PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( DISTINCT ?album ) AS ?albumCount ) WHERE {
  ?album wdt:P175 wd:Q1744 ; wdt:P31 wd:Q482994 .
}

Got 1 row and 1 column:
| ?albumCount |
| ----------- |
| 53          |

Madonna performs on 53 albums according to Wikidata.

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

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

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

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

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

[User] On how many albums does Madonna perform?

[Assistant]
Let's break down the question:

1. We need to identify the entity for "Madonna" (the singer).
2. We need to identify the property that links an artist to albums they perform on.
3. We need to count the number of unique albums Madonna has performed on.

First, I'll search for the entity "Madonna" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Madonna, also known as Madonna Ciccone, Madonna Louise Veronica Ciccone, Madonna Louise Ciccone, Madonna L. Ciccone (wd:Q1744): American singer, songwriter, and actress (born 1958), songwriter, singer, actor
2. Mary, also known as Mother of God, Mother of Jesus, Notre Dame, Our Lady, Queen of the Universe (wd:Q345): mother of Jesus
3. Madonna, also known as Madonna: The First Album (wd:Q177943): 1983 self-titled debut studio album by Madonna
4. Madonna (wd:Q1989780): painting composition by Edvard Munch, in different versions
5. Madonna, also known as Madonna in art, The Madonna in art, Virgin Mary in art (wd:Q926743): artistic representation of Mary, either alone or with her child Jesus
6. Madonna (wd:Q19794647): 2015 South Korean film directed by Shin Su-won
7. Madonna (wd:Q1147459): album by …And You Will Know Us by the Trail of Dead
8. Madonna (wd:Q486604): 2010 EP by Secret
9. Madonna, also known as Madonna, MD, Madonna, Maryland (wd:Q6728358): unincorporated community in Harford County, Maryland
10. Virgin and Child with an Angel (Madonna del Latte), also known as Madonna, Madonna with child and John the Baptist (wd:Q3842618): painting by Antonio da Correggio from 1520

[Assistant]
The correct entity for Madonna the singer is wd:Q1744.

Next, I need to identify the property that links an artist to albums they perform on. This could be something like "performer," "contributor," or "album participated in." I'll search for properties related to "album" for Madonna.

[Tool]
Top 10 property alternatives:
1. AllMusic artist ID, also known as AllMusic, AllMusic ID, amg artist (wd:P1728 as wdt/p): identifier for an artist, musical group, or record label in the AllMusic database (record labels are listed as "artists")
2. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as wdt/p): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
3. discography, also known as discography link, recording catalog (wd:P358 as wdt/p): item for list pages with discography of artist or band, list of works
4. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
5. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdt/p): the object is a country that recognizes the subject as its citizen, country
6. Album of the Year artist ID, also known as AOTY artist ID (wd:P7050 as wdt/p): identifier for an artist on the Album of the Year (AOTY) website
7. official shop URL, also known as online store, shop, shop URL, store, store URL (wd:P10225 as wdt/p): official URL where the agent sells products/merchandise, official website
8. record label, also known as label, labels (wd:P264 as wdt/p): brand and trademark associated with the marketing of subject music recordings and music videos
9. Apple Music artist ID (U.S. version), also known as iTunes author ID, music.apple.com/artist/, iTunes artist ID (American version), https://music.apple.com/artist/, Apple Music artist ID (American version) (wd:P2850 as wdt/p): identifier for a musical artist or author in the U.S. version of Apple Music
10. notable work, also known as artwork, wrote, writer of, works, work (wd:P800 as wdt/p): notable scientific, artistic or literary work, or other work of significance among subject's works

No other items found

[Assistant]
The search did not directly return a property like "performed on album" or "album participated in." The closest relevant properties are "discography" (wd:P358) and "notable work" (wd:P800), but these may not directly link to all albums Madonna has performed on.

To be thorough, I'll now search for properties related to "performer" or "performance" to see if there is a property that connects an artist to albums they perform on.

[Tool]
Top 10 property alternatives:
1. performer, also known as actor, sung by, singer, recording by, recorded by (wd:P175 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): actor, musician, band or other performer associated with this role or musical work, contributor to the creative work or subject
2. character role, also known as role, plays, performer of, as, acting role (wd:P453 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)
3. cover art by, also known as jacket art by, sleeve art by, designer, cover design by, cover artist (wd:P736 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): name of person or team creating cover artwork for book, record album, single record etc.
4. setlist, also known as set list, works performed, songs performed, performances, performance list (wd:P9793 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): performances of songs or other music at an event; concert program, presented works
5. number of representations, also known as shows, performances, number of shows, number of concerts, no. of shows (wd:P5027 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): number of shows (including the premiere) of a concert tour or a performing arts production
6. used by, also known as armiger, user, played by, of (wd:P1535 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): item or concept that makes use of the subject (use sub-properties when appropriate)
7. depicted by, also known as acted by, shown in, seen in, portrayed by, played by (wd:P1299 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): object depicting this subject (object being creative works such as books, films, paintings)
8. exhibited creator, also known as artist exhibited, exhibited artist (wd:P10661 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): intellectual or creative entity (person or organization) responsible for the elements exhibited, creator
9. Muziekweb performer ID, also known as Muziekweb artist ID, Muziekweb band ID (wd:P5882 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): identifier for a performer, composer or band at Muziekweb
10. talk show guest, also known as show guest, podcast guest, participant in talk show, participant in podcast interview, interviewed person (wd:P5030 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): person invited in a talk show, recorded participant

[Assistant]
The property "performer" (wd:P175) is likely the one that links an artist to albums or musical works they have performed on. To confirm, I'll check how this property is used—specifically, if it links albums to performers.

I'll list some triples where the property is "performer" (wdt:P175) to see if the subject is an album and the object is an artist.

