PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( ?game ) AS ?count ) WHERE {
  ?game wdt:P31 wd:Q7889 .
  ?game wdt:P577 ?releaseDate .
  FILTER ( YEAR( ?releaseDate ) = 2016 ) FILTER ( ?game != wd:Q24514682 )
}

5,007 other video games began the same year as Dead by Daylight.

[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 other video games began the same year as Dead by Daylight?

[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:
Show me Hemingway's autobiography.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P50 wd:Q23434 .
  ?uri wdt:P136 wd:Q4184 .
}

Using entities:
Ernest Hemingway, also known as Ernest Miller Hemingway, Ernest Miller Hemmingway, Hemingway, Papa, E. Hemingway (wd:Q23434): American author and journalist (1899–1961), short story writer, war correspondent, screenwriter, prose writer, playwright, journalist, novelist, writer, poet
autobiography, also known as Autobiography as Topic, self-biography, autobiographies, autobiographical writing (wd:Q4184): genre and publication type, biography written by the subject

Using properties:
genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as wdt): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
author, also known as writer, written by, poet, playwright, maker (wd:P50 as wdt): main creator(s) of a written work (use on works, not humans); us...hor name string) when Wikidata item is unknown or does not exist, creator

Example 3:
Question:
Give me all Apollo 14 astronauts.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q178871 wdt:P1029 ?uri
}

Using entities:
Apollo 14, also known as Apollo XIV (wd:Q178871): third Moon landing and eighth crewed flight of the United States Apollo program

Using properties:
crew member, also known as crewmember (wd:P1029 as wdt): person that participated operating or serving aboard this vehicle

[Assistant] From the examples, we can see that the SPARQL queries typically involve selecting entities and properties relevant to the question. In our case, we need to find out the year when "Dead by Daylight" was released and then count the number of other video games that were released in the same year. Let's first search for the entity "Dead by Daylight".

[Tool]
Top 10 entity alternatives:
1. Dead by Daylight, also known as dbd (wd:Q24514682): 2016 asymmetric survival horror video game developed by Behaviour Interactive
2. Dead by Daylight, also known as DBD (wd:Q116976554): upcoming horror film based in the videogame
3. Dead by Daylight universe (wd:Q125569668): narrative universe of the 2016 video game Dead by Daylight
4. Dead by Daylight: Bloodstained Sack (wd:Q98802595): 2016 downloadable content
5. Hooked on You: A Dead by Daylight Dating Sim, also known as A Dead by Daylight Dating Sim, Hooked on You (wd:Q113468031): 2022 video game
6. Dead by Daylight - Hellraiser chapter (wd:Q125760779): 2021 downloadable content
7. Dead by Daylight - All-Kill Chapter (wd:Q125760955): 2021 downloadable content
8. Dead by Daylight - Terror Expansion Pack (wd:Q125760940): 2021 downloadable content
9. Dead by Daylight - Sadako Rising Chapter (wd:Q125570431): 2022 downloadable content
10. Dead by Daylight - Resident Evil Chapter (wd:Q125760789): 2021 downloadable content

[Assistant] The top result is the correct one: "Dead by Daylight" (wd:Q24514682), which is the 2016 asymmetric survival horror video game. Next, we need to find the property that indicates the release date of a video game. We can search for this property using the search_property function.

[Tool]
Top 10 property alternatives:
1. date of commercialization, also known as availability date, commercialization date, product release date, release date (wd:P5204 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): date when a product was first commercialized
2. publication date, also known as launched, published, publication time, publication, pubdate (wd:P577 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): date or point in time when a work was first published or released, point in time
3. announcement date, also known as released, date teased, made public on, public announcement date, published (wd:P6949 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): time of the first public presentation of a subject by the creator, of information by the media, point in time
4. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): time when an entity begins to exist; for date of official opening use P1619, start time
5. day of regular release (wd:P6437 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): day(s) when parts of this creative work are released, aired, published, etc
6. service entry, also known as commissioned, time of service entry, service introduction, launch date, in service (wd:P729 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): date or point in time on which a piece or class of equipment entered operational service, start time
7. date of official opening, also known as launch date, launched, officially opened on, official opening, official opening time (wd:P1619 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): date or point in time a place, organization, or event officially opened, start time, inception
8. UTC date of spacecraft launch, also known as time of spacecraft launch, spacecraft launch time, spacecraft launch date, launch time, launch date (wd:P619 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): date of spacecraft launch in UTC
9. production date, also known as date of production, filming date, filming time, production date, year of production (wd:P2754 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): period of active production of (creative) work; the only date st... publication date (P577); in general cases, use inception (P571)
10. place of publication, also known as published in (place), where published, release region, released in, published from (wd:P291 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): geographical place of publication of the edition (use 1st edition when referring to works), significant place

[Assistant]
The property "publication date" (wdt:P577) seems to be the most appropriate for finding the release date of a video game. Now, let's construct a simple SPARQL query to find the release date of "Dead by Daylight" (wd:Q24514682).

```sparql
SELECT ?releaseDate WHERE {
  wd:Q24514682 wdt:P577 ?releaseDate
}
```

I'll execute this query to get the release date.

[Tool]
Got 1 row and 1 column:
| releaseDate                         |
| ----------------------------------- |
| 2016-06-14T00:00:00Z (xsd:dateTime) |

[Assistant]
The release date of "Dead by Daylight" is June 14, 2016. Now, we need to find other video games that were released in the same year, 2016. To do this, we will:

1. Identify the entity for "video game" to filter the results.
2. Construct a query to find video games released in 2016.

First, let's search for the entity "video game" to ensure we have the correct identifier.

