PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
ASK WHERE {
  wd:Q66432 wdt:P1344 wd:Q33881 .
}

False

[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] Did Udo Bölts participate in the Tour de France?

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

[Tool] No examples found

[Assistant] Since we couldn't find any similar examples, let's start by searching for the entity "Udo Bölts".

[Tool]
Top 10 entity alternatives:
1. Udo Bölts (wd:Q66432): German racing cyclist, sport cyclist
2. Wadjet, also known as Buto, Udṓ, Weʾd’ōjet (wd:Q146007): Ancient Egyptian snake-headed goddess, symbolizing Lower Egypt
3. Tampa Bay Lightning, also known as Bolts, Lightning, The Tampa Bay Lightning (wd:Q201864): ice hockey team of the National Hockey League
4. Udo (wd:Q496912): island
5. Udo, also known as Udo (Obotrite prince) (wd:Q13424614): Obotrite prince
6. Ultra Density Optical, also known as UDO (wd:Q1932063): optical disc format
7. Udo, also known as Udo (first name), Udo (given name) (wd:Q1465588): male given name
8. Lothair Udo I, Count of Stade, also known as Lothar-Udo I of Stade, Udo (wd:Q20498306): Count of Stade (950–994)
9. Udo Mechels, also known as Udo (wd:Q359510): Belgian Flemish singer-songwriter, singer
10. U Island, also known as U-do, Udo (wd:Q12608825): island in Incheon, Korea

[Assistant] From the search results, it looks like the first option, "Udo Bölts (wd:Q66432)", is the correct entity we're looking for. Now, let's search for the property "participate in" or something similar.

[Tool]
Top 10 property alternatives:
1. participant in, also known as participated in, present at, takes part, took part, took part in (wd:P1344 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): event in which a person or organization was/is a participant; inverse of P710 or P1923, significant event, part of
2. member of, also known as band member of, membership, member of musical group, in musical group, be member of (wd:P463 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): organization, club or musical group to which the subject belongs...ical position, such as a member of parliament (use P39 for that), part of
3. participant, also known as suspect, player, party, participants, has participant (wd:P710 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): person, group of people or organization (object) that actively t...ct has role" (P3831). Use P1923 for participants that are teams., significant person
4. number of participants, also known as number of competitors, number of teams, participant count, participants, qty participants (wd:P1132 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): number of participants of an event, e.g. people or groups of people that take part in the event (NO units), quantity
5. physically interacts with, also known as interact, interact with (wd:P129 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): physical entity that the subject interacts with
6. work location, also known as work place, working from, working at, worked from, worked at (wd:P937 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): location where persons or organisations were actively participating in employment, business or other work, significant place, location
7. qualifies for event, also known as league this event qualifies for (wd:P3085 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): this event qualifies for that event
8. aircraft registration, also known as reg, registration, tail number (wd:P426 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): identifier assigned to an individual aircraft by civil aircraft registry, fleet or registration number
9. language style, also known as manner, term register, obsolete, register, sense register (wd:P6191 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): to denote of the way a sense of a word is used, e.g., slang, vulgarism, babytalk, colloquialism, etc.
10. start time, also known as start date, since, valid, join time, joined (wd:P580 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): time an entity begins to exist or a statement starts being valid, point in time

[Assistant]
The property "participant in" (wd:P1344) seems to be the most relevant for our purpose. Now, let's check if Udo Bölts participated in the Tour de France by executing a SPARQL query.

We need to find the entity for "Tour de France" first.

[Tool]
Top 10 entity alternatives:
1. Tour de France, also known as Souvenir Henri Desgrange, TdF, Le Tour de France, Le Tour, La Grande Boucle (wd:Q33881): multiple-stage bicycle race primarily held in France
2. Tour de France (wd:Q2425911): 1983 Kraftwerk song
3. Pro Cycling Manager 2011, also known as Pro Cycling Manager: Season 2011, Tour de France (wd:Q3406163): 2011 video game
4. Tour de France (wd:Q23925083): 2016 film by Rachid Djaïdani
5. Tour de France, also known as Le Tour de France (wd:Q16964929): video game series
6. Tour de France (wd:Q3533332)
7. Tour de France (wd:Q70142694): 1985 video game
8. 2014 Tour de France, also known as Tour de France 2014, TdF 2014, Le Tour de France 2014 (wd:Q895853): 2014 edition of a multiple-stage bicycle race primarily held in France
9. 2012 Tour de France (wd:Q219414): cycling competition
10. 2010 Tour de France (wd:Q217287): cycling race

[Assistant]
The first option, "Tour de France (wd:Q33881)", is the correct entity for the Tour de France. Now, let's construct a SPARQL query to check if Udo Bölts participated in the Tour de France.

We will use the property "participant in" (wd:P1344) to see if Udo Bölts (wd:Q66432) participated in the Tour de France (wd:Q33881).

Let's execute the SPARQL query:

```sparql
ASK WHERE {
  wd:Q66432 wdt:P1344 wd:Q33881 .
}
```

This ASK query will return `true` if Udo Bölts participated in the Tour de France and `false` otherwise.

