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 DISTINCT ?product ?productLabel WHERE {
  wd:Q81965 wdt:P1056 ?product .
  OPTIONAL {
    ?product rdfs:label ?productLabel FILTER ( LANG( ?productLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| product              | productLabel   |
| -------------------- | -------------- |
| motor car (wd:Q1420) | motor car (en) |

General Motors (GM) makes motor cars.

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

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

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

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

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

[User] what does gm make?

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

[Tool]
Example 1:
Question:
what kind of currency does cuba use?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q241 wdt:P38 ?x .
}

Using entities:
Cuba, also known as cu, CUB, Republic of Cuba (wd:Q241): sovereign state situated on an island in the Caribbean Sea

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

Example 2:
Question:
what county is morristown tn in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q962499 wdt:P131 ?x .
}

Using entities:
Morristown, also known as Morristown, New Jersey, Morristown, NJ (wd:Q962499): town in Morris County, New Jersey, United States

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

Example 3:
Question:
who does dominic monaghan play in lord of the rings?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q127367 p:P161 ?p .
  ?p ps:P161 wd:Q152165 ; pq:P453 ?x .
}

Using entities:
The Lord of the Rings: The Fellowship of the Ring, also known as Lord of the Rings: The Fellowship of the Ring, The Fellowship of the Ring (wd:Q127367): 2001 film by Peter Jackson
Dominic Monaghan (wd:Q152165): German-born British actor, television actor, screenwriter, stage actor, film actor, actor

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as p/ps): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
character role, also known as role, plays, performer of, as, acting role (wd:P453 as pq): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)

[Assistant]
The question "what does gm make?" is ambiguous because "gm" could refer to different entities such as General Motors (the automobile manufacturer) or something else. The most likely interpretation is General Motors, which is known for making vehicles.

Step 1: Search for the entity "gm" to confirm if it corresponds to General Motors or any other relevant entities.
Step 2: Identify the property that relates to what an organization or company "makes" or "produces."
Step 3: Formulate a query to find what General Motors makes.

I will start by searching for the entity "gm" in Wikidata.

[Tool] No entity items found

[Assistant] The search for the entity "gm" did not return any results directly. I will try searching for "General Motors" explicitly to find the relevant entity.

[Tool]
Top 10 entity alternatives:
1. General Motors, also known as GM, General Motors Corporation (wd:Q81965): automotive manufacturing corporation based in Detroit, Michigan, USA, American automotive manufacturing corporation
2. General Motors railway station, also known as General Motors station, General Motors (wd:Q5532064): closed railway station in Dandenong South, Victoria, Australia
3. General Motors (wd:Q16891615): former Rochester Industrial and Rapid Transit Railway station and streetcar carhouse in Rochester, New York
4. General Motors (wd:Q84480751): scientific article published on 01 November 1983
5. General Motors, also known as General Motors (Poland) (wd:Q30338742): Polish subsidary of General Motors
6. General motors (wd:Q84481962): scientific article published on 01 February 1983
7. Grumman TBF Avenger, also known as TBM Avenger, TBM, Grumman Torpedo Bomber Design 1, Grumman TBM, Grumman Tarpon (wd:Q734103): 1941 torpedo bomber aircraft model by Grumman
8. Rogers Arena, also known as GM Place, General Motors Place (wd:Q517318): sports arena in Vancouver, British Columbia, Canada
9. GM Korea, also known as General Motors Korea, GM Daewoo, 한국GM (wd:Q497193): South Korean subsidiary of General Motors
10. General Motors EV1, also known as EV1 (wd:Q152013): electric compact car model

[Assistant]
The entity "General Motors" corresponds to wd:Q81965 in Wikidata, which is an automotive manufacturing corporation. This is likely the "gm" referred to in the question.

Next, I need to find the property that indicates what General Motors "makes" or "produces." Common properties for this could be "product," "manufactures," or "industry."

I will search for properties related to "make" or "produce" for the entity General Motors (wd:Q81965).

[Tool]
Top 10 property alternatives:
1. 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 p/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
2. 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
3. founded by, also known as starter, co-founded by, started by, institutor, instituted by (wd:P112 as p/wdt): founder or co-founder of this organization, religion, place or entity, creator
4. official shop URL, also known as online store, shop, shop URL, store, store URL (wd:P10225 as p/wdt): official URL where the agent sells products/merchandise, official website
5. 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
6. 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
7. 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)
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. location of formation, also known as place of incorporation, originates from, place of establishment, place of formation, place of foundation (wd:P740 as p/wdt): location where a group or organization was formed, location of creation
10. 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

No other items found

[Assistant]
The property "product, material, or service produced or provided" (wdt:P1056) is the most relevant property for what General Motors makes.

Now I will write a SPARQL query to find the products that General Motors (wd:Q81965) makes using the property wdt:P1056. I will also include labels for better readability.

[Tool]
Got 1 row and 2 columns:
| product              | productLabel   |
| -------------------- | -------------- |
| motor car (wd:Q1420) | motor car (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the product made by General Motors (GM) using the property 'product, material, or service produced or provided' (wdt:P1056). The result shows that GM makes motor cars, which is accurate and directly answers the user's question. The query also includes the English label for readability. The answer is concise and complete.


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 ?city ?cityLabel ?population WHERE {
  ?city wdt:P17 wd:Q29 ; wdt:P1082 ?population .
  OPTIONAL {
    ?city rdfs:label ?cityLabel FILTER ( LANG( ?cityLabel ) = "en" )
  }
  ?city wdt:P31 ?type .
  FILTER ( ?type IN ( wd:Q515 , wd:Q2074737 ) )
}
ORDER BY DESC ( ?population )
LIMIT 1

The largest city in Spain by population is Madrid.

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

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

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

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

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

[User] what the largest city in spain?

