PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?instrument ?instrumentLabel WHERE {
  wd:Q154216 wdt:P1303 ?instrument .
  OPTIONAL {
    ?instrument rdfs:label ?instrumentLabel FILTER ( LANG( ?instrumentLabel ) = "en" )
  }
}

Got 4 rows and 2 columns:
| instrument              | instrumentLabel  |
| ----------------------- | ---------------- |
| voice (wd:Q17172850)    | voice (en)       |
| bass guitar (wd:Q46185) | bass guitar (en) |
| piano (wd:Q5994)        | piano (en)       |
| guitar (wd:Q6607)       | guitar (en)      |

Cat Stevens plays the following instruments: voice, bass guitar, piano, and guitar.

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

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

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

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

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

[User] Which instruments does Cat Stevens play?

[Assistant] To answer the question "Which instruments does Cat Stevens play?" I will first search for the entity "Cat Stevens" in Wikidata to get its identifier. Then, I will look for properties related to musical instruments played by this entity. Finally, I will construct a SPARQL query to retrieve the instruments played by Cat Stevens.

[Tool]
Top 10 entity alternatives:
1. Cat Stevens, also known as Yusuf Islam, Yusuf Islam (Cat Stevens), Yusuf/Cat Stevens, Yusuf (wd:Q154216): British musician (born 1948), singer-songwriter, recording artist, guitarist, musician, composer, singer
2. Cat Stevens (wd:Q123717389): 2001 box set by Cat Stevens
3. Catherine Crowe, also known as Catherine Ann Crowe, Mrs. Crowe, Catherine Stevens Crowe, Catherine Stevens (wd:Q2537956): English novelist, story writer, and playwright; spiritualist and spirit story collector (1790–1872), translator, writer
4. Catherine Stevens (wd:Q14918517): Belgian athletics competitor, athletics competitor
5. Catrin Stevens (wd:Q47124278): historian, editor, writer
6. Catherine Stevens (wd:Q96292350)
7. Catherine Hamersly, also known as Catherine Stevens, Kate Hamersly, Kate Stevens (wd:Q118198771): (1823-1893)
8. Barbara Stanwyck, also known as Ruby Stevens, Ruby Catherine Stevens (wd:Q94002): American actress (1907–1990), television actor, screenwriter, stage actor, film actor, actor, model
9. Catasetum stevensonii (wd:Q15443245): species of plant
10. Catherine Octavia Stevens (wd:Q105812567): British astronomer (1865–1959), astronomer

[Assistant] The entity "Cat Stevens" corresponds to wd:Q154216 in Wikidata. Now I will search for properties related to musical instruments played by this entity. I will look for properties that might indicate the instruments he plays.

[Tool]
Top 10 property alternatives:
1. instrument, also known as uses this instrument, teaches instrument, instruments, plays this instrument, plays instrument (wd:P1303 as wdt/p): musical instrument that a person plays or teaches or used in a music occupation, uses
2. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as wdt/p): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
3. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
4. voice type, also known as range of voice, register, tessitura, type of voice, vocal type (wd:P412 as wdt/p): person's voice type. expected values: soprano, mezzo-soprano, contralto, countertenor, tenor, baritone, bass (and derivatives)
5. Pitchfork artist ID, also known as Pitchfork, Pitchfork ID (wd:P8819 as wdt/p): identifier for musical artists on the Pitchfork website
6. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdt/p): the object is a country that recognizes the subject as its citizen, country
7. occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt/p): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
8. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as wdt/p): 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 wdt/p): main Wikimedia category
10. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)

No other items found

[Assistant] The property "instrument" (wdt:P1303) is used to indicate the musical instruments that a person plays. I will now construct a SPARQL query to retrieve the instruments played by Cat Stevens (wd:Q154216). I will also include the labels of the instruments for better readability.

[Tool]
Got 4 rows and 2 columns:
| instrument              | instrumentLabel  |
| ----------------------- | ---------------- |
| voice (wd:Q17172850)    | voice (en)       |
| bass guitar (wd:Q46185) | bass guitar (en) |
| piano (wd:Q5994)        | piano (en)       |
| guitar (wd:Q6607)       | guitar (en)      |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the instruments that Cat Stevens plays using the property 'plays instrument' (wdt:P1303). The query returns the instrument identifiers and their English labels, which matches the user's question. The answer is accurate and complete, listing voice, bass guitar, piano, and guitar. No further refinement is needed.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT DISTINCT ?org ?orgLabel WHERE {
  ?org wdt:P31 ?orgType .
  VALUES ?orgType {
    wd:Q2401749 wd:Q16987274
  }
  ?org ( wdt:P17 | wdt:P131 | wdt:P276 ) wd:Q31 .
  ?org rdfs:label ?orgLabel .
  FILTER ( LANG( ?orgLabel ) = "en" )
}

Got 6 rows and 2 columns:
| org                                               | orgLabel                                |
| ------------------------------------------------- | --------------------------------------- |
| Certipost (wd:Q106917974)                         | Certipost (en)                          |
| Proximus (wd:Q2005282)                            | Proximus (en)                           |
| Mobile Vikings (wd:Q2206993)                      | Mobile Vikings (en)                     |
| Automatique Electrique de Belgique (wd:Q27863183) | Automatique Electrique de Belgique (en) |
| Alcatel-Lucent (Belgium) (wd:Q28975932)           | Alcatel-Lucent (Belgium) (en)           |
| Proximus Group (wd:Q566857)                       | Proximus Group (en)                     |

This refined query retrieves telecommunications organizations and companies located in Belgium, ensuring that all results have English labels for better clarity and usability.

