Now, let's construct a SPARQL query to find out for what literature prize Simone de Beauvoir was nominated.

We will use the following pattern:
- `wd:Q7197 wdt:P1411 ?prize .`
- Optionally, we can also include the label of the prize for better readability.

Let's execute this query.

[Tool]
Got 1 row and 2 columns:
| prize                                 | prizeLabel                     |
| ------------------------------------- | ------------------------------ |
| Nobel Prize in Literature (wd:Q37922) | Nobel Prize in Literature (en) |

[Assistant]
The SPARQL query returned that Simone de Beauvoir was nominated for the Nobel Prize in Literature.

Here is the final SPARQL query and the answer:

```sparql
SELECT ?prize ?prizeLabel WHERE {
  wd:Q7197 wdt:P1411 ?prize .
  OPTIONAL { ?prize rdfs:label ?prizeLabel . FILTER(LANG(?prizeLabel) = 'en') }
}
```

Answer: Simone de Beauvoir was nominated for the Nobel Prize in Literature.

Now, I will provide the final answer using the `answer` function.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?movie WHERE {
  ?movie wdt:P179 wd:Q169604 .
}

The movies that belong to the Cornetto trilogy are: The World's End, Hot Fuzz, and Shaun of the Dead.

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

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

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

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

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

[User] Which movies belong to the Cornetto trilogy ?

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

[Tool]
Example 1:
Question:
Give me all movies directed by Francis Ford Coppola.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 / wdt:P279 * wd:Q11424 ; wdt:P57 wd:Q56094 .
}

Using entities:
film, also known as cinematic work, moving picture, movie, motion pictures, motion picture (wd:Q11424): sequence of images that give the impression of movement, stored on film stock
Francis Ford Coppola, also known as Francis Coppola (wd:Q56094): American filmmaker, executive producer, businessperson, film producer, film director, screenwriter, film editor, winegrower, film actor, producer, director, composer, writer, actor

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)
director, also known as film director, movie director, game director, directed by (wd:P57 as wdt): director(s) of film, TV-series, stageplay, video game or similar, contributor to the creative work or subject, creator

Example 2:
Question:
Give me all movies with Tom Cruise.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P161 wd:Q37079 .
}

Using entities:
Tom Cruise, also known as Thomas Cruise Mapother IV (wd:Q37079): American actor and producer (born 1962), stunt performer, aircraft pilot, film producer, film director, screenwriter, film actor, producer, director, writer, actor

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as wdt): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer

Example 3:
Question:
Give me all movies with Tom Cruise.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P161 wd:Q37079 .
}

Using entities:
Tom Cruise, also known as Thomas Cruise Mapother IV (wd:Q37079): American actor and producer (born 1962), stunt performer, aircraft pilot, film producer, film director, screenwriter, film actor, producer, director, writer, actor

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as wdt): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer

[Assistant] From these examples, we can see that the SPARQL queries typically involve the `wdt:P31` (instance of) property to identify movies and then another property to specify the relationship (such as director or cast member). For our question, we need to find the movies that belong to the Cornetto trilogy. Let's first search for the entity representing the Cornetto trilogy.

[Tool]
Top 10 entity alternatives:
1. Three Flavours Cornetto trilogy, also known as Blood and Ice Cream trilogy, Cornetto trilogy, The Cornetto Trilogy (wd:Q169604): 2004–2013 three films directed by Edgar Wright
2. trilogy (wd:Q149010): set of three works of art that are connected
3. cornett, also known as zink, cornetto (wd:Q204638): early wind instrument with a cup mouthpiece
4. Trilogy (wd:Q930723): 1972 studio album by Emerson, Lake & Palmer
5. Cornetto, also known as Drumstick (ice cream) (wd:Q1899311): type of ice cream
6. Trilogy (wd:Q1753107): Yngwie Malmsteen studio album
7. Trilogy (wd:Q7842079): 2012 compilation album by the Weeknd
8. cornetto (wd:Q15629893): pastry similar to a croissant
9. Trilogy (wd:Q1041486): ATB album
10. Cornetto (wd:Q5171700): human settlement in Città di Castello, Province of Perugia, Umbria, Italy

[Assistant]
The top result is the entity for the Three Flavours Cornetto trilogy, which is what we are looking for. Now, let's find out which movies belong to this trilogy. We can use the `wdt:P179` (part of the series) property to link the movies to the trilogy.