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

[Tool]
Example 1:
Question:
who were demeter's brothers and sisters?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q40730 wdt:P3373 ?x .
}

Using entities:
Demeter, also known as Dêmêtêr, Deo (wd:Q40730): Greek goddess of the harvest, grains, and agriculture

Using properties:
sibling, also known as is sister of, is the brother of, is the sibling of, is the sister of, sib (wd:P3373 as wdt): the subject and the object have at least one common parent (brot...law, etc.) and step-siblings (step-brothers, step-sisters, etc.), relative

Example 2:
Question:
who played daniel larusso?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?p p:P161 ?y .
  ?y ps:P161 ?x ; pq:P453 wd:Q55315887 .
}

Using entities:
Daniel LaRusso, also known as Daniel-san (wd:Q55315887): fictional character from the Karate Kid franchise, business executive, car dealer, karateka

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as p/ps): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
character role, also known as role, plays, performer of, as, acting role (wd:P453 as pq): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)

Example 3:
Question:
what did the habsburg family control?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q65968 wdt:P1830 ?x .
}

Using entities:
House of Habsburg, also known as Habsburg, Habsburg family, Hapsburg, Hapsburg family, House of Austria (wd:Q65968): Austrian imperial house

Using properties:
owner of, also known as owns, owns property, shareholder of (wd:P1830 as wdt): entities owned by the subject

[Assistant]
The question is about the largest city in Spain. To answer this, I need to identify the entity for Spain and then find the city with the largest population within Spain.

Step 1: Search for the entity "Spain" in Wikidata.
Step 2: Find the property that relates cities to their population.
Step 3: Query for cities located in Spain and order them by population to get the largest city.

I will start by searching for the entity "Spain".

[Tool]
Top 10 entity alternatives:
1. Spain, also known as Kingdom of Spain (wd:Q29): country in southwestern Europe with territories in Africa
2. Spain men's national football team, also known as La Furia, The Spanish Fury, The Red One, The Red Fury, The Fury (wd:Q42267): men's national association football team representing Spain
3. Second Spanish Republic, also known as Spain (wd:Q178038): political regime established in Spain between April 14, 1931 and April 1, 1939
4. New Spain, also known as Colonial Central America, Central America under Spain, Viceroyalty of New Spain, Spanish Mexico, Spanish Central America (wd:Q170603): viceroyalty of the Spanish Empire (1535-1821)
5. Spain under the Restoration, also known as Bourbon Restoration, Spain, Second Bourbon Restoration, Restoration, Restoration (Spain) (wd:Q1044536): name given to a period between 1874 (end of First Spanish Republ...econd Spanish Republic), and the state of Spain during that time
6. Kingdom of Spain (1820-1823), also known as Kingdom of Spain, Spain, Trienio Liberal (wd:Q238809): 1820–1823 Spanish political period
7. Spain under Joseph Bonaparte, also known as Kingdom of Spain, Napoleonic Spain, Spain (wd:Q1709185): Napoleonic client state (1808–1813)
8. Sexenio Democrático, also known as Kingdom of Spain, Spain (wd:Q12411956): 1868–1874 period of fu under a provisional government
9. Ominous Decade, also known as Kingdom of Spain, second restoration of absolutism, Spain (wd:Q2378204): period in the history of Spain, corresponding to the second rest...reign of Fernando VII from August 31, 1823 to September 29, 1833
10. Hispanic Monarchy, also known as Spains, Hispanic Crown, Spain, Kingdom of Spains, Crown of Spain (wd:Q766543): (1479-1716) set of territories distributed throughout the world,...monarch and corresponding to the period of the House of Habsburg

[Assistant] The entity for Spain is wd:Q29. Next, I need to find the property that relates cities to their population. I will search for properties related to "population" to find the appropriate property for city population.

[Tool]
Top 10 property alternatives:
1. tabular population, also known as population (wd:P4179 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): same as population (P1082); used when there is data for many different points in time
2. population, also known as inhabitants, human population (wd:P1082 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): number of people inhabiting the place; number of people of subject
3. has census, also known as has human population census (wd:P8701 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): general population census of the country or region
4. urban population (wd:P6343 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): number of people living within the territorial entity who live in its urban parts, population
5. birth rate (wd:P8763 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): the total number of live births per 1,000 population
6. category populated by, also known as category filled by, category has template, cat populated by, component adding into the category, populated by (wd:P4329 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): software component (template, module, extension, MediaWiki core) populating the category
7. rural population (wd:P6344 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): number of people living within the territorial entity who live in its rural parts, population
8. female population (wd:P1539 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): number of female people inhabiting the place; number of female people of subject, population
9. male population, also known as male inhabitants, number of males (wd:P1540 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): number of male people inhabiting the place; number of male people of subject, population
10. number of households, also known as dwellings, households (wd:P1538 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): total number of households in this place, includes dwellings of all types

[Assistant] The property for population is wd:P1082. Now I need to find cities located in Spain. I will search for the property that indicates the country or location of a city. "country" is commonly used for this purpose. I will search for properties related to "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 ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): 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 ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): 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 ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): 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 ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): 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 ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): 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 ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): most specific known birth location of a person, animal or fictional character, location
7. continent (wd:P30 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): 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 ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): 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 ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): 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 ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): 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 for country is wd:P17. Now I will write a SPARQL query to find the largest city in Spain by population. The query will:
- Find entities that are instances of a city (wd:Q515).
- Have the country property set to Spain (wd:Q29).
- Have a population (wdt:P1082).
- Order the results by population in descending order and limit to 1 to get the largest city.

[Tool]
Got 1 row and 3 columns:
| city                 | cityLabel      | population            |
| -------------------- | -------------- | --------------------- |
| Barcelona (wd:Q1492) | Barcelona (en) | 1702547 (xsd:decimal) |

[Tool] Stopped generation process

[User]
Feedback (status=retry):
The SPARQL query correctly retrieves the largest city in Spain by population, but the answer given is incorrect. The largest city in Spain by population is Madrid, not Barcelona. The query should be double-checked or refined to ensure it returns Madrid as the largest city. Possibly the population data for Barcelona is being retrieved, but Madrid should have a larger population. The system should verify the data or adjust the query to confirm the largest city is Madrid.

[Assistant]
Thank you for the feedback. I will re-examine the query and the data to ensure it correctly identifies the largest city in Spain by population. It is possible that the query is missing some data or that the population values are not the most recent or complete.

I will first check the population of Madrid (wd:Q2807) to compare it with Barcelona's population.

[Tool]
Got 2 rows and 3 columns:
| city                 | cityLabel      | population            |
| -------------------- | -------------- | --------------------- |
| Madrid (wd:Q2807)    | Madrid (en)    | 3416771 (xsd:decimal) |
| Barcelona (wd:Q1492) | Barcelona (en) | 1702547 (xsd:decimal) |

[Assistant]
The population data shows that Madrid (3,416,771) has a larger population than Barcelona (1,702,547). This confirms that Madrid is the largest city in Spain by population.

The previous query should have returned Madrid as the largest city. I will re-run the original query to check if it returns Madrid as the largest city. If not, I will investigate further.