[Tool]
Got more than 131,072 rows and 3 columns, showing the first 10 rows below:
| subject                                         | property             | object                            |
| ----------------------------------------------- | -------------------- | --------------------------------- |
| wd:Q11255467                                    | performer (wdt:P175) | Barack Obama (wd:Q76)             |
| Justice for All (wd:Q116979449)                 | performer (wdt:P175) | Donald Trump (wd:Q22686)          |
| Billie Jean (wd:Q101077837)                     | performer (wdt:P175) | Michael Jackson (wd:Q2831)        |
| wd:Q114891769                                   | performer (wdt:P175) | Vladimir Putin (wd:Q7747)         |
| You're the Inspiration (wd:Q106327193)          | performer (wdt:P175) | Chicago (wd:Q1297)                |
| The Da Ponte Operas (wd:Q11786277)              | performer (wdt:P175) | Wolfgang Amadeus Mozart (wd:Q254) |
| Agbachaekurunwa Dance (wd:Q117075662)           | performer (wdt:P175) | woman (wd:Q467)                   |
| Sha La La / Remember Me (wd:Q11243196)          | performer (wdt:P175) | Hawaii (wd:Q782)                  |
| To Know Her Is to Love Her (wd:Q102119127)      | performer (wdt:P175) | The Beatles (wd:Q1299)            |
| Martin Luther King at Zion Hill (wd:Q108166631) | performer (wdt:P175) | Martin Luther King Jr. (wd:Q8027) |
| ...                                             | ...                  | ...                               |

[Assistant]
The property "performer" (wdt:P175) is used to link musical works (including albums and songs) to the artists who performed them. Therefore, to answer the question, I need to find all items where Madonna (wd:Q1744) is the performer, and the item is an album.

To do this, I need to:
1. Find all items where wdt:P175 is wd:Q1744.
2. Filter these items to only include those that are albums.

I'll search for the entity type "album" to get its QID, so I can use it to filter for albums.

[Tool]
Top 10 entity alternatives:
1. album, also known as full album, record album, music album, full-length album, audio album (wd:Q482994): grouping of album releases by an artist usually released at the ...racks but in different formats for consumption (digital, CD, LP)
2. album, also known as scrapbook (wd:Q1173065): book with pages used for assembling and presenting a collection,...blished sets of pages that are bound or loose-leaf and annotated
3. album (wd:Q2288488): board chalked or painted white, on which decrees, edicts and other public notices were inscribed in black in ancient Rome
4. Album (wd:Q531318): 1994 album by Quorthon
5. Album (wd:Q23925073): 2016 film by Mehmet Can Mertoğlu
6. Album (wd:Q1411632): 1983 album by Joan Jett
7. Album, also known as Cassette, Compact Disc (wd:Q1942675): 1986 album by Public Image Ltd
8. Álbum (wd:Q6172625): 2006 studio album by Lu
9. Album, also known as 82876 650 512 (wd:Q146378): 2004 studio album by Brodka a.k.a. Monika Brodka
10. Album (wd:Q4712765): 2002 Tamil film directed by Vasanthabalan

[Assistant]
The correct entity for "album" as a music album is wd:Q482994.

Now, I will construct a SPARQL query to:
- Find all items where Madonna (wd:Q1744) is the performer (wdt:P175).
- The item is an instance of album (wd:Q482994).
- Count the number of unique such albums.

I'll also optionally return the album labels for context, but the main result will be the count.

[Tool]
Got 1 row and 1 column:
| ?albumCount |
| ----------- |
| 53          |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?inception WHERE {
  wd:Q800176 wdt:P571 ?inception
}

The jazz club Birdland in Hamburg was founded in 1985.

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

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

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

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

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

[User] When was the jazz club Birdland in Hamburg founded?

[Assistant]
Let's break down the question:

1. The user is asking about the founding date of the jazz club "Birdland" in Hamburg.
2. I need to identify the correct entity for "Birdland" (the jazz club in Hamburg) in Wikidata.
3. Then, I need to find the property that represents the founding date.

First, I will search for the entity "Birdland Hamburg" in Wikidata to ensure I have the correct club.

[Tool]
Top 10 entity alternatives:
1. Hamburg, also known as Free and Hanseatic City of Hamburg, Hamburg, Germany, Hamburg, Freie und Hansestadt (wd:Q1055): city and state in the North of Germany
2. Hamburger SV, also known as Hamburg SV, HSV, H.S.V., Hamburg Sport Club, HamburgerSV (wd:Q51974): German sports club based in Hamburg, with its largest branch being its football department
3. Hamburg, also known as Hamburg, IA, Hamburg, Iowa (wd:Q998718): city in Fremont County, Iowa, United States
4. Hamburg, also known as Hamburg, AR, Hamburg, Arkansas (wd:Q79657): city in Ashley County, Arkansas, United States
5. Hamburg, also known as Hamburg, Minnesota, Hamburg, MN (wd:Q1005682): city in Carver County, Minnesota, United States
6. Hamburg, also known as Hamburg, New Jersey, Hamburg, NJ (wd:Q1082931): borough in Sussex County, New Jersey, United States
7. Hamburg, also known as Hamburg, New York, Hamburg, NY (wd:Q742785): town in Erie County, New York, United States
8. Hamburg, also known as Hamburg, IL (wd:Q2672139): village in Calhoun County, Illinois, United States
9. Oriole Park at Camden Yards, also known as Birdland, Camden Yards, The House that Cal Built, The Yard (wd:Q1141174): baseball stadium in Baltimore, Maryland
10. Hamburg, also known as Hamburg, PA, Hamburg, Pennsylvania (wd:Q1181264): borough in Berks County, Pennsylvania, United States

[Assistant]
The search did not return a direct match for "Birdland" jazz club in Hamburg. The closest match for "Birdland" is a baseball stadium in Baltimore, which is not relevant.

To refine the search, I will try searching for just "Birdland" to see if there is an entry for the jazz club, possibly without the city in the name.

