PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
ASK {
  wd:Q623561 wdt:P61 wd:Q5082829 .
}

False

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

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

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

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

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

[User] Is Dr. Pepper named after its inventor?

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

[Tool]
Example 1:
Question:
In which countries can you pay using the West African CFA franc?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P38 wd:Q861690 .
}

Using entities:
West African CFA franc, also known as BCEAO franc (wd:Q861690): Currency of several West African countries

Using properties:
currency, also known as base currency, used money (wd:P38 as wdt): currency used by item, uses

Example 2:
Question:
Where did Hillel Slovak die?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q186924 wdt:P20 ?uri .
}

Using entities:
Hillel Slovak (wd:Q186924): Israeli-American musician (1962–1988), songwriter, guitarist, musician

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

Example 3:
Question:
Who is the mayor of Tel Aviv?

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

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

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

[Assistant] Based on the examples, we need to identify the entity for Dr. Pepper and then check if it has a property indicating it was named after its inventor. Let's first search for the entity "Dr. Pepper".

[Tool]
Top 10 entity alternatives:
1. Dr Pepper, also known as Dr. Pepper (wd:Q623561): carbonated soft drink
2. Keurig Dr Pepper, also known as Green Mountain Coffee, Green Mountain Coffee Roasters, Keurig Green Mountain (wd:Q3116111): American beverage company
3. Comerica Center, also known as Deja Blue Arena, Dr Pepper Arena (wd:Q637300): stadium
4. Dr. Pepper Museum (wd:Q25421126): museum
5. Dublin Dr Pepper (wd:Q5310881): popular name for a style of Dr Pepper soft drink
6. Dr. Pepper Syrup Plant, also known as Dr. Pepper Building (wd:Q124038489): historic building in Birmingham, Alabama, United States
7. Diet Dr Pepper (wd:Q19903950): low-calorie soft drink
8. Pepper Drain (wd:Q49265671): canal in Imperial County, California, United States of America
9. Dr. William Pepper (wd:Q94045516): scientific article published in September 1898
10. Dr. Peppercorn (wd:Q20536983): painting by Gene Davis

[Assistant] The top result is the correct entity for Dr. Pepper, which is `wd:Q623561`. Now let's look for properties that might indicate whether Dr. Pepper was named after its inventor. We'll search for properties related to naming or origin for this entity.

[Tool]
Top 10 property alternatives:
1. named after, also known as toponym, namesake, named in honor of, named for, etymology (wd:P138 as p/wdt): entity or event that inspired the subject's name, or namesake (i...fier "applies to name" (P5168) can be used to indicate which one
2. official name, also known as long title, name, official title, registered name, full title (wd:P1448 as p/wdt): official name of the subject in its official language(s), name
3. subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as p/wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
4. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as p/wdt): time when an entity begins to exist; for date of official opening use P1619, start time
5. discoverer or inventor, also known as inventor or discoverer, inventor, invented by, invented, introduced by (wd:P61 as p/wdt): subject who discovered, first described, invented, or developed this discovery or invention or scientific hypothesis or theory
6. country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as p/wdt): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country
7. manufacturer, also known as manufactured by, provider, provided by, product of, producer (wd:P176 as p/wdt): (main or final) manufacturer or producer of this product
8. 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)
9. logo image, also known as masthead, wordmark, trademark, trade mark, sign (wd:P154 as p/wdt): graphic mark or emblem commonly used by commercial enterprises, organizations and products, icon
10. X (Twitter) username, also known as twitter.com/, X username, X handle, x.com/, X account (wd:P2002 as p/wdt): username on X (formerly Twitter); do not include the '@' symbol, website username or ID

No other items found

[Assistant] The property `named after` (wd:P138) seems relevant. We can use this property to check if Dr. Pepper is named after its inventor. Let's construct a SPARQL query to see if there is a value for this property for Dr. Pepper.

[Tool]
Got 1 row and 1 column:
| namedAfter                      |
| ------------------------------- |
| Charles T. Pepper (wd:Q5082829) |

[Assistant] The result shows that Dr. Pepper is named after Charles T. Pepper (wd:Q5082829). To confirm if Charles T. Pepper is the inventor of Dr. Pepper, we need to check if he is listed as the inventor of the drink. Let's use the property `discoverer or inventor` (wd:P61) to see if Charles T. Pepper is associated with the invention of Dr. Pepper.

[Tool]
Got 1 row and 1 column:
| inventor                                 |
| ---------------------------------------- |
| Charles Courtice Alderton (wd:Q24004555) |

[Assistant]
The result shows that the inventor of Dr. Pepper is Charles Courtice Alderton (wd:Q24004555), not Charles T. Pepper (wd:Q5082829). Therefore, Dr. Pepper is not named after its inventor.

To finalize this, we will use an ASK query to confirm this conclusion.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?album ?releaseDate WHERE {
  ?album wdt:P361 wd:Q83793562 ; wdt:P577 ?releaseDate .
}
ORDER BY ASC ( ?releaseDate )
LIMIT 1

The first album of Jay Chou is 'Fantasy' (wd:Q595532), released on September 14, 2001.

[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] The first album of Jay Chou

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

[Tool]
Example 1:
Question:
To which artistic movement did the painter of The Three Dancers belong?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q3235867 wdt:P170 ?painter .
  ?painter wdt:P135 ?uri .
}

Using entities:
The Three Dancers (wd:Q3235867): painting by Pablo Picasso

Using properties:
movement, also known as subculture, trend, scientific movement, school, philosophical movement (wd:P135 as wdt): literary, artistic, scientific or philosophical movement or scen...ed with this person or work. For political ideologies use P1142.
creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as wdt): maker of this creative work or other object (where no more specific property exists)

Example 2:
Question:
When is the movie Worst Case Scenario going to be in cinemas in the Netherlands?

SPARQL:
SELECT DISTINCT ?date WHERE {
  wd:Q6667101 wdt:P577 ?date
}

Using entities:
Worst Case Scenario (wd:Q6667101): 2008 unfinished film

Using properties:
publication date, also known as launched, published, publication time, publication, pubdate (wd:P577 as wdt): date or point in time when a work was first published or released, point in time

Example 3:
Question:
How many inhabitants does Maribor have?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q1010 wdt:P1082 ?uri .
}

Using entities:
Maribor (wd:Q1010): city in Slovenia

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

[Assistant] Based on the examples, we need to identify the entity for Jay Chou and the property for his albums. Let's start by searching for Jay Chou.