[Tool]
Got 5 rows and 3 columns:
| city                          | cityLabel           | population            |
| ----------------------------- | ------------------- | --------------------- |
| Barcelona (wd:Q1492)          | Barcelona (en)      | 1702547 (xsd:decimal) |
| Barcelona City (wd:Q31913048) | Barcelona City (en) | 1660122 (xsd:decimal) |
| Zaragoza City (wd:Q31926034)  | Zaragoza City (en)  | 666880 (xsd:decimal)  |
| Palma (wd:Q8826)              | Palma (en)          | 431521 (xsd:decimal)  |
| Alicante (wd:Q11959)          | Alicante (en)       | 358720 (xsd:decimal)  |

[Assistant]
The original query did not return Madrid as the largest city in Spain, which is unexpected given the population data for Madrid.

The issue might be that Madrid is not classified as an instance of "city" (wd:Q515) in Wikidata, or there might be some other classification issue.

I will check the instance types of Madrid to understand how it is classified.

[Tool]
Got 2 rows and 3 columns:
| subject           | property              | object                              |
| ----------------- | --------------------- | ----------------------------------- |
| Madrid (wd:Q2807) | instance of (wdt:P31) | municipality of Spain (wd:Q2074737) |
| Madrid (wd:Q2807) | instance of (wdt:P31) | tourist destination (wd:Q1200957)   |

[Assistant]
Madrid is classified as an instance of "municipality of Spain" (wd:Q2074737) rather than a direct instance of "city" (wd:Q515). This classification difference caused the original query to miss Madrid.

To fix this, I will modify the query to include entities that are instances of "municipality of Spain" (wd:Q2074737) or instances of "city" (wd:Q515) located in Spain. Then I will order by population to find the largest city.

[Tool]
Got 1 row and 3 columns:
| city              | cityLabel   | population            |
| ----------------- | ----------- | --------------------- |
| Madrid (wd:Q2807) | Madrid (en) | 3416771 (xsd:decimal) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly identifies the largest city in Spain by population. It filters for entities that are instances of either city (wd:Q515) or Spanish municipality (wd:Q2074737) within Spain (wd:Q29), retrieves their population, and orders them descendingly to get the largest. The answer 'Madrid' is accurate and matches the query result. The query also optionally retrieves the English label for readability. Overall, the output is correct and complete.


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 ?causeOfDeath ?causeOfDeathLabel WHERE {
  wd:Q40933 wdt:P509 ?causeOfDeath .
  OPTIONAL {
    ?causeOfDeath rdfs:label ?causeOfDeathLabel FILTER ( LANG( ?causeOfDeathLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| causeOfDeath                       | causeOfDeathLabel          |
| ---------------------------------- | -------------------------- |
| cervix uterine cancer (wd:Q160105) | cervix uterine cancer (en) |

Eva Peron had cervix uterine cancer.

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

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

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

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

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

[User] what type of cancer did eva peron have?

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

[Tool]
Example 1:
Question:
who plays lois in family guy?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q5930 p:P725 ?p .
  ?p ps:P725 ?x ; pq:P453 wd:Q853073 .
}

Using entities:
Family Guy (wd:Q5930): American adult animated sitcom
Lois Griffin, also known as Lois Pewterschmidt Griffin, Lois Pewterschmidt, Lois Patrice Pewterschmidt, Lois Patrice Griffin (wd:Q853073): fictional character from the Family Guy franchise, housewife

Using properties:
character role, also known as role, plays, performer of, as, acting role (wd:P453 as pq): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)
voice actor, also known as voice actors, voice dubber, voice actress, voice actresses, voiced by (wd:P725 as p/ps): performer of a spoken role in a creative work such as animation,... (P453) as qualifier] [use "cast member" (P161) for live acting], film crew member, cast member

Example 2:
Question:
what illnesses did george washington suffer from?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q23 wdt:P1050 ?x .
}

Using entities:
George Washington, also known as Father of the United States (wd:Q23): Founding Father and first U.S. president (1789–1797), revolutionary, statesperson, army officer, cartographer, politician, engineer, geometer, writer, farmer

Using properties:
medical condition, also known as disability, suffers from, suffer from, sickness, paralympic disability (wd:P1050 as wdt): any state relevant to the health of an organism, including diseases and positive conditions

Example 3:
Question:
who did rufus wainwright married?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q192402 wdt:P26 ?x .
}

Using entities:
Rufus Wainwright, also known as Rufus McGarrigle Wainwright (wd:Q192402): American-Canadian singer-songwriter and composer, singer-songwriter, television actor, voice actor, film actor, musician, composer, pianist, singer

Using properties:
spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as wdt): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative

[Assistant] From the examples, I see that medical conditions or illnesses are often queried using the property "medical condition" (wdt:P1050) in Wikidata. I will now search for the entity "Eva Peron" in Wikidata to find her identifier.

[Tool]
Top 10 entity alternatives:
1. Eva Perón, also known as Evita Perón, Maria Eva Duarte de Peron, Evita, María Eva Duarte de Perón, Maria Eva Duarte Peron (wd:Q40933): Argentine actress and politician (1919–1952), women's rights activist, trade unionist, stage actor, suffragist, politician, film actor
2. Eva Perón: The True Story, also known as Eva Peron, Eva Perón (wd:Q953441): 1996 film by Juan Carlos Desanzo
3. Fray Luis Beltrán, also known as Eva Perón, Eva Perón tanker, Fray Luis Beltrán tanker (wd:Q113059537): tanker
4. Eva Perón (wd:Q113030601): tanker
5. Hospital Lagomarsino, also known as Eva Perón (wd:Q5902632): hospital in Merlo, Buenos Aires
6. Uruguay, also known as Eva Perón (wd:Q113330807): 1951 passenger ship
7. Eva Perón (wd:Q47512378): painting by Boris Chaliapin
8. Estadio Eva Perón, also known as Estadio Eva Peron (wd:Q5400194): football stadium in Junín, Argentina
9. Puerto Eva Perón (wd:Q972928): ciudad en la provincia de Chaco, Argentina
10. Eva Perón Foundation (wd:Q2004004): former Argentine foundation

[Assistant] The entity for Eva Peron is wd:Q40933. Now I will search for properties related to medical conditions or illnesses for this entity.

