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 ?prop ?propLabel ?lang ?langLabel WHERE {
  VALUES ?prop {
    wdt:P37 wdt:P2936 wdt:P1412
  }
  wd:Q79 ?prop ?lang .
  OPTIONAL {
    ?lang rdfs:label ?langLabel .
    FILTER ( LANG( ?langLabel ) = "en" )
  }
  OPTIONAL {
    ?prop rdfs:label ?propLabel .
    FILTER ( LANG( ?propLabel ) = "en" )
  }
}
ORDER BY ?prop ?langLabel

Using entities:
Egypt (wd:Q79), also known as Arab Rep. Egypt, Arab Republic of Egypt, eg, EGY, Rep. Egypt, etc.

Using properties:
languages spoken, written or signed (wd:P1412 as wdt), also known as language, language of expression, language read, language signed, languages of expression, etc.
language used (wd:P2936 as wdt), also known as languages used, medium of instruction, used language, uses language, working language, etc.
official language (wd:P37 as wdt), also known as language official, language spoken, speaking, spoken in, P37

Got 13 rows and 4 columns, showing the first 5 and last 5 rows below:
| prop                        | propLabel | lang                                 | langLabel                   |
| --------------------------- | --------- | ------------------------------------ | --------------------------- |
| language used (wdt:P2936)   |           | Bedawi Arabic (wd:Q56714)            | Bedawi Arabic (en)          |
| language used (wdt:P2936)   |           | Beja (wd:Q33025)                     | Beja (en)                   |
| language used (wdt:P2936)   |           | Coptic (wd:Q36155)                   | Coptic (en)                 |
| language used (wdt:P2936)   |           | Egyptian Arabic (wd:Q29919)          | Egyptian Arabic (en)        |
| language used (wdt:P2936)   |           | Egyptian Sign Language (wd:Q5348443) | Egyptian Sign Language (en) |
| ...                         | ...       | ...                                  | ...                         |
| language used (wdt:P2936)   |           | Malay (wd:Q9237)                     | Malay (en)                  |
| language used (wdt:P2936)   |           | Modern Standard Arabic (wd:Q56467)   | Modern Standard Arabic (en) |
| language used (wdt:P2936)   |           | Saʽidi Arabic (wd:Q56592)            | Saʽidi Arabic (en)          |
| language used (wdt:P2936)   |           | Siwa (wd:Q36814)                     | Siwa (en)                   |
| official language (wdt:P37) |           | Arabic (wd:Q13955)                   | Arabic (en)                 |

Answer:
I looked up Egypt (wd:Q79) on Wikidata and queried the properties for official language and languages used. The query returns the following (IRI and English label):

- Official language (wdt:P37): Arabic (wd:Q13955)

- Languages used / languages spoken, written or signed (wdt:P2936 / wdt:P1412):
  - Egyptian Arabic (wd:Q29919)
  - Modern Standard Arabic (wd:Q56467)
  - Saʽidi Arabic (wd:Q56592)
  - Siwa (wd:Q36814)
  - Bedawi Arabic (wd:Q56714)
  - Beja (wd:Q33025)
  - Coptic (wd:Q36155)
  - Egyptian Sign Language (wd:Q5348443)
  - Libyan Arabic (wd:Q56503)
  - Malay (wd:Q9237)

In short: the official language of Egypt is Arabic (wd:Q13955). In everyday use, Egyptians commonly speak Egyptian Arabic (wd:Q29919) and various regional Arabic dialects; Modern Standard Arabic (wd:Q56467) is used formally. Other minority and regional languages (e.g., Coptic, Beja, Siwa) and Egyptian Sign Language are also listed on Wikidata as used in Egypt.

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

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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

You have access to the following knowledge graphs:
wikidata at http://localhost:7001 without notes

You are provided with the following notes across all knowledge graphs:
No notes available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
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 these rules:
- Explain your thought process before and after each step and function call.
- Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
- 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.
- Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
- 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.
- 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.
- 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.
- For questions with a "True" or "False" answer the SPARQL query should be an ASK query.

[User] what kind of language does egypt speak?

[Assistant] I will first find the Wikidata entity for "Egypt", then identify the property for official language, and then query the official and commonly spoken languages for Egypt. I'll explain each step and run SPARQL queries to verify. I'll start by searching for the entity "Egypt".

[Tool]
Top 10 entity alternatives:
1. Egypt (wd:Q79), also known as Arab Rep. Egypt, Arab Republic of Egypt, eg, EGY, Rep. Egypt, etc.: country in Northeast Africa and Southwest Asia / is instance of transcontinental country / is instance of Mediterranean country / is instance of sovereign state / country in Africa and Asia / country in Africa and Asia / country in Africa and Asia / is instance of country
2. Khedivate of Egypt (wd:Q127861, matched via Egypt), also known as Egypt, Egyptian Khedivate: 1867-1914 monarchy in Northeastern Africa / 1867-1914 monarchy in Northeastern Africa / is instance of transcontinental country / is instance of historical country / is instance of tributary state
3. Egypt Eyalet (wd:Q491507, matched via Egypt), also known as Beylerbeyilik of Egypt, Egypt, Mısır Eyalet, Pashalik of Egypt, QASR of Egypt: is instance of administrative territorial entity of the Ottoman Empire / is instance of Administrative divisions of the Ottoman Empire / is instance of privileged Ottoman province / Egyptian State (1517–1867) / is instance of eyalet / is instance of Eyalet
4. Egypt (wd:Q2083973), also known as Egypt, AK, Egypt, AR: is instance of town in the United States / town in Arkansas
5. Egypt (wd:Q5348306), also known as Egypt, Pennsylvania: is instance of unincorporated community in the United States / human settlement in Pennsylvania, United States
6. Egypt (wd:Q5348296), also known as Egypt, AL, Egypt, Etowah County, Alabama: is instance of census-designated place in the United States / census-designated place in Etowah County, Alabama / is instance of census-designated place
7. Egypt 1156 B.C. (wd:Q3586212, matched via Egypt), also known as Egypt, Egypt 1156 B.C.: Tomb of the Pharaoh: is instance of video game / 1999 video game / 1999 video game / 1999 video game
8. Egypt (wd:Q5348310), also known as Egypt, WV: is instance of unincorporated community in the United States / unincorporated community in Jefferson County, West Virginia
9. Southern Illinois (wd:Q3256684, matched via Egypt), also known as Egypt, Little Egypt: region of Illinois in the United States / is instance of geographical region / is instance of geographic region
10. Egypt (wd:Q5348317): 2004 album by Youssou N'Dour / is instance of album

[Assistant] I'll look up the Wikidata properties for languages, in particular "official language" and "language spoken", to prepare the SPARQL query. I'll search for properties with terms like "official language" and "language spoken".