[Tool]
Top 10 entity alternatives:
1. video game, also known as computer game, computer games, vg, videogame, videogames (wd:Q7889): electronic game with user interface and visual feedback
2. video game (wd:Q56312618): electronic game that involves interaction with a user interface ...edback on a video device such as a TV screen or computer monitor
3. 🎮, also known as U+1F3AE, VIDEO GAME (wd:Q87577146): Unicode character which may be used to communicate 'game'
4. Video Game (wd:Q105393890): 2021 single by Sufjan Stevens
5. VIDEO GAME (wd:Q126697592): 2018 video game
6. Gulf War, also known as Video Game War, Persian Gulf War, Operation Desert Storm, Kuwait War, Gulf War I (wd:Q37643): 1990–1991 conflict between Iraq and a 42-country coalition
7. video game console, also known as video-game console, Video game console, gaming console, games console, game console (wd:Q8076): interactive entertainment computer or customized computer system for running video games
8. first-person shooter, also known as FPS video game, FPS game, FPS, fps, first-person shooter video game (wd:Q185029): video game genre centered around gun and other weapon-based combat in a first-person perspective
9. game engine, also known as video game engine (wd:Q193564): system designed for the creation and development of video games
10. multiplayer video game, also known as multiplayer, multiplayer computer game, multiplayer game, multiplayer mode (wd:Q6895044): video game where multiple players can play together

[Assistant]
The correct entity for "video game" is wd:Q7889. Now, we can construct a query to find other video games that were released in 2016. We will exclude "Dead by Daylight" itself from the results.

Here is the SPARQL query:

```sparql
SELECT ?game WHERE {
  ?game wdt:P31 wd:Q7889 .  # Ensure it is a video game
  ?game wdt:P577 ?releaseDate .  # Get the release date
  FILTER(YEAR(?releaseDate) = 2016)  # Filter by the year 2016
  FILTER(?game != wd:Q24514682)  # Exclude Dead by Daylight
}
```

I'll execute this query to get the list of video games released in 2016.

[Tool]
Got 5,007 rows and 1 column, showing the first 5 and last 5 rows below:
| game                                      |
| ----------------------------------------- |
| Stars (wd:Q100387342)                     |
| Zombasite (wd:Q100462725)                 |
| Wick (wd:Q100567719)                      |
| Wick (wd:Q100567719)                      |
| Wick (wd:Q100567719)                      |
| ...                                       |
| Way of the Red (wd:Q98971891)             |
| Hunt Cook: Catch and Serve (wd:Q99297804) |
| Elemental 3 (wd:Q99633735)                |
| A Magical High School Girl (wd:Q99670586) |
| Quatros Origins (wd:Q99670635)            |

[Assistant]
The query returned 5,007 video games that were released in 2016, excluding "Dead by Daylight".

To provide the final answer, we can use an ASK query to confirm the count. However, since the ASK query is typically used for boolean responses, we will use a COUNT query to get the exact number of video games.

Here is the final SPARQL query to count the number of video games released in 2016, excluding "Dead by Daylight":

```sparql
SELECT (COUNT(?game) AS ?count) WHERE {
  ?game wdt:P31 wd:Q7889 .  # Ensure it is a video game
  ?game wdt:P577 ?releaseDate .  # Get the release date
  FILTER(YEAR(?releaseDate) = 2016)  # Filter by the year 2016
  FILTER(?game != wd:Q24514682)  # Exclude Dead by Daylight
}
```

I'll execute this query to get the count.

[Tool]
Got 1 row and 1 column:
| count          |
| -------------- |
| 5007 (xsd:int) |

[Assistant]
The final answer is that 5,007 other video games began the same year as "Dead by Daylight".

Here is the final SPARQL query and the answer:

```sparql
SELECT (COUNT(?game) AS ?count) WHERE {
  ?game wdt:P31 wd:Q7889 .  # Ensure it is a video game
  ?game wdt:P577 ?releaseDate .  # Get the release date
  FILTER(YEAR(?releaseDate) = 2016)  # Filter by the year 2016
  FILTER(?game != wd:Q24514682)  # Exclude Dead by Daylight
}
```

Answer: 5,007 other video games began the same year as "Dead by Daylight".

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( DISTINCT ?occupation ) AS ?count ) WHERE {
  ?winner wdt:P166 wd:Q37922 .
  ?winner wdt:P26 ?spouse .
  ?spouse wdt:P106 ?occupation .
}

Got 1 row and 1 column:
| count        |
| ------------ |
| 71 (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 different occupations did/do spouses of winners of the Nobel Prize in Literature hold?

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

[Tool]
Example 1:
Question:
What is the smallest city by area in Germany?

SPARQL:
SELECT ?res WHERE {
  ?res wdt:P17 wd:Q183 .
  ?res wdt:P31 / wdt:P279 * wd:Q515 .
  ?res wdt:P1082 ?inhabitants .
}
ORDER BY ?inhabitants
LIMIt 1

Using entities:
Germany, also known as BR Deutschland, Bundesrepublik Deutschland, Deutschland, Federal Republic of Germany (wd:Q183): country in Central Europe
city, also known as cities (wd:Q515): large human settlement

Using properties:
population, also known as inhabitants, human population (wd:P1082 as wdt): number of people inhabiting the place; number of people of subject
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)

Example 2:
Question:
How many films did Hal Roach produce?

SPARQL:
SELECT ( COUNT( ?uri ) as ?c ) WHERE {
  ?uri wdt:P162 wd:Q72792 .
}

Using entities:
Hal Roach (wd:Q72792): American filmmaker (1892–1992), television producer, film director, film producer, screenwriter, director, actor

Using properties:
producer, also known as music producer, record producer, produced by, film producer, creative producer (wd:P162 as wdt): person(s) who produced the film, musical work, theatrical produc...etc.) [for production company, use P272, video games - use P178]

Example 3:
Question:
Which airports does Yeti Airlines serve?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q1480118 wdt:P113 ?uri .
}

Using entities:
Yeti Airlines, also known as Yeti Airlines Domestic Pvt. Ltd. (wd:Q1480118): Airline based in Kathmandu, Nepal.

Using properties:
airline hub, also known as hub airport, hub (wd:P113 as wdt): airport that serves as a hub for an airline

[Assistant] Based on the examples, we need to identify the entities and properties relevant to our question. We need to find the Nobel Prize in Literature, the winners of this prize, their spouses, and the occupations held by these spouses. Let's start by searching for the Nobel Prize in Literature.

