PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
SELECT ?start ?end WHERE {
  wd:Q91 p:P39 ?statement .
  ?statement ps:P39 wd:Q11696 .
  OPTIONAL {
    ?statement pq:P580 ?start .
  }
  OPTIONAL {
    ?statement pq:P582 ?end .
  }
}

Abraham Lincoln was President of the United States from March 4, 1861 to April 15, 1865.

[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 http://amur:7001

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

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

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

[User] when was abe lincoln president?

[Assistant]
Let's break down the question:

1. The user is asking for the period when Abraham Lincoln was president.
2. We need to identify the entity for Abraham Lincoln and the property for "president" (likely "position held") and the qualifiers for the start and end time of his presidency.

First, I'll search for the entity "Abe Lincoln" in Wikidata to get the correct identifier.

[Tool]
Top 10 entity alternatives:
1. Abraham Lincoln, also known as President Lincoln, Uncle Abe, Honest Abe, Abe Lincoln (wd:Q91): president of the United States from 1861 to 1865, military officer, statesperson, postmaster, politician, farmer, writer, lawyer
2. Abe Lincoln, also known as Abram Lincoln (wd:Q4666410): American jazz trombonist (1907-2000), jazz musician
3. Abraham Lincoln, also known as Abe Lincoln (wd:Q4669012): named passenger train
4. Abe Lincoln (wd:Q49395851): mine in Santa Fe County, New Mexico, United States
5. Abe Lincoln (wd:Q63889409): musical character in the musical Abe
6. Abe Lincoln Mine (wd:Q49395856): mine in Lincoln County, Nevada, United States of America
7. Abe Lincoln Playground (wd:Q34631707)
8. Abe Lincoln Mountain (wd:Q49008420)
9. Abe Lincoln Mine (wd:Q49395859): mine in Colfax County, New Mexico, United States of America
10. Abe Lincoln Mine (wd:Q49395857): mine in Pershing County, Nevada, United States of America

[Assistant]
The correct entity for Abraham Lincoln, the president, is wd:Q91.

Next, I need to find the property for "president" or "position held" and the qualifiers for the start and end time of his presidency. I'll search for properties related to "position held" for Abraham Lincoln.

[Tool]
Top 10 property alternatives:
1. position held, also known as function, held position, holds position, job, office held (wd:P39 as p/wdt): subject currently or formerly holds the object position or public office
2. military or police rank, also known as military rank, naval rank, police rank, rank (wd:P410 as p/wdt): military or police rank achieved by a person (should usually hav...ualifier), or military or police rank associated with a position
3. 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)
4. work location, also known as work place, working from, working at, worked from, worked at (wd:P937 as p/wdt): location where persons or organisations were actively participating in employment, business or other work, significant place, location
5. candidacy in election, also known as ran in election, running in election, election candidacy, candidate in election, candidate in (wd:P3602 as p/wdt): election where the subject is a candidate, participant in
6. member of political party, also known as political party member, political party, party membership, party, member of party (wd:P102 as p/wdt): the political party of which a person is or has been a member or otherwise affiliated, member of
7. present in work, also known as is shown in, in work, in narrative, character in, from work (wd:P1441 as p/wdt): this (fictional or fictionalized) entity, place, or person appea...r works, P1343 for entities described in non-fictional accounts)
8. owner of, also known as owns, owns property, shareholder of (wd:P1830 as p/wdt): entities owned by the subject
9. religion or worldview, also known as believes, worldview, religious affiliation, religion or world view, religion (wd:P140 as p/wdt): religion of a person, organization or religious building, or associated with this subject
10. 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

No other items found

[Assistant]
The property "position held" (wdt:P39) is used to indicate offices such as "President of the United States." We need to find the qualifiers for start and end time of this position.

I'll now search for the relevant qualifiers for "position held" to identify start and end dates.

[Tool]
Top 10 property alternatives:
1. start time, also known as start date, since, valid, join time, joined (wd:P580 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): time an entity begins to exist or a statement starts being valid, point in time
2. end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time
3. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): time when an entity begins to exist; for date of official opening use P1619, start time
4. work period (start), also known as start working, flourished (start), start time for work, start date of activity, fl. (start) (wd:P2031 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): start of period during which a person or group flourished (fl. = "floruit") in their professional activity, start time, floruit
5. work period (end), also known as floruit end, floruit (end of work), flourished (end), retirement, work ends (wd:P2032 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): end of period during which a person or group flourished (fl. = "floruit") in their professional activity, end time, floruit
6. dissolved, abolished or demolished date, also known as ended, publication end date, final issue, date repealed, final year (wd:P576 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): point in time at which the subject (organisation, building) ceas...g equipment,  "discontinued date" (P2669) for stopping a product, end time
7. earliest end date, also known as end date (earliest) (wd:P8554 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): (qualifier) earliest date on which the statement could have begun to no longer be true, earliest date, end time
8. date of death, also known as DOD, deathdate, died, died on, year of death (wd:P570 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): dissolved, abolished or demolished date, date on which the subject died, end time
9. refine date, also known as date refinement, exact time, hour, local time, quarter (wd:P4241 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): qualifier to narrow down the precision of a date not fully specified by the Wikidata time datatype precision field
10. earliest date, also known as no earlier than, terminus post quem, start date (earliest), on or after this date, minimum date (wd:P1319 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): earliest date at which an event could have happened. Use as qualifier for other date properties

[Assistant]
The qualifiers "start time" (wdt:P580) and "end time" (wdt:P582) are used for the period of holding a position.