[Tool]
Top 10 property alternatives:
1. official language (wd:P37 as pq/wdtn/prv/pr/psv/pqv/ps/prn/p/psn/wdt/pqn), also known as language official, language spoken, speaking, spoken in, P37: language designated as official by this item / language designated as official by this item / language designated as official by this item / language designated as official by this item / is subproperty of language used
2. native label (wd:P1705 as pq/wdtn/prv/pr/psv/pqv/ps/prn/p/psn/wdt/pqn, matched via official language name), also known as autonym, label in official language, label in original language, name in official language, name in original language, etc.: label for the items in their official language (P37) or their original language (P364) / label for the items in their official language (P37) or their original language (P364) / label for the items in their official language (P37) or their original language (P364) / label for the items in their official language  or their original language / is subproperty of name
3. original language of film or TV show (wd:P364 as pq/wdtn/prv/pr/psv/pqv/ps/prn/p/psn/wdt/pqn, matched via original language), also known as created on language, language of the original work, media language, original language, P364: language in which a film or a performance work was originally ... and songs; use P407 ("language of work or name") instead. / language in which a film or a performance work was originally ... written works; use P407 ("language of work or name") instead. / language in which a film or a performance work was originally ... written works; use P407 ("language of work or name") instead. / is subproperty of language of work or name
4. language used (wd:P2936 as pq/wdtn/prv/pr/psv/pqv/ps/prn/p/psn/wdt/pqn, matched via working language), also known as languages used, medium of instruction, used language, uses language, working language, etc.: language widely used (spoken or written) in this place or at this event or organisation
5. native language (wd:P103 as pq/wdtn/prv/pr/psv/pqv/ps/prn/p/psn/wdt/pqn, matched via first language), also known as first language, L1 speaker of, language native, mother tongue, P103: language or languages a person has learned from early childhood / is subproperty of languages spoken, written or signed / language or languages a person has learned from birth / language or languages a person has learned from birth
6. language regulatory body (wd:P1018 as pq/wdtn/prv/pr/psv/pqv/ps/prn/p/psn/wdt/pqn, matched via language authority), also known as language authority, regulatory body, P1018: regulatory body of a language
7. language of work or name (wd:P407 as pq/wdtn/prv/pr/psv/pqv/ps/prn/p/psn/wdt/pqn, matched via used language), also known as audio language, available in, broadcasting language, language, language of name, etc.: language associated with this creative work (such as books, ... (P103) and "languages spoken, written or signed" (P1412)) / language associated with this creative work (such as books, ... (P103) and "languages spoken, written or signed" (P1412)) / language associated with this work or name (for persons use P103 and P1412)
8. languages spoken, written or signed (wd:P1412 as pq/wdtn/prv/pr/psv/pqv/ps/prn/p/psn/wdt/pqn, matched via used language), also known as language, language of expression, language read, language signed, languages of expression, etc.: language(s) that a person or a people speaks, writes or signs, including the native language(s) / language(s) that a person speaks or writes, including the native language(s) / language(s) that a person speaks or writes, including the native language(s)
9. programmed in (wd:P277 as pq/wdtn/prv/pr/psv/pqv/ps/prn/p/psn/wdt/pqn, matched via language), also known as language, programming language, written in, P277: the programming language(s) in which the software is developed
10. Ethnologue language status (wd:P3823 as pq/wdtn/prv/pr/psv/pqv/ps/prn/p/psn/wdt/pqn, matched via language status), also known as EGIDS, language status, P3823: language status identifier by Ethnologue.com using EGIDS scale / language status identifier by Ethnologue.com using EGIDS scale

[Assistant] Now I'll run a SPARQL query on Wikidata (wd:Q79 = Egypt) to retrieve languages linked via the properties "official language" (P37), "language used" (P2936) and "languages spoken, written or signed" (P1412). The query will return the property IRI, the language item IRI, and an English label when available. I'll execute the query to verify the actual items stored in Wikidata.

[Tool]
Got 13 rows and 3 columns, showing the first 5 and last 5 rows below:
| property                    | language                             | languageLabel               |
| --------------------------- | ------------------------------------ | --------------------------- |
| language used (wdt:P2936)   | Bedawi Arabic (wd:Q56714)            | Bedawi Arabic (en)          |
| language used (wdt:P2936)   | Beja (wd:Q33025)                     | Beja (en)                   |
| language used (wdt:P2936)   | Coptic (wd:Q36155)                   | Coptic (en)                 |
| language used (wdt:P2936)   | Egyptian Arabic (wd:Q29919)          | Egyptian Arabic (en)        |
| language used (wdt:P2936)   | Egyptian Sign Language (wd:Q5348443) | Egyptian Sign Language (en) |
| ...                         | ...                                  | ...                         |
| language used (wdt:P2936)   | Malay (wd:Q9237)                     | Malay (en)                  |
| language used (wdt:P2936)   | Modern Standard Arabic (wd:Q56467)   | Modern Standard Arabic (en) |
| language used (wdt:P2936)   | Saʽidi Arabic (wd:Q56592)            | Saʽidi Arabic (en)          |
| language used (wdt:P2936)   | Siwa (wd:Q36814)                     | Siwa (en)                   |
| official language (wdt:P37) | Arabic (wd:Q13955)                   | Arabic (en)                 |

[Assistant] I'll run a SPARQL query that retrieves for Egypt (wd:Q79) the languages linked by the properties "official language" (P37), "language used" (P2936) and "languages spoken, written or signed" (P1412). The query will return the property IRI, language IRI, and English labels where available so I can summarize which languages are official and which are commonly used. Now I'll execute the query.

[Tool]
Got 13 rows and 4 columns, showing the first 5 and last 5 rows below:
| prop                        | propLabel | language                           | languageLabel               |
| --------------------------- | --------- | ---------------------------------- | --------------------------- |
| official language (wdt:P37) |           | Arabic (wd:Q13955)                 | Arabic (en)                 |
| language used (wdt:P2936)   |           | Bedawi Arabic (wd:Q56714)          | Bedawi Arabic (en)          |
| language used (wdt:P2936)   |           | Beja (wd:Q33025)                   | Beja (en)                   |
| language used (wdt:P2936)   |           | Coptic (wd:Q36155)                 | Coptic (en)                 |
| language used (wdt:P2936)   |           | Egyptian Arabic (wd:Q29919)        | Egyptian Arabic (en)        |
| ...                         | ...       | ...                                | ...                         |
| language used (wdt:P2936)   |           | Libyan Arabic (wd:Q56503)          | Libyan Arabic (en)          |
| language used (wdt:P2936)   |           | Malay (wd:Q9237)                   | Malay (en)                  |
| language used (wdt:P2936)   |           | Modern Standard Arabic (wd:Q56467) | Modern Standard Arabic (en) |
| language used (wdt:P2936)   |           | Saʽidi Arabic (wd:Q56592)          | Saʽidi Arabic (en)          |
| language used (wdt:P2936)   |           | Siwa (wd:Q36814)                   | Siwa (en)                   |

[Assistant] I'll run a final SPARQL query that retrieves languages for Egypt (wd:Q79) using the properties official language (P37), language used (P2936), and languages spoken/written/signed (P1412). The query will return the property IRIs, the language IRIs, and optional English labels so we can see which languages are official and which are commonly used. I'll execute it now.