[Tool]
Top 10 property alternatives:
1. 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
2. cause of death, also known as death cause, murder method, method of murder, die of, die from (wd:P509 as p/wdt): underlying or immediate cause of death.  Underlying cause (e.g. ...adest category, e.g. natural causes, accident, homicide, suicide
3. field of work, also known as scientific discipline, scientific area, responsible for, research on, research fields (wd:P101 as p/wdt): specialization of a person or organization; see P106 for the occupation, interested in
4. manner of death, also known as type of death, nature of death, death manner, death type, circumstance of death (wd:P1196 as p/wdt): general circumstances of a person's death; e.g. natural causes, ...ysiological mechanism, e.g. heart attack, trauma, pneumonia etc.
5. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as p/wdt): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)
6. 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
7. CiNii Research ID, also known as CRID, cir.nii.ac.jp ID (wd:P11496 as wdt/p/wdtn): 19-digits identifier in CiNii Research
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. date of death, also known as DOD, deathdate, died, died on, year of death (wd:P570 as p/wdt): dissolved, abolished or demolished date, date on which the subject died, end time
10. occupation, also known as job, work, vocation, profession, employment (wd:P106 as p/wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)

No other items found

[Assistant] The property "cause of death" (wdt:P509) seems relevant to find the type of cancer Eva Peron had. I will now query the cause of death for Eva Peron.

[Tool]
Got 1 row and 2 columns:
| causeOfDeath                       | causeOfDeathLabel          |
| ---------------------------------- | -------------------------- |
| cervix uterine cancer (wd:Q160105) | cervix uterine cancer (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the cause of death for Eva Peron (wd:Q40933) using the property cause of death (wdt:P509). The result 'cervix uterine cancer' is accurate and matches the user's question about the type of cancer Eva Peron had. The query also optionally retrieves the English label for better readability. The output is correct and complete.


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 DISTINCT ?place ?placeLabel WHERE {
  wd:Q34271 wdt:P2341 ?place .
  OPTIONAL {
    ?place rdfs:label ?placeLabel FILTER ( LANG( ?placeLabel ) = "en" )
  }
}

Got 12 rows and 2 columns, showing the first 5 and last 5 rows below:
| place                        | placeLabel             |
| ---------------------------- | ---------------------- |
| Arunachal Pradesh (wd:Q1162) | Arunachal Pradesh (en) |
| Assam (wd:Q1164)             | Assam (en)             |
| Himachal Pradesh (wd:Q1177)  | Himachal Pradesh (en)  |
| Delhi (wd:Q1353)             | Delhi (en)             |
| Uttarakhand (wd:Q1499)       | Uttarakhand (en)       |
| ...                          | ...                    |
| Sichuan (wd:Q19770)          | Sichuan (en)           |
| Xinjiang (wd:Q34800)         | Xinjiang (en)          |
| Gansu (wd:Q42392)            | Gansu (en)             |
| Qinghai (wd:Q45833)          | Qinghai (en)           |
| Bhutan (wd:Q917)             | Bhutan (en)            |

Tibetan is spoken in the following places: Arunachal Pradesh, Assam, Himachal Pradesh, Delhi, Uttarakhand, Sichuan, Xinjiang, Gansu, Qinghai, and Bhutan.

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

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

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

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

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

[User] where do they speak tibetan?

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

[Tool]
Example 1:
Question:
who was the apostle paul considered to be?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q9200 wdt:P1559 ?x .
}

Using entities:
Paul the Apostle, also known as Saul of Tarsus, Saulus, Šā'ûl, Saul, Saint Paulus (wd:Q9200): Early Christian apostle and missionary (c. AD 5 – c. 64/65), religious figure, missionary, theologian, traveler, artisan, writer, rabbi

Using properties:
name in native language, also known as native name (wd:P1559 as wdt): name of a person in their native language, name

Example 2:
Question:
what countries around the world speak french?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P37 wd:Q150 ; wdt:P31 / wdt:P279 * wd:Q6256 .
}

Using entities:
French, also known as (fr), fr, fra, French language (wd:Q150): Romance language
country, also known as countries (wd:Q6256): distinct territorial body or political entity

Using properties:
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as wdt): language designated as official by this item, language used

Example 3:
Question:
what did lucille ball die of?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q209662 wdt:P509 ?x .
}

Using entities:
Lucille Ball, also known as Lucille Désirée Ball, Lucille Desiree Ball, Lucille Ball Arnaz, Queen of the B Movies,, Lucy Ball (wd:Q209662): American actress (1911–1989), film studio executive, television producer, television actor, film director, film actor, producer, director, comedian, actor

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

[Assistant]
From the examples, I see that to find where a language is spoken, we can use the property "official language" (wdt:P37) or similar properties related to language spoken in a country or region.

Step 1: I will search for the entity "Tibetan language" to get its Wikidata identifier.

[Tool]
Top 10 entity alternatives:
1. Tibetan, also known as bo, bod, Lhasa Tibetan, Standard Tibetan, Tibetan language (wd:Q34271): Tibeto-Burman language
2. Tibetan (language) (wd:L612746-S1)
3. Tibetan language (wd:L1020969-S1)
4. Tibetic, also known as Tibetan languages, Tibetic languages (wd:Q1641150): group of Bodic languages spoken by Tibetans in the Eastern Tibetan Plateau and in northern areas of the Indian subcontinent
5. Central Tibetan, also known as Dbus, Ü-Tsang, Central Tibetan language, Ü (wd:Q5061915): language and dialects ensemble from Central Tibet
6. Central Tibetan, also known as Ü-Tsang, Ü, Dbus, Central Tibetan language (wd:Q5061915): language and dialects ensemble from Central Tibet
7. Khams Tibetan, also known as Khams Tibetan language, khg (wd:Q56601): language
8. Amdo Tibetan, also known as adx, Amdo Tibetan language (wd:Q56509): Tibetic language of Amdo
9. Tibetan Sign Language (wd:Q15936110): deaf sign language of Tibet
10. Humla, also known as Humla Bhotiya, Humla language, Humla Tibetan, Humla Tibetan language, Humli Tamang (wd:Q17588918): Sino-Tibetan language

[Assistant] The entity "Tibetan" (wd:Q34271) corresponds to the Tibetan language. Now, I will query for the places where Tibetan is spoken. Typically, the property "official language" (wdt:P37) is used for countries or regions where a language is officially spoken. I will use this property to find the places where Tibetan is spoken.

[Tool] Got no rows and 2 columns

[Assistant] No countries have Tibetan as an official language. Tibetan might be spoken in regions or administrative divisions rather than countries. I will now try to find places where Tibetan is spoken using a broader property related to language spoken or official language in administrative divisions or regions. I will search for properties related to "language spoken" for the Tibetan language entity.