Now, I will construct a SPARQL query to find the start and end time of Abraham Lincoln's presidency by:
- Selecting statements where Abraham Lincoln (wd:Q91) held the position "President of the United States"
- Retrieving the qualifiers for start and end time

First, I need to confirm the entity for "President of the United States." I'll search for it.

[Tool]
Top 10 entity alternatives:
1. President of the United States, also known as US President, U.S. President, United States President, the president of the United States, President of the U.S. (wd:Q11696): head of state and head of government of the United States of America
2. cultural depictions of John F. Kennedy, also known as cultural depictions of JFK, cultural depictions of John Fitzgerald Kennedy, cultural depictions of President John F. Kennedy, cultural depictions of President Kennedy, President of the United States (wd:Q17512211): John F. Kennedy depicted in culture
3. President of the United States (wd:Q125680992): fictional position in the Grand Theft Auto video game series (HD)
4. Jimmy Carter, also known as James E. Carter, James Earl Carter, Jr., James E. Carter Jr., James E. Carter, Jr., 39th President of the United States (wd:Q23685): President of the United States from 1977 to 1981, human rights activist, environmentalist, autobiographer, businessperson, peace activist, naval officer, humanitarian, statesperson, submariner, politician, diplomat, engineer, novelist, farmer, writer
5. 2024 United States presidential election, also known as USA presidential election, 2024, US 2024 presidential election, POTUS 47, Harris v. Trump, Harris vs. Trump (wd:Q101110072): 60th quadrennial U.S. presidential election
6. Vice President of the United States, also known as President of the Senate, President of the United States Senate, United States Vice President, United States VP, USA VP (wd:Q11699): second-highest constitutional office in the United States
7. President of Mexico, also known as President of the United Mexican States (wd:Q628004): head of state of the country of Mexico
8. Executive Office of the President of the United States, also known as EOP, EOPOTUS, Executive Office of the President, The White House, United States Executive Office of the President (wd:Q1355327): U.S. federal government office of the president of the United States
9. President-elect of the United States, also known as President-Elect (wd:Q1467287): winning candidate of the U.S. presidential election in the time before inauguration
10. The Presidents of the United States of America, also known as Pot USA, PotUSA, PUSA, The Presidents, The Presidents of the United States (wd:Q176430): American rock band

[Assistant]
The correct entity for "President of the United States" is wd:Q11696.

Now, I will construct the SPARQL query:
- Find statements where Abraham Lincoln (wd:Q91) held the position "President of the United States" (wd:Q11696) using p:P39.
- Retrieve the qualifiers for start time (pq:P580) and end time (pq:P582).

Here is the query I will use:

[Tool]
Got 1 row and 2 columns:
| start                               | end                                 |
| ----------------------------------- | ----------------------------------- |
| 1861-03-04T00:00:00Z (xsd:dateTime) | 1865-04-15T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the start and end dates of Abraham Lincoln's presidency by querying his 'position held' statements for 'President of the United States' and extracting the relevant start and end times. The answer provided matches the query result and is accurate. No further refinement is needed.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?language ?languageLabel WHERE {
  {
    wd:Q79 wdt:P37 ?language .
  } UNION {
    wd:Q79 wdt:P2936 ?language .
  }
  OPTIONAL {
    ?language rdfs:label ?languageLabel FILTER ( lang( ?languageLabel ) = "en" )
  }
}

Got 13 rows and 2 columns, showing the first 5 and last 5 rows below:
| language                           | languageLabel               |
| ---------------------------------- | --------------------------- |
| Arabic (wd:Q13955)                 | Arabic (en)                 |
| English (wd:Q1860)                 | English (en)                |
| Kenzi (wd:Q20639851)               | Kenzi (en)                  |
| Egyptian Arabic (wd:Q29919)        | Egyptian Arabic (en)        |
| Beja (wd:Q33025)                   | Beja (en)                   |
| ...                                | ...                         |
| Modern Standard Arabic (wd:Q56467) | Modern Standard Arabic (en) |
| Libyan Arabic (wd:Q56503)          | Libyan Arabic (en)          |
| Saʽidi Arabic (wd:Q56592)          | Saʽidi Arabic (en)          |
| Bedawi Arabic (wd:Q56714)          | Bedawi Arabic (en)          |
| Malay (wd:Q9237)                   | Malay (en)                  |

Egypt is a multilingual country. The official language is Arabic, but other languages spoken or used in Egypt include English, Kenzi, Egyptian Arabic, Beja, Modern Standard Arabic, Libyan Arabic, Saʽidi Arabic, Bedawi Arabic, Malay, Coptic, and Siwa.

