PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
ASK WHERE {
  wd:Q183 wdt:P2046 ?germanyArea .
  wd:Q36 wdt:P2046 ?polandArea .
  FILTER ( ?germanyArea > ?polandArea )
}

True

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

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

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

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

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

[User] Is Germany bigger than Poland?

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

[Tool]
Example 1:
Question:
What is the alma mater of the chancellor of Germany Angela Merkel?

SPARQL:
SELECT ?res WHERE {
  wd:Q567 wdt:P69 ?res .
  ?res wdt:P31 / wdt:P279 * wd:Q3918 .
}

Using entities:
university, also known as uni, universities (wd:Q3918): academic institution for further education
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:
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)
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:
In which films directed by Garry Marshall was Julia Roberts starring?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q11424 .
  ?uri wdt:P57 wd:Q315087 .
  ?uri wdt:P161 wd:Q40523 .
}

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
Garry Marshall, also known as Garry K. Marshall, Garry Kent Marshall (wd:Q315087): American actor and filmmaker (1934–2016), television producer, television actor, film producer, film director, screenwriter, voice actor, director, comedian, writer, actor
Julia Roberts, also known as Julia Fiona Roberts (wd:Q40523): American actress (born 1967), television actor, film producer, voice actor, stage actor, film actor, actor, model

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)
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:
List all the musicals with music by Leonard Bernstein.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q2743 ; wdt:P86 wd:Q152505 .
}

Using entities:
Leonard Bernstein (wd:Q152505): American conductor and composer (1918–1990), film score composer, musicologist, conductor, composer, pianist
musical, also known as musical play, stage musical, musical theatre, musical theater, lyric drama (wd:Q2743): stage work that combines songs, music, spoken dialogue, acting, and dance

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)
composer, also known as music by, written by, songwriter, musical score by, film score by (wd:P86 as wdt): person(s) who wrote the music [for lyricist, use "lyrics by" (P676)], creator

[Assistant] To answer the question "Is Germany bigger than Poland?", we need to compare the area of Germany and Poland. Let's first find the entities for Germany and Poland.

[Tool]
Top 10 entity alternatives:
1. Germany, also known as BR Deutschland, Bundesrepublik Deutschland, Deutschland, Federal Republic of Germany (wd:Q183): country in Central Europe
2. Weimar Republic, also known as German Republic, Weimar Germany, Republic of Germany, Germany, German Reich (wd:Q41304): Germany in the years 1918/1919–1933
3. German Reich, also known as Deutsches Reich, German Empire, German Realm, Germany, Imperial Germany (wd:Q1206012): official name for the German nation state from 1871 to 1945, and name of Germany until 1949
4. Burg Drachenfels, also known as Germany (wd:Q1011486): castle
5. Germany (wd:Q5552078): European Parliament constituency
6. Geilenkirchen-Heinsberg, also known as Germany (wd:Q2268218)
7. Germany, also known as Germany, IN, Germany, Indiana (wd:Q18151573): unincorporated community in Clark County, Indiana
8. Germany (wd:Q19147844): poem by Vladimir Mayakovsky
9. Germany, also known as Ludwig, West (wd:Q3839160): Hetalia character
10. Germany, also known as Germany, Texas, Germany, TX (wd:Q15221573): unincorporated community in Houston County, Texas, United States

[Assistant] The correct entity for Germany is `wd:Q183`. Now let's find the entity for Poland.

[Tool]
Top 10 entity alternatives:
1. Poland, also known as Republic of Poland (wd:Q36): country in Central Europe
2. Polish–Lithuanian Commonwealth, also known as Commonwealth of Poland, First Republic of Poland, Poland, Poland-Lithuania, Poland–Lithuania (wd:Q172107): historical multinational monarchist state in Central Europe (Crown of the Kingdom of Poland and the Grand Duchy of Lithuania)
3. Crown of the Kingdom of Poland, also known as Kingdom of Poland, Poland (wd:Q171348): 1385–1795 territorial possessions of the King of Poland
4. Poland, also known as Poland, OH, Poland, Ohio (wd:Q2300093): village in Ohio, United States
5. Poland, also known as Poland, Maine, Poland, ME (wd:Q1572109): town in Androscoggin County, Maine, United States
6. Polish, also known as Poland (wd:Q385059): breed of chicken
7. Poland, also known as Boran (wd:Q5763870): village in Kiribati
8. Poland, also known as Poland, Chautauqua County, New York, Poland, New York, Poland, NY (wd:Q7208883): town in Chautauqua County, New York, United States
9. Poland, also known as Poland, Herkimer County, New York, Poland, NY (wd:Q7208887): village in Herkimer County, New York, United States
10. Poland - The Warsaw Concert, also known as Poland (wd:Q599300): album by Tangerine Dream

[Assistant] The correct entity for Poland is `wd:Q36`. Next, we need to find the property for the area of a country.

[Tool]
Top 10 property alternatives:
1. area, also known as total area, surface area, surface, size, resolution (wd:P2046 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): area occupied by an object
2. 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
3. applies to part, also known as when viewed as, valid for part, section, region, per (wd:P518 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): part, aspect, or form of the item to which the claim applies
4. applies to jurisdiction, also known as belongs to jurisdiction, applies to territorial jurisdiction, applies to region, applies to place, applies to geographic place (wd:P1001 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): the item (institution, law, public office, public register...) o...a territorial jurisdiction: a country, state, municipality, ...), significant place, characteristic of, operating area
5. operating area, also known as province served, serves jurisdiction, serves geographic region, serves geographic area, serves area (wd:P2541 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): geographic area or jurisdiction an organisation or industry operates in, serves, or has responsibility for, location
6. water area (wd:P8887 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): area/surface of a geographical entity that is covered by water, area
7. interested in, also known as area of interest, area of research, field of interest, field of research, field of study (wd:P2650 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): item of special or vested interest to this person or organisation
8. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
9. 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 prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
10. electoral district, also known as riding, seat, ward, electoral area, electorate (wd:P768 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): electoral district this person is representing, or of the office... or "office contested" (P541) or "candidacy in election" (P3602)

[Assistant] The correct property for the area of a country is `wd:P2046`. Now we can construct a SPARQL query to compare the areas of Germany and Poland.