[Tool]
Top 10 entity alternatives:
1. Jay Chou, also known as President Chou, Zhou Jielun, Chou Chieh-lun (wd:Q238819): Taiwanese pop singer, songwriter, and actor, recording artist, record producer, film director, songwriter, composer, director, rapper, singer, actor
2. Jayanta Choudhury (wd:Q102339960): Ph.D. University of Louisiana at Lafayette 2008
3. Jaya Choudhary (wd:Q88317282): researcher
4. Jayadratha Choudhury (wd:Q107562664): Indian Odia-language writer, writer
5. Jay Chou's Bedtime Stories (wd:Q24595331): 2016 studio album by Jay Chou
6. Jayanta Narayan Choudhury, also known as Jayanto Narayan Choudhury (wd:Q110437452): Indian police officer
7. Choudhury Jayprakash Das, also known as Choudhury Jayaprakash Das, Caudhurī Jaẏaprakāśa Dāsa (wd:Q60511536): Indian actor and academic, film actor, teacher, actor
8. Jay Chou 2007 World Tour Concert Live (wd:Q1100149): live album
9. J, also known as ᴊ, Juliett, Juliet, j, jay (wd:Q9773): 10th-17th letter of Latin alphabets
10. Eurasian Jay, also known as Garrulus glandarius, Jay, European Jay (wd:Q25354): species of bird

[Assistant] The correct entity for Jay Chou is `wd:Q238819`. Now let's find out the property that links Jay Chou to his albums. We can search for properties related to albums or discography for Jay Chou.

[Tool]
Top 10 property alternatives:
1. AllMusic artist ID, also known as AllMusic, AllMusic ID, amg artist (wd:P1728 as p/wdt): identifier for an artist, musical group, or record label in the AllMusic database (record labels are listed as "artists")
2. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as p/wdt): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
3. discography, also known as discography link, recording catalog (wd:P358 as p/wdt): item for list pages with discography of artist or band, list of works
4. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
5. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as p/wdt): the object is a country that recognizes the subject as its citizen, country
6. record label, also known as label, labels (wd:P264 as p/wdt): brand and trademark associated with the marketing of subject music recordings and music videos
7. 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 p/wdt): identifier for a musical artist or author in the U.S. version of Apple Music
8. work period (start), also known as start working, flourished (start), start time for work, start date of activity, fl. (start) (wd:P2031 as p/wdt): start of period during which a person or group flourished (fl. = "floruit") in their professional activity, start time, floruit
9. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as p/wdt): award or recognition received by a person, organization or creative work
10. instrument, also known as uses this instrument, teaches instrument, instruments, plays this instrument, plays instrument (wd:P1303 as p/wdt): musical instrument that a person plays or teaches or used in a music occupation, uses

No other items found

[Assistant] None of the top 10 properties directly link Jay Chou to his albums. However, the property `discography` (`wd:P358`) seems to be related to a list of works, which might include albums. To confirm, let's check the triples where Jay Chou is the subject and `discography` is the property.

[Tool]
Got 1 row and 3 columns:
| subject               | property               | object      |
| --------------------- | ---------------------- | ----------- |
| Jay Chou (wd:Q238819) | discography (wdt:P358) | wd:Q1100151 |

[Assistant]
The `discography` property (`wdt:P358`) links Jay Chou to an entity `wd:Q1100151`, which is likely a list of his albums. To find the first album, we need to explore the entity `wd:Q1100151` and see if it contains information about the albums and their release dates.

Let's list the triples where `wd:Q1100151` is the subject to understand what information it holds.

[Tool]
Got 57 rows and 3 columns, showing the first 10 rows below:
| subject     | property              | object                                          |
| ----------- | --------------------- | ----------------------------------------------- |
| wd:Q1100151 | instance of (wdt:P31) | Wikimedia artist discography (wd:Q104635718)    |
| wd:Q1100151 | has list (wdt:P2354)  | wd:Q129485781                                   |
| wd:Q1100151 | schema:description    | discografie van Jay Chou (nl)                   |
| wd:Q1100151 | schema:name           | dioscliosta Jay Chou (ga)                       |
| wd:Q1100151 | rdf:type              | wikibase:Item                                   |
| wd:Q1100151 | rdfs:label            | dioscliosta Jay Chou (ga)                       |
| wd:Q1100151 | skos:altLabel         | discography of Jay Chou (en)                    |
| wd:Q1100151 | skos:prefLabel        | dioscliosta Jay Chou (ga)                       |
| wd:Q1100151 | instance of (p:P31)   | s:Q1100151-15B410B8-92F5-470E-84E4-1A93907F8399 |
| wd:Q1100151 | has list (wdt:P2354)  | wd:Q83793562                                    |
| ...         | ...                   | ...                                             |

[Assistant]
The entity `wd:Q1100151` represents Jay Chou's discography and has a list of albums. The property `has list` (`wdt:P2354`) points to another entity that contains the list of albums. Let's explore the entity `wd:Q129485781` to find the albums and their release dates.

We will list the triples where `wd:Q129485781` is the subject to see what information it contains.

[Tool]
Got 11 rows and 3 columns, showing the first 10 rows below:
| subject       | property                | object                                            |
| ------------- | ----------------------- | ------------------------------------------------- |
| wd:Q129485781 | instance of (wdt:P31)   | Wikimedia singles discography (wd:Q59248059)      |
| wd:Q129485781 | part of (wdt:P361)      | wd:Q1100151                                       |
| wd:Q129485781 | is a list of (wdt:P360) | single (wd:Q134556)                               |
| wd:Q129485781 | schema:description      | Wikimedia singles discography (en)                |
| wd:Q129485781 | schema:name             | Jay Chou singles discography (en)                 |
| wd:Q129485781 | rdf:type                | wikibase:Item                                     |
| wd:Q129485781 | rdfs:label              | Jay Chou singles discography (en)                 |
| wd:Q129485781 | skos:prefLabel          | Jay Chou singles discography (en)                 |
| wd:Q129485781 | instance of (p:P31)     | s:Q129485781-e9b87bca-4fd5-6f48-9af7-75a1c042cd30 |
| wd:Q129485781 | part of (p:P361)        | s:Q129485781-8c7c997d-4d41-3492-2bbd-d9ee4d8280b6 |
| ...           | ...                     | ...                                               |

[Assistant]
It appears that `wd:Q129485781` is a list of Jay Chou's singles, not his albums. We need to find the correct list of albums. Let's try the other entity `wd:Q83793562` that is linked to `wd:Q1100151` via the `has list` property.

We will list the triples where `wd:Q83793562` is the subject to see what information it contains.

[Tool]
Got 19 rows and 3 columns, showing the first 10 rows below:
| subject      | property                             | object                                             |
| ------------ | ------------------------------------ | -------------------------------------------------- |
| wd:Q83793562 | instance of (wdt:P31)                | Wikimedia albums discography (wd:Q59191021)        |
| wd:Q83793562 | part of (wdt:P361)                   | wd:Q1100151                                        |
| wd:Q83793562 | is a list of (wdt:P360)              | album (wd:Q482994)                                 |
| wd:Q83793562 | category related to list (wdt:P1754) | wd:Q8564214                                        |
| wd:Q83793562 | schema:description                   | Wikimedia albums discography (en)                  |
| wd:Q83793562 | schema:name                          | albaim de chuid Jay Chou in ord croineolaíoch (ga) |
| wd:Q83793562 | rdf:type                             | wikibase:Item                                      |
| wd:Q83793562 | rdfs:label                           | albaim de chuid Jay Chou in ord croineolaíoch (ga) |
| wd:Q83793562 | skos:altLabel                        | Jay Chou albums discography (en)                   |
| wd:Q83793562 | skos:prefLabel                       | albaim de chuid Jay Chou in ord croineolaíoch (ga) |
| ...          | ...                                  | ...                                                |

[Assistant]
The entity `wd:Q83793562` is indeed the list of Jay Chou's albums. Now, we need to find the albums and their release dates. We will list the triples where `wd:Q83793562` is the subject and look for properties that link to albums and their release dates.