[Tool]
Got 13 rows and 4 columns, showing the first 5 and last 5 rows below:
| prop                        | propLabel | lang                                 | langLabel                   |
| --------------------------- | --------- | ------------------------------------ | --------------------------- |
| language used (wdt:P2936)   |           | Bedawi Arabic (wd:Q56714)            | Bedawi Arabic (en)          |
| language used (wdt:P2936)   |           | Beja (wd:Q33025)                     | Beja (en)                   |
| language used (wdt:P2936)   |           | Coptic (wd:Q36155)                   | Coptic (en)                 |
| language used (wdt:P2936)   |           | Egyptian Arabic (wd:Q29919)          | Egyptian Arabic (en)        |
| language used (wdt:P2936)   |           | Egyptian Sign Language (wd:Q5348443) | Egyptian Sign Language (en) |
| ...                         | ...       | ...                                  | ...                         |
| language used (wdt:P2936)   |           | Malay (wd:Q9237)                     | Malay (en)                  |
| language used (wdt:P2936)   |           | Modern Standard Arabic (wd:Q56467)   | Modern Standard Arabic (en) |
| language used (wdt:P2936)   |           | Saʽidi Arabic (wd:Q56592)            | Saʽidi Arabic (en)          |
| language used (wdt:P2936)   |           | Siwa (wd:Q36814)                     | Siwa (en)                   |
| official language (wdt:P37) |           | Arabic (wd:Q13955)                   | Arabic (en)                 |

[Assistant] I'll run one final verification query to get the complete list of languages (IRIs and English labels) for Egypt (wd:Q79) using properties official language (P37), language used (P2936), and languages spoken/written/signed (P1412). This will let me list all returned languages accurately in the final answer. I'll execute the query now.

[Tool]
Got 13 rows and 4 columns, showing the first 5 and last 5 rows below:
| prop                        | propLabel | lang                                 | langLabel                   |
| --------------------------- | --------- | ------------------------------------ | --------------------------- |
| language used (wdt:P2936)   |           | Bedawi Arabic (wd:Q56714)            | Bedawi Arabic (en)          |
| language used (wdt:P2936)   |           | Beja (wd:Q33025)                     | Beja (en)                   |
| language used (wdt:P2936)   |           | Coptic (wd:Q36155)                   | Coptic (en)                 |
| language used (wdt:P2936)   |           | Egyptian Arabic (wd:Q29919)          | Egyptian Arabic (en)        |
| language used (wdt:P2936)   |           | Egyptian Sign Language (wd:Q5348443) | Egyptian Sign Language (en) |
| ...                         | ...       | ...                                  | ...                         |
| language used (wdt:P2936)   |           | Malay (wd:Q9237)                     | Malay (en)                  |
| language used (wdt:P2936)   |           | Modern Standard Arabic (wd:Q56467)   | Modern Standard Arabic (en) |
| language used (wdt:P2936)   |           | Saʽidi Arabic (wd:Q56592)            | Saʽidi Arabic (en)          |
| language used (wdt:P2936)   |           | Siwa (wd:Q36814)                     | Siwa (en)                   |
| official language (wdt:P37) |           | Arabic (wd:Q13955)                   | Arabic (en)                 |

[Assistant] I'll now provide the final SPARQL query I used and a concise answer summarizing the query results (official language and other languages used in Egypt). The SPARQL query returns the property, language IRIs, and English labels. I have already executed this query and verified it returns the listed languages.

[Tool] Stopping


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

Using entities:
General Motors (wd:Q81965), also known as General Motors Corporation, GM

Using properties:
product or material produced (wd:P1056 as wdt), also known as commodity, creates, has product, maker of, makes, etc.

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

Answer: I interpreted “GM” as General Motors (wd:Q81965). I searched the company’s product statements on Wikidata and found that General Motors (wd:Q81965) has product motor car (wd:Q1420). In other words: GM makes motor cars (wd:Q1420).

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

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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

You have access to the following knowledge graphs:
wikidata at http://localhost:7001 without notes

You are provided with the following notes across all knowledge graphs:
No notes available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
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 these rules:
- Explain your thought process before and after each step and function call.
- Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
- 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.
- Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
- 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.
- 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.
- 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.
- For questions with a "True" or "False" answer the SPARQL query should be an ASK query.

[User] what does gm make?

[Assistant] I will first search Wikidata for the entity corresponding to "GM" (likely General Motors). I'll explain my intent, run a search for "GM" and "General Motors", and then inspect the entity and properties to find what products it makes (e.g., motor vehicles, trucks, auto brands). I'll run a search now.

[Tool]
Top 10 entity alternatives:
1. The Gambia (wd:Q1005, matched via 🇬🇲), also known as 🇬🇲, GAM, Gambia, GM, Islamic Republic of the Gambia, etc.: is instance of sovereign state / sovereign state in West Africa / is instance of country / country in West Africa / country in Africa
2. gram (wd:Q41803, matched via gm), also known as g, gm, gramme, grams: unit of mass equal to 1/1000th of a kilogram / is instance of SI derived unit / is instance of UCUM base unit / is instance of unit of mass
3. .gm (wd:Q41758): Internet country-code top level domain for the Gambia / is instance of country code top-level domain
4. General Motors (wd:Q81965, matched via GM), also known as General Motors Corporation, GM: American automotive manufacturing corporation / is instance of automobile manufacturer / is instance of car manufacturer
5. Grandmaster (wd:Q105269, matched via GM), also known as GM, Grand Master, IGM, International Grandmaster: title in chess awarded by FIDE / is subclass of chess player / is instance of FIDE titles / is instance of FIDE title
6. geometric mean (wd:Q185049, matched via GM), also known as geometric average, geometric mean value, GM, proportional mean: the n-th root of the product of n numbers / is subclass of weighted geometric mean / is subclass of quasi-arithmetic mean / is instance of type of statistic / is subclass of Pythagorean mean / is subclass of mean
7. gigametre (wd:Q854546, matched via Gm), also known as gigametres, Gm: SI unit of length equal to one billion meters or 1,000 megameters / SI unit of length equal to one billion metres or 1,000 megametres / is instance of SI derived unit / is instance of Unit of length / is instance of unit of length / is instance of metric unit
8. gamemaster (wd:Q930701, matched via GM), also known as game master, game moderator, GM, referee: person who acts as an organizer in role-playing games / is instance of game mechanic / is instance of occupation / is subclass of narrator / is subclass of referee / is subclass of player / is instance of role / is subclass of host
9. Greasemonkey (wd:Q901312, matched via GM), also known as GM, GreaseMonkey, user script, userscript: is instance of userscript manager / is instance of browser extension / is instance of Firefox extension / is instance of free software / Mozilla Firefox extension
10. George Medal (wd:Q1507907, matched via GM), also known as GM: is instance of courage award / is instance of medallion / is instance of medal / British award

[Assistant] I'll inspect properties of the General Motors entity (wd:Q81965) to find statements about what it makes or produces — likely "industry", "product", or "produces/manufactures". I'll search for properties related to "product", "produce", "manufacture", and "industry" for that entity.