[Tool]
Got 1 row and 2 columns:
| germanyArea          | polandArea           |
| -------------------- | -------------------- |
| 357588 (xsd:decimal) | 312683 (xsd:decimal) |

[Assistant]
The area of Germany is 357,588 square kilometers, and the area of Poland is 312,683 square kilometers. Therefore, Germany is indeed bigger than Poland.

Now, let's confirm this with an ASK query.

[Tool] True

[Assistant]
The ASK query confirms that Germany is indeed bigger than Poland.

Therefore, the answer to the question "Is Germany bigger than Poland?" is **True**.

[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 {
  wd:Q7245 wdt:P106 ?occupation .
}

Got 1 row and 1 column:
| count        |
| ------------ |
| 12 (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 occupations did Mark Twain have?

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

[Tool]
Example 1:
Question:
What languages are spoken in Pakistan?

SPARQL:
SELECT * {
  wd:Q843 wdt:P2936 ?uri .
}

Using entities:
Pakistan, also known as Islamic Republic of Pakistan, PAK, pk, Republic of Pakistan (wd:Q843): sovereign state in South Asia

Using properties:
language used, also known as languages used, medium of instruction, used language, uses language, working language (wd:P2936 as wdt): language widely used (spoken or written) in this place or at this event or organisation

Example 2:
Question:
Who wrote the book Les Piliers de la terre?

SPARQL:
SELECT DISTINCT ?res WHERE {
  wd:Q1163227 wdt:P50 ?res .
}

Using entities:
The Pillars of the Earth, also known as The Pillars of the Earth (Kingsbridge, #1) (wd:Q1163227): 1989 novel by Ken Follett

Using properties:
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:
Who is the governor of Texas?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q1439 wdt:P1313 wd:Q5589725 .
  wd:Q5589725 wdt:P1308 ?uri .
}

Using entities:
Texas, also known as Lone Star State, US-TX, TX, Texas, United States, Tex. (wd:Q1439): state of the United States of America
Governor of Texas, also known as Governor of the State of Texas, Texas Governor (wd:Q5589725): head of state and of government of the U.S. state of Texas

Using properties:
position holder, also known as incumbent, noble title holder, office holder, position held by (wd:P1308 as wdt): persons who hold and/or held the position
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 wdt): political office that is fulfilled by the head of the government of this item

[Assistant] Based on the examples, we need to identify the entity for Mark Twain and the property for occupation. Let's start by searching for the entity "Mark Twain".

[Tool]
Top 10 entity alternatives:
1. Mark Twain, also known as Samuel L. Clemens, Samuel Langhorne Clemens, Quintus Curtius Snodgrass, Samuel Clemens (wd:Q7245): American author and humorist (1835–1910), science fiction writer, opinion journalist, children's writer, autobiographer, travel writer, prose writer, journalist, humorist, novelist, aphorist, teacher, writer
2. 2362 Mark Twain, also known as Mark Twain (wd:Q959983): asteroid
3. Mark Twain (wd:Q6770075): crater on Mercury
4. Mark Twain (wd:Q6770076): 2001 documentary film on the life of Mark Twain directed by Ken Burns
5. Mark Twain (wd:Q66716403): 1873 article in Cartoon portraits and biographical sketches of men of the day
6. Mark Twain, also known as Mark Twain, St. Louis (wd:Q6770071): neighborhood of St. Louis, Missouri, United States
7. Rosa 'Mark Twain', also known as Mark Twain (wd:Q83668756): rose cultivar
8. Mark Twain (wd:Q116958637): bronze sculpture by unidentified artist
9. Mark Twain (wd:Q20174185): painting by Charles Noel Flagg
10. Mark Twain (wd:Q79493007): print by Samuel Johnson Woolf (American, 1880-1948) (1920.11)

[Assistant] The correct entity for Mark Twain is the first one, "Mark Twain, also known as Samuel L. Clemens, Samuel Langhorne Clemens, Quintus Curtius Snodgrass, Samuel Clemens (wd:Q7245)". Now let's find the property for occupation. We can search for it directly or look at the properties of the Mark Twain entity. I'll try searching for the property "occupation" first.

[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 correct property for occupation is "occupation, also known as job, work, vocation, profession, employment (wd:P106 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv)". Now we can construct a simple SPARQL query to count the number of distinct occupations that Mark Twain had.

Let's run the query:

```sparql
SELECT (COUNT(DISTINCT ?occupation) AS ?count)
WHERE {
  wd:Q7245 wdt:P106 ?occupation .
}
```

This query selects the count of distinct occupations associated with Mark Twain (wd:Q7245) through the property wdt:P106.

Let's execute this query.

[Tool]
Got 1 row and 1 column:
| count        |
| ------------ |
| 12 (xsd:int) |

[Assistant]
The SPARQL query has returned that Mark Twain had 12 distinct occupations.

Therefore, the answer to the question "How many occupations did Mark Twain have?" is 12.

Here is the final SPARQL query and answer:

```sparql
SELECT (COUNT(DISTINCT ?occupation) AS ?count)
WHERE {
  wd:Q7245 wdt:P106 ?occupation .
}
```

Answer: 12

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?birthPlace WHERE {
  wd:Q183883 wdt:P50 ?author .
  ?author wdt:P19 ?birthPlace .
}

Got 1 row and 1 column:
| birthPlace             |
| ---------------------- |
| New York City (wd:Q60) |

New York City (wd:Q60)

[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] Where was the author of The Catcher in the Rye born ?

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

[Tool]
Example 1:
Question:
how big is the total area of North Rhine- Westphalia?