[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 http://amur:7001

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 language does egypt speak?

[Assistant]
Let's break down the question:

1. The user wants to know what language is spoken in Egypt.
2. I need to identify the entity for "Egypt" and the property that links a country to its official or spoken languages.

Step 1: Search for the entity "Egypt".

[Tool]
Top 10 entity alternatives:
1. Egypt, also known as Republic of Egypt, Rep. Egypt, EGY, eg, Arab Republic of Egypt (wd:Q79): country in Northeast Africa and Southwest Asia
2. Khedivate of Egypt, also known as Egypt, Egyptian Khedivate (wd:Q127861): 1867-1914 monarchy in Northeastern Africa
3. Egypt Eyalet, also known as QASR of Egypt, Pashalik of Egypt, Egypt, Mısır Eyalet, Beylerbeyilik of Egypt (wd:Q491507): Egyptian State (1517–1867)
4. Egypt, also known as Egypt, AK, Egypt, AR (wd:Q2083973): town in Arkansas
5. Egypt, also known as Egypt, Etowah County, Alabama, Egypt, AL (wd:Q5348296): census-designated place in Etowah County, Alabama
6. Egypt, also known as Egypt, Pennsylvania (wd:Q5348306): human settlement in Pennsylvania, United States
7. Egypt 1156 B.C., also known as Egypt, Egypt 1156 B.C.: Tomb of the Pharaoh (wd:Q3586212): 1999 video game
8. Egypt, also known as Egypt, WV (wd:Q5348310): unincorporated community in Jefferson County, West Virginia
9. Egypt (wd:Q5348317): 2004 album by Youssou N'Dour
10. Egypt, also known as Egypt, IN, Egypt, Indiana (wd:Q5348297): unincorporated community in Jasper County, Minnesota

[Assistant]
The most relevant entity for modern Egypt is wd:Q79 (country in Northeast Africa and Southwest Asia).

Next, I need to find the property that links a country to its spoken or official languages. I will search for properties related to "language" for countries.

[Tool]
Top 10 property alternatives:
1. programmed in, also known as language, programming language, written in (wd:P277 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): the programming language(s) in which the software is developed
2. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): language(s) that a person or a people speaks, writes or signs, including the native language(s)
3. language of work or name, also known as language of the reference, language of URL, language of website, language of work, named in language (wd:P407 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): language associated with this creative work (such as books, show...guage" (P103) and "languages spoken, written or signed" (P1412))
4. official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): language designated as official by this item, language used
5. language used, also known as languages used, medium of instruction, used language, uses language, working language (wd:P2936 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): language widely used (spoken or written) in this place or at this event or organisation
6. language style, also known as manner, term register, obsolete, register, sense register (wd:P6191 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): to denote of the way a sense of a word is used, e.g., slang, vulgarism, babytalk, colloquialism, etc.
7. native language, also known as first language, L1 speaker of, language native, mother tongue (wd:P103 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): language or languages a person has learned from early childhood, languages spoken, written or signed
8. writing language, also known as languages of writings, languages written, language written, writing languages, language of works (wd:P6886 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): language in which the writer has written their work, languages spoken, written or signed
9. Ethnologue language status, also known as EGIDS, language status (wd:P3823 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): language status identifier by Ethnologue.com using EGIDS scale
10. variety of lexeme, form or sense, also known as dialect, used in dialect, variety of form (wd:P7481 as psn/prn/pqv/psv/wdt/prv/pq/pr/pqn/wdtn/p/ps): dialect, graphic or phonetic variety that this lexeme, form or sense is used in

[Assistant]
The most relevant properties for this question are:
- official language (wd:P37): language designated as official by this item
- languages spoken, written or signed (wd:P1412): language(s) that a person or a people speaks, writes or signs

For a country, "official language" is most direct, but "languages spoken" could provide a broader answer. I'll start with "official language" (wd:P37) for Egypt (wd:Q79), and can expand if needed.

I'll construct a SPARQL query to find the official language(s) of Egypt.

[Tool]
Got 1 row and 1 column:
| language           |
| ------------------ |
| Arabic (wd:Q13955) |

[Tool] Got no rows and 1 columns

[Assistant]
The official language of Egypt (wd:Q79) is Arabic (wd:Q13955). There are no additional results for "languages spoken, written or signed" for Egypt in Wikidata.