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

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

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

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

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

[User] Which telecommunications organizations are located in Belgium?

[Assistant]
Step 1: Identify the main entities and properties involved in the question.
- Entity: Telecommunications organizations
- Location: Belgium

Step 2: Search for the entity "Belgium" in Wikidata to get its identifier.

[Tool]
Top 10 entity alternatives:
1. Belgium, also known as Kingdom of Belgium, BEL, be, BE, 🇧🇪 (wd:Q31): country in western Europe
2. Belgium, also known as Belgium, IL, Belgium, Illinois (wd:Q2281631): village in Illinois, United States
3. Belgium, also known as Belgium, WI (wd:Q2025327): village in Ozaukee County, Wisconsin
4. Belgium (wd:Q1658699): town in Wisconsin, United States
5. Belgium, also known as Belgium, West Virginia, Belgium, WV (wd:Q2894385): unincorporated community in West Virginia, United States
6. Belgium in the Eurovision Young Musicians, also known as Belgium (wd:Q14849447): Belgium in youth classical music contest
7. Belgium in the long nineteenth century, also known as Belgium (wd:Q16951058): history of Belgium from 1789 to 1914
8. Belgium (wd:Q106879226): family name
9. Belgium (wd:Q109469128): 2019 single by Lil Peep
10. Belgium (wd:Q19072874): poem by Florence Earle Coates

[Assistant]
The entity for Belgium as a country in western Europe is wd:Q31.

Step 3: Identify the property for "located in" or "location" to find organizations located in Belgium.
Step 4: Identify the entity or class for "telecommunications organizations."

I will first search for the property related to "located in" or "location."

[Tool]
Top 10 property alternatives:
1. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
2. located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
3. occupant, also known as tenant, resident, renter, occupiers, lessee (wd:P466 as pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): person or organization occupying property, used by
4. headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place
5. adjacent building, also known as next to, neighboring building, located next to, adjoining building (wd:P3032 as pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): building adjacent to the item, connects with
6. operating area, also known as province served, serves jurisdiction, serves geographic region, serves geographic area, serves area (wd:P2541 as pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): geographic area or jurisdiction an organisation or industry operates in, serves, or has responsibility for, location
7. set in environment, also known as set in location, takes place in, setting location, playing in, narrative set in (wd:P8411 as pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): environment (geographic feature, building type, etc.) the narrative work is set in, significant place, depicts
8. narrative location, also known as set in location, set in, setting, setting location, setting of work (wd:P840 as pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): the narrative of the work is set in this location, significant place, depicts
9. located in the present-day administrative territorial entity, also known as present-day administrative territorial entity, located in the current administrative territorial entity, located in the modern-day administrative territorial entity, located in the present-day administrative territorial entity, would today be located in administrative territorial entity (wd:P3842 as pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): the item was located in the territory of this present-day administrative unit; however the two did not at any point coexist in time, location, part of
10. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment

[Assistant]
The most suitable properties for location are:
- located in the administrative territorial entity (wdt:P131)
- headquarters location (wdt:P159)

Step 5: Search for the entity or class for "telecommunications organizations." I will search for "telecommunications organization" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Intelsat, also known as International Telecommunications Satellite Organization, International Telecommunications Satellite Corporation, Intelsat S.A. (wd:Q778126): Luxembourgish communications satellite services provider
2. OTE, also known as Organismos Tilepikinonion Ellados AE, HTO, Hellenic Telecommunications Organization S.A. (wd:Q206678): Greek telecommunication company
3. International Telecommunications Satellite Organization, also known as Agreement relating to the Intern...nications Satellite Organization (wd:Q15546770): intergovernmental organization
4. European Telecommunications Satellite Organization, also known as Eutelsat IGO (wd:Q47537350): European intergovernmental organisation
5. Globalization, International Organizations, and Telecommunications (wd:Q60140176): scholarly article by Kirsten Rodine-Hardy published September 2015 in Review of Policy Research
6. Intelsat headquarters, also known as 3400 International Drive, 4000 Connecticut Avenue, INTELSAT Headquarter Building, INTELSAT Headquarters Building, International Telecommunications...ganization Headquarters Building (wd:Q6044259): space age style building in Washington, DC
7. organization, also known as organizations, organization in sociology, organisation, institution, organisations (wd:Q43229): social entity established to meet needs or pursue goals
8. .org, also known as dot-org, .organization, .org domain (wd:Q32131): generic top-level domain
9. The Organization, also known as Organization (wd:Q1986084): 1971 film by Don Medford
10. telecommunications, also known as telephone industry, telecoms, telecommunications sector, telecommunications market, ISIC 61 (wd:Q2401742): telecommunications industry in general or providers of telecommunications networks and services

[Assistant]
There is no direct entity for "telecommunications organization" as a class, but there is an entity for "organization" (wd:Q43229) and an entity for "telecommunications" as an industry (wd:Q2401742).