SPARQL:
SELECT DISTINCT ?val WHERE {
  wd:Q1198 wdt:P2046 ?val .
}

Using entities:
North Rhine-Westphalia, also known as Nordrhein-Westfalen, NRW (wd:Q1198): state in Germany

Using properties:
area, also known as total area, surface area, surface, size, resolution (wd:P2046 as wdt): area occupied by an object

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

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

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

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

Example 3:
Question:
In which films did Julia Roberts as well as Richard Gere play?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q11424 .
  ?uri wdt:P161 wd:Q48410 .
  ?uri wdt:P161 wd:Q40523 .
}

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
Julia Roberts, also known as Julia Fiona Roberts (wd:Q40523): American actress (born 1967), television actor, film producer, voice actor, stage actor, film actor, actor, model
Richard Gere, also known as Richard Tiffany Gere (wd:Q48410): American actor (born 1949), human rights activist, television actor, film director, film producer, photographer, voice actor, 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)

[Assistant] Based on the examples, we need to identify the author of "The Catcher in the Rye" and then find where they were born. Let's first search for the book "The Catcher in the Rye".

[Tool]
Top 10 entity alternatives:
1. The Catcher in the Rye, also known as Catcher in the Rye (wd:Q183883): 1951 novel by J. D. Salinger
2. Catcher in the Rye (wd:Q5051738): Chinese punk rock band
3. Catcher In the Rye (wd:Q16184712): 2011 EP by Datarock
4. Catcher in the Rye (wd:Q110065569): 2021 single by Ross Jennings
5. Catcher in the Rye (wd:Q10443835): song by Guns N' Roses
6. The Catcher in the Rye (wd:Q16689546): 2012 debut studio album by Ann
7. The Catcher in the Rye (wd:Q125291968): 2001 Back Bay edition
8. Catchers in the rye (wd:Q68693473): scientific article published on 01 January 1990
9. The Catcher in the Rye in popular culture (wd:Q7721703): Influence of J.D. Salinger's 1951 novel
10. The Catcher in the Rye in popular culture (wd:Q7721703): Influence of J.D. Salinger's 1951 novel

[Assistant] The correct entity for "The Catcher in the Rye" is the first one, which is `wd:Q183883`. Now let's find out who the author of this book is.

[Tool]
Got 1 row and 3 columns:
| subject                             | property         | object                     |
| ----------------------------------- | ---------------- | -------------------------- |
| The Catcher in the Rye (wd:Q183883) | author (wdt:P50) | J. D. Salinger (wd:Q79904) |

[Assistant] The author of "The Catcher in the Rye" is J. D. Salinger, represented by the entity `wd:Q79904`. Next, we need to find where J. D. Salinger was born. We will look for the property "place of birth" for this entity.

[Tool]
Got 1 row and 3 columns:
| subject                    | property                 | object                 |
| -------------------------- | ------------------------ | ---------------------- |
| J. D. Salinger (wd:Q79904) | place of birth (wdt:P19) | New York City (wd:Q60) |

[Assistant]
J. D. Salinger was born in New York City, represented by the entity `wd:Q60`.

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

```sparql
SELECT ?birthPlace WHERE {
  wd:Q183883 wdt:P50 ?author .
  ?author wdt:P19 ?birthPlace .
}
```

This query will return the birthplace of the author of "The Catcher in the Rye".

Let's execute this query to confirm the result.

[Tool]
Got 1 row and 1 column:
| birthPlace             |
| ---------------------- |
| New York City (wd:Q60) |

[Assistant]
The SPARQL query confirms that the author of "The Catcher in the Rye," J. D. Salinger, was born in New York City.

Here is the final SPARQL query and the answer:

```sparql
SELECT ?birthPlace WHERE {
  wd:Q183883 wdt:P50 ?author .
  ?author wdt:P19 ?birthPlace .
}
```

Answer: New York City (wd:Q60)

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
ASK WHERE {
  wd:Q213849 wdt:P576 ?dissolvedDate .
}

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] Does the ATI Company still exist?

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

[Tool]
Example 1:
Question:
Where was JFK assassinated?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q9696 wdt:P20 ?uri .
}

Using entities:
John F. Kennedy, also known as John Kennedy, John Fitzgerald Kennedy, John F Kennedy, Kennedy, President Kennedy (wd:Q9696): President of the United States from 1961 to 1963, anti-communist, naval officer, statesperson, journalist, politician, writer

Using properties:
place of death, also known as POD, location of death, killed in, deathplace, died in (wd:P20 as wdt): most specific known (e.g. city instead of country, or hospital i... city) death location of a person, animal or fictional character, location

Example 2:
Question:
Who wrote The Hunger Games?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q11679 wdt:P50 ?uri .
}

Using entities:
The Hunger Games, also known as Hunger Games Saga, The Hunger Games Saga (wd:Q11679): three books by Suzanne Collins (2008–2010)

Using properties:
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 Australian nonprofit organizations.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q163740 .
  {
    ?uri wdt:P159 | wdt:P17 wd:Q408 .
  } UNION {
    ?uri wdt:P159 | wdt:P17 ?city .
    ?city wdt:P159 wd:Q408
  }
}

Using entities:
nonprofit organization, also known as Organizations, Nonprofit, np organization, NPO, NPI, not-for-profit organization (wd:Q163740): organization operated for a collective benefit
Australia, also known as AU, The Commonwealth of Australia, Stria, Straya, Stralia (wd:Q408): country in Oceania

Using properties:
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
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
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 identify the entity for ATI Company and then check if it has a property indicating its current status or dissolution date. Let's first search for the entity "ATI Company".