Here is the final SPARQL query and answer.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The answer correctly identifies Arabic as the official language of Egypt, and the SPARQL query retrieves the official language (wdt:P37) of Egypt (wd:Q79). However, the user's question is phrased as 'what kind of language does Egypt speak?', which could be interpreted more broadly than just the official language. Egypt is a multilingual country, and other languages are spoken there, such as English, French, and various local dialects. To provide a more comprehensive answer, the query could be refined to include not only the official language but also other languages spoken in Egypt, using properties like 'languages spoken or written' (wdt:P2936) or similar. Additionally, the query should return the IRIs of the languages, and labels can be included optionally.

[Assistant]
Thank you for the feedback. To provide a more comprehensive answer, I will:

1. Retrieve not only the official language (wdt:P37) but also other languages spoken in Egypt using properties such as "language used" (wdt:P2936).
2. Optionally include rdfs:label for human-readable names of the languages.
3. Ensure the query returns the IRIs of the languages.

First, I'll check if Egypt (wd:Q79) has values for "language used" (wdt:P2936) or any other relevant properties.

[Tool]
Got 2,575 rows and 3 columns, showing the first 10 rows below:
| subject        | property                       | object                                                                          |
| -------------- | ------------------------------ | ------------------------------------------------------------------------------- |
| Egypt (wd:Q79) | instance of (wdt:P31)          | country (wd:Q6256)                                                              |
| Egypt (wd:Q79) | country (wdt:P17)              | Egypt (wd:Q79)                                                                  |
| Egypt (wd:Q79) | coordinate location (wdt:P625) | POINT(29.000000 27.000000) (geo:wktLiteral)                                     |
| Egypt (wd:Q79) | Commons category (wdt:P373)    | Egypt                                                                           |
| Egypt (wd:Q79) | image (wdt:P18)                | <http://commons.wikimedia.org/wiki/Special:FilePath/All%20Gizah%20Pyramids.jpg> |
| Egypt (wd:Q79) | part of (wdt:P361)             | Middle East (wd:Q7204)                                                          |
| Egypt (wd:Q79) | population (wdt:P1082)         | 114535772 (xsd:decimal)                                                         |
| Egypt (wd:Q79) | inception (wdt:P571)           | 1922-02-28T00:00:00Z (xsd:dateTime)                                             |
| Egypt (wd:Q79) | described at URL (wdt:P973)    | <http://68k.news/index.php?section=nation&loc=EG&lang=AR>                       |
| Egypt (wd:Q79) | short name (wdt:P1813)         | 🇪🇬 (zxx)                                                                        |
| ...            | ...                            | ...                                                                             |

[Tool]
Got 12 rows and 3 columns, showing the first 10 rows below:
| subject        | property                  | object                             |
| -------------- | ------------------------- | ---------------------------------- |
| Egypt (wd:Q79) | language used (wdt:P2936) | English (wd:Q1860)                 |
| Egypt (wd:Q79) | language used (wdt:P2936) | Malay (wd:Q9237)                   |
| Egypt (wd:Q79) | language used (wdt:P2936) | Coptic (wd:Q36155)                 |
| Egypt (wd:Q79) | language used (wdt:P2936) | Egyptian Arabic (wd:Q29919)        |
| Egypt (wd:Q79) | language used (wdt:P2936) | Modern Standard Arabic (wd:Q56467) |
| Egypt (wd:Q79) | language used (wdt:P2936) | Beja (wd:Q33025)                   |
| Egypt (wd:Q79) | language used (wdt:P2936) | Siwa (wd:Q36814)                   |
| Egypt (wd:Q79) | language used (wdt:P2936) | Libyan Arabic (wd:Q56503)          |
| Egypt (wd:Q79) | language used (wdt:P2936) | Saʽidi Arabic (wd:Q56592)          |
| Egypt (wd:Q79) | language used (wdt:P2936) | Bedawi Arabic (wd:Q56714)          |
| ...            | ...                       | ...                                |

[Tool]
Got 1 row and 3 columns:
| subject        | property                    | object             |
| -------------- | --------------------------- | ------------------ |
| Egypt (wd:Q79) | official language (wdt:P37) | Arabic (wd:Q13955) |

[Tool]
Got 13 rows and 2 columns, showing the first 5 and last 5 rows below:
| language                           | languageLabel               |
| ---------------------------------- | --------------------------- |
| Arabic (wd:Q13955)                 | Arabic (en)                 |
| English (wd:Q1860)                 | English (en)                |
| Kenzi (wd:Q20639851)               | Kenzi (en)                  |
| Egyptian Arabic (wd:Q29919)        | Egyptian Arabic (en)        |
| Beja (wd:Q33025)                   | Beja (en)                   |
| ...                                | ...                         |
| Modern Standard Arabic (wd:Q56467) | Modern Standard Arabic (en) |
| Libyan Arabic (wd:Q56503)          | Libyan Arabic (en)          |
| Saʽidi Arabic (wd:Q56592)          | Saʽidi Arabic (en)          |
| Bedawi Arabic (wd:Q56714)          | Bedawi Arabic (en)          |
| Malay (wd:Q9237)                   | Malay (en)                  |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves both the official language (wdt:P37) and other widely used languages (wdt:P2936) for Egypt (wd:Q79), returning their IRIs and English labels. The answer provided is accurate and comprehensive, listing the languages spoken in Egypt as per the query result. The query follows all the specified rules, including returning IRIs and using OPTIONAL for labels. No further refinement is needed.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?product ?productLabel WHERE {
  ?product wdt:P176 wd:Q81965 .
  OPTIONAL {
    ?product rdfs:label ?productLabel FILTER ( lang( ?productLabel ) = "en" )
  }
}