Step 6: I will search for subclasses or instances of organizations related to telecommunications. I will try to find subclasses of "organization" (wd:Q43229) related to telecommunications.

[Tool] Got no rows and 2 columns

[Assistant] No subclasses of "organization" (wd:Q43229) with "telecom" in the label were found directly. I will try a broader search for subclasses of "organization" with "telecommunications" or "telecom" in the label or description.

[Tool] Got no rows and 2 columns

[Assistant]
No subclasses of "organization" with "telecommunications" or "telecom" in the label were found. I will try to find instances of organizations (wd:Q43229) that have an industry or sector related to telecommunications (wd:Q2401742).

Step 7: Search for properties that link organizations to their industry or sector.

[Tool]
Top 10 property alternatives:
1. studied in, also known as is studied by, studied by, science, that studies, researched in, researched by (wd:P2579 as wdt/p): subject is studied by this science or domain, field of work
2. has characteristic, also known as has quality, inherent property, object has characteristic, parameter, quality (wd:P1552 as wdt/p): inherent or distinguishing quality or feature of the entity. Use a more specific property when possible
3. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as wdt/p): main Wikimedia category
4. has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as p): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).
5. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
6. subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt/p): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
7. Wikidata property, also known as main property, property for this item, property, has property (wd:P1687 as wdt/p): main Wikidata property for this item
8. Great Russian Encyclopedia portal ID, also known as bigenc.ru, GRE portal ID (wd:P11514 as wdt/p): identifier of an entry on the web portal based on the Great Russian Encyclopedia (for the older version of encyclopedia use P2924)
9. Commons category, also known as category on Wikimedia Commons, Wikimedia Commons category, Wikimedia Commons cat, Commons cat, commonscat (wd:P373 as wdt/p): name of the Wikimedia Commons category containing files related to this item (without the prefix "Category:")
10. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)

No other items found

[Assistant]
The property "industry" or "sector" does not appear directly in the top properties for the entity "organization" (wd:Q43229). I will try the property "instance of" (wdt:P31) to find organizations that are instances of telecommunications-related classes.

Step 8: Search for subclasses of telecommunications (wd:Q2401742) to find specific types of telecommunications organizations.

[Tool]
Got 5 rows and 2 columns:
| subclass                                               | subclassLabel                                |
| ------------------------------------------------------ | -------------------------------------------- |
| Wired telecommunications activities (wd:Q29584759)     | Wired telecommunications activities (en)     |
| Wireless telecommunications activities (wd:Q29584760)  | Wireless telecommunications activities (en)  |
| satellite telecommunications activities (wd:Q29584761) | satellite telecommunications activities (en) |
| other telecommunications activities (wd:Q29584762)     | other telecommunications activities (en)     |
| Continuous transmission mode (wd:Q5165528)             | Continuous transmission mode (en)            |

[Assistant]
The subclasses of telecommunications (wd:Q2401742) found are mostly activities, not organizations.

Step 9: I will try to find organizations that have the industry or field of work related to telecommunications (wd:Q2401742) using the property "field of work" (wdt:P101) or "industry" (wdt:P452).

I will try to find organizations (wd:Q43229) that have field of work telecommunications (wd:Q2401742).

[Tool]
Got 6 rows and 2 columns:
| org                          | orgLabel           |
| ---------------------------- | ------------------ |
| Iliad (wd:Q1239347)          | Iliad (en)         |
| Orange (wd:Q1431486)         | Orange (en)        |
| Altice France (wd:Q20967159) | Altice France (en) |
| SFR (wd:Q218765)             | SFR (en)           |
| Free (wd:Q2467627)           | Free (en)          |
| Scaleway (wd:Q3352745)       | Scaleway (en)      |

[Assistant]
I found some organizations that have the field of work telecommunications. Now I will filter these organizations to those located in Belgium (wd:Q31) using the property "located in the administrative territorial entity" (wdt:P131).

Step 10: Refine the query to get telecommunications organizations located in Belgium.

[Tool] Got no rows and 2 columns

[Assistant]
No telecommunications organizations were found with the property "located in the administrative territorial entity" (wdt:P131) set to Belgium (wd:Q31).

Step 11: Try using the property "headquarters location" (wdt:P159) instead of "located in the administrative territorial entity" (wdt:P131) to find telecommunications organizations headquartered in Belgium.