[Tool]
Top 10 entity alternatives:
1. company, also known as co., firm (wd:Q783794): legal entity representing an association of people, whether natural, legal or a mixture of both, with a specific objective
2. company, also known as company (military unit), military company (wd:Q102538): military unit size designation
3. enterprise, also known as business enterprise, firm, company (wd:Q6881511): organizational unit producing goods or services, which benefits ...n-making, especially for the allocation of its current resources
4. Ati (wd:Q755791): city
5. Aashaadha, also known as Ashadha, Āṭi (wd:Q1105198): month in Hindu calender
6. Artigas Airport, also known as ATI, SUAG (wd:Q1430852): airport
7. Company (wd:Q225093): 2002 film directed by Ram Gopal Varma
8. Company (wd:Q2915810): 1970 musical comedy by Stephen Sondheim
9. Company (wd:Q23723998): 2016 single by Justin Bieber
10. Ati, also known as Ati language, Ati (Philippines) (wd:Q3217458): Malayo-Polynesian language spoken and native to the Ati people of Panay

[Assistant] None of these results seem to match the ATI Company we are looking for. Let's try a more specific search with "ATI Technologies" since that is the full name of the company.

[Tool]
Top 10 entity alternatives:
1. ATI Technologies, also known as Array Technologies Incorporated (wd:Q213849): Canadian technology corporation
2. Atipa Technologies (wd:Q67904906): American hardware manufacturer
3. technology, also known as technologies, technological sciences, technicology, tech, technological science (wd:Q11016): making, modification, usage, and knowledge of tools, machines, t... and methods of organization, or tools and techniques so created
4. Ati (wd:Q755791): city
5. Aashaadha, also known as Ashadha, Āṭi (wd:Q1105198): month in Hindu calender
6. Artigas Airport, also known as ATI, SUAG (wd:Q1430852): airport
7. Ati, also known as Ati language, Ati (Philippines) (wd:Q3217458): Malayo-Polynesian language spoken and native to the Ati people of Panay
8. The Alan Turing Institute, also known as Turing Institute, turing.ac.uk, ATI (wd:Q16826821): research institute in Britain
9. Boneh-ye Ati, also known as Boneh-ye ‘Āţī, ‘Āţī (wd:Q4941616): village in Iran
10. Allegheny Technologies, also known as Allegheny Technologies Incorporated, ATI, ATI Metals (wd:Q1361648): company

[Assistant]
The top result, "ATI Technologies" (wd:Q213849), seems to be the correct entity. Now, let's check if this entity has any properties that indicate its current status or dissolution date. We can look for properties such as "dissolved" or "status."

Let's search for properties related to "dissolved" or "status" for this entity.

[Tool]
Top 10 property alternatives:
1. dissolved, abolished or demolished date, also known as ended, publication end date, final issue, date repealed, final year (wd:P576 as p/wdt): point in time at which the subject (organisation, building) ceas...g equipment,  "discontinued date" (P2669) for stopping a product, end time
2. replaced by, also known as heir, superseded by, successor, succeeded by, next job holder (wd:P1366 as p/wdt): other person or item which continues the item by replacing it in... nor identical, but adds to the series (e.g. books in a series)., followed by
3. total revenue, also known as turnover, sales, revenue, income, gross revenue (wd:P2139 as p/wdt): income gained by an organization during a given time frame. Not to be confused with fiscal revenue
4. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as p/wdt): time when an entity begins to exist; for date of official opening use P1619, start time
5. different from, also known as not to be confused with, to be distinguished from, similar to, see also, rejected match (wd:P1889 as p/wdt): item that is different from another item, with which it may be confused
6. owned by, also known as belongs to, stockholders, stockholder, shareholders, shareholder (wd:P127 as p/wdt): owner of the subject

No other items found

[Assistant]
The property "dissolved, abolished or demolished date" (wd:P576) is relevant. Let's check if ATI Technologies has a value for this property.

We will run a SPARQL query to check if ATI Technologies has a dissolved date.

[Tool]
Got 1 row and 1 column:
| dissolvedDate                       |
| ----------------------------------- |
| 2011-01-01T00:00:00Z (xsd:dateTime) |

[Assistant]
The SPARQL query returned a dissolved date for ATI Technologies, which is January 1, 2011. This indicates that the company no longer exists as an independent entity.

Therefore, the answer to the question "Does the ATI Company still exist?" is **False**.

Here is the final SPARQL query and answer:

[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 ?instrument ?instrumentLabel WHERE {
  wd:Q1779 wdt:P1303 ?instrument .
  OPTIONAL {
    ?instrument rdfs:label ?instrumentLabel .
    FILTER ( LANG( ?instrumentLabel ) = "en" )
  }
}

Got 3 rows and 2 columns:
| instrument           | instrumentLabel |
| -------------------- | --------------- |
| voice (wd:Q17172850) | voice (en)      |
| cornet (wd:Q202027)  | cornet (en)     |
| trumpet (wd:Q8338)   | trumpet (en)    |

Louis Armstrong played the following instruments: voice, cornet, and trumpet.

[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 instruments did Louis Armstrong play?

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

[Tool]
Example 1:
Question:
Which ingredients do I need for carrot cake?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q656071 wdt:P527 ?uri .
}

Using entities:
carrot cake (wd:Q656071): sweet cake that contains grated carrots as an ingredient

Using properties:
has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as wdt): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).

Example 2:
Question:
Who is the founder of Penguin Books?

SPARQL:
SELECT ?o1 WHERE {
  wd:Q1336200 wdt:P112 ?o1 .
}

Using entities:
Penguin Books, also known as Penguin Books, Limited (wd:Q1336200): British publishing house

Using properties:
founded by, also known as starter, co-founded by, started by, institutor, instituted by (wd:P112 as wdt): founder or co-founder of this organization, religion, place or entity, creator

Example 3:
Question:
Which countries have places with more than two caves?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?cave wdt:P31 wd:Q35509 ; wdt:P17 ?uri .
}
GROUP BY ?uri
HAVING ( COUNT( ?cave ) > 2 )

Using entities:
cave, also known as cavern (wd:Q35509): natural void under the Earth's surface