[Tool]
Top 10 entity alternatives:
1. Nobel Prize in Literature, also known as Nobel Literature Prize (wd:Q37922): one of five prizes established by Alfred Nobel
2. 2022 Nobel Prize in Literature (wd:Q112594135): literary award to French author Annie Ernaux
3. 1901 Nobel Prize in Literature (wd:Q15918052)
4. 2023 Nobel Prize in Literature (wd:Q115937544)
5. 2012 Nobel Prize in Literature (wd:Q10845886)
6. 1905 Nobel Prize in Literature (wd:Q112731128)
7. 1908 Nobel Prize in Literature (wd:Q112731708)
8. 2003 Nobel Prize in Literature (wd:Q113212896)
9. 1938 Nobel Prize in Literature (wd:Q112811579)
10. 1954 Nobel Prize in Literature (wd:Q107359944): award

[Assistant] The correct entity for the Nobel Prize in Literature is `wd:Q37922`. Next, we need to find the winners of this prize. We can use the property "awarded to" or "winner" to find the winners. Let's search for the appropriate property.

[Tool]
Top 10 property alternatives:
1. conferred by, also known as presented by, officiated by, issued by, granted by, given by (wd:P1027 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): person or organization who grants an award, certification, grant, or role
2. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): award or recognition received by a person, organization or creative work
3. winner, also known as nominee, prizewinner, titleholder, top dog, victor (wd:P1346 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): 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
4. nominated for, also known as nominee for, shortlisted for, selected for award, selected for, nominee for award (wd:P1411 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): award nomination received by a person, organisation or creative work (inspired from "award received" (Property:P166))
5. competition won, also known as won event, won, winner of, victory (wd:P2522 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): competition or sports event won by the subject, participant in
6. for work, also known as awarded for work, citation for award, for their work on, nominated for work (wd:P1686 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): qualifier of award received (P166) to specify the work that an award was given to the creator for
7. eligible recipient, also known as eligible recipient for award, type of recipient who is eligible for this award (wd:P8115 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): party that is eligible to receive something, like an award, grant or prize
8. nominee, also known as award nominee (wd:P2453 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): qualifier used with “nominated for” to specify which person or organization was nominated
9. awarded for period (wd:P4566 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): period during which the achievement must have been made to be eligible for an award
10. award rationale, also known as award citation, rationale, award reason (wd:P6208 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): 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 "award received" (`wd:P166`) seems to be the most appropriate for finding the winners of the Nobel Prize in Literature. Now, let's construct a query to find the winners of the Nobel Prize in Literature.

Next, we need to find the spouses of these winners. We can use the property "spouse" to find the spouses. Let's search for the appropriate property.

[Tool]
Top 10 property alternatives:
1. spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative
2. relative, also known as relatives, grandparent, relation, non-binary parent, niece (wd:P1038 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): family member (qualify with "kinship to subject", P1039; for direct family member please use specific property), significant person
3. unmarried partner, also known as romantic partner, partner of, partners, posslq, relationship (wd:P451 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): someone with whom the person is in a relationship without being married. Use "spouse" (P26) for married couples, significant person
4. married name, also known as full name (married) (wd:P2562 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): name or surname adopted by a person upon marriage, name
5. place of marriage, also known as marriage location, wedding location, wed at, married in, married at (wd:P2842 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): location where the marriage was celebrated. Use as qualifier for property "spouse" (P26), significant place
6. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): full name of a person at birth, if different from their current, generally used name, name
7. connects with, also known as contacts, couples with, intersects at grade, links to, mates with (wd:P2789 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): item with which the item is physically connected, physically interacts with
8. companion of, also known as has astronomical companion, has companion, companion, astronomic companion of, astronomic companion (wd:P399 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): two or more astronomic bodies of the same type relating to each other
9. end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time
10. relation (wd:P2309 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): qualifier to define a property constraint in combination with P2...h the property "relative" is "type of kinship" (P1039), not this

[Assistant] The property "spouse" (`wd:P26`) is the correct one to find the spouses of the Nobel Prize in Literature winners. Next, we need to find the occupations of these spouses. We can use the property "occupation" to find the occupations. Let's search for the appropriate property.

[Tool]
Top 10 property alternatives:
1. occupation, also known as job, work, vocation, profession, employment (wd:P106 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
2. field of this occupation, also known as practice, works in, profession's field, practices, field of this profession (wd:P425 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): field corresponding to this occupation or profession (use only f...fessions - for people use Property:P101, for companies use P452)
3. members have occupation, also known as profession of members, organization of, organization for, organisation of, organisation for (wd:P3989 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): some or all members of this group share the occupation
4. practiced by, also known as proponent, studied by, practitioners, practioner, occupation of this field (wd:P3095 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): type of agents that study this subject or work in this field
5. position held, also known as function, held position, holds position, job, office held (wd:P39 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): subject currently or formerly holds the object position or public office
6. employer, also known as working at, working for, working place, works at, works for (wd:P108 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): person or organization for which the subject works or worked, affiliation
7. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): the object is a country that recognizes the subject as its citizen, country
8. occupant, also known as tenant, resident, renter, occupiers, lessee (wd:P466 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): person or organization occupying property, used by
9. field of work, also known as scientific discipline, scientific area, responsible for, research on, research fields (wd:P101 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): specialization of a person or organization; see P106 for the occupation, interested in
10. work location, also known as work place, working from, working at, worked from, worked at (wd:P937 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): location where persons or organisations were actively participating in employment, business or other work, significant place, location

[Assistant]
The property "occupation" (`wd:P106`) is the correct one to find the occupations of the spouses. Now, let's construct a SPARQL query to find the number of different occupations held by the spouses of the Nobel Prize in Literature winners.

We will:
1. Find the winners of the Nobel Prize in Literature.
2. Find the spouses of these winners.
3. Find the occupations of these spouses.
4. Count the distinct occupations.

Here is the initial query:

```sparql
SELECT (COUNT(DISTINCT ?occupation) AS ?count) WHERE {
  ?winner wdt:P166 wd:Q37922 .
  ?winner wdt:P26 ?spouse .
  ?spouse wdt:P106 ?occupation .
}
```

Let's execute this query to get the result.