[Tool]
Top 10 property alternatives:
1. product or material produced (wd:P1056 as p/wdt, matched via product), also known as commodity, creates, has product, maker of, makes, etc.: material or product produced by an organization, industry, facility, or process / material or product produced by a business or industry / is subproperty of immediate cause of
2. official shop URL (wd:P10225 as p/wdt, matched via shop), also known as merch store, official shop website, official store URL, official store website, official website shop, etc.: official URL where the agent sells products/merchandise / official URL where the agent sells products/merchandise / is subproperty of official website
3. topic's main category (wd:P910 as p/wdt, matched via category), also known as article's main category, category, category for this topic, catmain, has category, etc.: main category of this topic / main Wikimedia category
4. part of (wd:P361 as p/wdt, matched via of), also known as assembly of, branch of, chain, collateral branch of, component of, etc.: object of which the subject is a part (if this subject is ... "has part" (P527, see also "has parts of the class" (P2670)) / object of which the subject is a part (if this subject is ... "has part" (P527, see also "has parts of the class" (P2670)) / object of which the subject is a part (if this subject is ... "has part" (P527, see also "has parts of the class" (P2670)) / object of which the subject is a part (if this subject is ... "has part" (P527, see also "has parts of the class" (P2670))
5. location of formation (wd:P740 as p/wdt, matched via from), also known as comes from, formation location, formation place, formed in, founded in, etc.: location where a group or organisation was formed / location where a group or organization was formed / is subproperty of location of creation
6. instance of (wd:P31 as p/wdt, matched via type), also known as example of, has type, is a, is an, is of type, etc.: type to which this subject corresponds/belongs. Different ... and the volcano is a type (instance) of volcanic landform / that class of which this subject is a particular example and ... a subclass of mountain (and an instance of volcanic landform)
7. industry (wd:P452 as p/wdt), also known as branch, economic branch, field of action, field of exercise, sector, etc.: specific industry of company or organization / is subproperty of part of
8. official name (wd:P1448 as p/wdt, matched via name), also known as be named, complete title, full title, legal name, long name, etc.: official name of the subject in its official language(s) / official name of the subject in its official language(s) / official name of the subject in its official language(s) / is subproperty of name
9. inception (wd:P571 as p/wdt, matched via constructed), also known as broke ground, built, commenced on date, commencement date, completed, etc.: time when an entity begins to exist; for date of official opening use P1619 / time when an entity begins to exist; for date of official opening use P1619 / date or point in time when the organisation / object was founded / created / is subproperty of start time
10. logo image (wd:P154 as p/wdt, matched via marque), also known as insignia, logo, logomark, mark, marque, etc.: graphic mark or emblem commonly used by commercial enterprises, organisations and products / graphic mark or emblem commonly used by commercial enterprises, organisations and products / graphic mark or emblem commonly used by commercial enterprises, organizations and products / graphic mark or emblem commonly used by commercial enterprises, organizations and products / is subproperty of icon

No other items found

[Assistant] I'll list triples for General Motors (wd:Q81965) with the property "product or material produced" (wdt:P1056) to see what Wikidata records as products GM makes. I'll run that query now.

[Tool]
Got 1 row and 3 columns:
| subject                    | property                                 | object               |
| -------------------------- | ---------------------------------------- | -------------------- |
| General Motors (wd:Q81965) | product or material produced (wdt:P1056) | motor car (wd:Q1420) |

[Assistant] I'll run a SPARQL query to get values of the "product or material produced" (P1056) property for General Motors (wd:Q81965). This should tell us what GM is recorded as making on Wikidata. I'll request English labels as optional.

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

[Assistant] I'll now provide the final SPARQL query (the same one I executed) and the concise answer based on its results.

[Tool] Stopping


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 ?place ?placeLabel ?population WHERE {
  ?place wdt:P17 wd:Q29 ; wdt:P31 / wdt:P279 * ?class ; wdt:P1082 ?population .
  FILTER ( ?class IN ( wd:Q515 , wd:Q2074737 ) ) OPTIONAL {
    ?place rdfs:label ?placeLabel FILTER ( LANG( ?placeLabel ) = "en" )
  }
}
ORDER BY DESC ( ?population )
LIMIT 1

Using entities:
municipality of Spain (wd:Q2074737), also known as Municipality of Spain, municipio de España, Spanish municipality
Spain (wd:Q29), also known as Kingdom of Spain
city (wd:Q515), also known as cities

Using properties:
population (wd:P1082 as wdt), also known as human population, inhabitants, P1082
country (wd:P17 as wdt), also known as host country, land, sovereign state, state, P17
subclass of (wd:P279 as wdt), also known as all members of this class also belong to, category of, form of, has superclass, is a class of, etc.
instance of (wd:P31 as wdt), also known as example of, has type, is a, is an, is of type, etc.

Answer: The largest city in Spain by population is Madrid (Wikidata: wd:Q2807) with a population of 3,416,771 (value from wdt:P1082).

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

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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

You have access to the following knowledge graphs:
wikidata at http://localhost:7001 without notes

You are provided with the following notes across all knowledge graphs:
No notes available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
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 these rules:
- Explain your thought process before and after each step and function call.
- Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
- 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.
- Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
- 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.
- 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.
- 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.
- For questions with a "True" or "False" answer the SPARQL query should be an ASK query.

[User] what the largest city in spain?

[Assistant] I will first locate the Wikidata entity for Spain and verify properties for population and country. I'll search for the entity "Spain" and properties related to "population" and "country". I'll explain each step before calling the search functions.

[Tool]
Top 10 entity alternatives:
1. Spain (wd:Q29), also known as Kingdom of Spain: country in southwestern Europe with territories in Africa / constitutional monarchy in Southwest Europe / constitutional monarchy in Southwest Europe / is instance of Mediterranean country / is instance of sovereign state / is instance of country / is instance of realm
2. Spain men's national football team (wd:Q42267, matched via Spain), also known as La Furia, La Furia Española, La Furia Roja, La Roja, Spain, etc.: team that represents Spain in international association football / men's national association football team representing Spain / men's national association football team representing Spain / team that represents Spain in international soccer / is instance of national association football team / is subclass of national association football team / is instance of national soccer team / is subclass of national soccer team
3. Second Spanish Republic (wd:Q178038, matched via Spain), also known as Spain: political regime established in Spain between April 14, 1931 and April 1, 1939 / is instance of historical country / is instance of historical period / is instance of Republic / is instance of republic
4. New Spain (wd:Q170603, matched via Spain), also known as Central America under Spain, Colonial Central America, Colonial Mexico, Kingdom of Mexico, Mexico under Spain, etc.: is instance of viceroyalty of the Spanish Empire / viceroyalty of the Spanish Empire (1535-1821)
5. Spain under the Restoration (wd:Q1044536, matched via Spain), also known as Bourbon Restoration, Kingdom of Spain, Restoration, Restoration (Spain), Second Bourbon Restoration, etc.: name given to a period between 1874 (end of First Spanish ... Spanish Republic), and the state of Spain during that time / is instance of historical country
6. Kingdom of Spain (1820-1823) (wd:Q238809, matched via Spain), also known as Kingdom of Spain, Spain, Trienio Liberal: 1820–1823 Spanish political period / is instance of historical country / is instance of historical period
7. Spain under Joseph Bonaparte (wd:Q1709185, matched via Spain), also known as Kingdom of Spain, Napoleonic Spain, Spain: is instance of Napoleonic client state / Napoleonic client state (1808–1813) / is instance of kingdom
8. Sexenio Democrático (wd:Q12411956, matched via Spain), also known as Kingdom of Spain, Spain: 1868–1874 period of fu under a provisional government / is instance of historical period
9. Ominous Decade (wd:Q2378204, matched via Spain), also known as Kingdom of Spain, second restoration of absolutism, Spain: period in the history of Spain, corresponding to the second ... of Fernando VII from August 31, 1823 to September 29, 1833 / is instance of historical period
10. Spain (wd:Q2306509): is instance of musical group / American rock band

[Assistant] Next I'll search for the population property in Wikidata to confirm its identifier (e.g., P1082) and find how to query it. I'll call the property search function for "population".