[Tool]
Top 10 property alternatives:
1. indigenous to, also known as native to, originating from, spoken by (wd:P2341 as p/wdt): place or ethnic group where a language, art genre, cultural trad...biological species or variety is found (or was originally found)
2. number of speakers, writers, or signers, also known as signers of a language, speakers of language, writers of a language (wd:P1098 as p/wdt): number of people who use a language
3. pronunciation audio, also known as listen, audio pronunciation (wd:P443 as p/wdt): audio file with pronunciation, audio
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. 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)
6. Ethnologue language status, also known as EGIDS, language status (wd:P3823 as p/wdt): language status identifier by Ethnologue.com using EGIDS scale
7. follows, also known as prev, successor to, succeeds to, succeeds, split from (wd:P155 as p/wdt): immediately prior item in a series of which the subject is a par... preceding item, e.g. political offices, use "replaces" (P1365)]
8. writing system, also known as script, writing script, written form (wd:P282 as p/wdt): alphabet, character set or other system of writing used by a language, word, or text, supported by a typeface
9. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as p/wdt): label for the items in their official language  or their original language, name
10. NDL Authority ID, also known as NDLSH (NDL Subject Headings), NDLNA (NDL Name Authority), NDLNAId, NDL identifier, NDL ID (wd:P349 as wdt/p/wdtn): identifier for authority control per the National Diet Library of Japan

No other items found

[Assistant] The property "indigenous to" (wdt:P2341) is related to the place or ethnic group where a language is spoken or originally found. This seems to be the most relevant property to find places where Tibetan is spoken. I will now query for places where Tibetan (wd:Q34271) is indigenous to or spoken by using this property.

[Tool]
Got 12 rows and 2 columns, showing the first 5 and last 5 rows below:
| place                        | placeLabel             |
| ---------------------------- | ---------------------- |
| Arunachal Pradesh (wd:Q1162) | Arunachal Pradesh (en) |
| Assam (wd:Q1164)             | Assam (en)             |
| Himachal Pradesh (wd:Q1177)  | Himachal Pradesh (en)  |
| Delhi (wd:Q1353)             | Delhi (en)             |
| Uttarakhand (wd:Q1499)       | Uttarakhand (en)       |
| ...                          | ...                    |
| Sichuan (wd:Q19770)          | Sichuan (en)           |
| Xinjiang (wd:Q34800)         | Xinjiang (en)          |
| Gansu (wd:Q42392)            | Gansu (en)             |
| Qinghai (wd:Q45833)          | Qinghai (en)           |
| Bhutan (wd:Q917)             | Bhutan (en)            |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the places where Tibetan is spoken using the property 'indigenous to' (wdt:P2341) for the language Tibetan (wd:Q34271). The query returns the identifiers and English labels of the places, which matches the user's question. The answer lists all the places found in the query result, providing a clear and complete response. The query follows the rules by returning identifiers and labels optionally, and the answer is accurate and complete. No further refinement is necessary.


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 ?medicalCondition ?medicalConditionLabel WHERE {
  wd:Q1345645 wdt:P1050 ?medicalCondition .
  OPTIONAL {
    ?medicalCondition rdfs:label ?medicalConditionLabel FILTER ( LANG( ?medicalConditionLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| medicalCondition              | medicalConditionLabel   |
| ----------------------------- | ----------------------- |
| multiple sclerosis (wd:Q8277) | multiple sclerosis (en) |

Montel Williams has the disease multiple sclerosis.

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

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

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

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

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

[User] what kind of disease does montel williams have?

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

[Tool]
Example 1:
Question:
where was governor cuomo born?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q11673 wdt:P19 ?x .
}

Using entities:
Andrew Cuomo, also known as Andrew Mark Cuomo (wd:Q11673): Governor of New York from 2011 to 2021, politician, lawyer

Using properties:
place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt): most specific known birth location of a person, animal or fictional character, location

Example 2:
Question:
where did queen isabella live?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q45859 wdt:P19 ?x .
}

Using entities:
Isabella I of Castile, also known as la Católica, Queen of Spain Isabel I, Queen Isabella, Queen Isabella of Spain, Queen of Castile and Leon Isabella, Queen of Castile and León Isabella (wd:Q45859): queen of the Crown of Castile, from 1474 to 1504; first queen of a dynastically-united Spain, from 1479 to 1504, ruler

Using properties:
place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt): most specific known birth location of a person, animal or fictional character, location

Example 3:
Question:
what is my timezone in california?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q99 wdt:P421 ?x .
}

Using entities:
California, also known as US-CA, State of California, The Golden State, Calif., Cali. (wd:Q99): state of the United States of America

Using properties:
located in time zone, also known as TZ, time zone, timezone (wd:P421 as wdt): time zone for this item

[Assistant]
The examples show how to query for specific properties of a person, such as place of birth or time zone. For the question about Montel Williams' disease, we need to find the entity for Montel Williams and then find the property that relates to the disease he has.

Step 1: Search for the entity "Montel Williams" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Montel Williams, also known as Montel Brian Anthony Williams (wd:Q1345645): American television host and actor, television presenter, television producer, radio personality, television actor, military officer, journalist, politician, actor
2. The Montel Williams Show (wd:Q2412902): television series
3. Montel Williams MS Foundation (wd:Q30289093): nonprofit organization in New York, United States
4. Williams Racing, also known as Williams, Williams Grand Prix Engineering Limited, Williams F1 (wd:Q171337): European Formula One motor racing team and constructor
5. Williams, also known as Williams, AZ, Williams, Arizona (wd:Q79864): city in Coconino County, Arizona, United States
6. Williams, also known as Williams, CA, Williams, California (wd:Q2685585): city in Colusa County, California, United States
7. Williams, also known as Williams, IA, Williams, Iowa (wd:Q1012283): city in Hamilton County, Iowa, United States
8. Williams, also known as Williams, MN, Williams, Minnesota (wd:Q963315): city in Lake of the Woods County, Minnesota, United States
9. Williams College, also known as Williams (wd:Q49166): liberal arts college in Massachusetts
10. Williams, also known as Williams, SC, Williams, South Carolina (wd:Q2562748): town in Collation County, South Carolina, United States

[Assistant] The entity for Montel Williams is wd:Q1345645. Next, I will search for properties related to diseases or medical conditions for this entity.