Let's list the triples where `wd:Q83793562` is the subject and the object is an album.

[Tool]
Got 1 row and 3 columns:
| subject      | property                | object             |
| ------------ | ----------------------- | ------------------ |
| wd:Q83793562 | is a list of (wdt:P360) | album (wd:Q482994) |

[Assistant]
The property `is a list of` (`wdt:P360`) confirms that `wd:Q83793562` is a list of albums. However, we need to find the specific albums and their release dates. Let's search for the albums that are part of this list.

We will use the `part of` property (`wdt:P361`) to find the albums that are part of `wd:Q83793562` and then look for their release dates using the `publication date` property (`wdt:P577`).

Let's start by finding the albums that are part of `wd:Q83793562`.

[Tool]
Got 24 rows and 3 columns, showing the first 10 rows below:
| subject                                   | property           | object       |
| ----------------------------------------- | ------------------ | ------------ |
| Common Jasmin Orange (wd:Q262153)         | part of (wdt:P361) | wd:Q83793562 |
| Fantasy (wd:Q595532)                      | part of (wdt:P361) | wd:Q83793562 |
| Still Fantasy (wd:Q259680)                | part of (wdt:P361) | wd:Q83793562 |
| The Eight Dimensions (wd:Q680715)         | part of (wdt:P361) | wd:Q83793562 |
| November's Chopin (wd:Q715325)            | part of (wdt:P361) | wd:Q83793562 |
| Aiyo, Nor Bad (wd:Q18652147)              | part of (wdt:P361) | wd:Q83793562 |
| Ye Hui Mei (wd:Q699622)                   | part of (wdt:P361) | wd:Q83793562 |
| Capricorn (wd:Q704376)                    | part of (wdt:P361) | wd:Q83793562 |
| Jay Chou's Bedtime Stories (wd:Q24595331) | part of (wdt:P361) | wd:Q83793562 |
| The Era (wd:Q541795)                      | part of (wdt:P361) | wd:Q83793562 |
| ...                                       | ...                | ...          |

[Assistant]
We have a list of Jay Chou's albums that are part of the discography `wd:Q83793562`. Now, we need to find the release dates of these albums. We will use the `publication date` property (`wdt:P577`) to get the release dates.

Let's construct a SPARQL query to find the first album by Jay Chou based on the earliest release date.

```sparql
SELECT ?album ?releaseDate WHERE {
  ?album wdt:P361 wd:Q83793562 ;
         wdt:P577 ?releaseDate .
}
ORDER BY ASC(?releaseDate)
LIMIT 1
```

This query will return the album with the earliest release date, which should be the first album by Jay Chou.

Let's execute this query.

[Tool]
Got 1 row and 2 columns:
| album                | releaseDate                         |
| -------------------- | ----------------------------------- |
| Fantasy (wd:Q595532) | 2001-09-14T00:00:00Z (xsd:dateTime) |

[Assistant]
The first album by Jay Chou is "Fantasy" (wd:Q595532), which was released on September 14, 2001.

Here is the final SPARQL query and answer:

```sparql
SELECT ?album ?releaseDate WHERE {
  ?album wdt:P361 wd:Q83793562 ;
         wdt:P577 ?releaseDate .
}
ORDER BY ASC(?releaseDate)
LIMIT 1
```

The first album of Jay Chou is "Fantasy" (wd:Q595532), released on September 14, 2001.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?show ?showLabel WHERE {
  ?show wdt:P31 wd:Q5398426 .
  ?show wdt:P580 ?date .
  FILTER ( YEAR( ?date ) = 1975 ) .
  OPTIONAL {
    ?show rdfs:label ?showLabel .
    FILTER ( LANG( ?showLabel ) = 'en' )
  }
}
LIMIT 100

Got 100 rows and 2 columns, showing the first 5 and last 5 rows below:
| show                             | showLabel               |
| -------------------------------- | ----------------------- |
| Gabriela (wd:Q10287918)          | Gabriela (en)           |
| On the Mat (wd:Q10340891)        | On the Mat (en)         |
| Cher (wd:Q10381261)              | Cher (en)               |
| Carry On Laughing (wd:Q1045360)  | Carry On Laughing (en)  |
| Space: 1999 (wd:Q1045743)        | Space: 1999 (en)        |
| ...                              | ...                     |
| Thalassa (wd:Q3519442)           | Thalassa (en)           |
| The Victory Garden (wd:Q3523222) | The Victory Garden (en) |
| wd:Q3571115                      |                         |
| Doc (wd:Q3712420)                | Doc (en)                |
| Fay (wd:Q3740518)                | Fay (en)                |

The following TV shows aired for the first time in 1975, the same year as Saturday Night Live: Gabriela, On the Mat, Cher, Carry On Laughing, Space: 1999, Thalassa, The Victory Garden, Doc, Fay.

[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 shows aired for the first time the same year as Saturday Night Live ?

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

[Tool]
Example 1:
Question:
Which poet wrote the most books?

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

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

Using properties:
occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
author, also known as writer, written by, poet, playwright, maker (wd:P50 as wdt): main creator(s) of a written work (use on works, not humans); us...hor name string) when Wikidata item is unknown or does not exist, creator

Example 2:
Question:
When was the Statue of Liberty built?

SPARQL:
SELECT DISTINCT ?date WHERE {
  wd:Q9202 wdt:P571 ?date .
}

Using entities:
Statue of Liberty, also known as La Liberte eclairant la monde, La Liberté éclairant le monde, Liberty Enlightening the World, The Statue of Liberty Enlightening the World (wd:Q9202): sculpture on Liberty Island in New York Harbor in New York City, New York, United States

Using properties:
inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as wdt): time when an entity begins to exist; for date of official opening use P1619, start time

Example 3:
Question:
Show me all the breweries in Australia.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q131734 .
  ?uri wdt:P17 wd:Q408 .
}

Using entities:
brewery, also known as beer company, brewing company (wd:Q131734): business that makes and sells beer
Australia, also known as AU, The Commonwealth of Australia, Stria, Straya, Stralia (wd:Q408): country in Oceania

Using properties:
country, also known as sovereign state, state, land, host country (wd:P17 as wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

[Assistant] Based on the examples, we need to identify the entity for "Saturday Night Live" and the property for "first aired". Then we can construct a query to find other shows that aired in the same year.

[Tool]
Top 10 entity alternatives:
1. Saturday Night Live, also known as Saturday Night, NBC's Saturday Night (wd:Q13979): American late-night live television sketch comedy show
2. Saturday Night Live (wd:Q6122059): television series
3. Saturday Night Live (wd:Q23039888): tv show aired in 2016
4. Saturday Night Live (wd:Q28452163): album by Trouble Funk
5. Saturday Night Live Korea, also known as SNL Korea, SNL.KOREA, SNL Korea 6 (wd:Q7426718): 2011 South Korean television series
6. Le Saturday Night Live (wd:Q28194825): French late-night live television comedy show
7. Saturday Night Live Japan (wd:Q11304712): Japanese TV series or program
8. history of Saturday Night Live, also known as Saturday Night Live history (wd:Q5866387): List article
9. Katy Perry/Robyn, also known as Saturday Night Live Season 37 Episode 9, Saturday Night Live S37E9, Saturday Night Live, season 37 episode 9 (wd:Q5483492): episode of Saturday Night Live (S37 E9)
10. Saturday Night Live Samurai (wd:Q7426709): recurring SNL character, samurai

[Assistant] The top result, "Saturday Night Live" (wd:Q13979), seems to be the correct entity for the show. Now let's find the property for "first aired".