[Tool]
Got 1 row and 1 column:
| count        |
| ------------ |
| 71 (xsd:int) |

[Assistant]
The query executed successfully and returned the result. The number of different occupations held by the spouses of the Nobel Prize in Literature winners is 71.

Here is the final SPARQL query and the answer:

```sparql
SELECT (COUNT(DISTINCT ?occupation) AS ?count) WHERE {
  ?winner wdt:P166 wd:Q37922 .
  ?winner wdt:P26 ?spouse .
  ?spouse wdt:P106 ?occupation .
}
```

Answer: 71

Now, let's provide the final answer using the `answer` function.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?university ?date WHERE {
  VALUES ?university {
    wd:Q34433 wd:Q35794
  }
  ?university wdt:P571 ?date .
}

The University of Oxford is established earlier than the University of Cambridge.

[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 university is established earlier, university of oxford or university of cambridge?

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

[Tool]
Example 1:
Question:
What are the official languages of the Philippines?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q928 wdt:P37 ?uri .
}

Using entities:
Philippines, also known as ph, The Philippines, RP, Republic of the Philippines, Philippine Islands (wd:Q928): archipelagic country in Southeast Asia

Using properties:
official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as wdt): language designated as official by this item, language used

Example 2:
Question:
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

Example 3:
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

[Assistant] Based on the examples, we need to identify the entities for the University of Oxford and the University of Cambridge, and then find the property for the establishment date. Let's start by searching for these entities.

[Tool]
Top 10 entity alternatives:
1. University of Oxford, also known as Univ. of Oxford, Universitas Oxoniensis, The University of Oxford, Oxon., Oxford (wd:Q34433): collegiate research university in Oxford, England
2. University of Oxford (wd:Q58944020): scholarly article
3. WikiProject University of Oxford (wd:Q21831045): Wikimedia subject-area collaboration
4. ISCA, University of Oxford (wd:Q52666568): Academic publisher based in United Kingdom
5. The University of Oxford (wd:Q61960212): scientific article published in March 2016
6. University of Oxford Finance (wd:Q102523083): business school
7. University of Oxford: Erratum (wd:Q94059932): scholarly article published in The BMJ
8. University of Oxford Latin American Centre, also known as University of Oxford LAC (wd:Q85960644): research centre in the UK
9. University of Oxford Blackfriars (wd:Q86020251): academic department in the UK
10. University of Oxford University College Oxford (wd:Q86020246): academic department in the UK

[Assistant] The correct entity for the University of Oxford is `wd:Q34433`. Now let's search for the University of Cambridge.

[Tool]
Top 10 entity alternatives:
1. University of Cambridge, also known as Cambridge University, The Chancellor, Masters, and Sch...s of the University of Cambridge, Cambridge, The University of Cambridge, Universitas Cantabrigiensis (wd:Q35794): collegiate public research university in Cambridge, England, United Kingdom
2. University of Cambridge, also known as The University of Cambridge, Universitas Cantabrigiensis, The Chancellor, Masters, and Sch...s of the University of Cambridge, Cambridge University, Cambridge (wd:Q35794): collegiate public research university in Cambridge, England, United Kingdom
3. University of Cambridge (wd:Q60109853): scholarly article published in Nature 148, November 1941
4. University of Cambridge (wd:Q60080699): scholarly article published in Nature 161, June 1948
5. University of Cambridge (wd:Q110095020): engraving by Nathaniel Parr
6. Cambridge University Constabulary, also known as University of Cambridge Constabulary (wd:Q304220)
7. University of Cambridge Museums & Botanic Garden, also known as University of Cambridge Museums (wd:Q17028042): consortium of museums of the University of Cambridge, United Kigdom
8. University of Cambridge legends (wd:Q7895218)
9. WikiProject University of Cambridge (wd:Q21831036): Wikimedia subject-area collaboration
10. Eur.Th.Group Of Cambridge University (wd:Q54909497): UK organization

[Assistant] The correct entity for the University of Cambridge is `wd:Q35794`. Next, we need to find the property for the establishment date. Let's search for this property.

[Tool]
Top 10 property alternatives:
1. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): time when an entity begins to exist; for date of official opening use P1619, start time
2. service entry, also known as commissioned, time of service entry, service introduction, launch date, in service (wd:P729 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): date or point in time on which a piece or class of equipment entered operational service, start time
3. subject named as, also known as established as, established form, established heading, named as, spelled as (wd:P1810 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): name by which a subject is recorded in a database, mentioned as a contributor of a work, or is referred to in a particular context, name
4. foundational text, also known as main text, treaty, organic law, founding document, establishing document (wd:P457 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): text through which an institution or object has been created or established
5. founded by, also known as starter, co-founded by, started by, institutor, instituted by (wd:P112 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): founder or co-founder of this organization, religion, place or entity, creator
6. notable work, also known as artwork, wrote, writer of, works, work (wd:P800 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): notable scientific, artistic or literary work, or other work of significance among subject's works
7. date of incorporation, also known as date incorporated, incorporated, incorporated on date, incorporation date, year incorporated (wd:P10786 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): date when company, organization or city was incorporated
8. location of formation, also known as place of incorporation, originates from, place of establishment, place of formation, place of foundation (wd:P740 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): location where a group or organization was formed, location of creation
9. main regulatory text, also known as regulated by, statutory authorization, statutory authority, legally established by, legal basis (wd:P92 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): text setting the main rules by which the subject is regulated
10. date of official opening, also known as launch date, launched, officially opened on, official opening, official opening time (wd:P1619 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): date or point in time a place, organization, or event officially opened, start time, inception

[Assistant] The property for the establishment date is `wd:P571` (inception). Now, let's write a SPARQL query to compare the establishment dates of the University of Oxford and the University of Cambridge.

[Tool]
Got 2 rows and 2 columns:
| university                          | date                                |
| ----------------------------------- | ----------------------------------- |
| University of Oxford (wd:Q34433)    | 1096-01-01T00:00:00Z (xsd:dateTime) |
| University of Cambridge (wd:Q35794) | 1209-01-01T00:00:00Z (xsd:dateTime) |

[Assistant]
The University of Oxford was established in 1096, while the University of Cambridge was established in 1209. Therefore, the University of Oxford is established earlier than the University of Cambridge.