Executing the query now:

[Tool] False

[Assistant]
The SPARQL query returned `false`, which means Udo Bölts did not participate in the Tour de France.

Therefore, the answer to the question "Did Udo Bölts participate in the Tour de France?" is **False**.

Final SPARQL query and answer:

```sparql
ASK WHERE {
  wd:Q66432 wdt:P1344 wd:Q33881 .
}
```

Answer: **False**

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?son ?sonLabel ?profession ?professionLabel WHERE {
  ?son wdt:P106 ?profession .
  VALUES ?son {
    wd:Q311238 wd:Q357974
  }
  OPTIONAL {
    ?son rdfs:label ?sonLabel .
    FILTER ( LANG( ?sonLabel ) = 'en' )
  }
  OPTIONAL {
    ?profession rdfs:label ?professionLabel .
    FILTER ( LANG( ?professionLabel ) = 'en' )
  }
}

Got 16 rows and 4 columns, showing the first 5 and last 5 rows below:
| son                        | sonLabel           | profession                      | professionLabel       |
| -------------------------- | ------------------ | ------------------------------- | --------------------- |
| Sean Lennon (wd:Q311238)   | Sean Lennon (en)   | singer (wd:Q177220)             | singer (en)           |
| Julian Lennon (wd:Q357974) | Julian Lennon (en) | singer (wd:Q177220)             | singer (en)           |
| Sean Lennon (wd:Q311238)   | Sean Lennon (en)   | screenwriter (wd:Q28389)        | screenwriter (en)     |
| Julian Lennon (wd:Q357974) | Julian Lennon (en) | photographer (wd:Q33231)        | photographer (en)     |
| Sean Lennon (wd:Q311238)   | Sean Lennon (en)   | actor (wd:Q33999)               | actor (en)            |
| ...                        | ...                | ...                             | ...                   |
| Sean Lennon (wd:Q311238)   | Sean Lennon (en)   | poet (wd:Q49757)                | poet (en)             |
| Julian Lennon (wd:Q357974) | Julian Lennon (en) | poet (wd:Q49757)                | poet (en)             |
| Julian Lennon (wd:Q357974) | Julian Lennon (en) | recording artist (wd:Q55960555) | recording artist (en) |
| Sean Lennon (wd:Q311238)   | Sean Lennon (en)   | guitarist (wd:Q855091)          | guitarist (en)        |
| Julian Lennon (wd:Q357974) | Julian Lennon (en) | guitarist (wd:Q855091)          | guitarist (en)        |

- **Sean Lennon**: Singer, Screenwriter, Actor, Composer, Pianist, Poet, Guitarist
- **Julian Lennon**: Singer, Photographer, Composer, Singer-songwriter, Poet, Recording artist, Guitarist

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

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

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

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

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

[User] What are the professions of John Lennon’s sons?

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

[Tool]
Example 1:
Question:
Who killed John Lennon?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q1203 wdt:P157 ?uri .
}

Using entities:
John Lennon, also known as John Winston Ono Lennon, John Ono Lennon (wd:Q1203): British musician (1940–1980), political activist, singer-songwriter, recording artist, record producer, peace activist, public figure, film director, film producer, prose writer, film actor, guitarist, composer, painter, pianist, singer, writer, actor, poet

Using properties:
killed by, also known as slaughtered by, slain by, shot dead by, murderer, murdered by (wd:P157 as wdt): person or organization who killed the subject, significant person

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:
In which studio did the Beatles record their first album?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?album wdt:P31 wd:Q482994 ; wdt:P175 wd:Q1299 ; wdt:P577 ?date ; wdt:P483 ?uri .
}
ORDER BY ?date
LIMIT 1

Using entities:
The Beatles, also known as Fab Four, The Lads from Liverpool, John, Paul, George, and Ringo (wd:Q1299): English pop rock band (1960–1970)
album, also known as full album, record album, music album, full-length album, audio album (wd:Q482994): grouping of album releases by an artist usually released at the ...racks but in different formats for consumption (digital, CD, LP)

Using properties:
performer, also known as actor, sung by, singer, recording by, recorded by (wd:P175 as wdt): actor, musician, band or other performer associated with this role or musical work, contributor to the creative work or subject
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
recorded at studio or venue, also known as venue, studio, recording venue, recording studio, recorded at event (wd:P483 as wdt): studio or location where a musical composition/release was recorded, recording location
publication date, also known as launched, published, publication time, publication, pubdate (wd:P577 as wdt): date or point in time when a work was first published or released, point in time

[Assistant] Based on the examples, we need to identify John Lennon, his sons, and their professions. Let's start by finding the entity for John Lennon.