[Tool]
Top 10 property alternatives:
1. original broadcaster, also known as TV channel, television channel, radio station, radio network, original network (wd:P449 as p/wdt): network(s) or service(s) that originally broadcast a radio or television program, broadcast by
2. number of episodes, also known as series length, no. of episodes, episodes, episode count (wd:P1113 as p/wdt): number of episodes in a film/TV/radio series, number of parts of this work
3. start time, also known as start date, since, valid, join time, joined (wd:P580 as p/wdt): time an entity begins to exist or a statement starts being valid, point in time
4. title, also known as name, titled, page name, original title, known as (wd:P1476 as p/wdt): published name of a work, such as a newspaper article, a literary work, piece of music, a website, or a performance work, name
5. original language of film or TV show, also known as media language, original language, language of the original work, created on language (wd:P364 as p/wdt): language in which a film or a performance work was originally cr... works and songs; use P407 ("language of work or name") instead., language of work or name
6. TheTVDB series ID, also known as TheTVDB.com series ID (wd:P4835 as p/wdt): identifier for a television series at TheTVDB.com
7. presenter, also known as TV host, TV presenter, presented by, hostess, hosted by (wd:P371 as p/wdt): main role in presenting a radio or television program or a performing arts show, significant person, cast member
8. production company, also known as broadcasting company, theatrical troupe, theatre company, theater company, studio (wd:P272 as p/wdt): company that produced this film, audio or performing arts work
9. cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as p/wdt): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
10. TV Maze series ID, also known as TV Maze ID (wd:P8600 as p/wdt): identifier number in the TV Maze database of shows

No other items found

[Assistant] The property "start time" (wdt:P580) seems to be the closest match for "first aired". Let's confirm this by checking the value of this property for "Saturday Night Live".

[Tool]
Got 1 row and 1 column:
| date                                |
| ----------------------------------- |
| 1975-10-11T00:00:00Z (xsd:dateTime) |

[Assistant]
The "start time" (wdt:P580) property for "Saturday Night Live" (wd:Q13979) is indeed the date it first aired, which is October 11, 1975.

Now, we need to find other shows that aired for the first time in the same year. We'll look for TV shows that have the "start time" property set to a date in 1975.

Let's construct the SPARQL query to find these shows.

[Tool]
Got 100 rows and 2 columns, showing the first 5 and last 5 rows below:
| show                             | showLabel               |
| -------------------------------- | ----------------------- |
| Gabriela (wd:Q10287918)          | Gabriela (en)           |
| On the Mat (wd:Q10340891)        | On the Mat (en)         |
| Cher (wd:Q10381261)              | Cher (en)               |
| Carry On Laughing (wd:Q1045360)  | Carry On Laughing (en)  |
| Space: 1999 (wd:Q1045743)        | Space: 1999 (en)        |
| ...                              | ...                     |
| Thalassa (wd:Q3519442)           | Thalassa (en)           |
| The Victory Garden (wd:Q3523222) | The Victory Garden (en) |
| wd:Q3571115                      |                         |
| Doc (wd:Q3712420)                | Doc (en)                |
| Fay (wd:Q3740518)                | Fay (en)                |

[Assistant]
The SPARQL query successfully returned a list of TV shows that first aired in 1975, the same year as "Saturday Night Live". Here are some of the shows:

- Gabriela
- On the Mat
- Cher
- Carry On Laughing
- Space: 1999
- Thalassa
- The Victory Garden
- Doc
- Fay

We can now finalize the SPARQL query and provide the answer.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?team ( COUNT( ?finals ) AS ?wins ) WHERE {
  ?finals wdt:P31 wd:Q842375 ; wdt:P1346 ?team .
}
GROUP BY ?team
ORDER BY DESC ( ?wins )

Got 18 rows and 2 columns, showing the first 5 and last 5 rows below:
| team                               | wins         |
| ---------------------------------- | ------------ |
| Boston Celtics (wd:Q131371)        | 17 (xsd:int) |
| Los Angeles Lakers (wd:Q121783)    | 16 (xsd:int) |
| Chicago Bulls (wd:Q128109)         | 6 (xsd:int)  |
| San Antonio Spurs (wd:Q159729)     | 5 (xsd:int)  |
| Golden State Warriors (wd:Q157376) | 4 (xsd:int)  |
| ...                                | ...          |
| Atlanta Hawks (wd:Q159893)         | 1 (xsd:int)  |
| Washington Wizards (wd:Q169165)    | 1 (xsd:int)  |
| Dallas Mavericks (wd:Q132893)      | 1 (xsd:int)  |
| Seattle SuperSonics (wd:Q235326)   | 1 (xsd:int)  |
| Baltimore Bullets (wd:Q2928124)    | 1 (xsd:int)  |

The NBA teams that have won the most seasons are the Boston Celtics with 17 wins and the Los Angeles Lakers with 16 wins.

[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 NBA teams have won the most seasons?

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

[Tool]
Example 1:
Question:
Who created Goofy?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q111135 wdt:P170 ?uri .
}

Using entities:
Goofy, also known as Dippy Dawg, George Geef, Goofy Goof (wd:Q111135): Disney cartoon character

Using properties:
creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as wdt): maker of this creative work or other object (where no more specific property exists)

Example 2:
Question:
Give me the homepage of Forbes.

SPARQL:
SELECT ?uri WHERE {
  wd:Q25161472 wdt:P856 ?uri
}

Using entities:
Forbes, also known as forbes.com, Forbes magazine (wd:Q25161472): American business magazine

Using properties:
official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as wdt): URL of the official page of an item (current or former). Usage: ...but see the "Hijacked or dead websites" section of the Talk page, URL

Example 3:
Question:
Give me the grandchildren of Elvis Presley.

SPARQL:
SELECT DISTINCT ?o2 WHERE {
  wd:Q303 wdt:P40 ?o1 .
  ?o1 wdt:P40 ?o2
}

Using entities:
Elvis Presley, also known as The King of Rock'n'Roll, Elvis A. Presley, King of Rock'n'Roll, Elvis, Elvis Aaron Presley (wd:Q303): American singer and actor (1935–1977), military personnel, military officer, philanthropist, film actor, composer, activist, singer, actor

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

[Assistant] Based on the examples, we need to identify the NBA teams and the number of seasons they have won. Let's first search for the NBA entity.