Using properties:
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
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 can see that to answer the question about the instruments played by Louis Armstrong, we need to identify the entity for Louis Armstrong and the property that indicates the instruments he played. Let's start by searching for the entity representing Louis Armstrong in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Louis Armstrong, also known as Satchelmouth, Satch, Satchmo, Louis Daniel Armstrong, Dipper (wd:Q1779): American jazz musician, trumpeter and singer (1901–1971), film score composer, radio personality, recording artist, jazz musician, street artist, film actor, songwriter, bandleader, trumpeter, conductor, writer, singer, actor
2. Louis Armstrong (wd:Q98823980): photograph by Lisette Model (MET, 2019.33)
3. Louis Armstrong (wd:Q132754304): online exhibition from Louis Armstrong House and Archives, Queens College, City University of New York
4. Louis Armstrong (wd:Q100721665): college basketball player (1991–1992) Northern Iowa, basketball player
5. Louis Armstrong Stadium (wd:Q1029132): tennis venue in New York City from 1978 to 2016
6. Louis Armstrong Park (wd:Q931042): park in New Orleans, Louisiana, U.S.
7. Louis Armstrong House, also known as Louis Armstrong House Museum (wd:Q6686652): NY location listed on National Register of Historic Places
8. Louise Armstrong (wd:Q6688616): American writer and feminist, human rights activist, children's writer, writer
9. Louis Armstrong Stadium (wd:Q47487977): tennis stadium opened in 2018, replacing a 1978 venue of the same name
10. Louis Armstrong Jazzfesztivál (wd:Q65218436)

[Assistant] The top result is the entity for Louis Armstrong, the American jazz musician. Now, let's find the property that indicates the instruments he played. We can search for properties related to "instruments" or "played" for this entity.

[Tool]
Top 10 property alternatives:
1. instrument, also known as uses this instrument, teaches instrument, instruments, plays this instrument, plays instrument (wd:P1303 as p/wdt): musical instrument that a person plays or teaches or used in a music occupation, uses
2. member of, also known as band member of, membership, member of musical group, in musical group, be member of (wd:P463 as p/wdt): 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. 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
4. discography, also known as discography link, recording catalog (wd:P358 as p/wdt): item for list pages with discography of artist or band, list of works
5. has works in the collection, also known as has items in the collection, works in collection, work in collection, museum housing this person's work, items in the collection (wd:P6379 as p/wdt): collection that has works of this person or organisation (use archives at [P485] for archives)
6. 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)
7. All About Jazz musician ID, also known as Allaboutjazz artist ID, Allaboutjazz musician ID (wd:P5121 as p/wdt): identifier for a musician or musical group at All About Jazz website
8. Rate Your Music artist ID, also known as RateYourMusic artist ID, Rate Your Music artist identifier, RYM artist ID, RYM artist identifier (wd:P5404 as p/wdt): identifier for an artist or group on the website Rate Your Music
9. voice type, also known as range of voice, register, tessitura, type of voice, vocal type (wd:P412 as p/wdt): person's voice type. expected values: soprano, mezzo-soprano, contralto, countertenor, tenor, baritone, bass (and derivatives)
10. AllMusic artist ID, also known as AllMusic, AllMusic ID, amg artist (wd:P1728 as p/wdt): identifier for an artist, musical group, or record label in the AllMusic database (record labels are listed as "artists")

No other items found

[Assistant]
The property `instrument` (P1303) seems to be the most relevant for indicating the instruments that Louis Armstrong played. Let's construct a SPARQL query to retrieve the instruments associated with Louis Armstrong using this property.

Here is the initial SPARQL query:

```sparql
SELECT ?instrument WHERE {
  wd:Q1779 wdt:P1303 ?instrument .
}
```

I will now execute this query to see the results.

[Tool]
Got 3 rows and 1 column:
| instrument           |
| -------------------- |
| voice (wd:Q17172850) |
| cornet (wd:Q202027)  |
| trumpet (wd:Q8338)   |

[Assistant]
The query returned the instruments that Louis Armstrong played, which include his voice, cornet, and trumpet. To provide a more complete answer, I will also include the labels of these instruments in the query. However, I will ensure that the labels are optional to avoid excluding any results if labels are not available.

Here is the refined SPARQL query:

```sparql
SELECT ?instrument ?instrumentLabel WHERE {
  wd:Q1779 wdt:P1303 ?instrument .
  OPTIONAL { ?instrument rdfs:label ?instrumentLabel . }
}
```

I will now execute this query to see the results with labels.

[Tool]
Got 297 rows and 2 columns, showing the first 5 and last 5 rows below:
| instrument           | instrumentLabel |
| -------------------- | --------------- |
| voice (wd:Q17172850) | ahots (eu)      |
| voice (wd:Q17172850) | a̱nwuat (kcg)   |
| voice (wd:Q17172850) | balsas (lt)     |
| voice (wd:Q17172850) | bos (pap)       |
| voice (wd:Q17172850) | boses (tl)      |
| ...                  | ...             |
| trumpet (wd:Q8338)   | 小号 (zh-hans)    |
| trumpet (wd:Q8338)   | 小號 (yue)        |
| trumpet (wd:Q8338)   | 小號 (zh)         |
| trumpet (wd:Q8338)   | 小號 (zh-hant)    |
| trumpet (wd:Q8338)   | 小號 (zh-tw)      |

[Assistant]
It appears that the query returned multiple labels for each instrument in different languages. To simplify the results and provide a more concise answer, I will filter the labels to only include English labels. Here is the updated SPARQL query:

```sparql
SELECT ?instrument ?instrumentLabel WHERE {
  wd:Q1779 wdt:P1303 ?instrument .
  OPTIONAL { ?instrument rdfs:label ?instrumentLabel . FILTER(LANG(?instrumentLabel) = "en") }
}
```

I will now execute this query to see the results with English labels.

[Tool]
Got 3 rows and 2 columns:
| instrument           | instrumentLabel |
| -------------------- | --------------- |
| voice (wd:Q17172850) | voice (en)      |
| cornet (wd:Q202027)  | cornet (en)     |
| trumpet (wd:Q8338)   | trumpet (en)    |

[Assistant]
The query has successfully returned the instruments that Louis Armstrong played, along with their English labels. The instruments are:

- Voice
- Cornet
- Trumpet

Now, I will provide the final SPARQL query and the answer to the user's question.