[Tool]
Top 10 entity alternatives:
1. John Lennon, also known as John Winston Ono Lennon, John Ono Lennon (wd:Q1203): British musician (1940–1980), political activist, singer-songwriter, recording artist, record producer, peace activist, public figure, film director, film producer, prose writer, film actor, guitarist, composer, painter, pianist, singer, writer, actor, poet
2. Liverpool John Lennon Airport, also known as John Lennon, John Lennon airport, Liverpool Airport, Liverpool (John Lennon), LPL (wd:Q8727): airport in Liverpool, England
3. John Lennon Silva Santos, also known as John Lennon (wd:Q6244563): association football player, Brazilian footballer
4. John Brown Lennon, also known as John B. Lennon, John Lennon (wd:Q6223555): American labor leader (1850–1923), trade unionist
5. John Lennon, also known as J. John Lennon, Justin John Lennon (wd:Q11979004): Scottish tourism researcher, university teacher, tourism scholar
6. John Lennon (wd:Q65548791): Irish hurler born 1996
7. John Lennon (wd:Q6244553): British naval captain, military personnel
8. John Lennon (wd:Q12871620): 1855 - 3 Aug 1921
9. John Lennon (wd:Q125643070): 2005 edition of written work by Jordi Sierra i Fabra
10. John Lennon (wd:Q106781630): 2015 song by SCH

[Assistant] The correct entity for John Lennon is `wd:Q1203`. Now let's find his sons by searching for the property "child" (`wdt:P40`).

[Tool]
Got 4 rows and 1 column:
| son                             |
| ------------------------------- |
| John Ono Lennon (wd:Q124306663) |
| John Lennon III (wd:Q124306740) |
| Sean Lennon (wd:Q311238)        |
| Julian Lennon (wd:Q357974)      |

[Assistant] We found four sons of John Lennon: John Ono Lennon, John Lennon III, Sean Lennon, and Julian Lennon. Next, we need to find the professions of these individuals. We can use the property "occupation" (`wdt:P106`) to find their professions.

[Tool]
Got 16 rows and 2 columns, showing the first 5 and last 5 rows below:
| son                        | profession                      |
| -------------------------- | ------------------------------- |
| Sean Lennon (wd:Q311238)   | singer (wd:Q177220)             |
| Sean Lennon (wd:Q311238)   | screenwriter (wd:Q28389)        |
| Sean Lennon (wd:Q311238)   | actor (wd:Q33999)               |
| Sean Lennon (wd:Q311238)   | composer (wd:Q36834)            |
| Sean Lennon (wd:Q311238)   | pianist (wd:Q486748)            |
| ...                        | ...                             |
| Julian Lennon (wd:Q357974) | composer (wd:Q36834)            |
| Julian Lennon (wd:Q357974) | singer-songwriter (wd:Q488205)  |
| Julian Lennon (wd:Q357974) | poet (wd:Q49757)                |
| Julian Lennon (wd:Q357974) | recording artist (wd:Q55960555) |
| Julian Lennon (wd:Q357974) | guitarist (wd:Q855091)          |

[Assistant] The query returned multiple professions for Sean Lennon and Julian Lennon. However, it seems that the other two sons, John Ono Lennon and John Lennon III, do not have occupations listed. Let's refine the query to include only the sons who have professions listed and also include their labels for better readability.

[Tool]
Got 16 rows and 4 columns, showing the first 5 and last 5 rows below:
| son                        | sonLabel           | profession                      | professionLabel       |
| -------------------------- | ------------------ | ------------------------------- | --------------------- |
| Sean Lennon (wd:Q311238)   | Sean Lennon (en)   | singer (wd:Q177220)             | singer (en)           |
| Julian Lennon (wd:Q357974) | Julian Lennon (en) | singer (wd:Q177220)             | singer (en)           |
| Sean Lennon (wd:Q311238)   | Sean Lennon (en)   | screenwriter (wd:Q28389)        | screenwriter (en)     |
| Julian Lennon (wd:Q357974) | Julian Lennon (en) | photographer (wd:Q33231)        | photographer (en)     |
| Sean Lennon (wd:Q311238)   | Sean Lennon (en)   | actor (wd:Q33999)               | actor (en)            |
| ...                        | ...                | ...                             | ...                   |
| Sean Lennon (wd:Q311238)   | Sean Lennon (en)   | poet (wd:Q49757)                | poet (en)             |
| Julian Lennon (wd:Q357974) | Julian Lennon (en) | poet (wd:Q49757)                | poet (en)             |
| Julian Lennon (wd:Q357974) | Julian Lennon (en) | recording artist (wd:Q55960555) | recording artist (en) |
| Sean Lennon (wd:Q311238)   | Sean Lennon (en)   | guitarist (wd:Q855091)          | guitarist (en)        |
| Julian Lennon (wd:Q357974) | Julian Lennon (en) | guitarist (wd:Q855091)          | guitarist (en)        |

[Assistant]
The query has successfully returned the professions of Sean Lennon and Julian Lennon along with their labels. Here are the results:

- **Sean Lennon**:
  - Singer
  - Screenwriter
  - Actor
  - Composer
  - Pianist
  - Poet
  - Guitarist

- **Julian Lennon**:
  - Singer
  - Photographer
  - Composer
  - Singer-songwriter
  - Poet
  - Recording artist
  - Guitarist

Since the other two sons, John Ono Lennon and John Lennon III, do not have professions listed, we will not include them in the final answer.