Here is the final SPARQL query:

```sparql
SELECT ?university ?date WHERE {
  VALUES ?university { wd:Q34433 wd:Q35794 }
  ?university wdt:P571 ?date .
}
```

And the answer is:

The University of Oxford is established earlier than the University of Cambridge.

[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 ?artMovement ?artMovementLabel WHERE {
  wd:Q117012 wdt:P135 ?artMovement .
  OPTIONAL {
    ?artMovement rdfs:label ?artMovementLabel .
    FILTER ( LANG( ?artMovementLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| artMovement         | artMovementLabel |
| ------------------- | ---------------- |
| Fluxus (wd:Q108908) | Fluxus (en)      |

Yoko Ono was part of the Fluxus art movement.

[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 art movement was Yoko Ono part of?

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

[Tool]
Example 1:
Question:
How many films did Leonardo DiCaprio star in?

SPARQL:
SELECT ( COUNT( DISTINCT ?uri ) AS ?c ) WHERE {
  ?uri wdt:P31 wd:Q11424 ; wdt:P161 wd:Q38111 .
}

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
Leonardo DiCaprio (wd:Q38111): American actor and film producer (born 1974), television actor, environmentalist, film producer, screenwriter, stage actor, film actor, 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
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:
List the children of Margaret Thatcher.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q7416 wdt:P40 ?uri .
}

Using entities:
Margaret Thatcher, also known as Margaret Hilda Thatcher, Margaret Roberts, Margaret Hilda Roberts, Mrs. T, Mrs. Thatcher (wd:Q7416): British stateswoman and prime minister (1925–2013), research scientist, business executive, autobiographer, statesperson, politician, barrister, chemist

Using properties:
child, also known as has son, kids, mother of, kid, issue (wd:P40 as wdt): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative

Example 3:
Question:
Who are the parents of the wife of Juan Carlos I?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q19943 wdt:P26 ?spouse .
  ?uri wdt:P40 ?spouse .
}

Using entities:
Juan Carlos I of Spain, also known as Juan Carlos I, Juan Carlos Alfonso Víctor María de Borbón y Borbón-Dos Sicilias (wd:Q19943): King of Spain from 1975 to 2014, military officer, aristocrat, royalty, monarch

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
child, also known as has son, kids, mother of, kid, issue (wd:P40 as wdt): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative

[Assistant] Based on the examples, we need to identify the entity for Yoko Ono and the property for the art movement she was associated with. Let's start by searching for Yoko Ono in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Yoko Ono, also known as Yōko Ono, Ono Yōko, Yoko Ono Lennon, Ĭoko Ono, Ono (wd:Q117012): Japanese artist and activist based in the United States, performance artist, conceptual artist, recording artist, peace activist, visual artist, film director, photographer, filmmaker, sculptor, composer, painter, singer
2. Yōko Ōno, also known as Ono Yoko, Youko Ouno, Yoko Ono, Ōno Yōko (wd:Q16264827): Japanese judoka, judoka
3. Yoko Ono (wd:Q1867590): song by Die Ärzte
4. Yōko Ono, also known as Ono Yoko, Youko Ono, Yoko Ono, Ono Yōko (wd:Q11464149): Japanese actress born in 1954, actor, seiyū
5. Ono, Yoko (wd:Q103989374): encyclopedia article
6. Yoko Ono/Plastic Ono Band (wd:Q507672): album
7. Plastic Ono Band, also known as Plastic Ono Elephant's Memory Band, Plastic Ono Nuclear Band, Plastic U.F. Ono Band, The Plastic Ono Band, Yoko Ono Plastic Ono Band (wd:Q731721): UK musical group; rock band
8. Be My Yoko Ono (wd:Q4875557): 1992 single by Barenaked Ladies
9. Yoko Ono Lennon Centre, also known as Tung Auditorium (wd:Q130417289): teaching and performance facility in Liverpool
10. John Lennon and Yoko Ono, also known as Yoko & John, Yoko Ono & John Lennon, Yoko Ono and John Lennon, John & Yoko, John Lennon & Yoko Ono (wd:Q47122619): musical duo; couple

[Assistant] The first result, wd:Q117012, seems to be the correct entity for Yoko Ono. Now let's search for the property that represents the art movement she was associated with.

[Tool]
Top 10 property alternatives:
1. movement, also known as subculture, trend, scientific movement, school, philosophical movement (wd:P135 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): literary, artistic, scientific or philosophical movement or scen...ed with this person or work. For political ideologies use P1142.
2. form of creative work, also known as work type, work form, type of work, artform, type of reference work (wd:P7937 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): structure of a creative work
3. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
4. main subject, also known as primary topic, primary subject, primary keyword, plot keyword, of (wd:P921 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): primary topic of a work (see also P180: depicts), depicts
5. expression, gesture or body pose, also known as action, expression, facial expression, gesture, movement (wd:P6022 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): qualifier on "depicts" (P180) for human position of an individual in an artwork
6. creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): maker of this creative work or other object (where no more specific property exists)
7. notable work, also known as artwork, wrote, writer of, works, work (wd:P800 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): notable scientific, artistic or literary work, or other work of significance among subject's works
8. after a work by, also known as inspirational artist, inspiring artist, copy of a work by, based on a work by, artist who inspired this (wd:P1877 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): artist whose work strongly inspired / was copied in this item, significant person
9. art name, also known as artistic name, hao, hiệu (wd:P1787 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): type of pseudonym of modern and historical artists as well as sp...ically traditionally adopted by writers and artists in East Asia
10. exhibited creator, also known as artist exhibited, exhibited artist (wd:P10661 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): intellectual or creative entity (person or organization) responsible for the elements exhibited, creator

[Assistant]
The property "movement" (wd:P135) appears to be the correct one for identifying the art movement associated with an artist. Let's now construct a SPARQL query to find out which art movement Yoko Ono was part of.