Final SPARQL query:
```sparql
SELECT ?instrument ?instrumentLabel WHERE {
  wd:Q1779 wdt:P1303 ?instrument .
  OPTIONAL { ?instrument rdfs:label ?instrumentLabel . FILTER(LANG(?instrumentLabel) = "en") }
}
```

Answer:
Louis Armstrong played the following instruments: voice, cornet, and trumpet.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( ?item ) AS ?count ) WHERE {
  ?item wdt:P31 wd:Q179651 .
}

Got 1 row and 1 column:
| count        |
| ------------ |
| 22 (xsd:int) |

There are 22 musical scales.

[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 musical scales are there?

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

[Tool]
Example 1:
Question:
How many awards has Bertrand Russell?

SPARQL:
SELECT ( COUNT( DISTINCT ?o1 ) as ?count ) WHERE {
  wd:Q33760 wdt:P166 ?o1 .
}

Using entities:
Bertrand Russell, also known as Bertrand Russell, Earl Russell, Bertrand Russell, 3rd Earl Russell, Russell, Bertrand Arthur William Russell, Bertrand Arthur William Russell, 3rd Earl Russell (wd:Q33760): British philosopher and logician (1872–1970), philosopher of language, science fiction writer, philosopher of science, analytic philosopher, university teacher, political activist, peace activist, autobiographer, epistemologist, social critic, mathematician, metaphysician, philosopher, journalist, politician, essayist, logician, writer

Using properties:
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:
Who produced films starring Natalie Portman?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?film wdt:P31 wd:Q11424 .
  ?film wdt:P161 wd:Q37876 .
  ?film wdt:P162 ?uri .
}

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
Natalie Portman, also known as Natalie Hershlag, Neta-Lee Herschlag, Natalie Herschlag, Nat (wd:Q37876): Israeli-American actress, television actor, film director, 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
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]
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:
Where did Abraham Lincoln die?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q91 wdt:P20 ?uri
}

Using entities:
Abraham Lincoln, also known as President Lincoln, Uncle Abe, Honest Abe, Abe Lincoln (wd:Q91): president of the United States from 1861 to 1865, military officer, statesperson, postmaster, politician, farmer, writer, lawyer

Using properties:
place of death, also known as POD, location of death, killed in, deathplace, died in (wd:P20 as wdt): most specific known (e.g. city instead of country, or hospital i... city) death location of a person, animal or fictional character, location

[Assistant] Based on the examples, we can see that to count something, we can use the COUNT function in SPARQL. We need to find the entity for "musical scale" and then count the number of instances of this entity.

[Tool]
Top 10 entity alternatives:
1. scale, also known as gamut, musical scale (wd:Q179651): set of musical notes ordered by pitch
2. musical scale (wd:L490906-S1)
3. Japanese musical scale (wd:Q1683319): Scales used in Japanese traditional music
4. minor scale; musical scale (wd:L739761-S2)
5. A Perfect Musical Scale (wd:Q60136008): scientific article published in Nature
6. Synthetic Musical Scales (wd:Q58123356)
7. type of musical scale (wd:L640378-S8)
8. MUSICAL INTELLIGENCE AND SCALE PREFERENCE. (wd:Q30335517): scientific article
9. sixth note in musical scale (wd:L739149-S1)
10. sixth note of musical scale (wd:L1405299-S1)

[Assistant] The first result, "scale" (wd:Q179651), seems to be the correct entity for "musical scale". Now let's write a SPARQL query to count the number of instances of this entity.

[Tool]
Got 1 row and 1 column:
| count        |
| ------------ |
| 22 (xsd:int) |

[Assistant] The SPARQL query returned a count of 22. Therefore, there are 22 musical scales according to the data in Wikidata.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?gender WHERE {
  wd:Q1983102 wdt:P21 ?gender
}

The binary gender of the partner of Allen Ginsberg is male.

[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 is the binary gender of the partner of Allen Ginsberg ?

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

[Tool]
Example 1:
Question:
How many airlines are there?

SPARQL:
SELECT ( COUNT( DISTINCT ?uri ) AS ?uriCount ) WHERE {
  ?uri wdt:P31 wd:Q46970
}

Using entities:
airline, also known as air company, air carrier (wd:Q46970): company that provides air transport services for traveling passengers and freight

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

Example 2:
Question:
In which country does the Ganges start?

SPARQL:
SELECT ?o2 WHERE {
  wd:Q5089 wdt:P885 ?o1 .
  ?o1 wdt:P17 ?o2 .
}

Using entities:
Ganges, also known as Ganga, River Ganges, Ganges River (wd:Q5089): major river in India

Using properties:
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
origin of the watercourse, also known as headwaters, water source, water origin, water body origin, stream source (wd:P885 as wdt): main source of a river, stream or lake

Example 3:
Question:
How many students does the Free University of Amsterdam have?

SPARQL:
SELECT ?o1 WHERE {
  wd:Q214341 wdt:P2196 ?o1 .
}

Using entities:
University of Amsterdam, also known as GUA, uva.nl, UvA, Univ. of Amsterdam, G.U.A. (wd:Q214341): public university in Amsterdam, Netherlands

Using properties:
count of students, also known as count of pupils, count of students, enrollment, number of pupils, number of pupils or students (wd:P2196 as wdt): number of pupils or students of any type in an educational organ...evious years normal rank (not deprecated rank). Don't overwrite.

[Assistant] From the examples, we can see how to structure a SPARQL query to retrieve information about entities and their properties. In our case, we need to find the binary gender of the partner of Allen Ginsberg. Let's start by identifying the entity for Allen Ginsberg.