[Tool]
Top 10 entity alternatives:
1. National Basketball Association, also known as Basketball Association of America, BAA, NBA, National Basketball Assn., Nat'l Basketball Assn. (wd:Q155223): North American professional men's basketball league
2. National Book Award, also known as American NBA, ANBA, NBA, American National Book Award (wd:Q572316): United States literary award in four categories
3. New Barnet railway station, also known as NBA, New Barnet Station (wd:Q1217434): railway station in New Barnet, London Borough of Barnet, England, UK
4. Niger Basin Authority, also known as Autorite du Bassin du Niger, NBA, Autorité du Bassin du Niger, ABN (wd:Q1162546): intergovernmental organisation in West Africa
5. Sybil, also known as NBA (wd:Q2915054): 1973 book Sybil. The True Story of A Woman Possessed By 16 Separaste Personalities.
6. National Biodiversity Authority, also known as NBA (wd:Q5054185): government agency in India
7. Nba Saghru, also known as NBA (wd:Q3874050): Moroccan singer-songwriter, poet and painter (1982-2011), singer-songwriter, painter, poet
8. .nba (wd:Q26980848)
9. Namibia Sports Commission, also known as NBA, Namibia Sports Commission*, Namibia Sport Commision, Namibia Sport Commission (wd:Q1490962): Umbrella organization of all sports associations in Namibia
10. NBA (wd:Q17062168): song by American rapper Joe Budden

[Assistant] The correct entity for the National Basketball Association (NBA) is `wd:Q155223`. Next, let's find the property that indicates the number of championships or seasons won by a team.

[Tool]
Top 10 property alternatives:
1. number of wins, also known as games won, won, wins, W, sporting wins (wd:P1355 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): number of sporting matches, games or events won
2. competition won, also known as won event, won, winner of, victory (wd:P2522 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): competition or sports event won by the subject, participant in
3. sports competition competed at (wd:P5249 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): edition of sports competitions at which the club or team that pl...ple: 2012–13 FC Barcelona season → 2012–13 UEFA Champions League
4. winner, also known as nominee, prizewinner, titleholder, top dog, victor (wd:P1346 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): winner of a competition or similar event, not to be used for awa...ssibly qualified with "for work" (P1686)) or for wars or battles, participating team, participant
5. participant in, also known as participated in, present at, takes part, took part, took part in (wd:P1344 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): event in which a person or organization was/is a participant; inverse of P710 or P1923, significant event, part of
6. points for, also known as championship points, competition points, league points, pf, points (wd:P1358 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): number of points in a league table or decathlon. (Use P1351 for goals/points in a match)
7. trophy awarded, also known as cup awarded, diploma awarded, medal awarded (wd:P4622 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): trophy awarded at the end of a selection process or of a competi...winners or finishers under the form of a cup, a medal, a diploma
8. commemorates, also known as monument to, memorial to, memorializes, marks, in memory of (wd:P547 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): what the place, monument, memorial, or holiday, commemorates, main subject
9. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): award or recognition received by a person, organization or creative work
10. member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): sports teams or clubs that the subject represents or represented, member of

[Assistant]
The property `number of wins` (`wd:P1355`) seems to be the most relevant for our purpose. However, it is important to verify if this property is used specifically for NBA championships. Let's check the usage of this property for NBA teams.

First, let's find some NBA teams.

[Tool]
Top 10 entity alternatives:
1. NBA All-Defensive Team (wd:Q1465181): annual National Basketball Association honor
2. NBA All-Rookie Team (wd:Q1418009): award
3. NBA 35th Anniversary Team (wd:Q6130281): Wikipedia list article
4. NBA 25th Anniversary Team (wd:Q4383249): Lists of player who still playing in NBA
5. NBA anniversary teams (wd:Q109299766): Fantasy teams to commemorate the NBA's anniversaries
6. Valley Suns, also known as Phoenix NBA G League team (wd:Q124649324): basketball team in Tempe, Arizona
7. NBA Live Legend All-Stars Teams (wd:Q16955386)
8. Billionaires Lay Out Bucks for NBA Team (wd:Q114844156): Wall Street Journal article (April 16, 2014)
9. National Basketball Association, also known as Basketball Association of America, BAA, NBA, National Basketball Assn., Nat'l Basketball Assn. (wd:Q155223): North American professional men's basketball league
10. team (wd:Q327245): group linked in a common purpose

[Assistant]
It looks like the search for "NBA team" did not return the specific teams we were looking for. Let's try searching for some well-known NBA teams individually to get their IRIs.

Let's start with the Boston Celtics.

[Tool]
Top 10 entity alternatives:
1. Boston Celtics, also known as Celtics, Celts, C's, Green and White (wd:Q131371): NBA team based in Boston; tied with most NBA Championships
2. history of the Boston Celtics, also known as the Boston Celtics history, Boston Celtics history (wd:Q5869142): The Celtics are an NBA franchise
3. 2018–19 Boston Celtics season (wd:Q54866896): season of National Basketball Association team the Boston Celtics
4. 2021–22 Boston Celtics season (wd:Q107723060): NBA professional basketball team season
5. 2022–23 Boston Celtics season (wd:Q112724824): NBA professional basketball team season
6. 1956–57 Boston Celtics season (wd:Q3465057): NBA basketball team season (Season champions)
7. 1962–63 Boston Celtics season (wd:Q628110): NBA basketball team season (NBA champions)
8. 1959–60 Boston Celtics season (wd:Q515484): NBA basketball team season (won championship)
9. 2020–21 Boston Celtics season (wd:Q98711426): NBA professional basketball team season
10. 2019–20 Boston Celtics season (wd:Q63859184): NHL ice hockey team season

[Assistant]
The correct entity for the Boston Celtics is `wd:Q131371`. Now, let's check if the property `number of wins` (`wd:P1355`) is used for this team to indicate the number of championships won.

We'll run a SPARQL query to check this.

[Tool] Got no rows and 1 columns

[Assistant]
It appears that the property `number of wins` (`wd:P1355`) is not used for the Boston Celtics to indicate the number of championships won. Let's try another property, such as `competition won` (`wd:P2522`), to see if it provides the information we need.

Let's run a SPARQL query to check if the `competition won` property is used for the Boston Celtics.

[Tool] Got no rows and 1 columns

[Assistant]
It seems that the `competition won` property (`wd:P2522`) is also not used for the Boston Celtics to indicate the number of championships won. Let's try another approach by looking for the property that directly indicates the number of championships won by an NBA team.

We can search for the property again with a more specific query.

Let's search for the property "NBA championships won".

[Tool]
Top 10 property alternatives:
1. number of wins, also known as games won, won, wins, W, sporting wins (wd:P1355 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): number of sporting matches, games or events won
2. Hoopla artist ID, also known as hoopladigital.com (wd:P6868 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): identifier for an individual on Hoopla
3. winner, also known as nominee, prizewinner, titleholder, top dog, victor (wd:P1346 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): winner of a competition or similar event, not to be used for awa...ssibly qualified with "for work" (P1686)) or for wars or battles, participating team, participant
4. Basketball Reference NBA coach ID, also known as Basketball-Reference.com NBA coach ID (wd:P4718 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): identifier for a NBA coach on the Basketball Reference website
5. NBA.com player ID (wd:P3647 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): identifier for a basketball player on the National Basketball Association's website
6. member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): sports teams or clubs that the subject represents or represented, member of
7. statistical leader, also known as most valuable player, MVP, record setter, statistical leader (wd:P3279 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): leader of a sports tournament in one of statistical qualities (points, assists, rebounds etc.).
8. Basketball Reference NBA player ID, also known as Basketball-Reference.com NBA player ID, BRCNBA (wd:P2685 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): identifier for a NBA player on the Basketball Reference website
9. Eurobasket.com coach ID, also known as eurobasket.com coach identifier, eurobasket.com ID, eurobasket.com identifier, eurobasket ID (wd:P6865 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): identifier for a basketball coach at Eurobasket.com
10. Eurobasket.com player ID, also known as Eurobasket.com ID, eurobasket.com identifier (wd:P3527 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): ID for a basketball player at Eurobasket.com

[Assistant]
None of the properties listed seem to directly indicate the number of NBA championships won by a team. However, we can try a different approach by looking for the teams that have won the NBA championship and then counting the number of times each team has won.