Got 793 rows and 2 columns, showing the first 5 and last 5 rows below:
| product                          | productLabel                   |
| -------------------------------- | ------------------------------ |
| Buick Estate (wd:Q1002745)       | Buick Estate (en)              |
| Buick Electra (wd:Q1002748)      | Buick Electra (en)             |
| Buick Invicta (wd:Q1002761)      | Buick Invicta (en)             |
| Buick Limited (wd:Q1002771)      | Buick Limited (en)             |
| Buick Master Six (wd:Q1002780)   | Buick Master Six (en)          |
| ...                              | ...                            |
| Cadillac ATS (wd:Q979003)        | Cadillac ATS (en)              |
| T18 Boarhound (wd:Q979464)       | T18 Boarhound (en)             |
| wd:Q991211                       | list of Opel concept cars (en) |
| Pontiac Trans Sport (wd:Q991256) | Pontiac Trans Sport (en)       |
| Isuzu 117 Coupé (wd:Q993674)     | Isuzu 117 Coupé (en)           |

General Motors (GM) manufactures a wide range of products, primarily motor vehicles. The query retrieves all items in Wikidata marked as manufactured by GM, which may include non-vehicle products if present. The list is not exhaustive and includes, for example, various Buick models such as the Buick Estate, Buick Electra, and others, as well as any other products associated with GM as manufacturer.

[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 http://amur:7001

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 break down the question:

1. "gm" likely refers to General Motors, a well-known automobile manufacturer.
2. The question asks what GM "makes," which could refer to products, such as vehicles, brands, or other manufactured goods.

First, I will search for the entity "gm" in Wikidata to confirm the correct entity for General Motors.

[Tool] No entity items found

[Assistant] The search for "gm" did not return any entities. It's possible that searching for "General Motors" instead of the abbreviation will yield the correct entity. I will try searching for "General Motors" in Wikidata.

[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 top result, wd:Q81965, is "General Motors," the automotive manufacturing corporation based in Detroit, Michigan, USA. This matches the intended meaning of "gm" in the question.

Next, I need to determine what General Motors "makes." This likely refers to products or manufactured items. I will search for properties related to "products" or "manufactures" for the entity 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. 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
3. 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
4. logo image, also known as masthead, wordmark, trademark, trade mark, sign (wd:P154 as p/wdt): graphic mark or emblem commonly used by commercial enterprises, organizations and products, icon
5. total revenue, also known as turnover, sales, revenue, income, gross revenue (wd:P2139 as p/wdt): income gained by an organization during a given time frame. Not to be confused with fiscal revenue
6. country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as p/wdt): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country
7. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
8. 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)
9. 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
10. 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)

No other items found

[Assistant] The property "product, material, or service produced or provided" (wdt:P1056) is the most relevant for finding what General Motors makes. I will now list the objects for this property for General Motors (wd:Q81965) to see what products are associated with the company.

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

[Assistant]
The only product explicitly listed for General Motors (wd:Q81965) under the property "product, material, or service produced or provided" (wdt:P1056) is "motor car" (wd:Q1420).

To provide a more comprehensive answer, I will check if there are other relevant properties, such as "manufacturer" or "brand," that might list specific products or brands made by General Motors. I will search for properties related to "manufacturer" for General Motors.

[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. has subsidiary, also known as subordinate body, subsidiary body, subordinate unit, subsidiary, subsidiary company (wd:P355 as p/wdt): subsidiary of a company or organization; generally a fully owned...siness division" (P199). Opposite of parent organization (P749)., has part(s), owner of
3. 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
4. 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
5. 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
6. industry, also known as branch, economic branch, field of action, field of exercise, sector (wd:P452 as p/wdt): specific industry of company or organization, part of
7. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
8. logo image, also known as masthead, wordmark, trademark, trade mark, sign (wd:P154 as p/wdt): graphic mark or emblem commonly used by commercial enterprises, organizations and products, icon
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. member of, also known as band member of, membership, member of musical group, in musical group, be member of (wd:P463 as p/wdt): organization, club or musical group to which the subject belongs...ical position, such as a member of parliament (use P39 for that), part of

No other items found

[Assistant]
The search did not reveal a more specific property for "manufacturer" that would list individual products. The "product, material, or service produced or provided" property (wdt:P1056) is the main one used, and it only lists "motor car" (wd:Q1420) for General Motors.