[Tool]
Top 10 property alternatives:
1. tabular population (wd:P4179 as pq/wdtn/prv/pr/psv/pqv/ps/prn/p/psn/wdt/pqn, matched via population), also known as population, P4179: same as population (P1082); used when there is data for many different points in time
2. population (wd:P1082 as pq/wdtn/prv/pr/psv/pqv/ps/prn/p/psn/wdt/pqn), also known as human population, inhabitants, P1082: number of people inhabiting the place; number of people of subject / number of people inhabiting the place; number of people of subject / number of people inhabiting the place; number of people of subject
3. male population (wd:P1540 as pq/wdtn/prv/pr/psv/pqv/ps/prn/p/psn/wdt/pqn), also known as male inhabitants, number of males, P1540: number of male people inhabiting the place; number of male people of subject / is subproperty of population
4. urban population (wd:P6343 as pq/wdtn/prv/pr/psv/pqv/ps/prn/p/psn/wdt/pqn), also known as P6343: number of people living within the territorial entity who live in its urban parts / is subproperty of population
5. occupant (wd:P466 as pq/wdtn/prv/pr/psv/pqv/ps/prn/p/psn/wdt/pqn, matched via inhabitant), also known as home team, houses, inhabitant, lessee, location of, etc.: person or organization occupying a building or facility / person or organization occupying property / is subproperty of used by
6. category populated by (wd:P4329 as pq/wdtn/prv/pr/psv/pqv/ps/prn/p/psn/wdt/pqn, matched via populated by), also known as category filled by, category has template, cat populated by, component adding into the category, populated by, etc.: software component (template, module, extension, MediaWiki core) populating the category
7. rural population (wd:P6344 as pq/wdtn/prv/pr/psv/pqv/ps/prn/p/psn/wdt/pqn), also known as P6344: number of people living within the territorial entity who live in its rural parts / is subproperty of population
8. country of citizenship (wd:P27 as pq/wdtn/prv/pr/psv/pqv/ps/prn/p/psn/wdt/pqn, matched via nationality), also known as citizen of, citizenship, country, (legal) nationality, nation, etc.: the object is a country that recognizes the subject as its citizen / the object is a country that recognizes the subject as its citizen / is subproperty of country
9. ethnic group (wd:P172 as pq/wdtn/prv/pr/psv/pqv/ps/prn/p/psn/wdt/pqn, matched via people), also known as (cultural) nationality, culture, ethnicity, ethnic or cultural origin, people, etc.: subject's ethnicity (consensus is that a VERY high standard ... on by scholars, or 3) is fictional and portrayed as such) / subject's ethnicity (consensus is that a VERY high standard ... on by scholars, or 3) is fictional and portrayed as such)
10. valid in place (wd:P3005 as pq/wdtn/prv/pr/psv/pqv/ps/prn/p/psn/wdt/pqn, matched via country), also known as applies to country, applies to location, applies to place, country, true in, etc.: is subproperty of applies to part / place where a statement is valid / place where a statement is valid

[Assistant] Population is property P1082. I will now find the administrative territorial entities (cities) within Spain. The property "country" is P17. I'll search for places that are instance of city and located in country Spain. I will construct a SPARQL query to find cities (instance of city: Q515) in Spain (Q29) and order them by population (P1082) to get the largest city. I'll first verify the entity id for "city" and possibly "municipality" or "capital" if needed. I'll search for entity "city".

[Tool]
Top 10 entity alternatives:
1. city (wd:Q515), also known as cities: is instance of classification of human settlements / is subclass of urban settlement / is subclass of city or town / large human settlement / large human settlement
2. Manchester City F.C. (wd:Q50602, matched via City), also known as Citizens, City, Manchester City, Manchester City FC, Manchester City F.C. Soccer, etc.: association football club in Manchester, England / association soccer club in Manchester, England / is instance of association football club / English national soccer team / is instance of soccer club
3. Leicester City F.C. (wd:Q19481, matched via City), also known as City, L.C.F.C., LCFC, Leicester, Leicester City, etc.: association football club in Leicester, England / is instance of association football club / is instance of soccer club / English football club
4. Swansea City A.F.C. (wd:Q18659, matched via City), also known as City, SCAFC, Swansea, Swansea City, Swansea City AFC, etc.: association football club in Swansea, Wales / is instance of association football club / English national soccer team / is instance of soccer club / Welsh football club
5. Stoke City F.C. (wd:Q18736, matched via City), also known as City, SCFC, Stoke, Stoke City, Stoke City FC, etc.: association football club in Stoke-on-Trent, England / is instance of association football club / English national soccer team / is instance of soccer club / English football club
6. Birmingham City F.C. (wd:Q19444, matched via City), also known as BCFC, Birmingham, Birmingham City, Birmingham City FC, Birmingham City Football Club, etc.: association football club in Birmingham, England / is instance of association football club / is instance of soccer club / English football club
7. Norwich City F.C. (wd:Q18721, matched via City), also known as City, NCFC, Norwich, Norwich City, Norwich City FC, etc.: association football club in Norwich, England / is instance of association football club / English national soccer team / is instance of soccer club / English football club
8. Cardiff City F.C. (wd:Q18662, matched via City), also known as Cardiff, Cardiff City, Cardiff City FC, Cardiff City Football Club, CCFC, etc.: association football club in Cardiff, Wales / is instance of association football club / is instance of soccer club / Welsh football club
9. Hull City A.F.C. (wd:Q19477, matched via City), also known as City, HCAFC, Hull, Hull City, Hull City AFC, etc.: association football club in Hull, England / is instance of association football club / is instance of soccer club / English football club
10. Coventry City F.C. (wd:Q19580, matched via City), also known as CCFC, City, Coventry, Coventry City, Coventry City FC, etc.: association football club in Coventry, England / is instance of association football club / is instance of soccer club / English football club

[Assistant]
I will build a SPARQL query that selects entities which are instance of city (wd:Q515) and country Spain (wd:Q29), retrieving their population P1082 (most recent value). I need to ensure I get the population value and rank to order by the most recent population. In Wikidata, population statements often have qualifiers for point in time (P585). To get latest population, I'll retrieve the population value and optionally the point in time and order by point in time desc and population value desc. I'll construct a query that finds ?city wdt:P31/wdt:P279? But better to use either instance of (P31) or instance of subclass. Many cities have P31 city. I'll query for ?city wdt:P17 wd:Q29 and a statement ?city p:P1082 ?popStatement; ?popStatement ps:P1082 ?population; OPTIONAL ?popStatement pq:P585 ?pointInTime. Then group by city and take the population with the latest pointInTime (MAX). But aggregation in QLever? It's SPARQL standard. I'll attempt to select cities and the population with the most recent point in time using ORDER BY and LIMIT 1. However need to ensure limit across cities—so better to select city and population sorted by COALESCE(pointInTime, ?some) desc, population desc, limit 1. But ordering across triples will produce multiple rows per city; we need to get the latest population per city. Another approach: for each city, get the population statements and order by pointInTime desc, then use GROUP BY ?city and MAX(?pointInTime) and corresponding population via subquery.