[Tool]
Top 10 entity alternatives:
1. Oriole Park at Camden Yards, also known as Birdland, Camden Yards, The House that Cal Built, The Yard (wd:Q1141174): baseball stadium in Baltimore, Maryland
2. Birdland (wd:Q256347): New York City jazz club
3. Birdland (wd:Q2904435): album by The Yardbirds
4. Birdland (wd:Q784489): song
5. Birdland (wd:Q800176): jazz club in Hamburg
6. Birdland (wd:Q55652970): 2018 film directed by Peter Lynch
7. Birdland (wd:Q11854283)
8. Birdland, also known as Birdland, San Diego (wd:Q4916004): neighborhood of San Diego, California, United States
9. Oliver Ho, also known as Raudive, Seeker, Veil, Zov Zov, Life (wd:Q1722141): British DJ and electronic music producer, disc jockey, DJ producer
10. Birdland (wd:Q118905393): erotic comic book series

[Assistant]
From the search results, "Birdland (wd:Q800176)" is identified as the jazz club in Hamburg. Now, I need to find the property for "founding date" or similar to get the year it was founded.

I will search for properties related to "founding date" to ensure I use the correct property.

[Tool]
Top 10 property alternatives:
1. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): time when an entity begins to exist; for date of official opening use P1619, start time
2. location of formation, also known as place of incorporation, originates from, place of establishment, place of formation, place of foundation (wd:P740 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): location where a group or organization was formed, location of creation
3. date of incorporation, also known as date incorporated, incorporated, incorporated on date, incorporation date, year incorporated (wd:P10786 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): date when company, organization or city was incorporated
4. notable work, also known as artwork, wrote, writer of, works, work (wd:P800 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): notable scientific, artistic or literary work, or other work of significance among subject's works
5. founded by, also known as starter, co-founded by, started by, institutor, instituted by (wd:P112 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): founder or co-founder of this organization, religion, place or entity, creator
6. foundational text, also known as main text, treaty, organic law, founding document, establishing document (wd:P457 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): text through which an institution or object has been created or established
7. time of discovery or invention, also known as invented in, time of invention, time of discovery, invention time, invented on (wd:P575 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): date or point in time when the item was discovered or invented
8. introduced on, also known as bill introduced on, introduction date, introduced date (wd:P9448 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): date when a bill was introduced into a legislature, inception
9. start time, also known as start date, since, valid, join time, joined (wd:P580 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): time an entity begins to exist or a statement starts being valid, point in time
10. earliest date, also known as no earlier than, terminus post quem, start date (earliest), on or after this date, minimum date (wd:P1319 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): earliest date at which an event could have happened. Use as qualifier for other date properties

[Assistant]
The property "inception" (wd:P571) is the correct one to use for the founding date of organizations such as clubs.

Now, I will construct a SPARQL query to get the inception (founding date) of Birdland (wd:Q800176), the jazz club in Hamburg.

[Tool]
Got 1 row and 1 column:
| ?inception           |
| -------------------- |
| 1985-01-01T00:00:00Z |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?author WHERE {
  wd:Q44649835 wdt:P50 ?author .
}

The author of "Prototypical Networks for Few-shot Learning" is Richard S. Zemel (wd:Q26702597).

[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 wrote "Prototypical Networks for Few-shot Learning"?

[Assistant]
Let's break down the question:

1. The user is asking for the author(s) of the paper "Prototypical Networks for Few-shot Learning".
2. I need to identify the entity for this paper in Wikidata.
3. Then, I need to find the property that links a scholarly work to its author(s).

First, I'll search for the entity "Prototypical Networks for Few-shot Learning" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Prototypical Networks for Few-shot Learning (wd:Q44649835): scientific article published in January 2017
2. Hybrid Graph Neural Networks for Few-Shot Learning (wd:Q114887023): scientific article published in 2022
3. Convolutional Shrinkage Neural N...a-Learning for Few-Shot Learning (wd:Q114955057): scientific article published in 2022
4. Facial Skin Type Analysis Using ...rning with Prototypical Networks (wd:Q129793741): scholarly article published on 31 December 2023
5. Few-Shot Ensemble Learning for V...on with SlowFast Memory Networks (wd:Q130987343): scientific article published on 12 October 2020
6. Co-Learning for Few-Shot Learning (wd:Q114955104): scientific article published in 2022
7. Differential learning for learning networks (wd:Q123992464): US patent 11468327
8. Bayesian Learning for Neural Networks (wd:Q60016544): scientific article published in 1996
9. Information Maximization for Few-Shot Learning (wd:Q104090143): scientific article published in November 2020
10. Ensemble Learning for Multi-Layer Networks (wd:Q77697315): scholarly article by David Barber & Christopher M. Bishop published 1998 in Advances in Neural Information Processing Systems 10

[Assistant]
The entity "Prototypical Networks for Few-shot Learning" corresponds to wd:Q44649835 in Wikidata.

Next, I need to find the property that links a scientific article to its author(s). I'll search for properties related to "author".

[Tool]
Top 10 property alternatives:
1. theorized by, also known as author, supported by, suggested by, proposer, proposed by (wd:P8403 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): subject who suggested or proposed this concept or immaterial invention
2. lyricist, also known as text poet, writer (of song lyrics), words by, text writer, text by (wd:P676 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): author of song lyrics, author
3. author, also known as writer, written by, poet, playwright, maker (wd:P50 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/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
4. notable work, also known as artwork, wrote, writer of, works, work (wd:P800 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): notable scientific, artistic or literary work, or other work of significance among subject's works
5. author given names, also known as given name, given names, first name, author first names, author first name (wd:P9687 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): qualifier for string representation of given or secondary sortin...presented in a bibliographic reference file (for example BibTeX), given name
6. used by, also known as armiger, user, played by, of (wd:P1535 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): item or concept that makes use of the subject (use sub-properties when appropriate)
7. operator, also known as offered by, operated by, provided by, run by, service operator (wd:P137 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): person, profession, organization or entity that operates the equipment, facility, or service, used by
8. creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): maker of this creative work or other object (where no more specific property exists)
9. author last names, also known as author last name, surnames, surname, last names, last name (wd:P9688 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): qualifier to provide string representation of family or primary ...presented in a bibliographic reference file (for example BibTeX), family name
10. object named as, also known as original wording, place name string, printed as, reference wording, [sic] (wd:P1932 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): use as qualifier to indicate how the object's value was given in the source, name

[Assistant]
The property "author" (wd:P50) is the main property used to link a written work to its author(s).

Now, I'll construct a SPARQL query to find the author(s) (as Wikidata entities) of "Prototypical Networks for Few-shot Learning" (wd:Q44649835), and optionally retrieve their labels.