[Tool] Got no rows and 2 columns

[Assistant]
No telecommunications organizations were found with the property "headquarters location" (wdt:P159) set to Belgium (wd:Q31).

Step 12: I will try to find organizations that have "telecommunications" in their label and are located in Belgium (wd:Q31) using either "located in the administrative territorial entity" (wdt:P131) or "headquarters location" (wdt:P159). This might help find relevant organizations that are not explicitly linked to the telecommunications industry property.

[Tool] Got no rows and 2 columns

[Assistant]
No organizations with "telecom" or "telecommunications" in their label were found located in Belgium using the property "located in the administrative territorial entity" (wdt:P131).

Step 13: Try the same query but using the property "headquarters location" (wdt:P159) instead.

[Tool] Got no rows and 2 columns

[Assistant]
No organizations with "telecom" or "telecommunications" in their label were found headquartered in Belgium using the property "headquarters location" (wdt:P159).

Step 14: As a last attempt, I will try to find organizations located in Belgium (wd:Q31) that are instances of "telecommunications company" or similar entities. I will search for entities with "telecommunications company" in the label to find a suitable class.

[Tool]
Top 10 entity alternatives:
1. telephone company, also known as telco, phone company, telephone service provider, telecom operator, telecommunications company (wd:Q1266169): organization that provides telephone and/or other telecommunications service
2. telecommunication company, also known as telecom service provider, telecoms company, telecom company, telecom, telco (wd:Q2401749): company that operates in the telecommunications industry
3. telecommunications company (wd:L779293-S1)
4. mobile network operator, also known as Mobile Network Operator, MNO, wireless telecommunications company, wireless service provider, wireless carrier, mobile service provider (wd:Q1941618): cellular service provider
5. Omantel, also known as Oman Telecommunications Company (wd:Q1535581): telecommunication company in Oman
6. t2 (cellular operator), also known as Tele2 Russia, Tele2 (Russia), Tele2, T2 (telecommunications company), T2 (mobile operator) (wd:Q4050799): Mobile service provider in Russia
7. Vivacom, also known as BTC, Bulgarian Telecommunications Company (wd:Q7937522): Bulgarian telecommunications company
8. Gamtel, also known as Gambia Telecommunications Company (wd:Q1492955): Gambian telecommunication company
9. Miranda (telecommunications company) (wd:Q133119943): Russian mobile network operator
10. BTC, also known as Bahamas Telecommunications Company (wd:Q4837035): telecommunication company in the Bahamas

[Assistant]
There are entities for telecommunications companies:
- telephone company (wd:Q1266169)
- telecommunication company (wd:Q2401749)

Step 15: I will try to find instances of telecommunication companies (wd:Q2401749) located in Belgium (wd:Q31) using the property "located in the administrative territorial entity" (wdt:P131).

[Tool] Got no rows and 2 columns

[Assistant]
No telecommunication companies were found with the property "located in the administrative territorial entity" (wdt:P131) set to Belgium (wd:Q31).

Step 16: Try the same query but using the property "headquarters location" (wdt:P159) instead.

[Tool] Got no rows and 2 columns

[Assistant]
No telecommunication companies were found headquartered in Belgium using the property "headquarters location" (wdt:P159).

Step 17: I will now try to find organizations that have the industry telecommunications (wd:Q2401742) and are located in Belgium (wd:Q31) using either "located in the administrative territorial entity" (wdt:P131) or "headquarters location" (wdt:P159) without restricting to instance of organization (wd:Q43229). This might find more results.

[Tool] Got no rows and 2 columns

[Assistant]
No entities with the field of work telecommunications (wd:Q2401742) were found located in Belgium using the property "located in the administrative territorial entity" (wdt:P131).

Step 18: Try the same query but using the property "headquarters location" (wdt:P159) instead.

[Tool] Got no rows and 2 columns

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query uses the property wdt:P131 (located in the administrative territorial entity) to find telecommunications organizations in Belgium. However, many organizations might use the property wdt:P17 (country) or wdt:P276 (location) instead to indicate their location. Also, the query restricts to instance of telecommunications company (wd:Q2401749), but some telecommunications organizations might be classified differently, e.g., as telecommunications organizations (wd:Q16987274) or other subclasses. To improve recall, consider using multiple location properties (wdt:P17, wdt:P131, wdt:P276) and possibly include subclasses or related classes of telecommunications organizations. Additionally, ensure that labels are retrieved optionally and filtered by language. This refinement might yield more results and better answer the question.

[Assistant]
Thank you for the feedback. To improve recall, I will:
- Use multiple location properties: country (wdt:P17), located in the administrative territorial entity (wdt:P131), and location (wdt:P276).
- Include instances of both telecommunications company (wd:Q2401749) and telecommunications organization (wd:Q16987274).
- Retrieve labels optionally and filter by English language.