[Tool]
Top 10 property alternatives:
1. 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
2. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as p/wdt): work where this item is described, attested in
3. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as p/wdt): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)
4. 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
5. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as p/wdt): language(s) that a person or a people speaks, writes or signs, including the native language(s)
6. occupation, also known as job, work, vocation, profession, employment (wd:P106 as p/wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
7. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as p/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
8. Freebase ID, also known as Freebase, MID, Freebase identifier, FID (wd:P646 as p/wdt): identifier for a page in the Freebase database. Format: "/m/0" f...r IDs starting with "/g/", use Google Knowledge Graph ID (P2671)
9. given name, also known as name, proper name, personal name, middle name, forename (wd:P735 as p/wdt): first name or another given name of this person; values used with the property should not link disambiguations nor family names, name
10. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)

No other items found

[Assistant] The property "medical condition" (wdt:P1050) is the most relevant for diseases or medical conditions. I will now query the medical condition of Montel Williams (wd:Q1345645).

[Tool]
Got 1 row and 2 columns:
| medicalCondition              | medicalConditionLabel   |
| ----------------------------- | ----------------------- |
| multiple sclerosis (wd:Q8277) | multiple sclerosis (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the medical condition associated with Montel Williams using the property 'medical condition' (wdt:P1050). The query returns the disease 'multiple sclerosis' along with its English label, which directly answers the user's question. The answer is accurate and complete based on the data from Wikidata. No further refinement is necessary.


PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
SELECT ?team ?teamLabel ?start WHERE {
  wd:Q169452 p:P54 ?statement .
  ?statement ps:P54 ?team .
  OPTIONAL {
    ?statement pq:P580 ?start
  }
  .
  OPTIONAL {
    ?team rdfs:label ?teamLabel FILTER ( LANG( ?teamLabel ) = "en" )
  }
}
ORDER BY ?start
LIMIT 1

Shaquille O'Neal entered the NBA in June 1992 when he started playing for the Orlando Magic, according to the start date of his membership in the team on 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] when did shaq come into the nba?

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

[Tool]
Example 1:
Question:
where did pres clinton go to college?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q1124 wdt:P69 ?x .
  ?x wdt:P31 / wdt:P279 * wd:Q38723 .
}

Using entities:
Bill Clinton, also known as William Jefferson Blythe, William Jefferson Blythe III, William Jefferson "Bill" Clinton, William Jefferson Clinton, WJC (wd:Q1124): President of the United States from 1993 to 2001, autobiographer, statesperson, saxophonist, politician, governor, diplomat, teacher, jurist, lawyer, writer
higher education institution, also known as HEI, Higher Education school, institution of higher education, Superior Institute (wd:Q38723): institution that provides higher education (e.g., universities, ...es, liberal arts colleges, institutes of technology, and others)

Using properties:
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as wdt): educational institution attended by subject, affiliation

Example 2:
Question:
what school did kurt vonnegut go to?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q49074 wdt:P69 ?x .
}

Using entities:
Kurt Vonnegut, also known as Kurt Vonnegut, Jr. (wd:Q49074): American author (1922–2007), writer

Using properties:
educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as wdt): educational institution attended by subject, affiliation

Example 3:
Question:
what 3 countries does mexico border?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q96 wdt:P47 ?x .
}
LIMIT 3

Using entities:
Mexico, also known as US of M, United Mexican States, MXN, MX, Mexican United States (wd:Q96): country in North America

Using properties:
shares border with, also known as shares borders with, next to, bordered by, border, borders clockwise (wd:P47 as wdt): countries or administrative subdivisions, of equal level, that t...rders, either by land or water. A single common point is enough.

[Assistant]
The question is about when Shaquille O'Neal (Shaq) entered the NBA. This corresponds to the year he started his NBA career or the year he was drafted into the NBA. We need to find the entity for Shaquille O'Neal and then find a property related to the start of his NBA career or draft year.

Step 1: Search for the entity "Shaquille O'Neal" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Shaquille O'Neal, also known as Shaquille O’Neal, Shaquille Rashaun O'Neal, Shaq O'Neal, Shaquille Rashaun O’Neal, Shaq (wd:Q169452): American basketball player, real estate entrepreneur, television producer, sports commentator, basketball player, businessperson, film producer, screenwriter, film actor, Thai boxer, podcaster, singer, rapper, actor
2. Shaquille O'Neal (wd:Q125446160): episode of All That (S5 E3)
3. Shaquille Cleare, also known as Shaquille O'Neal Cleare (wd:Q61953486): college basketball player (2013–2017) Maryland; Texas, basketball player
4. Shaquille O'Neal Motors (wd:Q114535400): episode of Fresh Off the Boat (S2 E3)
5. Shaq Belson, also known as Shaquille Belson, Shaquille O'Neal Belson (wd:Q106725566): American American football player, American football player
6. Shaquille Allen, also known as Shaquille O'Neal Allen (wd:Q106725550): American football player
7. Upload with Shaquille O'Neal (wd:Q7898386): American comedy television series
8. Statue of Shaquille O'Neal (wd:Q114363921): sculpture in Los Angeles, California, U.S
9. The Best of Shaquille O'Neal (wd:Q7717219): album by Shaquille O'Neal
10. A Message from Shaquille O'Neal (wd:Q110058550): sketch from Saturday Night Live

[Assistant] The entity for Shaquille O'Neal is wd:Q169452. Now, I need to find the property that indicates when he started his NBA career or the year he was drafted into the NBA. I will search for properties related to "NBA draft" or "start of career" for this entity.