[Tool]
Top 10 entity alternatives:
1. Allen Ginsberg, also known as Irwin Allen Ginsberg (wd:Q6711): American poet and writer (1926–1997), autobiographer, photographer, screenwriter, playwright, musician, diarist, teacher, writer, poet
2. Allen Ginsberg (wd:Q102249265): Ph.D. Rutgers University, New Brunswick 1986
3. Allen Ginsberg Library (wd:Q117833470): this entity is a library in the state of colorado. it was identified and verified by the chr task force
4. Untitled (Allen Ginsberg) (wd:Q76558858): print in the National Gallery of Art (NGA 155538)
5. Allen Ginsberg no number (wd:Q64163104): photograph in the National Gallery of Art (NGA 88333)
6. Allen Ginsberg no number (wd:Q64163625): photograph in the National Gallery of Art (NGA 88331)
7. Allen Ginsberg no number (wd:Q64163102): photograph in the National Gallery of Art (NGA 88336)
8. Allen Ginsberg no number (wd:Q64163079): photograph in the National Gallery of Art (NGA 88334)
9. Allen Ginsberg no number (wd:Q64162725): photograph in the National Gallery of Art (NGA 88330)
10. Allen Ginsberg no number (wd:Q64162264): photograph in the National Gallery of Art (NGA 88332)

[Assistant]
The top result for "Allen Ginsberg" is the correct entity: Allen Ginsberg, also known as Irwin Allen Ginsberg (wd:Q6711).

Next, let's identify the property for "partner" or "spouse" to find out who Allen Ginsberg's partner was.

[Tool]
Top 10 property alternatives:
1. 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
2. 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
3. partner in business or sport, also known as professional partner, sport partner, sports partner, team mate, team-mate (wd:P1327 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): professional collaborator, significant person
4. partnership with, also known as works with, collaborates with, collaboration with (wd:P2652 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): partnership (commercial or/and non-commercial) between this organization and another organization or institution
5. twinned administrative body, also known as twin cities, twin town, twin city, sister town, sister city (wd:P190 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): twin towns, sister cities, twinned municipalities and other loca..., either legally or informally acknowledged by their governments
6. contributor to the creative work or subject, also known as assistant, collaborator, contributor, contributor(s) to the subject, creative contributor (wd:P767 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): person or organization that contributed to a subject: co-creator of a creative work or subject, participant
7. funder, also known as benefactor, sponsored by, sponsor, has funder, has donor (wd:P8324 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): entity that gives money to a person, organization, or project for a specific purpose, sponsor
8. sponsor, also known as benefactor, endorsed by, patron, sponsored by (wd:P859 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): organization or individual that sponsors this item
9. commissioned by, also known as client, orderer, made for, commissioner, built for (wd:P88 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): person or organization that commissioned this work
10. 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

[Assistant]
The most relevant property for "partner" is "spouse" (wd:P26), as it is commonly used for married couples. However, since Allen Ginsberg was known to have had both romantic and non-romantic relationships, we should also consider "unmarried partner" (wd:P451).

Let's check if Allen Ginsberg has any values for these properties.

[Tool]
Got 1 row and 1 column:
| partner                      |
| ---------------------------- |
| Peter Orlovsky (wd:Q1983102) |

[Assistant]
Allen Ginsberg had a partner named Peter Orlovsky (wd:Q1983102). Now, let's find out the binary gender of Peter Orlovsky.

We need to identify the property for "binary gender" or "gender" in Wikidata.

[Tool]
Top 10 property alternatives:
1. grammatical gender, also known as gender (wd:P5185 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): grammatical gender of the word
2. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)
3. requires grammatical feature, also known as grammatical feature required, required grammatical feature, requires case, requires mood, uses case (wd:P5713 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): grammatical features required or generally used with lexeme or form of lexeme
4. has grammatical gender, also known as grammatical genders, has genders (wd:P5109 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): specific form of noun class system of a language. Use qualifier ... subject of" (P805) to link to language specific item if present
5. personal pronoun, also known as gender pronoun, personal gender pronoun, personal pronouns, PGP, PGPs (wd:P6553 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): personal pronoun(s) this person goes by
6. semantic gender, also known as natural gender (wd:P10339 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): used when a word is only used to refer to people of this gender or to animals of this sex, independent of the grammatical gender
7. female form of label, also known as female form of label (string), female gender sense, feminine form of label (wd:P2521 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): female form of name or title (for male use P3321)
8. gender educated (wd:P7419 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): genders educated at this educational institution
9. male form of label, also known as male form of label (string), male gender sense, masculine form of label (wd:P3321 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): male form of name or title (for female use P2521)
10. given name version for other gender, also known as personal name version for other gender, other genders given name, male version of this female given name, gender inflection of given name, female version of this male given name (wd:P1560 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): equivalent name (with respect to the meaning of the name) in the...n of a female first name. Add primarily the closest matching one

[Assistant] The most relevant property for "binary gender" is "sex or gender" (wd:P21). Let's use this property to find out the binary gender of Peter Orlovsky.

[Tool]
Got 1 row and 1 column:
| gender             |
| ------------------ |
| male (wd:Q6581097) |

[Assistant]
The binary gender of Peter Orlovsky, the partner of Allen Ginsberg, is male (wd:Q6581097).

Here is the final SPARQL query and answer:

```sparql
SELECT ?gender WHERE {
  wd:Q1983102 wdt:P21 ?gender
}
```

Answer: The binary gender of the partner of Allen Ginsberg is male.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?member ?birthDate WHERE {
  VALUES ?member {
    wd:Q26707915 wd:Q56259927 wd:Q55287306 wd:Q61100297 wd:Q56761923 wd:Q55287305
  }
  ?member wdt:P569 ?birthDate .
}
ORDER BY ASC ( ?birthDate )
LIMIT 1

The youngest member of G-IDLE is Cho Mi-yeon.

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

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

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

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

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

[User] who is the youngested member in g-idle?

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

[Tool]
Example 1:
Question:
Who is the mayor of Tel Aviv?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q33935 wdt:P6 ?uri .
}

Using entities:
Tel Aviv, also known as Tel Aviv City, TLV, Tel Aviv-Jafo, Tel-Aviv Jaffa, Tel Aviv-Jaffa (wd:Q33935): city in Israel

Using properties:
head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as wdt): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson

Example 2:
Question:
Which U.S. state has the highest population density?