To provide a more detailed answer, I will check if General Motors is listed as the manufacturer (using the property "manufacturer" wdt:P176) of specific products, such as car models or brands. I will search for objects of the property "manufacturer" (wdt:P176) with the query "General Motors".

[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. GM Korea, also known as General Motors Korea, GM Daewoo, 한국GM (wd:Q497193): South Korean subsidiary of General Motors
3. SAIC General Motors, also known as SAIC GM, Shanghai General Mtoros, Shanghai GM (wd:Q7488453): automotive joint venture
4. General Motors of Argentina, also known as General Motors Argentina, GM Argentina (wd:Q5876985): subsidiary of General Motors
5. General Motors of Canada, also known as General Motors Canada, GM Canada (wd:Q1475085): automobile manufacturer in Canada
6. General Motors Diesel, also known as General Motors Diesel, Limited, GMD (wd:Q5532044): Canadian locomotive manufacturer
7. General Motors de México, also known as General Motors Mexico (wd:Q5876989): automobile manufacturer
8. Holden, also known as General Motors-Holden's Ltd, Holden Ltd, GM Holden Ltd (Holden) (wd:Q29281): Australian subsidiary of General Motors, an automaker
9. Vauxhall, also known as General Motors UK Limited, GMUK, Vauxhall Motors (wd:Q59187): English car company, subsidiary of Stellantis
10. General Motors do Brasil (wd:Q10752027): Auto manufacturer

No other items found

No literal items found

[Assistant]
The search for objects of the property "manufacturer" (wdt:P176) with "General Motors" returned various subsidiaries and related companies, but not specific products or car models.

To find specific products made by General Motors, I will look for items where General Motors (wd:Q81965) is the manufacturer (wdt:P176). I will construct a SPARQL query to find such items and optionally include their labels for clarity.

[Tool]
Got 20 rows and 2 columns, showing the first 5 and last 5 rows below:
| product                          | productLabel            |
| -------------------------------- | ----------------------- |
| Buick Estate (wd:Q1002745)       | Buick Estate (en)       |
| Buick Electra (wd:Q1002748)      | Buick Electra (en)      |
| Buick Invicta (wd:Q1002761)      | Buick Invicta (en)      |
| Buick Limited (wd:Q1002771)      | Buick Limited (en)      |
| Buick Master Six (wd:Q1002780)   | Buick Master Six (en)   |
| ...                              | ...                     |
| Buick Park Avenue (wd:Q1002838)  | Buick Park Avenue (en)  |
| Buick Reatta (wd:Q1002842)       | Buick Reatta (en)       |
| Buick Rainier (wd:Q1002843)      | Buick Rainier (en)      |
| Buick Rendezvous (wd:Q1002847)   | Buick Rendezvous (en)   |
| Buick Serie D-Four (wd:Q1002854) | Buick Serie D-Four (en) |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query is mostly correct in that it retrieves all products manufactured by General Motors (GM) using the property 'manufacturer' (wd:P176). However, the query only returns the IRIs of the products and does not provide any human-readable labels, which would be helpful for users. While labels are not strictly required unless requested, including them in an OPTIONAL clause would improve the answer's usefulness without violating the rules. Additionally, the answer summary could mention that the list is not exhaustive and that the query retrieves all items in Wikidata marked as manufactured by GM, which may include non-vehicle products if present.

Suggested refinement: Add an OPTIONAL clause to retrieve rdfs:label for each product.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves all items manufactured by General Motors (GM) by using the manufacturer property (wdt:P176) and the GM entity (wd:Q81965). It returns the IRIs of the products as required, and the labels are included optionally. The answer accurately summarizes the query's intent and results. No further refinement is necessary.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?city WHERE {
  ?city wdt:P17 wd:Q29 ; wdt:P1082 ?population ; wdt:P31 ?type .
  VALUES ?type {
    wd:Q515 wd:Q2074737
  }
}
ORDER BY DESC ( ?population )
LIMIT 1

The largest city in Spain by population is Madrid (wd:Q2807).

[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 http://amur:7001

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 break down the question:

1. We need to identify the entity for "Spain".
2. We need to find cities in Spain.
3. We need to determine the population of each city to find the largest.
4. We need to select the city with the highest population.

First, let's search for the entity "Spain" in Wikidata.

[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 correct entity for Spain as a country is wd:Q29.

Next, we need to find cities in Spain. Let's search for properties related to "city" or "largest city" for Spain.