I'll write a subquery that finds for each city the latest pointInTime, then join to get the population at that time. Simpler: use p:P1082 with ps:P1082 ?population and OPTIONAL pq:P585 ?date. Then use GROUP BY ?city ?cityLabel and MAX(xsd:dateTime(?date)) as ?latestDate and MAX(?population)?? That may pick wrong population if multiple dates. Better: use subquery:

SELECT ?city ?cityLabel ?population ?date WHERE {
  ?city wdt:P17 wd:Q29.
  ?city wdt:P31/wdt:P279* wd:Q515.
  ?city p:P1082 ?popStmt.
  ?popStmt ps:P1082 ?population.
  OPTIONAL { ?popStmt pq:P585 ?date. }
  # get latest date per city
}
Then use an inner SELECT to get max date per city:
{
 SELECT ?city (MAX(?date) AS ?latestDate) WHERE { ... } GROUP BY ?city
}
Then join on ?date = ?latestDate OR if no date, handle nulls: use COALESCE with blank? If population without date, treat date as "0000"? Hmm.

Perhaps simpler for this user's question: They ask "what the largest city in spain?" Likely answer: Madrid. We must produce SPARQL query and execute it to ensure returns correct. Could do a simpler query: find cities in Spain and order by population (using wdt:P1082 which is the direct property (may return a single value, often the most recent preferred value). Using wdt:P1082 returns the direct value of population (preferred version) — that's often the latest. So query:

SELECT ?city ?cityLabel ?population WHERE {
  ?city wdt:P17 wd:Q29;
        wdt:P31/wdt:P279* wd:Q515;
        wdt:P1082 ?population.
  OPTIONAL { ?city rdfs:label ?cityLabel FILTER(LANG(?cityLabel)="en") }
}
ORDER BY DESC(?population)
LIMIT 1

This should yield Madrid. Let's proceed with that simpler approach and execute.

Before calling execute, explain thought process and then run.

I'll run a SPARQL query that finds items that are instance of (or subclass of) city (Q515), are located in country Spain (Q29), and have a direct population value (wdt:P1082). I'll order by population descending and return the top result. This uses wdt:P1082 which usually gives the preferred/latest population value. Now I'll execute the query.

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

[Assistant] I'll search for the Wikidata entity for Madrid to inspect its population statements.

[Tool]
Top 10 entity alternatives:
1. Madrid (wd:Q2807): is instance of municipality of Spain / is instance of tourist destination / municipality and capital of Spain / is instance of tourist place / capital of Spain
2. Madrid (wd:Q1934324), also known as Madrid, Iowa: is instance of city in the United States / is instance of city of the United States / city in Iowa, United States
3. Madrid (wd:Q66470): is instance of human settlement / city in Alabama, United States
4. Madrid (wd:Q1331390), also known as Madrid, New Mexico, Madrid, NM: census-designated place in Santa Fe County, New Mexico, United States / is instance of census-designated place in the United States / is instance of census-designated place
5. Madrid (wd:Q2323298), also known as Madrid, NE: is instance of village in the United States / village in Iowa, United States
6. Madrid (wd:Q2316396): Colombian municipality of the department of Cundinamarca / is instance of municipality of Colombia
7. Madrid (wd:Q155605), also known as Municipality of Madrid: municipality of the Philippines in the province of Surigao del Sur / is instance of municipality of the Philippines
8. Madrid (wd:Q3708806), also known as Madrid, New York, Madrid, NY: is instance of town in the United States / is instance of town of New York / city in New York, United States
9. Madrid (wd:Q5638036): is instance of locality of Mexico / human settlement in Mexico
10. Madrid (wd:Q6728617): is instance of electoral district of the Spanish Congress / Spanish Congress Electoral District

[Assistant] I will check Madrid's population using a query similar to the earlier one but specifically for Madrid (wd:Q2807) to see its population via wdt:P1082.

[Tool]
Got 1 row and 1 column:
| population            |
| --------------------- |
| 3416771 (xsd:decimal) |

[Assistant] I'll list the P31 (instance of) statements for Madrid to see how it's classified in Wikidata. I'll call the list function for subject wd:Q2807 and property wdt:P31.

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

[Assistant] I will check Barcelona's instance of statements to see how it's classified.

[Tool]
Got 2 rows and 3 columns:
| subject              | property              | object                                   |
| -------------------- | --------------------- | ---------------------------------------- |
| Barcelona (wd:Q1492) | instance of (wdt:P31) | city (wd:Q515)                           |
| Barcelona (wd:Q1492) | instance of (wdt:P31) | municipality of Catalonia (wd:Q33146843) |

[Assistant] I will verify the Wikidata item for "human settlement" and then run a refined query that includes cities, municipalities of Spain, or human settlements, to ensure Madrid is included and returned as the largest city. I'll search for "human settlement" in the KG.

[Tool]
Top 10 entity alternatives:
1. human settlement (wd:Q486972), also known as human settlements, inhabited place, settlement, settlements: place of any size, in which people permanently live / is subclass of group of structures or buildings / community of any size, in which people live / place of any size, in which people live / densely populated geographic location / is subclass of geographical feature / is subclass of geographical object / is instance of first-order class / is subclass of populated place
2. Kwande (wd:Q6450151, matched via Human settlement), also known as Human settlement: is instance of local government area of Nigeria / is instance of human settlement / LGA in Benue State, Nigeria
3. Burunduki (human settlement) (wd:Q11031822): human settlement in Krasnoarmeysky District, Chuvash Republic", Chuvash Republic, Russia / is instance of administrative territorial entity of Russia / is instance of hamlet
4. Svetlogorsk human settlement (wd:Q4145591): human settlement in Svetlogorsky District, Kaliningrad Oblast, Russia / is instance of urban settlement in Russia / is instance of former municipality
5. Ozherelye human settlement (wd:Q4145561): human settlement in Kashirsky District, Moscow Oblast, Russia / is instance of urban settlement in Russia / is instance of former municipality
6. Sabiñánigo (human settlement) (wd:Q24013331): capital of Sabiñánigo Municipality, Spain / is instance of municipality capital / is instance of locality / is instance of city
7. Ateca (wd:Q24016487, matched via Ateca (human settlement)), also known as Ateca (human settlement), Ateca town: capital town of Ateca Municipality, Spain / is instance of municipality capital / is instance of town
8. submerged city (wd:Q20616831, matched via sunken human settlement), also known as submerged settlement, submerged town, sunken city, sunken human settlement, sunken settlement, etc.: city or town no longer inhabited, due to flooding, or being submerged underwater / is subclass of destroyed settlement / is subclass of abandoned village / is subclass of former settlement / is subclass of submerged place / is subclass of sunken entity / is subclass of city
9. history of a human settlement (wd:Q116885401, matched via human settlement history), also known as history of settlement, human settlement history, settlement history: is instance of aspect of history / is subclass of locality / is subclass of history / aspect of history
10. Noginsk human settlement (wd:Q4145557): human settlement in Noginsky District, Moscow Oblast, Russia / is instance of urban settlement in Russia

[Assistant]
Barcelona was returned as the top result earlier because it's classified as instance of city (Q515) and has a population value P1082 of 1,702,547, while Madrid had P1082 of 3,416,771 but wasn't returned because Madrid's P31 doesn't include Q515 (it's a municipality). To correctly find the largest city by population, I should include items that are instance of city (Q515) OR instance of municipality of Spain (Q2074737) or subclass of human settlement. A better approach is to select any human settlement (wd:Q486972) or municipality of Spain (Q2074737) located in Spain and order by wdt:P1082.