[Tool]
Top 10 property alternatives:
1. drafted by (wd:P647 as p/wdt): which team the player was drafted by
2. Basketball Reference international player ID, also known as BRCIP, Basketball Reference player ID, Basketball-Reference.com Europe player ID, Basketball-Reference.com international player ID (wd:P4790 as p/wdt): identifier for a basketball player in a non-U.S. league on Basketball-Reference.com
3. NBA.com player ID (wd:P3647 as p/wdt): identifier for a basketball player on the National Basketball Association's website
4. Basketball Reference NBA player ID, also known as Basketball-Reference.com NBA player ID, BRCNBA (wd:P2685 as p/wdt): identifier for a NBA player on the Basketball Reference website
5. Eurobasket.com player ID, also known as Eurobasket.com ID, eurobasket.com identifier (wd:P3527 as p/wdt): ID for a basketball player at Eurobasket.com
6. FIBA.com player ID (archived), also known as FIBA.com player ID, FIBA ID, FIBA identifier, FIBA player ID (wd:P3542 as p/wdt): identifier for a basketball player at archive.FIBA.com
7. FIBA.basketball player ID, also known as FIBA.basketball ID, FIBA player ID, FIBA identifier, FIBA ID (wd:P12338 as p/wdt): identifier for a basketball player at www.FIBA.basketball
8. Sports Reference college basketball player ID, also known as Basketball-Reference.com NCAA player ID, NCAA player Basketball-Reference.com, Sports Reference college basketball player ID, Sports-Reference.com college basketball player ID, SR CBB player ID (wd:P3696 as p/wdt): identifier for a NCAA Division I college basketball player on the Sports-Reference.com college basketball website
9. RealGM basketball player ID (wd:P3957 as p/wdt): identifier for a basketball player on the RealGM website
10. The Draft Review ID, also known as Draft Review identifier, The Draft Review identifier, Draft Review ID (wd:P9514 as p/wdt): identifier for a basketball player in the database of The Draft Review

No other items found

[Assistant] There is a property "drafted by" (wdt:P647) which indicates the team that drafted the player, but it does not directly give the year. I will now search for properties related to "start of career" or "career start" for Shaquille O'Neal.

[Tool]
Top 10 property alternatives:
1. 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
2. occupation, also known as job, work, vocation, profession, employment (wd:P106 as p/wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
3. educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as p/wdt): educational institution attended by subject, affiliation
4. academic degree, also known as academic diploma, degree, diploma (wd:P512 as p/wdt): academic degree that the person holds
5. position played on team / speciality, also known as position (on team), speciality, specialism, position, player position (wd:P413 as p/wdt): position or specialism of a player on a team
6. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as p/wdt): most specific known birth location of a person, animal or fictional character, location
7. member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as p/wdt): sports teams or clubs that the subject represents or represented, member of
8. participant in, also known as participated in, present at, takes part, took part, took part in (wd:P1344 as p/wdt): event in which a person or organization was/is a participant; inverse of P710 or P1923, significant event, part of
9. nominated for, also known as nominee for, shortlisted for, selected for award, selected for, nominee for award (wd:P1411 as p/wdt): award nomination received by a person, organisation or creative work (inspired from "award received" (Property:P166))
10. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as p/wdt): date on which the subject was born, inception

No other items found

[Assistant] There is a property "work period (start)" (wdt:P2031) which could indicate the start of Shaquille O'Neal's professional activity. This might be used to represent the year he started his NBA career. I will query the value of this property for Shaquille O'Neal.

[Tool]
Got 1 row and 1 column:
| start                               |
| ----------------------------------- |
| 1993-01-01T00:00:00Z (xsd:dateTime) |

[Assistant] Shaquille O'Neal's work period (start) is 1993-01-01, which indicates he started his professional career in 1993. This is the year he came into the NBA. I will now provide the final answer with the SPARQL query.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly retrieves the start date of Shaquille O'Neal's professional activity (P2031), which is 1993, matching the answer. However, the property P2031 (work period start) is a general property for the start of a person's professional activity and may not specifically indicate the exact year Shaq entered the NBA. A more precise property or approach would be to query for the year Shaquille O'Neal was drafted into the NBA or the year of his first NBA season. For example, querying for the NBA draft year (if available) or the start date of his sports career specifically in basketball might be more accurate. Therefore, the answer is sensible but could be refined by using a more specific property related to NBA entry rather than the general work period start property.

[Assistant]
Thank you for the feedback. To refine the answer, I will try to find a more specific property related to Shaquille O'Neal's NBA draft year or the start of his basketball career in the NBA.

Step 1: Search for properties related to "NBA draft year" or "draft year" for Shaquille O'Neal.

[Tool]
Top 10 property alternatives:
1. drafted by (wd:P647 as p/wdt): which team the player was drafted by
2. The Draft Review ID, also known as Draft Review identifier, The Draft Review identifier, Draft Review ID (wd:P9514 as p/wdt): identifier for a basketball player in the database of The Draft Review
3. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as p/wdt): date on which the subject was born, inception
4. position played on team / speciality, also known as position (on team), speciality, specialism, position, player position (wd:P413 as p/wdt): position or specialism of a player on a team
5. 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
6. member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as p/wdt): sports teams or clubs that the subject represents or represented, member of
7. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as p/wdt): most specific known birth location of a person, animal or fictional character, location
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. work period (end), also known as floruit end, floruit (end of work), flourished (end), retirement, work ends (wd:P2032 as p/wdt): end of period during which a person or group flourished (fl. = "floruit") in their professional activity, end time, floruit
10. nominated for, also known as nominee for, shortlisted for, selected for award, selected for, nominee for award (wd:P1411 as p/wdt): award nomination received by a person, organisation or creative work (inspired from "award received" (Property:P166))

No other items found

[Assistant]
There is no direct property for "draft year" but there is "drafted by" (wdt:P647) which indicates the team that drafted the player. I will check if there is a statement about the draft event or draft year related to Shaquille O'Neal.

Step 2: List statements for Shaquille O'Neal with property "drafted by" (wdt:P647) to see if there is a qualifier or related property indicating the draft year.

[Tool]
Got 1 row and 3 columns:
| subject                       | property              | object                     |
| ----------------------------- | --------------------- | -------------------------- |
| Shaquille O'Neal (wd:Q169452) | drafted by (wdt:P647) | Orlando Magic (wd:Q161337) |

[Assistant] Shaquille O'Neal was drafted by the Orlando Magic (wd:Q161337). Now I will check if there is a draft event or draft year qualifier related to this statement. I will look for qualifiers or statements related to the draft event for Shaquille O'Neal.