Here is the final SPARQL query and answer:

```sparql
SELECT ?son ?sonLabel ?profession ?professionLabel WHERE {
  ?son wdt:P106 ?profession .
  VALUES ?son { wd:Q311238 wd:Q357974 }
  OPTIONAL { ?son rdfs:label ?sonLabel . FILTER(LANG(?sonLabel) = 'en') }
  OPTIONAL { ?profession rdfs:label ?professionLabel . FILTER(LANG(?professionLabel) = 'en') }
}
```

Answer:
- **Sean Lennon**: Singer, Screenwriter, Actor, Composer, Pianist, Poet, Guitarist
- **Julian Lennon**: Singer, Photographer, Composer, Singer-songwriter, Poet, Recording artist, Guitarist

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 ?stadium WHERE {
  wd:Q213417 wdt:P115 ?stadium .
}

Yankee Stadium

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

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

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

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

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

[User] In which stadium do the New York Yankees play?

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

[Tool]
Example 1:
Question:
Where do the Red Sox play?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q213959 wdt:P115 ?uri
}

Using entities:
Boston Red Sox, also known as Sox, redsoxs, RedSox, Red Sox, redsox (wd:Q213959): baseball team and Major League Baseball franchise in Boston, Massachusetts, United States

Using properties:
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 2:
Question:
What is the biggest stadium in Spain?

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

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

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

Example 3:
Question:
Which museum in New York has the most visitors?

SPARQL:
SELECT ?s1 WHERE {
  ?s1 wdt:P159 wd:Q60 .
  ?s1 wdt:P31 wd:Q33506 .
  ?s1 wdt:P1174 ?o1
}
order by ?o1
limit 1

Using entities:
museum, also known as museal institution, museum-style institution (wd:Q33506): institution that holds artifacts and other objects of scientific, artistic, cultural, historical, or other importance
New York City, also known as Capital of the World, Big Apple, the five boroughs, The City So Nice They Named It Twice, NY, NY (wd:Q60): most populous city in the United States

Using properties:
visitors per year, also known as annual visitors, yearly visitors (wd:P1174 as wdt): number of people visiting a location or an event each year
headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as wdt): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

[Assistant] Based on the examples, we need to find the home venue of the New York Yankees. Let's first identify the entity for the New York Yankees.

[Tool]
Top 10 entity alternatives:
1. New York Yankees, also known as New York Highlanders, Yankees, NY Yankees, NYY, Highlanders (wd:Q213417): baseball team and Major League Baseball franchise in the Bronx, New York, United States
2. New York Yankees (wd:Q979646): defunct American football team
3. New York Yankees (wd:Q1275088): American football team from 1946 to 1949
4. New York Yankees (wd:Q7014865): American football team in 1936
5. New York Yankees (wd:Q16845944): association football (soccer) team
6. New York Yankees (wd:Q7014868): American football team in 1940
7. New York Yankees Museum (wd:Q7014872): baseball museum in The Bronx
8. New York Black Yankees, also known as Black Yankees (wd:Q7013072): Negro League Baseball team active from 1931-1948; record: 243-462-19 (.345)
9. history of the New York Yankees, also known as New York Yankees history, the New York Yankees history (wd:Q5870090): Sports team history
10. Saratoga Harlem Yankees, also known as Glens Falls-Saratoga, New York Harlem Yankees, Schenectady Yankees (wd:Q7423363): defunct American basketball team

[Assistant] The correct entity for the New York Yankees is `wd:Q213417`. Now, let's find the property for the home venue.

[Tool]
Top 10 property alternatives:
1. home venue, also known as home water, venue, stadium, home ground, home field (wd:P115 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): home stadium or venue of a sports team or applicable performing arts organization, location
2. recorded at studio or venue, also known as venue, studio, recording venue, recording studio, recorded at event (wd:P483 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): studio or location where a musical composition/release was recorded, recording location
3. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
4. published in, also known as song on album, tome of the book, tome of, track of, track on (wd:P1433 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): larger work that a given work was published in, like a book, journal or music album, part of
5. distributed from, also known as distributed via, host, hosted at, web host, webhost (wd:P10754 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): place or location where a good or service is distributed from
6. residence, also known as living in, place of residence, resided at, resided in, resident in (wd:P551 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): the place where the person is or has been, resident, location
7. has facility, also known as has amenity, has feature, features, amenity, facility (wd:P912 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): the subject item has this type of facility, e.g. toilet, car park, has part(s) of the class
8. operating area, also known as province served, serves jurisdiction, serves geographic region, serves geographic area, serves area (wd:P2541 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): geographic area or jurisdiction an organisation or industry operates in, serves, or has responsibility for, location
9. work location, also known as work place, working from, working at, worked from, worked at (wd:P937 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): location where persons or organisations were actively participating in employment, business or other work, significant place, location
10. location of formation, also known as place of incorporation, originates from, place of establishment, place of formation, place of foundation (wd:P740 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): location where a group or organization was formed, location of creation

[Assistant]
The correct property for the home venue is `wdt:P115`. Now, let's construct the SPARQL query to find the home venue of the New York Yankees.

```sparql
SELECT ?stadium WHERE {
  wd:Q213417 wdt:P115 ?stadium .
}
```

I will now execute this query.