Let's search for the NBA championship event and see if we can find the teams that have won it.

First, let's find the entity for the NBA championship.

[Tool]
Top 10 entity alternatives:
1. NBA Championship ring, also known as The NBA Championship (wd:Q18156668): Championship ring for winning the NBA Finals
2. Larry O'Brien Championship Trophy, also known as Larry O'Brien NBA Championship Trophy (wd:Q31736): basketball trophy
3. 1957 NBA World Championship Series, also known as 1957 National Basketball Association World Championship Series, 1957 NBA Finals, 1957 National Basketball Association Finals (wd:Q3072448): 1957 basketball championship series
4. 1952 NBA World Championship Series, also known as 1952 National Basketball Association World Championship Series, 1952 NBA Finals, 1952 National Basketball Association Finals (wd:Q4567490): 1952 basketball championship series
5. 1950 NBA World Championship Series, also known as 1950 National Basketball Association Finals, 1950 National Basketball Association World Championship Series, 1950 NBA Finals, first NBA Finals (wd:Q4566866): basketball championship series of the first National Basketball ...iation season (1st annual NBA finale, officially the 4th annual)
6. 1951 NBA World Championship Series, also known as 1951 National Basketball Association World Championship Series, 1951 NBA Finals, 1951 National Basketball Association Finals (wd:Q4567168): 1951 basketball championship series
7. 1985 NBA World Championship Series, also known as 1985 National Basketbal Association World Championship Series, 1985 National Basketball Association Finals, 1985 NBA Finals (wd:Q3072478): 1985 basketball championship series
8. 1983 NBA World Championship Series, also known as 1983 NBA Finals, Showdown '83, 1983 National Basketball Association World Championship Series, 1983 National Basketball Association Finals (wd:Q2886405): 1983 basketball championship series
9. 1984 NBA World Championship Series, also known as 1984 National Basketball Association Finals, 1984 National Basketball Association World Championship Series, 1984 NBA Finals, Showdown '84 (wd:Q3072477): 1984 basketball championship series
10. 1987 NBA World Championship Series, also known as 1987 National Basketball Association World Championship Series, 1987 NBA Finals, 1987 National Basketball Association Finals (wd:Q3072482): 1987 basketball championship series

[Assistant]
The correct entity for the NBA championship is `wd:Q18156668` (NBA Championship ring). However, this entity represents the championship ring rather than the event itself. Let's try searching for the NBA Finals, which is the event where the championship is decided.

Let's search for the NBA Finals.

[Tool]
Top 10 entity alternatives:
1. NBA Finals, also known as NBA World Championship Series [until 1987], NBA title, National Basketball Association ...Championship Series [until 1987], BAA World Championship Series [1947-49], Basketball Association of Americ...ld Championship Series [1947-49] (wd:Q842375): championship series of the National Basketball Association, annu...al Basketball Association World Championship Series through 1987
2. Bill Russell NBA Finals Most Valuable Player Award, also known as Bill Russell NBA Finals MVP Award, NBA Finals Most Valuable Player, NBA Finals Most Valuable Player Award, NBA Finals MVP, NBA Finals MVP Award (wd:Q739499): award
3. 2022 NBA Finals (wd:Q112083544): 2022 edition of the NBA Finals
4. 2019 NBA Finals (wd:Q63940565): 2019 edition of the NBA Finals, between the Golden State Warriors and the Toronto Raptors
5. NBA conference finals, also known as National Basketball Association conference finals (wd:Q2628047): Eastern and Western championship series of the NBA
6. 2023 NBA Finals (wd:Q118126592): 2023 edition of the NBA Finals
7. 2021 NBA Finals (wd:Q107377340): 2021 edition of the NBA Finals between the Phoenix Suns and Milwaukee Bucks
8. 2008 NBA Finals (wd:Q2036161): 2008 basketball championship series
9. 2012 NBA Finals (wd:Q2628013): 2012 basketball championship series
10. 2016 NBA Finals (wd:Q24264147): 2016 edition of the Finals between the Cleveland Cavaliers and Golden State Warriors

[Assistant]
The correct entity for the NBA Finals is `wd:Q842375`. Now, let's find the teams that have won the NBA Finals and count the number of times each team has won.

We'll run a SPARQL query to get the teams that have won the NBA Finals and the number of times they have won.

[Tool]
Got 18 rows and 2 columns, showing the first 5 and last 5 rows below:
| team                               | wins         |
| ---------------------------------- | ------------ |
| Boston Celtics (wd:Q131371)        | 17 (xsd:int) |
| Los Angeles Lakers (wd:Q121783)    | 16 (xsd:int) |
| Chicago Bulls (wd:Q128109)         | 6 (xsd:int)  |
| San Antonio Spurs (wd:Q159729)     | 5 (xsd:int)  |
| Golden State Warriors (wd:Q157376) | 4 (xsd:int)  |
| ...                                | ...          |
| Atlanta Hawks (wd:Q159893)         | 1 (xsd:int)  |
| Washington Wizards (wd:Q169165)    | 1 (xsd:int)  |
| Dallas Mavericks (wd:Q132893)      | 1 (xsd:int)  |
| Seattle SuperSonics (wd:Q235326)   | 1 (xsd:int)  |
| Baltimore Bullets (wd:Q2928124)    | 1 (xsd:int)  |

[Assistant]
The SPARQL query has successfully returned the NBA teams that have won the most championships. The top teams are:

1. **Boston Celtics** (`wd:Q131371`) - 17 wins
2. **Los Angeles Lakers** (`wd:Q121783`) - 16 wins
3. **Chicago Bulls** (`wd:Q128109`) - 6 wins
4. **San Antonio Spurs** (`wd:Q159729`) - 5 wins
5. **Golden State Warriors** (`wd:Q157376`) - 4 wins

These are the teams that have won the most NBA seasons.

Here is the final SPARQL query and answer:

```sparql
SELECT ?team (COUNT(?finals) AS ?wins) WHERE {
  ?finals wdt:P31 wd:Q842375 ;
          wdt:P1346 ?team .
} GROUP BY ?team ORDER BY DESC(?wins)
```

Answer: The NBA teams that have won the most seasons are the Boston Celtics with 17 wins and the Los Angeles Lakers with 16 wins.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?height WHERE {
  wd:Q4176 wdt:P2048 ?height .
}

The height of Cologne Cathedral is 157 meters.

[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 high is the Cologne Cathedral ?