I will now construct a refined SPARQL query incorporating these improvements.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly targets telecommunications organizations and companies located in Belgium by using the instance of property with the relevant types and multiple location properties. However, the result includes some entities without labels, which reduces clarity and usability. To improve, the query should ensure that labels are retrieved for all results, possibly by adjusting the OPTIONAL clause or adding a FILTER to exclude results without labels if labels are essential for the answer. Additionally, the query could be refined to better distinguish between organizations and companies if the user expects a specific type. Overall, the approach is good but needs refinement to improve the completeness and clarity of the answer.

[Assistant]
Thank you for the feedback. To improve clarity and usability, I will adjust the query to ensure that only results with English labels are returned by moving the label retrieval out of the OPTIONAL clause and adding a FILTER to exclude entities without labels. This will ensure all results have labels. I will keep the current approach of including both telecommunications companies and telecommunications organizations as types for broader coverage.

I will now refine the SPARQL query accordingly.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?award ?awardLabel WHERE {
  wd:Q319308 wdt:P166 ?award .
  OPTIONAL {
    ?award rdfs:label ?awardLabel FILTER ( LANG( ?awardLabel ) = "en" )
  }
}

Got 8 rows and 2 columns:
| award                                                              | awardLabel                                               |
| ------------------------------------------------------------------ | -------------------------------------------------------- |
| Guggenheim Fellowship (wd:Q1316544)                                | Guggenheim Fellowship (en)                               |
| Albertus-Magnus professorate (wd:Q2639529)                         | Albertus-Magnus professorate (en)                        |
| Barwise Prize (wd:Q4865981)                                        | Barwise Prize (en)                                       |
| Fellow of the American Academy of Arts and Sciences (wd:Q52382875) | Fellow of the American Academy of Arts and Sciences (en) |
| National Book Award (wd:Q572316)                                   | National Book Award (en)                                 |
| CSS Fellow (wd:Q59766571)                                          | CSS Fellow (en)                                          |
| Fellow of the Committee for Skeptical Inquiry (wd:Q61745062)       | Fellow of the Committee for Skeptical Inquiry (en)       |
| Pulitzer Prize for General Nonfiction (wd:Q784589)                 | Pulitzer Prize for General Nonfiction (en)               |

Douglas Hofstadter won the following awards: Guggenheim Fellowship, Albertus-Magnus professorate, Barwise Prize, Fellow of the American Academy of Arts and Sciences, National Book Award, CSS Fellow, Fellow of the Committee for Skeptical Inquiry, and Pulitzer Prize for General Nonfiction.

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

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

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

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

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

[User] Which awards did Douglas Hofstadter win?

[Assistant] To answer the question about which awards Douglas Hofstadter won, I will first search for the entity "Douglas Hofstadter" in Wikidata to get his identifier. Then, I will look for properties related to awards that he might have received. Finally, I will construct a SPARQL query to retrieve the awards associated with Douglas Hofstadter.

[Tool]
Top 10 entity alternatives:
1. Douglas Hofstadter, also known as Douglas R. Hofstadter, Douglas Richard Hofstadter (wd:Q319308): American physicist, computer scientist and  professor of cognitive science, university teacher, computer scientist, philosopher, physicist, writer
2. Douglas, also known as Doolish, Douglas, Isle of Man (wd:Q18569): capital city of the Isle of Man
3. Douglas, also known as Douglas, Arizona, Douglas, AZ (wd:Q79878): city in Cochise County, Arizona, United States
4. Douglas, also known as Douglas, Wyoming, Douglas, WY (wd:Q983438): city in Converse County, Wyoming, United States
5. Douglas, also known as Douglas Aircraft Company (wd:Q651778): 1921-1967 aerospace manufacturer in the United States
6. Douglas, also known as Douglas, GA, Douglas, Georgia (wd:Q1004791): city in Coffee County, Georgia, United States
7. Douglas, also known as Douglas, AL (wd:Q66753): town in Marshall County, Alabama, in the United States
8. Douglas, also known as Douglas Pereira, Douglas Pereira dos Santos (wd:Q1988686): Brazilian association football player, born 1990, association football player
9. Douglas, also known as Douglas, MI, Douglas, Michigan (wd:Q2172413): city in Michigan, United States
10. Douglas, also known as Douglas, ND, Douglas, North Dakota (wd:Q2226686): city in Ward County, North Dakota, United States

[Assistant] The entity for Douglas Hofstadter is wd:Q319308. Now I will search for properties related to awards for this entity to find the appropriate property to use in the SPARQL query.

[Tool]
Top 10 property alternatives:
1. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as wdt/p): award or recognition received by a person, organization or creative work
2. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdt/p): the object is a country that recognizes the subject as its citizen, country
3. member of, also known as band member of, membership, member of musical group, in musical group, be member of (wd:P463 as wdt/p): organization, club or musical group to which the subject belongs...ical position, such as a member of parliament (use P39 for that), part of
4. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
5. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as wdt/p): work where this item is described, attested in
6. given name, also known as name, proper name, personal name, middle name, forename (wd:P735 as wdt/p): first name or another given name of this person; values used with the property should not link disambiguations nor family names, name
7. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
8. academic degree, also known as academic diploma, degree, diploma (wd:P512 as wdt/p): academic degree that the person holds
9. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt/p): most specific known birth location of a person, animal or fictional character, location
10. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as wdt/p): date on which the subject was born, inception

No other items found

[Assistant] The property "award received" (wdt:P166) is the appropriate property to use to find the awards won by Douglas Hofstadter. I will now construct a SPARQL query to retrieve the awards associated with Douglas Hofstadter (wd:Q319308). I will also include the labels of the awards for better readability.