[Tool]
Got 1 row and 1 column:
| stadium                     |
| --------------------------- |
| Yankee Stadium (wd:Q753529) |

[Assistant]
The New York Yankees play in Yankee Stadium.

Here is the final SPARQL query:

```sparql
SELECT ?stadium WHERE {
  wd:Q213417 wdt:P115 ?stadium .
}
```

And the answer is: **Yankee Stadium**.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?country WHERE {
  wd:Q1771942 wdt:P159 ?headquarters .
  ?headquarters wdt:P131 * ?country .
  ?country wdt:P31 wd:Q6256
}

Got 1 row and 1 column:
| country                |
| ---------------------- |
| United States (wd:Q30) |

United States

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

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

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

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

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

[User] In which country did the United Fruit Company have their headquarters?

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

[Tool]
Example 1:
Question:
In which U.S. state is Fort Knox located?

SPARQL:
SELECT ?res WHERE {
  wd:Q983650 wdt:P131 + ?res .
  ?res wdt:P31 wd:Q35657 .
}

Using entities:
U.S. state, also known as U.S. states, US state, USA state, U.S.A. state, United States states (wd:Q35657): constituent political entity of the United States of America
Fort Knox, also known as Camp Henry Knox, Camp Henry Knox Army Reservation, Camp Knox, Camp Knox Military Reservation (wd:Q983650): United States Army post in Kentucky, United States

Using properties:
located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
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:
In which U.S. state is Area 51 located?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q177397 wdt:P131 ?obj .
  ?obj wdt:P131 ?uri .
}

Using entities:
Area 51, also known as Paradise Ranch, Groom Lake, Area 51 (hawkin I., Nevada Area 51, KXTA (wd:Q177397): classified U.S. Military Base situated in Groom Lake, Nevada

Using properties:
located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of

Example 3:
Question:
In which U.S. state is Mount McKinley located?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q130018 wdt:P131 ?uri
}

Using entities:
Denali, also known as Bolshaya Gora, Mount Denali, Mount McKinley, Mt. Denali, Mt. McKinley (wd:Q130018): highest mountain in North America, located in Alaska

Using properties:
located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of

[Assistant] Based on these examples, we need to find the entity for the United Fruit Company and then look for its headquarters location. Let's first search for the entity of the United Fruit Company.

[Tool]
Top 10 entity alternatives:
1. United Fruit Company (wd:Q1771942): American corporation
2. United Fruit Company Building (wd:Q79310992): historic building in Wellington, New Zealand
3. United Fruit Company Infrastructure (wd:Q65591387): Tentative World Heritage Site in Colombia
4. Kossick v. United Fruit Company (wd:Q19089122): United States Supreme Court case
5. United Fruit Company Medal (obverse) (wd:Q122934149): bronze medal-sample by Paul Manship
6. United Fruit Company Medal (reverse) (wd:Q122934151): bronze medal-sample by Paul Manship
7. American Banana Company v. United Fruit Company (wd:Q19037455)
8. United Fruit Company strike of 1913 (wd:Q105962401)
9. United States v. Fruit Growers' Express Company (wd:Q19030798): United States Supreme Court case
10. United Surety Company v. American Fruit Product Company (wd:Q19041555)

[Assistant] The correct entity for the United Fruit Company is `wd:Q1771942`. Now, let's find out where its headquarters were located. We will use the property `headquarters` (P159) to find this information.

[Tool]
Got 1 row and 1 column:
| headquarters            |
| ----------------------- |
| New Orleans (wd:Q34404) |

[Assistant]
The headquarters of the United Fruit Company was located in New Orleans. However, the question asks for the country where the headquarters was located. We need to find the country of New Orleans. We can use the property `located in the administrative territorial entity` (P131) to find the country.

Let's execute a query to find the country of New Orleans.

[Tool]
Got 1 row and 1 column:
| country                |
| ---------------------- |
| United States (wd:Q30) |

[Assistant]
The country where the United Fruit Company had its headquarters is the United States.

Here is the final SPARQL query:

```sparql
SELECT ?country WHERE {
  wd:Q1771942 wdt:P159 ?headquarters .
  ?headquarters wdt:P131* ?country .
  ?country wdt:P31 wd:Q6256
}
```

And the answer to the question is: **United States**.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ( COUNT( ?victim ) AS ?numberOfVictims ) WHERE {
  ?victim wdt:P157 wd:Q201377 .
}

Got 1 row and 1 column:
| numberOfVictims |
| --------------- |
| 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 people did Oscar Pistorius kill?

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

[Tool]
Example 1:
Question:
Who killed Caesar?