SPARQL:
SELECT ?uri {
  ?uri wdt:P31 wd:Q35657 .
  ?uri wdt:P1082 ?population .
  ?uri wdt:P2046 ?area .
  BIND( ( ?population / ?area ) AS ?density )
}
ORDER BY DESC ( ?density )
LIMIT 1

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

Using properties:
population, also known as inhabitants, human population (wd:P1082 as wdt): number of people inhabiting the place; number of people of subject
area, also known as total area, surface area, surface, size, resolution (wd:P2046 as wdt): area occupied by an object
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 3:
Question:
How many languages are spoken in Turkmenistan?

SPARQL:
SELECT ( COUNT( DISTINCT ?uri ) as ?c ) WHERE {
  wd:Q874 wdt:P2936 ?uri .
}

Using entities:
Turkmenistan, also known as TKM, tm, Turkmenia (wd:Q874): country in Central Asia

Using properties:
language used, also known as languages used, medium of instruction, used language, uses language, working language (wd:P2936 as wdt): language widely used (spoken or written) in this place or at this event or organisation

[Assistant] Based on the examples, we need to identify the group G-IDLE and then find the youngest member of that group. We'll start by searching for the entity representing G-IDLE.

[Tool]
Top 10 entity alternatives:
1. Neverland, also known as Neverland (fandom), Neverland (G-Idle) (wd:Q99515216): Neverland are the fanbase of (G)I-DLE.
2. Moon, also known as Moon ((G)I-dle song), Moon (G-Idle song) (wd:Q104969991): 2021 single by (G)I-dle
3. Lost, also known as Lost (G-Idle song) (wd:Q105132486): 2021 song by (G)I-DLE
4. Last Dance, also known as Last Dance ((G)I-dle song), Last Dance (G-Idle song) (wd:Q106584541): song written and composed by Kriz and Soyeon, adapted by GroovyRoom; recorded 2021 by (G)I-dle

[Assistant] None of these results seem to directly represent the group G-IDLE. Let me try another search with a slightly different query to see if we can find the correct entity.

[Tool]
Top 10 entity alternatives:
1. (G)I-dle, also known as (G)I-DLE (wd:Q51885404): South Korean girl group
2. (G)I-DLE: I-TALK, also known as I-Talk (wd:Q98844809): original program made by Cube Entertainment, showing behind-the-scenes footage of MVs as series
3. Hwaa, also known as Hwaa ((G)I-dle song), Hwaa (song) (wd:Q104600483): 2021 single by (G)I-dle
4. Moon, also known as Moon ((G)I-dle song), Moon (G-Idle song) (wd:Q104969991): 2021 single by (G)I-dle
5. Last Dance, also known as Last Dance ((G)I-dle song), Last Dance (G-Idle song) (wd:Q106584541): song written and composed by Kriz and Soyeon, adapted by GroovyRoom; recorded 2021 by (G)I-dle
6. I-Land: Who Am I, also known as 2020 (G)I-dle Online Concert 'I-Land: Who Am I' (wd:Q96381600): 2020 (G)I-dle online concert
7. (G)I-dle Just Me ( )I-dle in Seoul, June 2022 (wd:Q124058812)
8. (G)I-dle Just Me ( )I-dle in Monterrey, 14 August 2022 (wd:Q124058808)
9. (G)I-dle at 2020 Tainan Christmas & New Year Eve Party (wd:Q124058809)
10. (G)I-dle Just Me ( )I-dle in San Francisco, 24 July 2022 (wd:Q124058817)

[Assistant] We found the correct entity for the group G-IDLE, which is `wd:Q51885404`. Next, we need to find the members of this group and their birth dates to determine who is the youngest. Let's list the members of G-IDLE.

[Tool]
Got 6 rows and 3 columns:
| subject                 | property               | object                     |
| ----------------------- | ---------------------- | -------------------------- |
| (G)I-dle (wd:Q51885404) | has part(s) (wdt:P527) | Jeon Soyeon (wd:Q26707915) |
| (G)I-dle (wd:Q51885404) | has part(s) (wdt:P527) | Cho Mi-yeon (wd:Q56259927) |
| (G)I-dle (wd:Q51885404) | has part(s) (wdt:P527) | Song Yuqi (wd:Q55287306)   |
| (G)I-dle (wd:Q51885404) | has part(s) (wdt:P527) | Soojin (wd:Q61100297)      |
| (G)I-dle (wd:Q51885404) | has part(s) (wdt:P527) | Minnie (wd:Q56761923)      |
| (G)I-dle (wd:Q51885404) | has part(s) (wdt:P527) | Shuhua (wd:Q55287305)      |

[Assistant]
We have identified the members of G-IDLE. Now, let's find the birth dates of these members to determine who is the youngest. We will use the `wdt:P569` property, which represents the date of birth.

Let's construct a SPARQL query to get the birth dates of the members and then determine the youngest member.

```sparql
SELECT ?member ?birthDate WHERE {
  VALUES ?member { wd:Q26707915 wd:Q56259927 wd:Q55287306 wd:Q61100297 wd:Q56761923 wd:Q55287305 }
  ?member wdt:P569 ?birthDate .
}
ORDER BY ASC(?birthDate)
LIMIT 1
```

This query will return the member with the latest birth date, which will be the youngest member.

Let's execute this query.

[Tool]
Got 1 row and 2 columns:
| member                     | birthDate                           |
| -------------------------- | ----------------------------------- |
| Cho Mi-yeon (wd:Q56259927) | 1997-01-31T00:00:00Z (xsd:dateTime) |

[Assistant]
The query returned Cho Mi-yeon (wd:Q56259927) as the youngest member of G-IDLE, born on January 31, 1997.

To finalize the answer, I will provide the SPARQL query and the answer to the user question.

[Tool] Stopped generation process