[Tool]
Got 8 rows and 2 columns:
| award                                                              | awardLabel                                               |
| ------------------------------------------------------------------ | -------------------------------------------------------- |
| Guggenheim Fellowship (wd:Q1316544)                                | Guggenheim Fellowship (en)                               |
| Albertus-Magnus professorate (wd:Q2639529)                         | Albertus-Magnus professorate (en)                        |
| Barwise Prize (wd:Q4865981)                                        | Barwise Prize (en)                                       |
| Fellow of the American Academy of Arts and Sciences (wd:Q52382875) | Fellow of the American Academy of Arts and Sciences (en) |
| National Book Award (wd:Q572316)                                   | National Book Award (en)                                 |
| CSS Fellow (wd:Q59766571)                                          | CSS Fellow (en)                                          |
| Fellow of the Committee for Skeptical Inquiry (wd:Q61745062)       | Fellow of the Committee for Skeptical Inquiry (en)       |
| Pulitzer Prize for General Nonfiction (wd:Q784589)                 | Pulitzer Prize for General Nonfiction (en)               |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves all awards received by Douglas Hofstadter using the property wdt:P166. The query returns both the award identifiers and their English labels, which is helpful for readability. The answer lists all the awards found in the query result accurately and completely. The query follows the rules by returning identifiers and labels in an optional clause. No irrelevant items are included, and no further refinement is necessary. The output is correct and complete.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?areaCode WHERE {
  wd:Q64 wdt:P473 ?areaCode .
}

Got 1 row and 1 column:
| areaCode |
| -------- |
| 030      |

The area code of Berlin is 030.

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

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

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

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

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

[User] What is the area code of Berlin?

[Assistant]
To answer the question "What is the area code of Berlin?", I need to identify the entity for Berlin and then find the property related to its area code (telephone area code).

Step 1: Search for the entity "Berlin" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Berlin, also known as Berlin (Germany), Berlin, Germany, DE-BE (wd:Q64): federated state, capital and largest city of Germany
2. Berlin, also known as Berlin, New Hampshire, Berlin, NH (wd:Q821244): city in Coos County, New Hampshire, United States
3. Lincoln, also known as Berlin, Lincoln, IA, Lincoln, Iowa (wd:Q1930098): city in Iowa, United States
4. Berlin (wd:Q614184): town in Maryland, United States
5. Berlin, also known as Berlin, New Jersey, Long-a-Coming, New Jersey, Berlin, NJ (wd:Q1086827): borough in Camden County, New Jersey, United States
6. Berlin, also known as Berlin, GA, Berlin, Georgia, USA, Berlin, USA (wd:Q2345711): town in Colquitt County, Georgia, United States
7. Berlin, also known as Berlin, WI, Berlin, Wisconsin (wd:Q1569850): city in Green Lake and Waushara counties, Wisconsin, United States
8. Berlin, also known as Berlin, ND, Berlin, North Dakota (wd:Q821229): city in North Dakota
9. Berlin (wd:Q2504681): village in Illinois, U.S.
10. Berlin (wd:Q821198): American synthpop band

[Assistant] The entity for Berlin as the capital and largest city of Germany is wd:Q64. Next, I will search for properties related to the area code or telephone area code for this entity.

[Tool]
Top 10 property alternatives:
1. local dialing code, also known as area code, dialling code, local calling code, local dialling code, STD code (wd:P473 as wdt/p): identifier dedicated to subject city by the area communication network
2. postal code, also known as pincode, PIN Code, postal index number, post code, postcode (wd:P281 as wdt/p): identifier assigned by postal authorities for the subject area or building
3. UN/LOCODE, also known as LOCCODE, LOCODE, UNECE location code, UNECE LOCODE, United Nations location code (wd:P1937 as wdt/p): geographic location code maintained by UNECE
4. social media followers, also known as number of subs, number of subscribers, sub count, sub number, subscriber number (wd:P8687 as wdt/p): number of subscribers on a particular social media website (use ... in time" and property for account. For Twitter, use numeric id.
5. area, also known as total area, surface area, surface, size, resolution (wd:P2046 as wdt/p): area occupied by an object
6. licence plate code, also known as license plate code, vehicle registration plate (wd:P395 as wdt/p): distinguishing signs or parts of license plate associated with t...al licence plate country code or distinguishing sign of vehicles
7. PM20 geo code (wd:P8483 as wdt/p): code for a geographical category in the 20th Century Press Archives' "countries" category system
8. HASC, also known as Hierarchical Administrative Subdivision Code (wd:P8119 as wdt/p): codes to represent country subdivisions
9. FIPS 10-4 (countries and regions), also known as fips country codes (wd:P901 as wdt/p): Identifier for countries and regions per former Federal Information Processing Standard FIPS 10-4
10. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as wdt/p): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment

No other items found

[Assistant] The property "local dialing code" (wdt:P473) corresponds to the area code or telephone area code. Now I will write a SPARQL query to get the local dialing code (area code) of Berlin (wd:Q64).