SPARQL:
SELECT DISTINCT ?o1 WHERE {
  wd:Q1048 wdt:P157 ?o1 .
}

Using entities:
Julius Caesar, also known as Divine Julius (wd:Q1048): Roman general and dictator (100 – 44 BC), ancient Roman military personnel, Ancient Roman politician, Ancient Roman historian, Ancient Roman priest, military leader, politician, historian, memoirist, writer, orator, ruler, poet

Using properties:
killed by, also known as slaughtered by, slain by, shot dead by, murderer, murdered by (wd:P157 as wdt): person or organization who killed the subject, significant person

[Assistant] Based on the example, we need to find the property that indicates the number of people killed by Oscar Pistorius. Let's first search for Oscar Pistorius in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Oscar Pistorius, also known as Oscar Leonard Carl Pistorius, Fastest man on no legs, Blade Runner (wd:Q201377): South African sprinter and convicted murderer (born 1986), athletics competitor, murderer
2. trial of Oscar Pistorius, also known as The State v Oscar Pistorius (wd:Q16328520): adjudication of murder and gun charges brought against athlete Oscar Pistorius in 2014
3. Oscar Pistorius: Blade Runner Killer (wd:Q55698496): 2017 television film
4. Oscar Pistorius, enhancement and post-humans. (wd:Q47375029): scientific article published in September 2008
5. Mechanics of Oscar Pistorius' running blades (wd:Q6804597): blades used by South African Paralympic runner Oscar Pistorius
6. Oscar Pistorius and the melancholy of intersectionality (wd:Q58274689)
7. O, also known as letter 15, o, O, Oscar (wd:Q9941): letter of the Latin alphabet
8. Oscar, also known as Oscar dos Santos Emboaba Junior, Oscar dos Santos Emboaba Júnior (wd:Q19497): Brazilian association football player (born 1991), association football player
9. Astronotus ocellatus, also known as marble cichlid, oscar, Oscar (fish), tiger oscar, velvet cichlid (wd:Q3442): species of fish from the cichlid family
10. Nakajima Ki-43 Hayabusa, also known as Oscar, Ki-43, Hayabusa, Army Zero, Army Type 1 Fighter (wd:Q700703): Japanese fighter aircraft

[Assistant] The correct entity for Oscar Pistorius is wd:Q201377. Now let's search for the property that indicates the number of people he killed. We can try searching for "killed" or "number of victims".

[Tool]
Top 10 property alternatives:
1. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as p/wdt): most specific known birth location of a person, animal or fictional character, location
2. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as p/wdt): date on which the subject was born, inception
3. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as p/wdt): work where this item is described, attested in
4. medical condition, also known as disability, suffers from, suffer from, sickness, paralympic disability (wd:P1050 as p/wdt): any state relevant to the health of an organism, including diseases and positive conditions
5. significant event, also known as significant occurrence, significant incident, significant achievment, sign. event, outcome (wd:P793 as p/wdt): significant or notable events associated with the subject
6. participant in, also known as participated in, present at, takes part, took part, took part in (wd:P1344 as p/wdt): event in which a person or organization was/is a participant; inverse of P710 or P1923, significant event, part of
7. educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as p/wdt): educational institution attended by subject, affiliation
8. NDL Authority ID, also known as NDLSH (NDL Subject Headings), NDLNA (NDL Name Authority), NDLNAId, NDL identifier, NDL ID (wd:P349 as wdtn/p/wdt): identifier for authority control per the National Diet Library of Japan
9. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as p/wdt): language(s) that a person or a people speaks, writes or signs, including the native language(s)
10. penalty, also known as judicial sentence, punishment, sentence (wd:P1596 as p/wdt): penalty imposed by an authority

No other items found

[Assistant] It seems that the property we're looking for is not directly listed. However, we can try using the property "significant event" (wd:P793) and see if it provides us with the information about the number of people killed. Let's execute a SPARQL query to check this.

[Tool]
Got 2 rows and 1 column:
| event                                   |
| --------------------------------------- |
| trial of Oscar Pistorius (wd:Q16328520) |
| shooting (wd:Q2252077)                  |

[Assistant] The significant events associated with Oscar Pistorius include his trial and a shooting. To find out how many people he killed, we need to look into the details of these events. Specifically, we need to find the property that indicates the number of victims or the number of people killed in the shooting event. Let's search for the property "number of victims" or "killed" for the shooting event.

[Tool]
Top 10 property alternatives:
1. 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
2. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as p/wdt): work where this item is described, attested in
3. practiced by, also known as proponent, studied by, practitioners, practioner, occupation of this field (wd:P3095 as p/wdt): type of agents that study this subject or work in this field
4. 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)

No other items found

[Assistant] It appears that the property "number of victims" or "killed" is not directly associated with the shooting event. However, we can try to find the number of victims by looking at the details of the shooting event. Let's execute a SPARQL query to see if there is any information about the number of victims in the shooting event.

[Tool] Got no rows and 1 columns

[Assistant]
It seems that the property `P157` (killed by) is not directly linked to the shooting event. Let's try another approach by looking at the trial of Oscar Pistorius to see if there is any information about the number of victims or the specific victim involved.

We can search for the property "victim" or "number of victims" for the trial of Oscar Pistorius.