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

[Tool]
Example 1:
Question:
Who developed Slack?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P1056 wd:Q17130715
}

Using entities:
Slack, also known as Slack HQ, chatlyio, chatly.io (wd:Q17130715): web-based instant messaging service

Using properties:
product, material, or service produced or provided, also known as products, product or service provided, product, material, or service produced or provided, product, output (wd:P1056 as wdt): material or product produced or sold by an organization, industry, facility, or process, material or product produced by an organization, industry, facility, or process, immediate cause of

Example 2:
Question:
When was Jack Wolfskin founded?

SPARQL:
SELECT ?date WHERE {
  wd:Q536133 wdt:P571 ?date .
}

Using entities:
Jack Wolfskin, also known as Jack Wolfskin Ausrüstung für Draussen GmbH & Co. KGaA (wd:Q536133): German outdoors clothing and equipment manufacturer and retail chain

Using properties:
inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as wdt): time when an entity begins to exist; for date of official opening use P1619, start time

Example 3:
Question:
How many people live in Eurasia?

SPARQL:
SELECT DISTINCT ?val WHERE {
  wd:Q5401 wdt:P1082 ?val .
}

Using entities:
Eurasia, also known as Euroasia (wd:Q5401): continental landmass comprising Europe and Asia

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

[Assistant] Based on these examples, we need to identify the entity for Cologne Cathedral and the property for height. Let's first search for the entity "Cologne Cathedral".

[Tool]
Top 10 entity alternatives:
1. Cologne Cathedral, also known as High Cathedral of St. Peter (wd:Q4176): Roman-Catholic cathedral in Cologne, Germany
2. Cologne Cathedral (wd:Q20891184): painting by Oskar Kokoschka
3. Cologne Cathedral Seal (wd:Q1795817): part of Cologne Cathedral
4. Baptistry Cologne Cathedral (wd:Q106498805)
5. Cologne Cathedral, 1869 (wd:Q119111134): painting by James Webb (1835–1895), Bristol Museum & Art Gallery
6. Bells of Cologne Cathedral (wd:Q1795814)
7. Finials of Cologne Cathedral (wd:Q1408999): cologne cathedral
8. Organs of Cologne Cathedral, also known as Organs in Cologne Cathedral (wd:Q7102106)
9. The Beggar from Cologne Cathedral, also known as Beggar from Cologne Cathedral (wd:Q15241065): 1927 film by Rolf Randolf
10. Surroundings of Cologne Cathedral (wd:Q65233962): cologne Cathedral surroundings

[Assistant] The correct entity for Cologne Cathedral is the first one: "Cologne Cathedral, also known as High Cathedral of St. Peter" (wd:Q4176). Now let's search for the property related to height.

[Tool]
Top 10 property alternatives:
1. clearance, also known as span height, height of deck bottom, bridge height, height above water, height above valley floor (wd:P2793 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): distance between surface under bridge and bottom of a bridge deck
2. height, also known as heighth, size, depth over terrain (wd:P2048 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): vertical length of an entity, length
3. elevation above sea level, also known as MAMSL, MASL, height, elevation above mean sea level, elevation (wd:P2044 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): height of the item (geographical object) as measured relative to sea level
4. height of center of mass, also known as center of mass height, centre of gravity height, centre of mass height, CG height, CGZ (wd:P8497 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): distance between the center of gravity and the bottom of this object
5. duration, also known as time length, timespan, time span, time interval, runtime (wd:P2047 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): length of time of an event or process
6. length, also known as size, long, LOA, distance, dimension (wd:P2043 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): measured dimension of an object
7. area, also known as total area, surface area, surface, size, resolution (wd:P2046 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): area occupied by an object
8. width, also known as breadth, bus width, size (wd:P2049 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): width of an object, length
9. height of letters (wd:P12549 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): height of the letters of an inscription, height
10. entry height (wd:P13238 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): height of the entrance above ground level for boarding vehicles

[Assistant]
The correct property for height is "height" (wd:P2048). Now we can construct a simple SPARQL query to find the height of Cologne Cathedral.

Let's execute the following SPARQL query:

```sparql
SELECT ?height WHERE {
  wd:Q4176 wdt:P2048 ?height .
}
```

This query selects the height of the entity representing Cologne Cathedral.

[Tool]
Got 1 row and 1 column:
| height            |
| ----------------- |
| 157 (xsd:decimal) |

[Assistant]
The height of Cologne Cathedral is 157 meters.

Here is the final SPARQL query and the answer:

```sparql
SELECT ?height WHERE {
  wd:Q4176 wdt:P2048 ?height .
}
```

Answer: The height of Cologne Cathedral is 157 meters.

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

[Tool] Stopped generation process


PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX p: <http://www.wikidata.org/prop/>
SELECT ?secretary ?start WHERE {
  ?secretary p:P39 ?statement .
  ?statement ps:P39 wd:Q1048744 ; pq:P580 ?start .
  FILTER ( ?start < '1964-10-14T00:00:00Z' ^^ xsd:dateTime )
}
ORDER BY ?start

There were 2 General Secretaries of the CPSU before Leonid Brezhnev.

[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 General Secretaries of the CPSU were there before Leonid Brezhnev?

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

[Tool]
Example 1:
Question:
Give me the capitals of all countries in Africa.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?country wdt:P31 wd:Q6256 .
  ?country wdt:P30 wd:Q15 .
  ?country wdt:P36 ?uri .
}

Using entities:
Africa, also known as African continent (wd:Q15): continent
country, also known as countries (wd:Q6256): distinct territorial body or political entity

Using properties:
continent (wd:P30 as wdt): continent of which the subject is a part, located in/on physical feature
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as wdt): seat of government of a country, province, state or other type of administrative territorial entity

Example 2:
Question:
Where is Syngman Rhee buried?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q171684 wdt:P119 ?uri .
}

Using entities:
Syngman Rhee, also known as Yi Seung-man, Unam, Sŭng-man Yi, Rhee Syng-man, Ri Seung-man (wd:Q171684): President of South Korea from 1948 to 1960, politician, journalist, writer

Using properties:
place of burial, also known as interment, interment location, interment place, interred at, location of burial (wd:P119 as wdt): location of grave, resting place, place of ash-scattering, etc. ...veral places: e.g., re-burials, parts of body buried separately., location

Example 3:
Question:
How many inhabitants does Maribor have?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q1010 wdt:P1082 ?uri .
}

Using entities:
Maribor (wd:Q1010): city in Slovenia

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

[Assistant]
From the examples, we can see how to structure a SPARQL query to get specific information about entities. In our case, we need to find out how many General Secretaries of the CPSU were there before Leonid Brezhnev.

First, let's identify the entity for Leonid Brezhnev and the property for being a General Secretary of the CPSU.