[Tool]
Got 919 rows and 3 columns, showing the first 10 rows below:
| subject                       | property                         | object                                                                                |
| ----------------------------- | -------------------------------- | -------------------------------------------------------------------------------------------------------------- |
| Shaquille O'Neal (wd:Q169452) | instance of (wdt:P31)            | human (wd:Q5)                                                                                |
| Shaquille O'Neal (wd:Q169452) | occupation (wdt:P106)            | actor (wd:Q33999)                                                                                |
| Shaquille O'Neal (wd:Q169452) | sex or gender (wdt:P21)          | male (wd:Q6581097)                                                                                |
| Shaquille O'Neal (wd:Q169452) | given name (wdt:P735)            | Shaquille (wd:Q16875708)                                                                                |
| Shaquille O'Neal (wd:Q169452) | date of birth (wdt:P569)         | 1972-03-06T00:00:00Z (xsd:dateTime)                                                                            |
| Shaquille O'Neal (wd:Q169452) | Commons category (wdt:P373)      | Shaquille O'Neal                                                                                |
| Shaquille O'Neal (wd:Q169452) | image (wdt:P18)                  | <http://commons.wikimedia.org/wiki/Special:FilePath/Shaquille%20O%27Neal%20October%202017%20%28cropped%29.jpg> |
| Shaquille O'Neal (wd:Q169452) | country of citizenship (wdt:P27) | United States (wd:Q30)                                                                                |
| Shaquille O'Neal (wd:Q169452) | family name (wdt:P734)           | O'Neal (wd:Q42717190)                                                                                |
| Shaquille O'Neal (wd:Q169452) | part of (wdt:P361)               | Shaq–Kobe feud (wd:Q7489331)                                                                                |
| ...                           | ...                              | ...                                                                                |

[Assistant]
Listing all properties for Shaquille O'Neal returns many results, but I need to specifically check the statement for "drafted by" (wdt:P647) to see if it has qualifiers indicating the draft year.

I will now query for the draft year or draft date related to the draft statement for Shaquille O'Neal. I will check if there is a property like "draft date" or "draft year" connected to the draft event or the drafted by statement.

[Tool] Got no rows and 1 columns

[Assistant]
There is no qualifier with property P585 (point in time) on the "drafted by" statement for Shaquille O'Neal. I will try to find if there is a property for the NBA draft event or draft year directly associated with Shaquille O'Neal.

I will search for properties related to "draft" for Shaquille O'Neal again but more broadly.

[Tool]
Top 10 property alternatives:
1. drafted by (wd:P647 as p/wdt): which team the player was drafted by
2. The Draft Review ID, also known as Draft Review identifier, The Draft Review identifier, Draft Review ID (wd:P9514 as p/wdt): identifier for a basketball player in the database of The Draft Review
3. nominated for, also known as nominee for, shortlisted for, selected for award, selected for, nominee for award (wd:P1411 as p/wdt): award nomination received by a person, organisation or creative work (inspired from "award received" (Property:P166))
4. sport, also known as play, plays, sport played, sports (wd:P641 as p/wdt): sport that the subject participates or participated in or is associated with
5. 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)
6. occupation, also known as job, work, vocation, profession, employment (wd:P106 as p/wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
7. league or competition, also known as tournament, sports league, division, cup, competition (wd:P118 as p/wdt): league or competition in which team or player has played, or in which an event occurs, participant in
8. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as p/wdt): most specific known birth location of a person, animal or fictional character, location
9. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as p/wdt): date on which the subject was born, inception
10. position played on team / speciality, also known as position (on team), speciality, specialism, position, player position (wd:P413 as p/wdt): position or specialism of a player on a team

No other items found

[Assistant]
There is no direct property for the draft year or draft date for Shaquille O'Neal. The best available property related to the draft is "drafted by" (wdt:P647) which indicates the team that drafted him, but it does not have a qualifier for the draft year.

Given this, the most accurate information available is the start of his professional career (work period start, P2031) which is 1993, the year he entered the NBA.

I will finalize the answer with this explanation and the SPARQL query for the start of his professional career.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The system correctly identified that Shaquille O'Neal started his professional career in 1993 using the property 'work period (start)' (wdt:P2031). However, this property indicates the start of his professional activity in general, not specifically his entry into the NBA. A more precise approach would be to query for the year he was drafted into the NBA or the year he first played for an NBA team, if such data is available. The current answer is reasonable given the data, but the query could be refined to check for NBA draft year or first NBA team membership to be more accurate.

[Assistant]
Thank you for the feedback. To refine the query further, I will try to find the year Shaquille O'Neal first played for an NBA team, which would more precisely indicate when he entered the NBA.

Step 1: Find the teams Shaquille O'Neal played for and the time periods for each team.

I will query for the teams he was a member of (wdt:P54) along with the qualifiers indicating the start time (P580) of his membership. Then I will filter for NBA teams.

[Tool]
SPARQL execution failed:
Error while executing a SERVICE request to <http://wikiba.se:80/ontology#label>: SERVICE responded with HTTP status code: 301, Moved Permanently. First 100 bytes of the response: '<html>
<head><title>301 Moved Permanently</title></head>
<body>
<center><h1>301 Moved Permanently'

[Assistant]
The query failed due to the use of SERVICE wikibase:label which is not supported by the endpoint. I will rewrite the query without using SERVICE wikibase:label and instead use optional rdfs:label to get team labels.

I will query for the teams Shaquille O'Neal played for (wdt:P54) and the start time qualifiers (pq:P580) on the membership statements, and get the team labels optionally.

[Tool]
Got 8 rows and 3 columns:
| team                                      | teamLabel                        | start                               |
| ----------------------------------------- | -------------------------------- | ----------------------------------- |
| LSU Tigers men's basketball (wd:Q6460027) | LSU Tigers men's basketball (en) | 1989-01-01T00:00:00Z (xsd:dateTime) |
| LSU Tigers men's basketball (wd:Q6460027) | LSU Tigers men's basketball (en) | 1989-01-01T00:00:00Z (xsd:dateTime) |
| Orlando Magic (wd:Q161337)                | Orlando Magic (en)               | 1992-06-01T00:00:00Z (xsd:dateTime) |
| Los Angeles Lakers (wd:Q121783)           | Los Angeles Lakers (en)          | 1996-01-01T00:00:00Z (xsd:dateTime) |
| Miami Heat (wd:Q169138)                   | Miami Heat (en)                  | 2004-07-14T00:00:00Z (xsd:dateTime) |
| Phoenix Suns (wd:Q164177)                 | Phoenix Suns (en)                | 2008-01-01T00:00:00Z (xsd:dateTime) |
| Cleveland Cavaliers (wd:Q162990)          | Cleveland Cavaliers (en)         | 2009-01-01T00:00:00Z (xsd:dateTime) |
| Boston Celtics (wd:Q131371)               | Boston Celtics (en)              | 2010-01-01T00:00:00Z (xsd:dateTime) |

[Assistant]
Shaquille O'Neal played for the Orlando Magic starting in 1992-06-01, which is likely the time he entered the NBA. This is more precise than the general work period start.

I will finalize the answer with this information and the corresponding SPARQL query.

[Tool] Stopped generation process