Here is the initial SPARQL query:

```sparql
SELECT ?artMovement WHERE {
  wd:Q117012 wdt:P135 ?artMovement .
}
```

I will execute this query to see the results.

[Tool]
Got 1 row and 1 column:
| artMovement         |
| ------------------- |
| Fluxus (wd:Q108908) |

[Assistant]
The SPARQL query returned that Yoko Ono was part of the Fluxus art movement. To provide a more complete answer, I will include the label of the art movement in the final query.

Here is the refined SPARQL query:

```sparql
SELECT ?artMovement ?artMovementLabel WHERE {
  wd:Q117012 wdt:P135 ?artMovement .
  OPTIONAL { ?artMovement rdfs:label ?artMovementLabel . FILTER(LANG(?artMovementLabel) = "en") }
}
```

I will execute this query to confirm the label.

[Tool]
Got 1 row and 2 columns:
| artMovement         | artMovementLabel |
| ------------------- | ---------------- |
| Fluxus (wd:Q108908) | Fluxus (en)      |

[Assistant]
The refined SPARQL query confirms that Yoko Ono was part of the Fluxus art movement. Here is the final SPARQL query and the answer to the user's question:

```sparql
SELECT ?artMovement ?artMovementLabel WHERE {
  wd:Q117012 wdt:P135 ?artMovement .
  OPTIONAL { ?artMovement rdfs:label ?artMovementLabel . FILTER(LANG(?artMovementLabel) = "en") }
}
```

Answer: Yoko Ono was part of the Fluxus art movement.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?releaseDate WHERE {
  wd:Q19798744 wdt:P580 ?releaseDate .
}

The OA was first released on December 16, 2016.

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

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

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

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

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

[User] When did The OA was first released?

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

[Tool]
Example 1:
Question:
What is the second highest mountain on Earth?

SPARQL:
SELECT ?res WHERE {
  ?res wdt:P31 / wdt:P279 * wd:Q8502 .
  ?res wdt:P2044 ?elevation .
  ?res wdt:P30 / wdt:P361 wd:Q2 .
}
ORDER BY DESC ( ?elevation )
LIMIT 1
OFFSET 1

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
mountain, also known as mt., mtn., mountains, mount (wd:Q8502): large natural elevation of the Earth's surface

Using properties:
elevation above sea level, also known as MAMSL, MASL, height, elevation above mean sea level, elevation (wd:P2044 as wdt): height of the item (geographical object) as measured relative to sea level
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
continent (wd:P30 as wdt): continent of which the subject is a part, located in/on physical feature
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))

Example 2:
Question:
Which movies did Kurosawa direct?

SPARQL:
SELECT DISTINCT * WHERE {
  ?uri wdt:P57 wd:Q8006 .
}

Using entities:
Akira Kurosawa, also known as Kurosawa Akira, Kurosawa (wd:Q8006): Japanese filmmaker (1910–1998), film producer, film director, screenwriter, film editor, producer, director, painter, writer

Using properties:
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 3:
Question:
What did Bruce Carver die from?

SPARQL:
SELECT DISTINCT ?o1 WHERE {
  wd:Q4977246 wdt:P509 ?o1 .
}

Using entities:
Bruce Carver, also known as Bruce E. Carver, Bruce Eugene Carver (wd:Q4977246): Video game designer and programmer, video game director, businessperson, engineer

Using properties:
cause of death, also known as death cause, murder method, method of murder, die of, die from (wd:P509 as wdt): underlying or immediate cause of death.  Underlying cause (e.g. ...adest category, e.g. natural causes, accident, homicide, suicide

[Assistant] Based on the examples, we need to identify the entity for "The OA" and then find the property that corresponds to the release date. Let's start by searching for the entity "The OA".

[Tool]
Top 10 entity alternatives:
1. The OA (wd:Q19798744): 2016 American mystery drama television series
2. The Oa, also known as The Oa RSPB Nature Reserve (wd:Q1325866): peninsula in the southwest of Islay, Argyll and Bute, Scotland, UK
3. The Oa (wd:Q126204501): Special Protection Area in Scotland, UK
4. The Oath, also known as Oath, Eiðurinn (wd:Q27834781): 2016 film by Baltasar Kormákur
5. Di Shvue, also known as Di Bundishe Shvue, The Oath (wd:Q5270055): Jewish song, anthem of the Bund
6. Il giuramento, also known as The Oath (wd:Q1469058): opera by Saverio Mercadante
7. The Oak, also known as Oak (wd:Q2328850): 1992 film
8. Epsom Oaks, also known as Oaks, The Oaks, The Oaks Stakes (wd:Q3347856): British Group 1 horse race tor 3-year-old filles over 1 mile, 4 furlongs and 10 yards (2,423 metres)
9. The Oatmeal, also known as theoatmeal.com (wd:Q2015830): humor website
10. The Oath (wd:Q39071891): television series

[Assistant] The top result for "The OA" is the 2016 American mystery drama television series (wd:Q19798744). Now, let's find the property that corresponds to the release date. We can search for properties related to "release date" or "first aired" for this entity.

[Tool]
Top 10 property alternatives:
1. start time, also known as start date, since, valid, join time, joined (wd:P580 as p/wdt): time an entity begins to exist or a statement starts being valid, point in time
2. end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as p/wdt): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time
3. distribution format, also known as book format, type of media, publication format, method of distribution, medium (wd:P437 as p/wdt): method (or type) of distribution for the subject
4. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as p/wdt): 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 p/wdt): published name of a work, such as a newspaper article, a literary work, piece of music, a website, or a performance work, name
6. country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as p/wdt): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country
7. producer, also known as music producer, record producer, produced by, film producer, creative producer (wd:P162 as p/wdt): person(s) who produced the film, musical work, theatrical produc...etc.) [for production company, use P272, video games - use P178]
8. duration, also known as time length, timespan, time span, time interval, runtime (wd:P2047 as p/wdt): length of time of an event or process
9. original broadcaster, also known as TV channel, television channel, radio station, radio network, original network (wd:P449 as p/wdt): network(s) or service(s) that originally broadcast a radio or television program, broadcast by
10. distributed by, also known as distributor (wd:P750 as p/wdt): distributor of a creative work; distributor for a record label; news agency; film distributor

No other items found

[Assistant]
The property "start time" (wdt:P580) seems to be the most relevant for the release date of a television series. Let's construct a SPARQL query to retrieve the start time of "The OA" (wd:Q19798744).

```sparql
SELECT ?releaseDate WHERE {
  wd:Q19798744 wdt:P580 ?releaseDate .
}
```

Let's execute this query.