[Tool]
Got 1 row and 2 columns:
| ?author                         | ?authorLabel     |
| ------------------------------- | ---------------- |
| Richard S. Zemel (wd:Q26702597) | Richard S. Zemel |

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?university ?count ?universityLabel WHERE {
  ?university wdt:P31 wd:Q3918 .
  ?university wdt:P2196 ?count .
  FILTER ( ?count > 200000 ) OPTIONAL {
    ?university rdfs:label ?universityLabel FILTER ( lang( ?universityLabel ) = "en" )
  }
}

Got 7 rows and 3 columns:
| ?university                                                | ?count  | ?universityLabel                           |
| ---------------------------------------------------------- | ------- | ------------------------------------------ |
| National Open University of Nigeria, Lafia (wd:Q131290725) | 500000  | National Open University of Nigeria, Lafia |
| University of Phoenix (wd:Q1889100)                        | 420000  | University of Phoenix                      |
| Cairo University (wd:Q194445)                              | 257200  | Cairo University                           |
| National Autonomous University of Mexico (wd:Q222738)      | 360883  | National Autonomous University of Mexico   |
| Ain Shams University (wd:Q2723670)                         | 220000  | Ain Shams University                       |
| Allama Iqbal Open University (wd:Q3694529)                 | 1326266 | Allama Iqbal Open University               |
| Universitas Terbuka (wd:Q7894421)                          | 525360  | Universitas Terbuka                        |

The universities with more than 200,000 students are:
- National Open University of Nigeria, Lafia (wd:Q131290725)
- University of Phoenix (wd:Q1889100)
- Cairo University (wd:Q194445)
- National Autonomous University of Mexico (wd:Q222738)
- Ain Shams University (wd:Q2723670)
- Allama Iqbal Open University (wd:Q3694529)
- Universitas Terbuka (wd:Q7894421)

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

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

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

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

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

[User] Which universities have more than 200000 students?

[Assistant]
To answer this question, I need to:

1. Identify the entity for "university" in Wikidata.
2. Find the property that represents the number of students at a university.
3. Write a SPARQL query to select universities with more than 200,000 students.

First, I'll search for the entity "university" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. university, also known as uni, universities (wd:Q3918): academic institution for further education
2. University, also known as Suitcase City, University, FL (wd:Q2463874): human settlement in Hillsborough County, Florida, USA
3. medieval university, also known as mediaeval university, university (wd:Q1143413): corporation organized during the High Middle Ages
4. University, also known as University, Orange County, University, FL, University, Florida (wd:Q7894478): Orange County, Florida, USA
5. University, also known as University CDP, University Census Designated Place, University, Mississippi, University, MS (wd:Q3612349): census-designated place in Mississippi, United States
6. Expo Park/USC, also known as University (wd:Q1953496): Los Angeles Metro station
7. University Avenue, also known as University, University Ave (wd:Q3551335): street in Toronto, Ontario
8. Universidad, also known as Universidad station, University (wd:Q25442975): subway station in San Juan, Puerto Rico
9. University (wd:Q7894493): constituency of the Central and Western District Council of Hong Kong
10. Hochschule, also known as technical university, university (wd:Q21028957): German term for "higher schooling", i.e. institutions of tertiar... which may or may not include vocational or professional schools

[Assistant]
The main entity for "university" as an academic institution is wd:Q3918.

Next, I need to find the property that represents the "number of students" at a university. I'll search for properties related to "number of students".

[Tool]
Top 10 property alternatives:
1. count of students, also known as count of pupils, count of students, enrollment, number of pupils, number of pupils or students (wd:P2196 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): number of pupils or students of any type in an educational organ...evious years normal rank (not deprecated rank). Don't overwrite.
2. student, also known as teacher to, teacher of, had student, students, pupils (wd:P802 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): notable student(s) of the subject individual, significant person
3. number of out-of-school children (wd:P2573 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): number of out-of-school children reported for a place
4. number of teachers, also known as faculty count (wd:P10610 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): number of teachers at an educational facility
5. school class, also known as class, cohort, grade, school cohort, stage (wd:P7174 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): (qualifier) class of a given year/time period to which the person belonged in an educational institution
6. number of children, also known as children, children (number), how many children, issue, kids (wd:P1971 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): number of children of the person, animal, or character
7. educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): educational institution attended by subject, affiliation
8. student retention rate (wd:P11698 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): proportion of first-year students at the educational institution who return for their second year
9. number of participants, also known as number of competitors, number of teams, participant count, participants, qty participants (wd:P1132 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): number of participants of an event, e.g. people or groups of people that take part in the event (NO units), quantity
10. educational stage, also known as student classification (wd:P7374 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): educational stage of a specific school; qualifier of "educated at" (P69): the education stage of someone's attendance of school

[Assistant]
The property "count of students" (wd:P2196) is the correct one for the number of students at a university.

Now, I will write a SPARQL query to select universities (wd:Q3918) with a count of students (wd:P2196) greater than 200,000. I will also try to include optional labels for readability.

[Tool]
Got 7 rows and 3 columns:
| ?university                                                | ?count  | ?universityLabel                           |
| ---------------------------------------------------------- | ------- | ------------------------------------------ |
| National Open University of Nigeria, Lafia (wd:Q131290725) | 500000  | National Open University of Nigeria, Lafia |
| University of Phoenix (wd:Q1889100)                        | 420000  | University of Phoenix                      |
| Cairo University (wd:Q194445)                              | 257200  | Cairo University                           |
| National Autonomous University of Mexico (wd:Q222738)      | 360883  | National Autonomous University of Mexico   |
| Ain Shams University (wd:Q2723670)                         | 220000  | Ain Shams University                       |
| Allama Iqbal Open University (wd:Q3694529)                 | 1326266 | Allama Iqbal Open University               |
| Universitas Terbuka (wd:Q7894421)                          | 525360  | Universitas Terbuka                        |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( ?holiday ) AS ?numHolidays ) WHERE {
  wd:Q980 wdt:P832 ?holiday
}

Got 1 row and 1 column:
| ?numHolidays |
| ------------ |
| 13           |

Bavaria has 13 public holidays in a year.