[Tool]
Top 10 property alternatives:
1. defendant, also known as litigant, respondant, plaintiff in, accused (wd:P1591 as p/wdt): person or organization accused at a trial, object of occurrence, participant
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. court, also known as court (wd:P4884 as p/wdt): specific court a legal case is or was heard or decided in
4. point in time, also known as at time, as of, year, when, time of event (wd:P585 as p/wdt): date something took place, existed or a statement was true; for providing time use the "refine date" property (P4241)
5. 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
6. 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)
7. 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]
It seems that the property "victim" or "number of victims" is not directly associated with the trial of Oscar Pistorius either. However, we can try to find the specific victim of the shooting by looking at the details of the trial.

Let's execute a SPARQL query to find the defendant in the trial of Oscar Pistorius, which might give us a clue about the victim.

[Tool]
Got 1 row and 1 column:
| defendant                    |
| ---------------------------- |
| Oscar Pistorius (wd:Q201377) |

[Assistant]
The defendant in the trial of Oscar Pistorius is Oscar Pistorius himself, which confirms that he was the one on trial. However, this does not directly tell us about the victim or the number of victims.

Since the direct properties are not yielding the desired information, let's try a different approach. We can look for the specific victim of the shooting event by searching for the property "killed by" (wd:P157) and see if it links to any specific person.

Let's execute a SPARQL query to find the victim of the shooting event.

[Tool]
Got 1 row and 1 column:
| victim                        |
| ----------------------------- |
| Reeva Steenkamp (wd:Q4584302) |

[Assistant]
The victim of the shooting event involving Oscar Pistorius is Reeva Steenkamp (wd:Q4584302). This indicates that Oscar Pistorius killed one person.

To finalize the answer, we can use an ASK query to confirm that Oscar Pistorius killed exactly one person.

Here is the final SPARQL query:

```sparql
ASK {
  wd:Q201377 wdt:P157 ?victim .
  FILTER NOT EXISTS {
    ?otherVictim wdt:P157 wd:Q201377 .
    FILTER (?otherVictim != ?victim)
  }
}
```

This query checks if Oscar Pistorius (wd:Q201377) killed exactly one person by ensuring there is no other victim besides the one already identified.

Let's execute this query to confirm.

[Tool] False

[Assistant]
The ASK query returned `False`, which means that there is more than one victim associated with Oscar Pistorius. However, based on the previous query, we only found one victim, Reeva Steenkamp. This discrepancy suggests that the data might be incomplete or there might be other contexts where Oscar Pistorius is associated with killing someone else.

Given the information we have, the most accurate answer based on the available data is that Oscar Pistorius killed one person, Reeva Steenkamp.

Here is the final SPARQL query to confirm the number of victims:

```sparql
SELECT (COUNT(?victim) AS ?numberOfVictims)
WHERE {
  ?victim wdt:P157 wd:Q201377 .
}
```

This query counts the number of victims associated with Oscar Pistorius.

Let's execute this query to get the final count.

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

[Assistant]
The final SPARQL query confirms that Oscar Pistorius killed one person.

Here is the final SPARQL query and the answer:

```sparql
SELECT (COUNT(?victim) AS ?numberOfVictims)
WHERE {
  ?victim wdt:P157 wd:Q201377 .
}
```

The answer to the question "How many people did Oscar Pistorius kill?" is 1.

Let's provide the final answer using the `answer` function.

[Tool] Stopped generation process


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

[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 similar examples.

[Tool]
Example 1:
Question:
List all games by GMT.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 / wdt:P279 * wd:Q11410 ; wdt:P123 wd:Q928726 .
}

Using entities:
game, also known as games, plays and games, recreational game, recreational games (wd:Q11410): structured form of play
GMT Games (wd:Q928726): American board game publisher

Using properties:
publisher, also known as video game publisher, software publisher, comic book publisher, sheet music publisher, publishing house (wd:P123 as wdt): organization or person responsible for publishing books, periodicals, printed music, podcasts, games or software
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:
List all boardgames by GMT.

SPARQL:
SELECT ?uri WHERE {
  ?uri wdt:P31 wd:Q131436 .
}

Using entities:
board game, also known as boardgame (wd:Q131436): game that involves counters or pieces moved or placed on a pre-marked surface or "board", according to a set of rules

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

[Assistant] These examples don't directly help us with our specific question about the release year of "Dead by Daylight" and other video games released in the same year. However, we can infer that we need to look for the entity representing "Dead by Daylight" and the property for the release year of a video game. Let's start by searching 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 first result, "Dead by Daylight" (wd:Q24514682), is the correct entity for the video game. Next, let's find the property for the release year of a video game.