Let's construct the SPARQL query to find the movies that are part of the Cornetto trilogy.

[Tool]
Got 3 rows and 1 column:
| movie                          |
| ------------------------------ |
| The World's End (wd:Q722379)   |
| Hot Fuzz (wd:Q729788)          |
| Shaun of the Dead (wd:Q858724) |

[Assistant]
The SPARQL query successfully returned the movies that belong to the Cornetto trilogy. The movies are:

- The World's End (wd:Q722379)
- Hot Fuzz (wd:Q729788)
- Shaun of the Dead (wd:Q858724)

Now, let's provide the final answer.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
ASK WHERE {
  wd:Q169452 p:P54 ?shaqStatement .
  ?shaqStatement ps:P54 wd:Q121783 .
  ?shaqStatement pq:P580 ?shaqStart .
  ?shaqStatement pq:P582 ?shaqEnd .
  wd:Q25369 p:P54 ?kobeStatement .
  ?kobeStatement ps:P54 wd:Q121783 .
  ?kobeStatement pq:P580 ?kobeStart .
  ?kobeStatement pq:P582 ?kobeEnd .
  FILTER ( ?shaqStart <= '2000-01-01T00:00:00Z' ^^ xsd:dateTime && ?shaqEnd >= '2000-01-01T00:00:00Z' ^^ xsd:dateTime && ?kobeStart <= '2000-01-01T00:00:00Z' ^^ xsd:dateTime && ?kobeEnd >= '2000-01-01T00:00:00Z' ^^ xsd:dateTime )
}

True

[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] Was Shaquille O'Neal the teammate of Kobe Bryant in the year of 2000?

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

[Tool]
Example 1:
Question:
Who is the tallest basketball player?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P106 wd:Q3665646 ; wdt:P2048 ?height .
}
ORDER BY DESC ( ?height )
LIMIT 1

Using entities:
basketball player, also known as basketballer, basketeer, cager, hoopster, professional basketball player (wd:Q3665646): person who plays in basketball

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)
height, also known as heighth, size, depth over terrain (wd:P2048 as wdt): vertical length of an entity, length

[Assistant] None of the examples found directly relate to our question about Shaquille O'Neal being a teammate of Kobe Bryant in 2000. However, we can use the information from the example to guide us in constructing our own query. We need to identify the entities for Shaquille O'Neal and Kobe Bryant, and then check if they were teammates in the same team during the year 2000. Let's start by searching for the entities.

[Tool]
Top 10 entity alternatives:
1. Shaquille O'Neal, also known as Shaquille O’Neal, Shaquille Rashaun O'Neal, Shaq O'Neal, Shaquille Rashaun O’Neal, Shaq (wd:Q169452): American basketball player, real estate entrepreneur, television producer, sports commentator, basketball player, businessperson, film producer, screenwriter, film actor, Thai boxer, podcaster, singer, rapper, actor
2. Shaquille O'Neal (wd:Q125446160): episode of All That (S5 E3)
3. Shaquille Cleare, also known as Shaquille O'Neal Cleare (wd:Q61953486): college basketball player (2013–2017) Maryland; Texas, basketball player
4. Shaquille O'Neal Motors (wd:Q114535400): episode of Fresh Off the Boat (S2 E3)
5. Shaq Belson, also known as Shaquille Belson, Shaquille O'Neal Belson (wd:Q106725566): American American football player, American football player
6. Shaquille Allen, also known as Shaquille O'Neal Allen (wd:Q106725550): American football player
7. Upload with Shaquille O'Neal (wd:Q7898386): American comedy television series
8. Statue of Shaquille O'Neal (wd:Q114363921): sculpture in Los Angeles, California, U.S
9. The Best of Shaquille O'Neal (wd:Q7717219): album by Shaquille O'Neal
10. A Message from Shaquille O'Neal (wd:Q110058550): sketch from Saturday Night Live

[Assistant] The correct entity for Shaquille O'Neal is `wd:Q169452`. Now let's search for the entity for Kobe Bryant.

[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]
The correct entity for Kobe Bryant is `wd:Q25369`. Now that we have both entities, we need to find out if they were teammates in the same team during the year 2000. To do this, we will look for the teams they played for and the years they played for those teams. Let's start by finding the teams Shaquille O'Neal played for and the years he played for them.

We will use the property "member of sports team" (`P54`) to find the teams and the qualifier "start time" (`P580`) and "end time" (`P582`) to find the years.