[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 public holidays does the state Bavaria have in a year?

[Assistant]
Let's break down the question:

1. We need to identify the entity for "Bavaria" (the German state).
2. We need to find the property that links a region to its public holidays.
3. We need to count the number of public holidays for Bavaria in a year.

First, I will search for the entity "Bavaria" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Bavaria, also known as Bayern, Free State of Bavaria, Freistaat Bayern, Freistoot Bayern (wd:Q980): federated state in the south of Germany
2. Kingdom of Bavaria, also known as Bavaria, Kinereich Baiern, Kinereich Bayern, Königreich Baiern, Königreich Bayern (wd:Q154195): kingdom in Central Europe between 1806 and 1918, from January 1871 part of the German Empire
3. Electorate of Bavaria, also known as Bavaria (wd:Q256961): state in the Holy Roman Empire
4. 301 Bavaria, also known as (301) Bavaria, Bavaria (wd:Q150590): main-belt asteroid
5. Bavaria, also known as Bavaria statue (wd:Q707669): Statue of Bavaria in Munich, Germany
6. Bavaria (wd:Q874953): former train on the Trans-Europ-Express connection Zurich-Munich
7. Bavaria, also known as Bavaria, Kansas, Bavaria, KS (wd:Q4873636): unincorporated community in Kansas, USA
8. Bavaria Brewery, also known as Bavaria S.A., Bavaria (wd:Q2946947): Colombian brewery company
9. Bavaria Fluggesellschaft, also known as Bavaria (wd:Q811995): former German airline
10. Bavaria (wd:Q117323380): female figure symbolising Bavaria

[Assistant]
The correct entity for the German state of Bavaria is wd:Q980.

Next, I need to find the property that links a region (like Bavaria) to its public holidays. I will search for properties related to "public holiday".

[Tool]
Top 10 property alternatives:
1. public holiday, also known as bank holiday, legal holiday, national holiday (wd:P832 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): official public holiday that occurs in this place in its honor, usually a non-working day, significant event
2. closed on, also known as closed days, days not open, except (wd:P3026 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): exceptions to open days (P3025), usually special dates
3. open days, also known as open on days, days open, opening days (wd:P3025 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): days in the week subject item is open within the opening season
4. day in year for periodic occurrence, also known as date, day, day in year, day of periodic occurrence, day of year (wd:P837 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): when a specific holiday or periodic event occurs. Can be used as property or qualifier
5. day of week, also known as day of the week, days of week (wd:P2894 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): day of the week on which this item occurs, applies to or is valid
6. date of official closure, also known as closed, official closure, date of closure, closure date, closing date (wd:P3999 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): date of official closure of a building or event, end time
7. set during recurring event, also known as narrative event, narrative holiday, set during event, set during holiday (wd:P9215 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): recurring event (e.g. season, month, holiday) during which this fictional work is set
8. opening time, also known as hour opens, opens at, opening hour, open hour (wd:P8626 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): time when an establishment or attraction opens, qualifier for P3025
9. date of official opening, also known as launch date, launched, officially opened on, official opening, official opening time (wd:P1619 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): date or point in time a place, organization, or event officially opened, start time, inception
10. created for, also known as cause of creation, commissioned for, made for, occasion, on the occasion of (wd:P9883 as ps/p/psn/pqv/psv/pr/pq/prv/pqn/prn/wdtn/wdt): a work, event, etc. for which the subject work was created (e.g.... play was created for; a film that a screenplay was written for)

[Assistant]
The property "public holiday" (wd:P832) is the most relevant for linking a place to its public holidays.

Now, I will check how this property is used for Bavaria (wd:Q980) to see if it lists the public holidays directly.

[Tool]
Got 13 rows and 3 columns, showing the first 10 rows below:
| subject           | property                  | object                                 |
| ----------------- | ------------------------- | -------------------------------------- |
| Bavaria (wd:Q980) | public holiday (wdt:P832) | Christmas (wd:Q19809)                  |
| Bavaria (wd:Q980) | public holiday (wdt:P832) | New Year (wd:Q34812)                   |
| Bavaria (wd:Q980) | public holiday (wdt:P832) | International Workers' Day (wd:Q47499) |
| Bavaria (wd:Q980) | public holiday (wdt:P832) | Good Friday (wd:Q40317)                |
| Bavaria (wd:Q980) | public holiday (wdt:P832) | All Saints' Day (wd:Q587)              |
| Bavaria (wd:Q980) | public holiday (wdt:P832) | Epiphany (wd:Q132001)                  |
| Bavaria (wd:Q980) | public holiday (wdt:P832) | Assumption of Mary (wd:Q162691)        |
| Bavaria (wd:Q980) | public holiday (wdt:P832) | Feast of the Ascension (wd:Q51638)     |
| Bavaria (wd:Q980) | public holiday (wdt:P832) | Feast of Corpus Christi (wd:Q152395)   |
| Bavaria (wd:Q980) | public holiday (wdt:P832) | Easter Monday (wd:Q209663)             |
| ...               | ...                       | ...                                    |

[Assistant]
There are 13 public holidays listed for Bavaria using the property wdt:P832.

To answer the question precisely, I will write a SPARQL query that counts the number of public holidays (wdt:P832) for Bavaria (wd:Q980).

[Tool] Stopped generation process


PREFIX geof: <http://www.opengis.net/def/function/geosparql/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
ASK {
  ?place wdt:P17 wd:Q39 ; wdt:P625 ?coord .
  BIND( geof:latitude ( ?coord ) AS ?lat ) FILTER ( ?lat > 47.8 )
}

Yes, Switzerland has at least one place north of the point (8.57 47.8).

[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 Switzerland have a place north of the Point (8.57 47.8)?

[Assistant]
Let's break down the question:

1. The user is asking if Switzerland has a place north of a specific geographic point (longitude 8.57, latitude 47.8).
2. We need to:
   - Identify Switzerland in Wikidata.
   - Find places (likely administrative regions, cities, or settlements) within Switzerland.
   - For each place, get its coordinates.
   - Check if any place has a latitude greater than 47.8 (i.e., is north of the given point).