[Tool]
Got 1 row and 1 column:
| areaCode |
| -------- |
| 030      |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the area code of Berlin using the property wdt:P473 (local dialing code) for the entity wd:Q64 (Berlin). The answer '030' matches the known area code for Berlin. The query and answer are accurate and complete.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?company ?companyLabel ?website WHERE {
  ?company wdt:P31 wd:Q783794 ; wdt:P1128 ?employees ; wdt:P856 ?website .
  FILTER ( ?employees > 500000 ) OPTIONAL {
    ?company rdfs:label ?companyLabel FILTER ( LANG( ?companyLabel ) = "en" )
  }
}

The companies with more than 500,000 employees and their websites are:
1. DHL Group - https://www.dpdhl.com
2. DHL - https://www.dhl.com

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

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

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

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

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

[User] Give me the websites of companies with more than 500000 employees.

[Assistant]
To answer this question, I need to identify companies with more than 500,000 employees and then retrieve their websites.

Step 1: Identify the property for "number of employees" and the property for "website" in Wikidata.
Step 2: Find companies (instances of "company" or similar) with more than 500,000 employees.
Step 3: Retrieve the websites of those companies.

I will start by searching for the property related to "number of employees."

[Tool]
Top 10 property alternatives:
1. employees, also known as workers, staff, personnel, number of employees, employee count (wd:P1128 as pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): total number of employees of a company at a given "point in time...not deprecated rank). Add data for recent years, don't overwrite
2. employer, also known as working at, working for, working place, works at, works for (wd:P108 as pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): person or organization for which the subject works or worked, affiliation
3. significant person, also known as significant people, sigper, sign. person, relevant person, relevant people (wd:P3342 as pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): person linked to the item in any possible way
4. member count, also known as total members, number of members, count of members, amount of members, membership (wd:P2124 as pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): number of entities that are part of an organization at a particular time
5. number of seats, also known as membership quantity, number of seats (members), quantity of members, seats (members) (wd:P1342 as pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): total number of seats/members in an assembly (legislative house or similar)
6. category for employees of the organization, also known as Academic staff, category for employees of the organisation, Professor (wd:P4195 as pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): Wikimedia category for people who work or worked at this organization
7. work location, also known as work place, working from, working at, worked from, worked at (wd:P937 as pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): location where persons or organisations were actively participating in employment, business or other work, significant place, location
8. number of works, also known as works, works posted, work count, posts posted, posts (wd:P3740 as pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): qualifier on identifiers, e.g. for creators or locations, giving... external database associated with the subject of the identifier
9. employment by economic sector, also known as employment by industry, employment by sector (wd:P2297 as pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): employment divided by sector
10. in work (wd:P2553 as pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): qualifier of award received and nominated for (P1411) to specify...ominated creative work appeared causing the nomination/award win

[Assistant] The property for "number of employees" is wd:P1128. Next, I need to identify the property for "website" to retrieve the websites of companies. I will search for the property related to "website."

[Tool]
Top 10 property alternatives:
1. official shop URL, also known as online store, shop, shop URL, store, store URL (wd:P10225 as pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): official URL where the agent sells products/merchandise, official website
2. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): 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
3. title of broader work, also known as container title, website title (wd:P6333 as pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): title of website, journal or other work in which an article (or ...is published in. Use "published in" (P1433) instead if possible.
4. login URL, also known as sign-in URL, sign in URL, sign-in page, sign in page, login page (wd:P11903 as pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): URL of a webpage used to log into a service, URL
5. product or material produced, also known as products, product or service provided, product, material, or service produced or provided, product, producer of (wd:P1056 as pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): 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
6. 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 pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): 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
7. sitemap URL, also known as sitemap xml, site map URL, sitemap (wd:P11212 as pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): URL to the sitemap of the subject's official website, URL
8. subreddit, also known as r/, reddit, Reddit community ID, Reddit forum, Reddit sub ID (wd:P3984 as pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): name of the Reddit forum associated to this subject
9. reference URL, also known as URL fonte, webref, URL ref, URL, site (wd:P854 as pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): should be used for Internet URLs as references. Use "Wikimedia import URL" (P4656) for imports from WMF sites, URL
10. URL, also known as Uniform Resource Locator, URLs, Uniform Resource Locators (wd:P2699 as pqv/pqn/p/psn/psv/pq/wdtn/wdt/prn/pr/prv/ps): location of a resource