I'll craft a query that selects any item that is an instance of (P31) any class that's a subclass of human settlement (Q486972) or municipality of Spain (Q2074737), or include both city (Q515) and municipality of Spain (Q2074737). Using wdt:P31/wdt:P279* wd:Q486972 should include cities and municipalities. Let's run a query for items with wdt:P31/wdt:P279* wd:Q486972 and wdt:P17 wd:Q29 and wdt:P1082 population, order desc limit 10 to see top results.

[Tool]
Got 10 rows and 3 columns:
| place                                    | placeLabel                       | population            |
| ---------------------------------------- | -------------------------------- | --------------------- |
| Madrid Metropolitan Area (wd:Q959356)    | Madrid Metropolitan Area (en)    | 5682111 (xsd:decimal) |
| Barcelona metropolitan area (wd:Q249489) | Barcelona metropolitan area (en) | 5093585 (xsd:decimal) |
| Barcelona metropolitan area (wd:Q249489) | Barcelona metropolitan area (en) | 5082355 (xsd:decimal) |
| Barcelona metropolitan area (wd:Q249489) | Barcelona metropolitan area (en) | 4082000 (xsd:decimal) |
| Barcelona metropolitan area (wd:Q249489) | Barcelona metropolitan area (en) | 3239337 (xsd:decimal) |
| Valencia metropolitan area (wd:Q3325101) | Valencia metropolitan area (en)  | 1775845 (xsd:decimal) |
| Valencia metropolitan area (wd:Q3325101) | Valencia metropolitan area (en)  | 1763704 (xsd:decimal) |
| Barcelona (wd:Q1492)                     | Barcelona (en)                   | 1702547 (xsd:decimal) |
| Barcelona City (wd:Q31913048)            | Barcelona City (en)              | 1660122 (xsd:decimal) |
| Barcelona City (wd:Q31913048)            | Barcelona City (en)              | 1660122 (xsd:decimal) |

[Assistant] I'll check whether 'municipality of Spain' (wd:Q2074737) is a subclass of 'human settlement' (wd:Q486972) by inspecting its subclass chain. I'll list triples for wd:Q2074737 with property wdt:P279 (subclass of).

[Tool]
Got 5 rows and 3 columns:
| subject                             | property               | object                                                   |
| ----------------------------------- | ---------------------- | -------------------------------------------------------- |
| municipality of Spain (wd:Q2074737) | subclass of (wdt:P279) | municipality (wd:Q15284)                                 |
| municipality of Spain (wd:Q2074737) | subclass of (wdt:P279) | administrative territorial entity of Spain (wd:Q3183364) |
| municipality of Spain (wd:Q2074737) | subclass of (wdt:P279) | LAU 2 (wd:Q11618417)                                     |
| municipality of Spain (wd:Q2074737) | subclass of (wdt:P279) | municipio (wd:Q1763214)                                  |
| municipality of Spain (wd:Q2074737) | subclass of (wdt:P279) | third-order administrative division (wd:Q48909258)       |

[Assistant]
Municipality of Spain isn't explicitly shown as subclass of human settlement but municipality is often subclass of administrative territorial entity. To include Madrid (which is instance of municipality of Spain), I should include items that are instance of municipality of Spain as well as items that are instance of city. I'll craft a query that finds places where ?place wdt:P17 wd:Q29 and (wdt:P31/wdt:P279* wd:Q515 OR wdt:P31 wd:Q2074737 OR wdt:P31/wdt:P279* wd:Q486972). But simpler: include either instance of city (Q515) OR instance of municipality of Spain (Q2074737) OR instance of human settlement (Q486972). However including human settlement returns metropolitan areas etc. But I can filter to exclude metropolitan areas by excluding items that are instance of 'metropolitan area' (wd:Q4448567) or that have 'metropolitan area' in their label. But better is to target items that are instance of municipality of Spain OR instance of city. Many large Spanish municipalities (Madrid, Barcelona) will be included.

I'll write a query that gets items with country Spain and (P31 Q515 OR P31 Q2074737 OR subclass chain). Use VALUES to allow multiple classes.

I'll select ?place with wdt:P17 wd:Q29 and ?place wdt:P31 ?class. FILTER(?class IN (wd:Q515, wd:Q2074737, wd:Q486972)). But if classes are subclass of those, we miss. Use wdt:P31/wdt:P279* ?class and then filter. Let's build:

SELECT ?place ?placeLabel ?population WHERE {
  ?place wdt:P17 wd:Q29;
         wdt:P31/wdt:P279* ?class;
         wdt:P1082 ?population.
  FILTER (?class IN (wd:Q515, wd:Q2074737, wd:Q486972))
  OPTIONAL label
}
ORDER BY DESC(?population)
LIMIT 1

Execute.

[Tool]
Got 1 row and 3 columns:
| place                                 | placeLabel                    | population            |
| ------------------------------------- | ----------------------------- | --------------------- |
| Madrid Metropolitan Area (wd:Q959356) | Madrid Metropolitan Area (en) | 5682111 (xsd:decimal) |

[Tool]
Got 10 rows and 4 columns:
| place                         | placeLabel          | class                               | population            |
| ----------------------------- | ------------------- | ----------------------------------- | --------------------- |
| Madrid (wd:Q2807)             | Madrid (en)         | municipality of Spain (wd:Q2074737) | 3416771 (xsd:decimal) |
| Barcelona (wd:Q1492)          | Barcelona (en)      | municipality of Spain (wd:Q2074737) | 1702547 (xsd:decimal) |
| Barcelona (wd:Q1492)          | Barcelona (en)      | city (wd:Q515)                      | 1702547 (xsd:decimal) |
| Barcelona City (wd:Q31913048) | Barcelona City (en) | city (wd:Q515)                      | 1660122 (xsd:decimal) |
| Barcelona City (wd:Q31913048) | Barcelona City (en) | city (wd:Q515)                      | 1660122 (xsd:decimal) |
| Barcelona City (wd:Q31913048) | Barcelona City (en) | city (wd:Q515)                      | 1660122 (xsd:decimal) |
| Barcelona City (wd:Q31913048) | Barcelona City (en) | city (wd:Q515)                      | 1660122 (xsd:decimal) |
| Valencia (wd:Q8818)           | Valencia (en)       | municipality of Spain (wd:Q2074737) | 825948 (xsd:decimal)  |
| Valencia (wd:Q8818)           | Valencia (en)       | municipality of Spain (wd:Q2074737) | 825948 (xsd:decimal)  |
| Seville (wd:Q8717)            | Seville (en)        | municipality of Spain (wd:Q2074737) | 687488 (xsd:decimal)  |

[Assistant] I'll run a final SPARQL query that selects places in Spain that are instances (or subclasses) of city (Q515) or municipality of Spain (Q2074737), retrieves their population (wdt:P1082), orders by population descending, and returns the top result. This should give the largest city (by population) in Spain with its Wikidata IRI. Now I'll execute that query.