First, let's search for the entity representing Switzerland in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Switzerland, also known as Confoederatio Helvetica, Swiss, Swiss Confederation (wd:Q39): country in Central Europe
2. Old Swiss Confederacy, also known as Swiss Confederation, Switzerland (wd:Q435583): confederation of cantons (1291-1798)
3. Old Swiss Confederacy, also known as Swiss Confederation, Switzerland (wd:Q435583): confederation of cantons (1291-1798)
4. Switzerland at the 1900 Summer Olympics, also known as Switzerland (wd:Q141744): sporting event delegation
5. federation of eight cantons, also known as Confederacy of eight cantons, Switzerland, Swiss Confederation, federation of 8 cantons, Old Swiss Confederacy (wd:Q340787)
6. Federation of thirteen cantons, also known as Federation of 13 cantons, Swiss Confederacy, Swiss Confederation, Switzerland (wd:Q351537)
7. Switzerland, also known as Switzerland, SC (wd:Q2373348): community in South Carolina, USA
8. Switzerland (wd:Q80282): community in Florida, United States
9. Switzerland in the Eurovision Song Contest 2006, also known as Switzerland (wd:Q7659174)
10. Switzerland (wd:Q420049): album by rock band Electric Six

[Assistant]
The correct entity for Switzerland (the country) is wd:Q39.

Next, we need to find places within Switzerland and their coordinates. In Wikidata, "places" can be settlements, administrative regions, etc. For this query, let's focus on populated places (instances of "human settlement" or subclasses).

We also need to find the property for "coordinate location" to get the latitude of each place. Let's search for the property "coordinate location".

[Tool]
Top 10 property alternatives:
1. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
2. this zoological name is coordinate with, also known as coordinate name (wd:P2743 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): links coordinate zoological names, different from
3. coordinates of depicted place, also known as depicted item geolocation, geolocation of object, object geolocation (wd:P9149 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): coordinates of the place depicted in the work (or Commons image)
4. location map (wd:P1943 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): blank geographic map image suitable for overlaying coordinate points, as defined at c:Category:Location maps, image
5. genomic start, also known as start coordinate, genomic from, Genloc From, from, Genloc Start (wd:P644 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): genomic starting coordinate of the biological sequence (e.g. a gene)
6. set in environment, also known as set in location, takes place in, setting location, playing in, narrative set in (wd:P8411 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): environment (geographic feature, building type, etc.) the narrative work is set in, significant place, depicts
7. narrative location, also known as set in location, set in, setting, setting location, setting of work (wd:P840 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): the narrative of the work is set in this location, significant place, depicts
8. location of discovery, also known as found in, location of discovered object, place of discovery, site of discovery, source (wd:P189 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): where the item was located when discovered, significant place
9. spatial reference system, also known as coordinate reference system, CRS, SRS (wd:P3037 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): frame of reference used to produce a map
10. coordinates of geographic center, also known as coordinates of geographic centre, geographic centre, geographic center, geographical midpoint, geographical centre (wd:P5140 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): coordinates of the center of an area. Use qualifier "determination method" (P459) to indicate how, coordinate location

[Assistant]
The property for "coordinate location" is wd:P625.

Now, we need to:
- Find entities that are instances of "human settlement" (or subclasses) within Switzerland.
- For each, get their coordinate location (wd:P625).
- Extract the latitude from the coordinate.
- Check if any have latitude > 47.8.

Let's search for the entity "human settlement" to get its QID.

[Tool]
Top 10 entity alternatives:
1. human settlement, also known as human settlements, inhabited place, settlement, settlements (wd:Q486972): place of any size, in which people permanently live
2. Kwande, also known as Human settlement (wd:Q6450151): LGA in Benue State, Nigeria
3. human settlement (wd:L457328-S1)
4. human settlement (wd:L457329-S1)
5. human settlement (wd:L457330-S1)
6. human settlement (wd:L457332-S1)
7. human settlement (wd:L457333-S1)
8. human settlement (wd:L457334-S1)
9. human settlement (wd:L457339-S1)
10. human settlement (wd:L457346-S1)

[Assistant]
The entity for "human settlement" is wd:Q486972.

Now, let's construct a SPARQL query that:
- Finds entities that are instances of wd:Q486972 (human settlement).
- Are located in Switzerland (wd:Q39).
- Have a coordinate location (wd:P625).
- Extracts the latitude from the coordinate.
- Checks if any latitude > 47.8.

To do this, we need to know the property for "country" or "located in the administrative territorial entity" to link settlements to Switzerland. Let's search for the property "country".

[Tool]
Top 10 property alternatives:
1. valid in place, also known as applies to country, applies to location, applies to place, country, true in (wd:P3005 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): place where a statement is valid, applies to part
2. country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country
3. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): the object is a country that recognizes the subject as its citizen, country
4. country, also known as sovereign state, state, land, host country (wd:P17 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
5. operating area, also known as province served, serves jurisdiction, serves geographic region, serves geographic area, serves area (wd:P2541 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): geographic area or jurisdiction an organisation or industry operates in, serves, or has responsibility for, location
6. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): most specific known birth location of a person, animal or fictional character, location
7. continent (wd:P30 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): continent of which the subject is a part, located in/on physical feature
8. 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 wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
9. place of publication, also known as published in (place), where published, release region, released in, published from (wd:P291 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): geographical place of publication of the edition (use 1st edition when referring to works), significant place
10. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object

[Assistant]
The property "country" is wd:P17, which links a place to its country.

Now, let's construct the SPARQL query:
- Find ?place that is an instance of wd:Q486972 (human settlement)
- ?place wdt:P17 wd:Q39 (country is Switzerland)
- ?place wdt:P625 ?coord (has coordinate location)
- Extract latitude from ?coord
- Filter latitude > 47.8

We will use the Wikidata function to extract latitude from the coordinate.

Let's write the query.

[Tool] Got no rows and 1 columns

[Assistant]
The query found no human settlements in Switzerland with a latitude greater than 47.8. However, Switzerland's northernmost point is slightly above 47.8, so perhaps there are other types of places (not just human settlements) north of this point.