[Tool]
Top 10 entity alternatives:
1. Leonid Brezhnev, also known as Brezhnev, Leonid Ilyich Brezhnev (wd:Q765165): General Secretary of the Communist Party of the Soviet Union (1906–1982), military personnel, politician, engineer, surveyor
2. Admiral Kuznetsov, also known as Admiral Flota Sovetskovo Soyuza Kuznetsov, aircraft carrier Admiral Kuznetsov, Leonid Brezhnev, Riga, Tbilisi (wd:Q274924): 1985 Kuznetsov-class aircraft carrier
3. Starry Metropolis, also known as Neptune, Olivia, IMO 7359498, Kareliya, Leonid Brezhnev (wd:Q22968553): ship built in 1976
4. Leonid Brezhnev (wd:Q47510509): painting by Boris Chaliapin
5. Leonid Brezhnev, also known as Whiskey on the Rocks Leonid Brezhnev (wd:Q131583282): Leonid Brezhnev as depicted in television series Whiskey on the Rocks, politician
6. Leonid Brezhnev (wd:Q58345911): Scientific article (April 2014)
7. Leonid Brezhnev (wd:Q47511657): painting by Harvey Simpson
8. Leonid Brezhnev (wd:Q47510378): painting by Burton Philip Silverman
9. Leonid Brezhnev (wd:Q47509621): painting by Boris Artzybasheff
10. Yuri Brezhnev, also known as Yuri Leonidovich Brezhnev (wd:Q8061482): Soviet politician (1933-2013), politician

[Assistant]
The correct entity for Leonid Brezhnev is `wd:Q765165`. Now, let's find the property that indicates someone was a General Secretary of the CPSU.

I will search for the property related to "General Secretary of the CPSU".

[Tool]
Top 10 property alternatives:
1. party chief representative, also known as communist party chief, Communist Party Secretary, party chief, party secretary (wd:P210 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): chief representative of a party in an institution or an administrative unit (use qualifier to identify the party)
2. general secretary, also known as secretary general, perpetual secretary, leader (wd:P3975 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): leader of a political or international organization, sometimes below the chairperson (P488), significant person, director / manager
3. Communist Party of the Russian Federation person ID, also known as CPRF ID, KPRF ID (wd:P10984 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): identifier for a member of the Communist Party of the Russian Federation
4. parliamentary group, also known as faction, party organization, party (wd:P4100 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): parliamentary group to which a member of a parliament belongs, member of
5. position held by head of the organization, also known as position held by head of the organisation, secretary's position, president's position, position held by head of the organization, office held by head of the organisation (wd:P2388 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): position of the head of this item
6. member of political party, also known as political party member, political party, party membership, party, member of party (wd:P102 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): the political party of which a person is or has been a member or otherwise affiliated, member of
7. director / manager, also known as leader, manager, manager/director, managing director, Officer-in-Charge (wd:P1037 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): person who manages any kind of group, significant person
8. general manager (wd:P505 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): general manager of a sports team. If they are also an on-field manager use P286 instead
9. organization directed by the office or position, also known as leader of, head of, leads, organization directed by, organization directed from the office (wd:P2389 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): organization which is directed by this office
10. office held by head of government, also known as title of head of government, position of head of government, office of head of government, head of government's office, position held by head of government (wd:P1313 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): political office that is fulfilled by the head of the government of this item

[Assistant]
The property that indicates someone was a General Secretary of the CPSU is `wd:P3975` (general secretary).

Now, let's construct a SPARQL query to find all the General Secretaries of the CPSU before Leonid Brezhnev. We will use the `wdt:P3975` property and filter the results to only include those who served before Leonid Brezhnev.

First, we need to find the start date of Leonid Brezhnev's term as General Secretary.

[Tool] Got no rows and 1 columns

[Assistant]
It seems that the property `wdt:P3975` does not directly provide the start date of Leonid Brezhnev's term. Let's try another approach by finding the start date using the `position held` property (`wdt:P39`) and the specific position of General Secretary of the CPSU.

First, let's find the specific position of General Secretary of the CPSU.

[Tool]
Top 10 entity alternatives:
1. General Secretary of the Communist Party of the Soviet Union, also known as First Secretary of the Communist Party of the Soviet Union, General Secretary of the Soviet Union, Gensek of the CPSU (wd:Q1048744): de facto head of state of the Soviet Union and dirigent of the Communist Party of the Soviet Union
2. Secretary of the Communist Party of the Soviet Union (wd:Q115147301)
3. General Department of the Communist Party of the Soviet Union (wd:Q16682297): organization
4. General Secretary Xi Jin-ping’s ...and Their Practical Significance (wd:Q120857259): scholarly article in Studies on Mao Zedong and Deng Xiaoping Theories, no. 9, 2019
5. Communist Party of the Soviet Union, also known as Bolshevik Party, CPSU, RCP(b), Russian Communist Party (Bolsheviks), All-Union Communist Party (Bolsheviks) (wd:Q79854): Marxist–Leninist founding and ruling party of the Soviet Union
6. Communist Party of the Soviet Union (wd:Q4229911): Political party founded in 2001
7. Communist Party of the Soviet Union (wd:Q3701765): Political party founded in 1992
8. Appeal to the General Secretary ...States of America, Ronald Reagan (wd:Q43929775): scientific article published on July 13, 1985
9. General Secretary of the Chinese Communist Party, also known as CCP General Secretary, General Secretary of the Communist Party of China, General Secretary of the Central...e of the Chinese Communist Party, General Secretary, General Secretary of the CCP (wd:Q849418): head of the Chinese Communist Party (CCP) and de facto leader of China
10. Congress of the Communist Party of the Soviet Union (wd:Q2415599): supreme decision-making body of the Communist Party of the Soviet Union

[Assistant]
The correct entity for the position of General Secretary of the Communist Party of the Soviet Union is `wd:Q1048744`.

Now, let's find the start date of Leonid Brezhnev's term as General Secretary using the `position held` property (`wdt:P39`) and the specific position `wd:Q1048744`.

[Tool]
Got 1 row and 1 column:
| start                               |
| ----------------------------------- |
| 1964-10-14T00:00:00Z (xsd:dateTime) |

[Assistant]
The start date of Leonid Brezhnev's term as General Secretary of the CPSU is October 14, 1964.

Next, we will find all the General Secretaries of the CPSU who started their terms before this date. We will use the `position held` property (`wdt:P39`) and the specific position `wd:Q1048744`, and filter the results to only include those who started their terms before October 14, 1964.

Let's construct the SPARQL query to find these individuals.

[Tool]
Got 2 rows and 2 columns:
| secretary                     | start                               |
| ----------------------------- | ----------------------------------- |
| Joseph Stalin (wd:Q855)       | 1922-04-03T00:00:00Z (xsd:dateTime) |
| Nikita Khrushchev (wd:Q35314) | 1953-09-14T00:00:00Z (xsd:dateTime) |

[Assistant]
The SPARQL query has returned two General Secretaries of the CPSU who started their terms before Leonid Brezhnev:

1. Joseph Stalin (wd:Q855) - started on April 3, 1922
2. Nikita Khrushchev (wd:Q35314) - started on September 14, 1953

Therefore, there were 2 General Secretaries of the CPSU before Leonid Brezhnev.

Here is the final SPARQL query and answer:

```sparql
SELECT ?secretary ?start WHERE {
  ?secretary p:P39 ?statement .
  ?statement ps:P39 wd:Q1048744 ;
             pq:P580 ?start .
  FILTER(?start < '1964-10-14T00:00:00Z'^^xsd:dateTime)
} ORDER BY ?start
```

Answer: There were 2 General Secretaries of the CPSU before Leonid Brezhnev.

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

[Tool] Stopped generation process