[Tool]
Got 1 row and 1 column:
| releaseDate                         |
| ----------------------------------- |
| 2016-12-16T00:00:00Z (xsd:dateTime) |

[Assistant]
The release date of "The OA" is December 16, 2016.

Here is the final SPARQL query and answer:

```sparql
SELECT ?releaseDate WHERE {
  wd:Q19798744 wdt:P580 ?releaseDate .
}
```

Answer: The OA was first released on December 16, 2016.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( ?headOfState ) AS ?count ) WHERE {
  wd:Q794 wdt:P35 ?headOfState
}

Got 1 row and 1 column:
| count       |
| ----------- |
| 1 (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 head of the state does iran have?

[Assistant] Let's start by looking at some 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:
What is the population of Cairo?

SPARQL:
SELECT DISTINCT ?val WHERE {
  wd:Q85 wdt:P1082 ?val .
}

Using entities:
Cairo, also known as al-Qāhira, Cairo, Egypt, Qahira (wd:Q85): capital city of Egypt

Using properties:
population, also known as inhabitants, human population (wd:P1082 as wdt): number of people inhabiting the place; number of people of subject

Example 3:
Question:
Give me all Danish films.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?type wdt:P279 * wd:Q11424 .
  ?uri wdt:P31 ?type ; wdt:P495 wd:Q35 .
}

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
Denmark, also known as 🇩🇰, Danmark, DEK, TAN, DEN (wd:Q35): country in Northern Europe

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)
country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as wdt): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country

[Assistant] Based on the examples, we need to identify the entity for Iran and the property for head of state. Let's first search for the entity Iran.

[Tool]
Top 10 entity alternatives:
1. Iran, also known as ir, IRI, IRN, Islamic Rep. Iran, Islamic Republic of Iran (wd:Q794): country in Western Asia
2. Qajar Iran, also known as Guarded Domains of Persia, Sublime State of Persia, Qajar Persia, Persia, Iran (wd:Q63158027): country in Western Asia (1789–1925)
3. Iran (wd:Q2043606): village in North Ossetia, Russia
4. Iran, also known as Īrān (wd:Q10859757): Iranian newspaper
5. IRAN, also known as Iran: Journal of the British Institute of Persian Studies (wd:Q5973372): academic journal
6. Irane Man, also known as Iran (wd:Q100939484): 2018 studio by Homayoun Shajarian & Sohrab Pournazeri
7. IRAN (wd:Q108434787): herbarium
8. Iran, also known as Iran (first name), Iran (given name) (wd:Q21286079): male given name
9. Iran, also known as IMO 5327817 (wd:Q101778560): ship built in 1941
10. Iran (wd:Q96382820): About Iran

[Assistant] The correct entity for Iran is `wd:Q794`. Now let's search for the property related to the head of state.

[Tool]
Top 10 property alternatives:
1. office held by head of state, also known as head of state, position held by head of state, state headed by (wd:P1906 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): political office that is fulfilled by the head of state of this item
2. head of state, also known as leader, state headed by, monarch, president, queen (wd:P35 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): official with the highest formal authority in a country/state, director / manager, chairperson
3. head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson
4. office held by head of government, also known as title of head of government, position of head of government, office of head of government, head of government's office, position held by head of government (wd:P1313 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): political office that is fulfilled by the head of the government of this item
5. rector, also known as chancellor, university president, Rector (academia), president (wd:P1075 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): senior official in an educational institution., director / manager, chairperson
6. chairperson, also known as dean, headed by, leader, president, chairwoman (wd:P488 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): presiding member of an organization, group or body, director / manager, significant person
7. organization directed by the office or position, also known as leader of, head of, leads, organization directed by, organization directed from the office (wd:P2389 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): organization which is directed by this office
8. position held by head of the organization, also known as position held by head of the organisation, secretary's position, president's position, position held by head of the organization, office held by head of the organisation (wd:P2388 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): position of the head of this item
9. position holder, also known as incumbent, noble title holder, office holder, position held by (wd:P1308 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): persons who hold and/or held the position
10. country, also known as sovereign state, state, land, host country (wd:P17 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity

[Assistant]
The correct property for the head of state is `wd:P35`. Now, let's construct a simple SPARQL query to find out how many heads of state Iran has.

We'll start with a basic query to list the heads of state:

```sparql
SELECT ?headOfState
WHERE {
  wd:Q794 wdt:P35 ?headOfState
}
```

Let's execute this query to see the results.

[Tool]
Got 1 row and 1 column:
| headOfState              |
| ------------------------ |
| Ali Khamenei (wd:Q57336) |

[Assistant]
The query returned one head of state for Iran, which is Ali Khamenei. To confirm the number of heads of state, we can modify the query to count the results:

```sparql
SELECT (COUNT(?headOfState) AS ?count)
WHERE {
  wd:Q794 wdt:P35 ?headOfState
}
```

Let's execute this query to get the count.

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

[Assistant]
The query confirms that Iran has 1 head of state.

Therefore, the answer to the question "How many heads of state does Iran have?" is 1.

Here is the final SPARQL query and the answer:

```sparql
SELECT (COUNT(?headOfState) AS ?count)
WHERE {
  wd:Q794 wdt:P35 ?headOfState
}
```

Answer: 1

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( DISTINCT ?country ) AS ?count ) WHERE {
  wd:Q3233785 wdt:P17 ?country .
}

Got 1 row and 1 column:
| count        |
| ------------ |
| 14 (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] In how many countries is pysanka practiced?