[Tool]
Top 10 property alternatives:
1. publication date, also known as launched, published, publication time, publication, pubdate (wd:P577 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): date or point in time when a work was first published or released, point in time
2. announcement date, also known as released, date teased, made public on, public announcement date, published (wd:P6949 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): time of the first public presentation of a subject by the creator, of information by the media, point in time
3. production date, also known as date of production, filming date, filming time, production date, year of production (wd:P2754 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): period of active production of (creative) work; the only date st... publication date (P577); in general cases, use inception (P571)
4. place of publication, also known as published in (place), where published, release region, released in, published from (wd:P291 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): geographical place of publication of the edition (use 1st edition when referring to works), significant place
5. date of commercialization, also known as availability date, commercialization date, product release date, release date (wd:P5204 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): date when a product was first commercialized
6. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): time when an entity begins to exist; for date of official opening use P1619, start time
7. point in time, also known as at time, as of, year, when, time of event (wd:P585 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): date something took place, existed or a statement was true; for providing time use the "refine date" property (P4241)
8. software version identifier, also known as software release number, software version number, software release version, software update identifier, software update number (wd:P348 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): numeric or nominal identifier of a version of a software program or file format, current or past, has edition or translation, edition number
9. date of first performance, also known as time of first performance, world premiere date, world premiere, premiere date, premiere (wd:P1191 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): date a work was first debuted, performed or live-broadcasted, publication date
10. release of, also known as music release of, release of music (wd:P9831 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): release group this release belongs to, edition or translation of, part of

[Assistant]
The property "publication date" (wd:P577) seems to be the most appropriate for the release year of a video game. Now, let's construct a simple SPARQL query to get the publication date of "Dead by Daylight" and then extend it to count other video games released in the same year.

First, let's get the publication date of "Dead by Daylight".

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

[Assistant]
The publication date of "Dead by Daylight" is June 14, 2016. Now, let's construct a query to count other video games that were released in the same year, 2016.

We'll need to identify the entity for "video game" and then use the publication date property to filter the results.

First, let's find the entity for "video game".

[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 entity "video game" (wd:Q7889) is the correct one. Now, let's construct the SPARQL query to count other video games that were released in the same year as "Dead by Daylight" (2016).

We'll use the `wdt:P577` property to filter the publication date and ensure it matches the year 2016. We'll also exclude "Dead by Daylight" itself from the count.

Here's the SPARQL query:

```sparql
SELECT (COUNT(?game) AS ?count)
WHERE {
  ?game wdt:P31 wd:Q7889 ;
        wdt:P577 ?date .
  FILTER(YEAR(?date) = 2016 && ?game != wd:Q24514682)
}
```

Let's execute this query.

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

[Assistant]
The query returned a count of 5007 other video games that began the same year as "Dead by Daylight" (2016).

Therefore, the answer to the question "How many other video games began the same year as Dead by Daylight?" is 5007.

Here is the final SPARQL query and answer:

```sparql
SELECT (COUNT(?game) AS ?count)
WHERE {
  ?game wdt:P31 wd:Q7889 ;
        wdt:P577 ?date .
  FILTER(YEAR(?date) = 2016 && ?game != wd:Q24514682)
}
```

Answer: 5007

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
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) |

Spouses of Nobel Prize in Literature winners hold 71 different occupations.

[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 similar examples.

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

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

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

Using properties:
occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as wdt): award or recognition received by a person, organization or creative work

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

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

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

Using properties:
occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as wdt): award or recognition received by a person, organization or creative work

Example 3:
Question:
Which poet wrote the most books?

SPARQL:
SELECT DISTINCT ?s1 ( COUNT( ?s2 ) as ?c ) WHERE {
  ?s1 wdt:P106 wd:Q49757 .
  ?s2 wdt:P50 ?s1 .
  ?s2 wdt:P31 wd:Q571 .
}
GROUP BY ?s1
ORDER BY DESC ( COUNT( ?s2 ) )
OFFSET 0
LIMIT 1

Using entities:
poet, also known as bard, poetry writer, poetry author, poetess (wd:Q49757): person who writes poetry
book, also known as books (wd:Q571): medium for recording information (words or images) typically on bound pages or more abstractly in electronic or audio form

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)
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)
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

[Assistant] From the examples, we can see that the Nobel Prize in Literature (wd:Q37922) and the property "award received" (wdt:P166) are relevant to our question. We also need to find the property for "spouse" and the property for "occupation". Let's search for these properties.

[Tool]
Top 10 property alternatives:
1. spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): 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 pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): 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 pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): 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 pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): 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 pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): 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 pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): 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 pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): 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 pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): 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 pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): 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 pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): 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" (wdt:P26) is the correct one for our query. Now let's search for the property "occupation".

[Tool]
Top 10 property alternatives:
1. occupation, also known as job, work, vocation, profession, employment (wd:P106 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): 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 pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): 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 pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): 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 pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): 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 pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): 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 pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): 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 pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): 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 pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): 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 pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): 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 pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): location where persons or organisations were actively participating in employment, business or other work, significant place, location

[Assistant] The property "occupation" (wdt:P106) is the correct one for our query. Now we have all the necessary elements to construct the SPARQL query. We will first select the Nobel Prize in Literature winners, then their spouses, and finally count the distinct occupations of those spouses. Let's write the query and execute it.

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

[Assistant]
The SPARQL query has returned the number of distinct occupations held by the spouses of Nobel Prize in Literature winners. There are 71 different occupations.

I will now provide the final answer using the `answer` function.

[Tool] Stopped generation process