Let's first list the teams Shaquille O'Neal played for and the years he played for them.

[Tool]
Got 7 rows and 3 columns:
| subject                       | property                        | object                                    |
| ----------------------------- | ------------------------------- | ----------------------------------------- |
| Shaquille O'Neal (wd:Q169452) | member of sports team (wdt:P54) | Los Angeles Lakers (wd:Q121783)           |
| Shaquille O'Neal (wd:Q169452) | member of sports team (wdt:P54) | Boston Celtics (wd:Q131371)               |
| Shaquille O'Neal (wd:Q169452) | member of sports team (wdt:P54) | Cleveland Cavaliers (wd:Q162990)          |
| Shaquille O'Neal (wd:Q169452) | member of sports team (wdt:P54) | Phoenix Suns (wd:Q164177)                 |
| Shaquille O'Neal (wd:Q169452) | member of sports team (wdt:P54) | Orlando Magic (wd:Q161337)                |
| Shaquille O'Neal (wd:Q169452) | member of sports team (wdt:P54) | Miami Heat (wd:Q169138)                   |
| Shaquille O'Neal (wd:Q169452) | member of sports team (wdt:P54) | LSU Tigers men's basketball (wd:Q6460027) |

[Assistant]
Shaquille O'Neal played for several teams, including the Los Angeles Lakers, Boston Celtics, Cleveland Cavaliers, Phoenix Suns, Orlando Magic, Miami Heat, and LSU Tigers men's basketball. Next, we need to find the specific years he played for these teams. We will focus on the Los Angeles Lakers since it is the most relevant to our question. Let's check the start and end times for his tenure with the Los Angeles Lakers.

We will use the qualifiers "start time" (`P580`) and "end time" (`P582`) to find the years.

Let's execute a SPARQL query to get this information.

[Tool]
Got 1 row and 3 columns:
| team | startTime                           | endTime                             |
| ---- | ----------------------------------- | ----------------------------------- |
|      | 1996-01-01T00:00:00Z (xsd:dateTime) | 2004-07-14T00:00:00Z (xsd:dateTime) |

[Assistant]
Shaquille O'Neal played for the Los Angeles Lakers from 1996 to 2004. Now, let's find out the teams Kobe Bryant played for and the years he played for them, focusing on the Los Angeles Lakers.

We will use the same approach to find the start and end times for Kobe Bryant's tenure with the Los Angeles Lakers.

Let's execute a SPARQL query to get this information.

[Tool]
Got 1 row and 3 columns:
| team | startTime                           | endTime                             |
| ---- | ----------------------------------- | ----------------------------------- |
|      | 1996-01-01T00:00:00Z (xsd:dateTime) | 2016-01-01T00:00:00Z (xsd:dateTime) |

[Assistant]
Kobe Bryant played for the Los Angeles Lakers from 1996 to 2016. Since both Shaquille O'Neal and Kobe Bryant were playing for the Los Angeles Lakers in the year 2000, they were indeed teammates during that year.

To confirm this, we can use an ASK query to check if both players were members of the Los Angeles Lakers in the year 2000.

Let's execute the ASK query.

[Tool] True

[Assistant]
The ASK query confirms that Shaquille O'Neal and Kobe Bryant were indeed teammates on the Los Angeles Lakers in the year 2000.

Therefore, the answer to the question is **True**.

Here is the final SPARQL query:

```sparql
ASK WHERE {
  wd:Q169452 p:P54 ?shaqStatement .
  ?shaqStatement ps:P54 wd:Q121783 .
  ?shaqStatement pq:P580 ?shaqStart .
  ?shaqStatement pq:P582 ?shaqEnd .
  wd:Q25369 p:P54 ?kobeStatement .
  ?kobeStatement ps:P54 wd:Q121783 .
  ?kobeStatement pq:P580 ?kobeStart .
  ?kobeStatement pq:P582 ?kobeEnd .
  FILTER(?shaqStart <= '2000-01-01T00:00:00Z'^^xsd:dateTime && ?shaqEnd >= '2000-01-01T00:00:00Z'^^xsd:dateTime && ?kobeStart <= '2000-01-01T00:00:00Z'^^xsd:dateTime && ?kobeEnd >= '2000-01-01T00:00:00Z'^^xsd:dateTime)
}
```

The answer to the question is **True**.

[Tool] Stopped generation process