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

[Tool]
Example 1:
Question:
Which movies star both Liz Taylor and Richard Burton?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P161 wd:Q34851 .
  ?uri wdt:P161 wd:Q151973 .
}

Using entities:
Richard Burton, also known as Richard Jenkins, Richard Walter Jenkins, Jr. (wd:Q151973): Welsh actor (1925–1984), film producer, film director, stage actor, film actor, producer, director, diarist, actor
Elizabeth Taylor, also known as Liz Taylor, Elizabeth Rosemond Taylor, Dame Elizabeth Taylor, Dame Elizabeth Rosemond Taylor (wd:Q34851): British-American actress, HIV/AIDS activist, television actor, philanthropist, autobiographer, art collector, film producer, stage actor, film actor, 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 2:
Question:
Give me a list of all bandleaders that play trumpet.

SPARQL:
SELECT ?res WHERE {
  ?res wdt:P106 wd:Q806349 .
  ?res wdt:P1303 wd:Q8338 .
}

Using entities:
bandleader, also known as Harmony orchestra leader, Wind band conductor (wd:Q806349): leader of a band of musicians
trumpet, also known as Bb trumpet, B-flat trumpet, B♭ trumpet, natural trumpet, slide trumpet (wd:Q8338): musical instrument

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)
instrument, also known as uses this instrument, teaches instrument, instruments, plays this instrument, plays instrument (wd:P1303 as wdt): musical instrument that a person plays or teaches or used in a music occupation, uses

Example 3:
Question:
Who was Tom Hanks married to?

SPARQL:
SELECT ?o1 WHERE {
  wd:Q2263 wdt:P26 ?o1 .
}

Using entities:
Tom Hanks, also known as Thomas Jeffrey Hanks, Thomas Hanks (wd:Q2263): American actor and film producer (born 1956), television presenter, television director, television producer, executive producer, short story writer, television actor, character actor, film producer, film director, screenwriter, stage actor, voice actor, film actor, narrator, director, composer, comedian, writer, actor

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

[Assistant] Based on the examples, we need to identify the entity for "pysanka" and the property that indicates where it is practiced. Let's start by searching for the entity "pysanka".

[Tool]
Top 10 entity alternatives:
1. pysanka, also known as pisanica, pisanka (wd:Q3233785): egg decorating tradition in Slavic countries
2. Pysanka (wd:Q12140613)
3. Pysanka Museum (wd:Q746631): museum in Kolomyia, Ukraine
4. Ruslana Pysanka, also known as Ruslana Pysanko (wd:Q2506290): Ukrainian actress (1965–2022), television presenter, weather presenter, film actor, presenter, actor
5. Vegreville egg, also known as Vegreville Pysanka (wd:Q7918394): sculpture by Paul Maxum Sembaliuk
6. Hutsul pysanka (wd:Q116733019): Traditional hutsul painted Eastern egg
7. pysankar (wd:Q50333861): Ukrainian ethnic occupation, artists that produces pysanka
8. FORMATION OF PRESCHOOLERS’ AWARE...SANKA PAINTING REGIONAL FEATURES (wd:Q113694374): scientific article published in 2022

[Assistant] The first result, "pysanka" (wd:Q3233785), seems to be the most relevant. Now let's find out what properties are associated with this entity, specifically those that might indicate where it is practiced.

[Tool]
Top 10 property alternatives:
1. 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
2. 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)
3. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as p/wdt): main Wikimedia category
4. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
5. manufacturer, also known as manufactured by, provider, provided by, product of, producer (wd:P176 as p/wdt): (main or final) manufacturer or producer of this product
6. religion or worldview, also known as believes, worldview, religious affiliation, religion or world view, religion (wd:P140 as p/wdt): religion of a person, organization or religious building, or associated with this subject
7. subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as p/wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
8. Freebase ID, also known as Freebase, MID, Freebase identifier, FID (wd:P646 as p/wdt): identifier for a page in the Freebase database. Format: "/m/0" f...r IDs starting with "/g/", use Google Knowledge Graph ID (P2671)

No other items found

[Assistant] The property "country" (wd:P17) seems to be the most relevant for identifying where pysanka is practiced. However, we need to verify if this property is actually used with the entity "pysanka" (wd:Q3233785). Let's check the triples involving this entity and property.

[Tool]
Got 14 rows and 3 columns, showing the first 10 rows below:
| subject               | property          | object                           |
| --------------------- | ----------------- | -------------------------------- |
| pysanka (wd:Q3233785) | country (wdt:P17) | Poland (wd:Q36)                  |
| pysanka (wd:Q3233785) | country (wdt:P17) | Ukraine (wd:Q212)                |
| pysanka (wd:Q3233785) | country (wdt:P17) | Bulgaria (wd:Q219)               |
| pysanka (wd:Q3233785) | country (wdt:P17) | Belarus (wd:Q184)                |
| pysanka (wd:Q3233785) | country (wdt:P17) | Czech Republic (wd:Q213)         |
| pysanka (wd:Q3233785) | country (wdt:P17) | Croatia (wd:Q224)                |
| pysanka (wd:Q3233785) | country (wdt:P17) | Romania (wd:Q218)                |
| pysanka (wd:Q3233785) | country (wdt:P17) | Serbia (wd:Q403)                 |
| pysanka (wd:Q3233785) | country (wdt:P17) | Slovakia (wd:Q214)               |
| pysanka (wd:Q3233785) | country (wdt:P17) | Bosnia and Herzegovina (wd:Q225) |
| ...                   | ...               | ...                              |

[Assistant]
The results show that "pysanka" (wd:Q3233785) is practiced in multiple countries. We can count the number of distinct countries by executing a SPARQL query.

Let's write and execute the SPARQL query to count the number of distinct countries where pysanka is practiced.

[Tool]
Got 1 row and 1 column:
| count        |
| ------------ |
| 14 (xsd:int) |

[Assistant]
The SPARQL query returned that pysanka is practiced in 14 distinct countries.

Therefore, the answer to the question "In how many countries is pysanka practiced?" is:

14

Here is the final SPARQL query:

```sparql
SELECT (COUNT(DISTINCT ?country) AS ?count)
WHERE {
  wd:Q3233785 wdt:P17 ?country .
}
```

And the answer is 14.

[Tool] Stopped generation process