[Tool]
Top 10 property alternatives:
1. contains the administrative territorial entity, also known as has shires, has rural cities, has regions, has municipalities, has members (wd:P150 as p/wdt): (list of) direct subdivisions of an administrative territorial entity, has part(s)
2. capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as p/wdt): seat of government of a country, province, state or other type of administrative territorial entity
3. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
4. urban population (wd:P6343 as p/wdt): number of people living within the territorial entity who live in its urban parts, population
5. head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as p/wdt): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson
6. legislative body, also known as aboriginal council, Zila, Tehsil, rural council, representative body (wd:P194 as p/wdt): legislative body governing this entity; political institution wi...ted representatives, such as a parliament/legislature or council
7. part of, also known as of, within, system of, subsystem of, subgroup of (wd:P361 as p/wdt): object of which the subject is a part (if this subject is alread... of "has part" (P527, see also "has parts of the class" (P2670))
8. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as p/wdt): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
9. area, also known as total area, surface area, surface, size, resolution (wd:P2046 as p/wdt): area occupied by an object
10. population, also known as inhabitants, human population (wd:P1082 as p/wdt): number of people inhabiting the place; number of people of subject

No other items found

[Assistant]
The property "contains the administrative territorial entity" (wdt:P150) is likely to list cities or subdivisions within Spain. To find the largest city, we need to get the population (wdt:P1082) of each city and select the one with the highest value.

Let's construct a query to:
- Get all entities contained within Spain (using wdt:P150)
- For each, get its population (wdt:P1082)
- Return the city with the highest population

I'll write and execute a query to check the results.

[Tool]
Got 1 row and 2 columns:
| city                 | population            |
| -------------------- | --------------------- |
| Andalusia (wd:Q5783) | 8619616 (xsd:decimal) |

[Assistant]
The result shows "Andalusia" (wd:Q5783) as the largest by population, but Andalusia is an autonomous community, not a city. This suggests that wdt:P150 for Spain includes regions, not just cities.

We need to refine our approach to get actual cities in Spain. Let's search for the class "city" in Wikidata and then find all cities in Spain (country = wd:Q29), then get their populations.

[Tool]
Top 10 entity alternatives:
1. city, also known as cities (wd:Q515): large human settlement
2. Manchester City F.C., also known as The Sky Blues, City, The Citizens, The Blues, Sky Blues (wd:Q50602): association football club in Manchester, England
3. Leicester City F.C., also known as The Foxes, Leicester Fosse Football Club, Leicester Fosse FC, Leicester Fosse, Leicester City (wd:Q19481): association football club in Leicester, England
4. Swansea City A.F.C., also known as Swansea City Association Football Club, The Swans, The Jacks, Swansea City AFC, Swansea City (wd:Q18659): association football club in Swansea, Wales
5. Stoke City F.C., also known as City, SCFC, Stoke, Stoke City, Stoke City FC (wd:Q18736): association football club in Stoke-on-Trent, England
6. Birmingham City F.C., also known as BCFC, City, Blues, Birmingham City Football Club, Birmingham City (wd:Q19444): association football club in Birmingham, England
7. Norwich City F.C., also known as Norwich City FC, The Canaries, Norwich City Football Club, Norwich City, Norwich (wd:Q18721): association football club in Norwich, England
8. Cardiff City F.C., also known as Cardiff, The Bluebirds, City, CCFC, Cardiff City Football Club (wd:Q18662): association football club in Cardiff, Wales
9. Hull City A.F.C., also known as City, HCAFC, Hull, Hull City, Hull City AFC (wd:Q19477): association football club in Hull, England
10. Coventry City F.C., also known as Coventry City FC, Sky Blues, Coventry City Football Club, Coventry City, Coventry (wd:Q19580): association football club in Coventry, England

[Assistant]
The correct entity for "city" as a human settlement is wd:Q515.

Now, let's find all entities that are instances of "city" (wd:Q515) and are located in Spain (country = wd:Q29), and get their populations. We'll then select the city with the highest population.

I'll write and execute this refined query.

[Tool]
Got 1 row and 1 column:
| city                 |
| -------------------- |
| Barcelona (wd:Q1492) |

[Tool]
Got 3 rows and 2 columns:
| city                          | population            |
| ----------------------------- | --------------------- |
| Barcelona (wd:Q1492)          | 1702547 (xsd:decimal) |
| Barcelona City (wd:Q31913048) | 1660122 (xsd:decimal) |
| Zaragoza City (wd:Q31926034)  | 666880 (xsd:decimal)  |

[Tool]
Top 10 entity alternatives:
1. Madrid (wd:Q2807): capital of Spain
2. Madrid (wd:Q2807): capital of Spain
3. Madrid (wd:Q824651): municipality of Spain
4. Madrid, also known as Madrid, Iowa (wd:Q1934324): city in Iowa, United States
5. Madrid (wd:Q66470): city in Alabama, United States
6. Madrid, also known as Madrid, New Mexico, Madrid, NM (wd:Q1331390): census-designated place in Santa Fe County, New Mexico, United States
7. Madrid, also known as Madrid, NE (wd:Q2323298): village in Iowa, United States
8. Madrid (wd:Q2316396): Colombian municipality of the department of Cundinamarca
9. Madrid, also known as Municipality of Madrid (wd:Q155605): municipality of the Philippines in the province of Surigao del Sur
10. Madrid, also known as Madrid, New York, Madrid, NY (wd:Q3708806): city in New York, United States