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

[Assistant] The query returned Madrid (wd:Q2807) with population 3,416,771 as the largest city in Spain by population (using wdt:P1082). I'll now provide the final SPARQL query and answer.

[Tool] Stopping


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

Using entities:
Eva Perón (wd:Q40933), also known as Eva, Eva Duarte Ibarguren, Eva Peron, Evita, Evita Perón, etc.

Using properties:
cause of death (wd:P509 as wdt), also known as death cause, died of, die from, die of, method of murder, etc.

Answer: Eva Perón died of cervical cancer (cervix uterine cancer), Wikidata: wd:Q160105.

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

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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

You have access to the following knowledge graphs:
wikidata at http://localhost:7001 without notes

You are provided with the following notes across all knowledge graphs:
No notes available

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/
qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
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 these rules:
- Explain your thought process before and after each step and function call.
- Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
- 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.
- Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
- 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.
- 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.
- 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.
- For questions with a "True" or "False" answer the SPARQL query should be an ASK query.

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

[Assistant] Step 1 — I'll search for the Wikidata item for "Eva Perón" to get the entity identifier I should use. I'll query the knowledge graph for that entity.

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

[Assistant] I'll search for properties of the Eva Perón item related to illness, cause of death, or medical condition to find the correct property used in Wikidata.

[Tool]
Top 10 property alternatives:
1. cause of death (wd:P509 as p/wdt), also known as death cause, died of, die from, die of, method of murder, etc.: underlying or immediate cause of death.  Underlying cause ... category, e.g. natural causes, accident, homicide, suicide / underlying or immediate cause of death.  Underlying cause ... category, e.g. natural causes, accident, homicide, suicide / an item describing the cause of a person or specific organism's death. Samples: leukaemia, car crash / medical cause of a person or specific organism's death (not to be confused with P1196)
2. manner of death (wd:P1196 as p/wdt, matched via circumstance of death), also known as circumstance of death, death manner, death type, nature of death, type of death, etc.: general circumstances of a person's death; e.g. natural ... mechanism, e.g. heart attack, trauma, pneumonia etc. / general circumstances of a person's death; e.g. natural ... mechanism, e.g. heart attack, trauma, pneumonia etc. / general circumstances of a person's death; e.g. natural ... mechanism, e.g. heart attack, trauma, pneumonia...
3. place of death (wd:P20 as p/wdt, matched via died), also known as death location, death place, deathplace, died, died in, etc.: most specific known (e.g. city instead of country, or ... death location of a person, animal or fictional character / most specific known (e.g. city instead of country, or ... death location of a person, animal or fictional character / most specific known (e.g. city instead of country, or ... death location of a person, animal or fictional character / is subproperty of location
4. date of death (wd:P570 as p/wdt, matched via died), also known as date of the end, dead, death, death date, deathdate, etc.: is subproperty of dissolved, abolished or demolished date / is subproperty of dissolved, abolished or demolished / date on which the subject died / date on which the subject died / date on which the subject died / is subproperty of end time
5. place of burial (wd:P119 as p/wdt, matched via interment), also known as ashes scattered at, burial location, burial place, buried at, buried in, etc.: location of grave, resting place, place of ash-scattering, ... places: e.g., re-burials, parts of body buried separately. / location of grave, resting place, place of ash-scattering, ... places: e.g., re-burials, parts of body buried separately. / location of grave, resting place, place of ash-scattering, ... e.g. re-burials, cenotaphs, parts of body buried separately / location of grave, resting place, place of ash-scattering, etc, (e.g. city or cemetery) for a person / is subproperty of location
6. described by source (wd:P1343 as p/wdt, matched via described by obituary), also known as defined in, described by biography, described by encyclopedia, described by obituary, described by reference work, etc.: dictionary, encyclopaedia, etc. where this item is described / work where this item is described / is subproperty of attested in
7. birth name (wd:P1477 as p/wdt, matched via né), also known as birthname, bn, bname, born as, full birth name, etc.: full name of a person at birth, if different from their ... John Peter Doe for Joe Doe, Ann Smith for Ann Miller) / full name of a person at birth, if different from their current, generally used name / full name of a person at birth, if different from their current name / is subproperty of name
8. place of birth (wd:P19 as p/wdt, matched via born), also known as birth city, birth location, birth place, birthplace, born, etc.: most specific known (e.g. city instead of country, or ... birth location of a person, animal or fictional character / most specific known (e.g. city instead of country, or ... birth location of a person, animal or fictional character / most specific known birth location of a person, animal or fictional character / is subproperty of location
9. date of birth (wd:P569 as p/wdt, matched via born), also known as birth date, birthdate, birth year, birthyear, born, etc.: is subproperty of date of foundation or creation / date on which the subject was born / date on which the subject was born / date on which the subject was born / is subproperty of inception
10. religion or worldview (wd:P140 as p/wdt, matched via life stance), also known as belief system, believes, denomination, devotee of, faith, etc.: religion of a person, organisation or religious building, or associated with this subject / religion of a person, organisation or religious building, or associated with this subject / religion of a person, organization or religious building, or associated with this subject

No other items found

[Assistant] I'll run a SPARQL query to get the value of the "cause of death" (P509) statement for Eva Perón (wd:Q40933), and also fetch an English label for that cause.

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

[Assistant]
Step-by-step summary of my process (explaining each action and its result), followed by the final SPARQL query and the answer. Then I'll finalize by returning the query and the concise answer.

1) I searched for the Wikidata item for "Eva Perón" to find the correct entity identifier.
- Thought before the call: I need to find the Wikidata QID for Eva Perón to use in SPARQL queries.
- Action: search_entity("Eva Perón").
- Result: the top match is Eva Perón — wd:Q40933 (Argentine actress and politician).
- Thought after the call: I will use wd:Q40933 as the subject for querying medical/illness properties.

2) I looked for which property on that item represents cause of death or illness.
- Thought before the call: Wikidata uses properties like "cause of death" (P509) or "medical condition" (P1050), so I should confirm the property used for Eva Perón.
- Action: search_property_of_entity on wd:Q40933 with query "cause of death".
- Result: The property "cause of death" (wd:P509) was identified as relevant.
- Thought after the call: I'll query wd:Q40933 wdt:P509 to get the cause of death item.

3) I executed a SPARQL query to retrieve the cause of death for Eva Perón and its English label.
- Thought before the call: Run a simple query: wd:Q40933 wdt:P509 ?cause and fetch rdfs:label in English if available.
- Action: executed the SPARQL query (shown below) against Wikidata.
- Result: The query returned one result: cause = wd:Q160105 with English label "cervix uterine cancer".
- Thought after the call: This indicates Eva Perón died of cervical cancer (Wikidata item wd:Q160105).

Final SPARQL query I used:
SELECT ?cause ?causeLabel WHERE {
  wd:Q40933 wdt:P509 ?cause .
  OPTIONAL { ?cause rdfs:label ?causeLabel . FILTER(LANG(?causeLabel) = "en") }
}

Final answer based on the query result:
Eva Perón died of cervical cancer (cervix uterine cancer), Wikidata: wd:Q160105.

I will now return the final query and the concise answer.

[Tool] Stopping