Let's broaden the query to include any place (not just human settlements) within Switzerland that has a coordinate location north of latitude 47.8. We'll look for any entity with:
- wdt:P17 wd:Q39 (country is Switzerland)
- wdt:P625 ?coord (coordinate location)
- latitude > 47.8

Let's try this broader query.

[Tool]
Got 1 row and 1 column:
| place         |
| ------------- |
| wd:Q107262026 |

[Tool]
Got 5 rows and 3 columns:
| place                   | label        | coord                                      |
| ----------------------- | ------------ | ------------------------------------------ |
| wd:Q107262026           |              | POINT(7.384722 48.008611) (geo:wktLiteral) |
| Pöschen (wd:Q108091347) | Pöschen (en) | POINT(8.604836 47.800866) (geo:wktLiteral) |
| wd:Q11783200            |              | POINT(7.000000 49.233300) (geo:wktLiteral) |
| wd:Q11783215            |              | POINT(5.950000 52.217000) (geo:wktLiteral) |
| wd:Q11783221            |              | POINT(9.738600 52.374400) (geo:wktLiteral) |

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?entrepreneur ?netWorth ?label WHERE {
  ?entrepreneur wdt:P31 wd:Q5 .
  ?entrepreneur wdt:P106 wd:Q131524 .
  ?entrepreneur wdt:P2218 ?netWorth .
  OPTIONAL {
    ?entrepreneur rdfs:label ?label FILTER ( lang( ?label ) = "en" )
  }
}
ORDER BY DESC ( ?netWorth )
LIMIT 1

The most wealthy entrepreneur is Elon Musk (wd:Q317521), with a net worth of 270,100,000,000.

[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 most wealthy entrepreneur?

[Assistant]
Let's break down the question:

1. We need to identify entities that are "entrepreneurs".
2. We need to find their wealth (likely "net worth").
3. We need to determine who is the "most wealthy" (i.e., the entrepreneur with the highest net worth).

First, let's search for the property related to "net worth" in Wikidata.

[Tool]
Top 10 property alternatives:
1. net worth, also known as declared patrimony, estimated net worth, net wealth, net worth estimate, personal assets (wd:P2218 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): totality of wealth possessed by a person
2. net profit, also known as profit, net return, net income, clear profit, clear gain (wd:P2295 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): private entity profit after accounting for all costs
3. estimated value, also known as valuation, traded value, traded cap, price estimation, estimated worth (wd:P8340 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): estimated value of a house, company, patent, etc
4. total revenue, also known as turnover, sales, revenue, income, gross revenue (wd:P2139 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): income gained by an organization during a given time frame. Not to be confused with fiscal revenue
5. item of property constraint, also known as claim value, value, qid, property value, item qualifier (wd:P2305 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): qualifier to define a property constraint in combination with "property constraint" (P2302)
6. prize money, also known as money, purse, value (wd:P2121 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): amount in a specific currency
7. price, also known as cost, exchange rate, list price, MSRP, published price (wd:P2284 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): published price listed or paid for a product (use with unit of currency)
8. numeric value, also known as numerical value, value (wd:P1181 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): numerical value of a number, a mathematical constant, or a physical constant
9. total assets, also known as assets, balance sheet total (wd:P2403 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): value of assets held by a private or public entity
10. box office, also known as earnings (wd:P2142 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): box office takings accumulated by a film, total revenue

[Assistant]
The property for "net worth" is `wdt:P2218`. Next, we need to identify the entity or class for "entrepreneur" so we can filter for people who are entrepreneurs.

I'll search for the entity "entrepreneur" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. entrepreneur, also known as undertaking (wd:Q131524): person who owns and operates a business
2. Entrepreneur (wd:Q5380740): business magazine for entrepreneurs
3. The Entrepreneur, also known as Entrepreneur (wd:Q3204987): 2011 film by Giuliano Montaldo
4. Entrepreneur (wd:Q30598698): 1997 video game
5. Entrepreneur (wd:Q5380739): British Thoroughbred racehorse
6. Entrepreneur (wd:Q98669462): 2020 single by Pharrell Williams featuring Jay-Z
7. Entrepreneur, also known as Yrittäjä (wd:Q104145164): 2018 film directed by Virpi Suutari
8. Darren Lopes, also known as Entrepreneur (wd:Q112113075): entrepreneur, Entrepreneur
9. Adil Sami, also known as Entrepreneur (wd:Q111692090): Entrepreneur, entrepreneur
10. Alee Club Miss & Mr Teen India, also known as Entrepreneur (wd:Q113526755): entrepreneur

[Assistant]
The relevant entity for an "entrepreneur" as a person is `wd:Q131524`. Now, to find the most wealthy entrepreneur, we need to:

- Select all entities that are instances of "entrepreneur" (`wd:Q131524`).
- Get their net worth (`wdt:P2218`).
- Order by net worth in descending order and select the top result.

Let's check if "instance of" is the correct property to use for linking people to "entrepreneur". I'll search for properties related to "instance of" for a person.

[Tool]
Top 10 property alternatives:
1. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
2. permanent duplicated item, also known as same concept as, same as, duplicate of, permanently duplicated item, duplicate of item (wd:P2959 as p/wdt): this item duplicates another item and the two can't be merged, a... cdowiki, gomwiki, nanwiki).  Use P31=Q17362920 for other wikis.
3. present in work, also known as is shown in, in work, in narrative, character in, from work (wd:P1441 as p/wdt): this (fictional or fictionalized) entity, place, or person appea...r works, P1343 for entities described in non-fictional accounts)
4. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as p/wdt): work where this item is described, attested in
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. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
7. significant event, also known as significant occurrence, significant incident, significant achievment, sign. event, outcome (wd:P793 as p/wdt): significant or notable events associated with the subject
8. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as p/wdt): main Wikimedia category
9. described at URL, also known as mentioned at URL, descURL, described on webpage, discussed at URL, d@url (wd:P973 as p/wdt): item is described at the following URL, URL
10. medical condition, also known as disability, suffers from, suffer from, sickness, paralympic disability (wd:P1050 as p/wdt): any state relevant to the health of an organism, including diseases and positive conditions

No other items found

[Assistant]
The property "instance of" (`wdt:P31`) is indeed the correct one to use for linking people to the class "entrepreneur" (`wd:Q131524`).