[Tool]
Got 1,336 rows and 3 columns, showing the first 10 rows below:
| subject           | property                                                    | object                                                                              |
| ----------------- | ----------------------------------------------------------- | ----------------------------------------------------------------------------------- |
| Madrid (wd:Q2807) | instance of (wdt:P31)                                       | municipality of Spain (wd:Q2074737)                                                 |
| Madrid (wd:Q2807) | country (wdt:P17)                                           | Spain (wd:Q29)                                                                      |
| Madrid (wd:Q2807) | located in the administrative territorial entity (wdt:P131) | Community of Madrid (wd:Q5756)                                                      |
| Madrid (wd:Q2807) | coordinate location (wdt:P625)                              | POINT(-3.703333 40.416944) (geo:wktLiteral)                                         |
| Madrid (wd:Q2807) | Commons category (wdt:P373)                                 | Madrid                                                                              |
| Madrid (wd:Q2807) | image (wdt:P18)                                             | <http://commons.wikimedia.org/wiki/Special:FilePath/Madrid%20%2838624991251%29.jpg> |
| Madrid (wd:Q2807) | part of (wdt:P361)                                          | Villa y corte (wd:Q111805205)                                                       |
| Madrid (wd:Q2807) | population (wdt:P1082)                                      | 3416771 (xsd:decimal)                                                               |
| Madrid (wd:Q2807) | described by source (wdt:P1343)                             | Brockhaus and Efron Encyclopedic Dictionary (wd:Q602358)                            |
| Madrid (wd:Q2807) | official name (wdt:P1448)                                   | Madrid (es)                                                                         |
| ...               | ...                                                         | ...                                                                                |

[Assistant]
It appears that Madrid (wd:Q2807) is the capital of Spain and has a population of 3,416,771, which is higher than Barcelona's population in the previous query. The earlier query missed Madrid because it is classified as a "municipality of Spain" (wd:Q2074737) rather than directly as a "city" (wd:Q515).

To accurately answer the question, we should include both "city" (wd:Q515) and "municipality of Spain" (wd:Q2074737) as possible types for Spanish cities.

Let me write the final SPARQL query to find the largest city or municipality in Spain by population, considering both types.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly identifies the largest city in Spain by population, returning the IRI for Madrid. The query uses appropriate properties (country, population, instance of) and restricts the type to city or municipality, ensuring relevance. The answer is accurate and the query follows all required guidelines.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?cancer ?cancerLabel WHERE {
  wd:Q40933 wdt:P509 ?cancer .
  OPTIONAL {
    ?cancer rdfs:label ?cancerLabel FILTER ( lang( ?cancerLabel ) = "en" )
  }
}

Eva Perón 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 http://amur:7001

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 break down the question:

1. The user is asking about the type of cancer that Eva Perón had.
2. We need to identify the entity for Eva Perón and the property that links a person to their cause or type of death, specifically focusing on cancer.

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

[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 correct entity for Eva Perón, the Argentine actress and politician, is wd:Q40933.

Next, I need to find the property that links a person to the type of cancer they had. This could be "cause of death" or a more specific property related to medical conditions or diseases suffered.

I will search for properties related to "cancer" for the entity wd:Q40933.

[Tool]
Top 10 property alternatives:
1. 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
2. religion or worldview, also known as believes, worldview, religious affiliation, religion or world view, religion (wd:P140 as p/wdt): religion of a person, organization or religious building, or associated with this subject
3. 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
4. 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)
5. 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
6. movement, also known as subculture, trend, scientific movement, school, philosophical movement (wd:P135 as p/wdt): literary, artistic, scientific or philosophical movement or scen...ed with this person or work. For political ideologies use P1142.
7. 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
8. 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
9. 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
10. 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)

No other items found

[Assistant]
The most relevant property found is "cause of death" (wd:P509). This property should link Eva Perón to the specific type of cancer she had.

Next, I will list the values for the "cause of death" property (wdt:P509) for Eva Perón (wd:Q40933) to see which type of cancer is specified.

[Tool]
Got 1 row and 3 columns:
| subject               | property                  | object                             |
| --------------------- | ------------------------- | ---------------------------------- |
| Eva Perón (wd:Q40933) | cause of death (wdt:P509) | cervix uterine cancer (wd:Q160105) |

[Tool]
Got 1 row and 1 column:
| cancer                             |
| ---------------------------------- |
| cervix uterine cancer (wd:Q160105) |

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

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the type of cancer (cervix uterine cancer) that Eva Perón had by querying the 'cause of death' property (wdt:P509) for her Wikidata entity (wd:Q40933). The query also optionally retrieves the English label for the cancer type. The answer is accurate, complete, and follows all the specified rules for SPARQL queries. No further refinement is needed.