Now, I'll write a SPARQL query to:
- Select all entities that are instances of "entrepreneur"
- Get their net worth
- Order by net worth descending
- Limit to the top result

I'll also optionally get the label for the person.

[Tool] Got no rows and 3 columns

[Assistant]
It appears that there are no entities in Wikidata that are directly marked as "instance of" entrepreneur (`wd:Q131524`) with a net worth (`wdt:P2218`). This is likely because most entrepreneurs are classified as "humans" (`wd:Q5`) and have "occupation" (`wdt:P106`) as entrepreneur, rather than being "instance of" entrepreneur.

Let's search for the property "occupation" and see if "entrepreneur" is used as an occupation for people.

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

[Assistant]
The property "occupation" is `wdt:P106`. Now, I'll write a query to:

- Select all humans (`wd:Q5`) whose occupation (`wdt:P106`) is entrepreneur (`wd:Q131524`)
- Get their net worth (`wdt:P2218`)
- Order by net worth descending
- Limit to the top result

I'll also optionally get the label for the person.

[Tool]
Got 1 row and 3 columns:
| entrepreneur           | netWorth                   | label          |
| ---------------------- | -------------------------- | -------------- |
| Elon Musk (wd:Q317521) | 270100000000 (xsd:decimal) | Elon Musk (en) |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
ASK {
  wd:Q283 wdt:P462 wd:Q1396399
}

True. Water is considered colorless according to Wikidata.

[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 water colorless?

[Assistant]
Let's break down the question:

1. The question asks whether water is colorless, which is a "True" or "False" type question.
2. We need to identify the entity for "water" and find a property or statement in Wikidata that describes its color.
3. If the color property for water is "colorless," the answer is True; otherwise, False.

First, I will search for the entity "water" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. water, also known as dihydrogen oxide, hydrogen hydroxide, dihydrogen monoxide, hydrogen oxide, oxidane (wd:Q283): chemical compound whose molecules are formed by two hydrogen atoms and one oxygen atom
2. water, also known as dihydridooxygen, pure water, oxidane, hydrogen oxide, hydrogen hydroxide (wd:Q283): chemical compound whose molecules are formed by two hydrogen atoms and one oxygen atom
3. ice, also known as crystalline water, frozen ice, frozen water, solid water, water (wd:Q23392): water frozen into the solid state
4. drinking water, also known as drinkable water, improved drinking water, potable water, water (wd:Q7892): water safe for consumption
5. Water, also known as Water (2005), Water (2005 movie) (wd:Q617395): 2005 film by Deepa Mehta
6. water (wd:Q2637515): classical element in philosophy and cosmology
7. Water (wd:Q123169436): 2023 single by Tyla
8. ☵, also known as water, U+2635, TRIGRAM FOR WATER, kan3, k’an (wd:Q2785811): trigram for water (U+2635): kan3, kǎn, k’an
9. liquid water, also known as water (wd:Q29053744): form of water
10. Water, also known as Water (Elitsa & Stoyan song) (wd:Q2735297): song by Elitsa Todorova and Stoyan Yankoulov

[Assistant] The main entity for "water" as a chemical compound is wd:Q283. Next, I need to find the property in Wikidata that describes the color of a substance. I will search for properties related to "color."

[Tool]
Top 10 property alternatives:
1. color, also known as with the colour, with the color, pigment, of the colour, of the color (wd:P462 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): color of subject
2. colorist, also known as colouring by, colours by, colourist, colors by, coloring by (wd:P6338 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): artist in charge of adding colors to drawings, comics, movie film, etc., illustrator
3. hair color, also known as color of hair, colour of hair, haircolor, hair colour, haircolour (wd:P1884 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): person's hair color. Use P585 as qualifier if there's more than one value, color
4. color produced, also known as colour produced (wd:P7253 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): color or color range produced by a dye, alone or with a mordant
5. for color scheme, also known as color mode, uses colour scheme, uses color scheme, theme, prefers colour scheme (wd:P8798 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): which color scheme this statement is designed for
6. sRGB color hex triplet, also known as color hex triplet, sRGB, RGB, hex color, hexcode (wd:P465 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): sRGB hex triplet format for subject color (e.g. 7FFFD4) specifying the 8-bit red, green and blue components
7. eye color, also known as eyecolour, eye colour, eyecolor (wd:P1340 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): color of the irises of a person's eyes, color
8. color index (wd:P1458 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): color index of an astronomical object
9. official color, also known as official colors, signature colors, signature color (wd:P6364 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): official colors chosen to represent or identify an item
10. flower color, also known as bloom color, flower colour, colour of the flower, color of the flower, bloom colour (wd:P2827 as wdtn/pqn/psn/psv/pq/pqv/pr/ps/prn/p/prv/wdt): colour of flowers of a plant species, hybrid or cultivar, color

[Assistant] The property "color" (wd:P462) is the most relevant for describing the color of water. Now, I will check what value is given for the color property of water (wd:Q283) in Wikidata.

[Tool]
Got 5 rows and 3 columns:
| subject         | property         | object                       |
| --------------- | ---------------- | ---------------------------- |
| water (wd:Q283) | color (wdt:P462) | green (wd:Q3133)             |
| water (wd:Q283) | color (wdt:P462) | white (wd:Q23444)            |
| water (wd:Q283) | color (wdt:P462) | turquoise (wd:Q5960345)      |
| water (wd:Q283) | color (wdt:P462) | color of water (wd:Q5148636) |
| water (wd:Q283) | color (wdt:P462) | colorless (wd:Q1396399)      |

[Assistant]
The color property for water (wd:Q283) in Wikidata includes "colorless" (wd:Q1396399) among other values like green, white, turquoise, and "color of water." Since "colorless" is explicitly listed, the answer to the question "Is water colorless?" is True.

I will now provide the final SPARQL query and answer.

[Tool] Stopped generation process