[Assistant] The property for "official website" is wd:P856. Now, I need to find companies with more than 500,000 employees. For that, I need to identify the entity for "company" or similar. I will search for the entity "company" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. company, also known as co., firm (wd:Q783794): legal entity representing an association of people, whether natural, legal or a mixture of both, with a specific objective
2. company, also known as company (military unit), military company (wd:Q102538): military unit size designation
3. enterprise, also known as business enterprise, firm, company (wd:Q6881511): organizational unit producing goods or services, which benefits ...n-making, especially for the allocation of its current resources
4. Company (wd:Q225093): 2002 film directed by Ram Gopal Varma
5. Company (wd:Q2915810): 1970 musical comedy by Stephen Sondheim
6. Company (wd:Q23723998): 2016 single by Justin Bieber
7. The Company, also known as Company (wd:Q681815): 2003 film by Robert Altman
8. Company (wd:Q5155503): 1979 short novel by Samuel Beckett, Your dream team, real rewards
9. .company (wd:Q16048325): top-level domain
10. Manuel Compañy, also known as Compañy (wd:Q15876995): Spanish photographer, photographer

[Assistant] The entity for "company" as a legal entity representing an association of people is wd:Q783794. Now I will write a SPARQL query to find companies (instances of wd:Q783794) with more than 500,000 employees (property wd:P1128) and retrieve their official websites (property wd:P856).

[Tool]
Got 2 rows and 3 columns:
| company                   | companyLabel   | website                 |
| ------------------------- | -------------- | ----------------------- |
| DHL Group (wd:Q109931818) | DHL Group (en) | <https://www.dpdhl.com> |
| DHL (wd:Q489815)          | DHL (en)       | <https://www.dhl.com>   |

[Assistant] I found two companies with more than 500,000 employees: DHL Group and DHL. Both have their official websites listed. I will now provide the final answer with the SPARQL query and the websites of these companies.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves companies with more than 500,000 employees along with their official websites. The query uses appropriate properties and filters, and the results are relevant and accurate. The answer clearly lists the companies and their websites as requested. No further refinement is necessary.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?cosmonaut ?cosmonautLabel WHERE {
  ?cosmonaut wdt:P106 wd:Q12634815 .
  FILTER ( ?cosmonaut != wd:Q106373153 ) OPTIONAL {
    ?cosmonaut rdfs:label ?cosmonautLabel FILTER ( LANG( ?cosmonautLabel ) = "en" )
  }
}

Got 7 rows and 2 columns:
| cosmonaut                                       | cosmonautLabel                       |
| ----------------------------------------------- | ------------------------------------ |
| Svetlana Oktyabrevna Omelchenko (wd:Q108169808) | Svetlana Oktyabrevna Omelchenko (en) |
| Aleksandr Gorbunov (wd:Q109493064)              | Aleksandr Gorbunov (en)              |
| Marina Vasilevskaya (wd:Q118185958)             | Marina Vasilevskaya (en)             |
| Ural Sultanov (wd:Q15210574)                    | Ural Sultanov (en)                   |
| Anna Kikina (wd:Q18352451)                      | Anna Kikina (en)                     |
| Vladimír Remek (wd:Q254985)                     | Vladimír Remek (en)                  |
| Arnaldo Tamayo Méndez (wd:Q362902)              | Arnaldo Tamayo Méndez (en)           |

I refined the query to exclude the irrelevant entity 'Void' (wd:Q106373153). Here are cosmonauts from Wikidata with their labels: Svetlana Oktyabrevna Omelchenko, Aleksandr Gorbunov, Marina Vasilevskaya, Ural Sultanov, Anna Kikina, Vladimír Remek, and Arnaldo Tamayo Méndez. This list is based on the occupation 'cosmonaut' and excludes the irrelevant entry. Note that the number of cosmonauts in Wikidata with this occupation is limited.

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

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

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

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

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

[User] Give me all cosmonauts.

[Assistant] To find all cosmonauts, I need to identify the entity or class that represents "cosmonaut" in Wikidata. Then I will query for all individuals who are instances of or have the occupation "cosmonaut." I will start by searching for the entity "cosmonaut" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. astronaut, also known as cosmonaut, vyomanaut, taikonaut, spationaut, spacionaut (wd:Q11631): person who commands, pilots, or serves as a crew member of a spacecraft
2. The Cosmonaut, also known as Cosmonaut (wd:Q3016381): 2013 film directed by Nicolás Alcalá
3. Forsaken, also known as Cosmonaut, Forsaken: Mission Mars, Martian, Prishelets, The Cosmonaut (wd:Q55659194): 2018 Russian science fiction film by Aleksandr Kulikov
4. Cosmonaut, also known as Cosmonauta (wd:Q3695198): 2009 film directed by Susanna Nicchiarelli
5. cosmonaut, also known as Russian astronaut (wd:Q12634815): astronaut from the former Soviet Union and its satellite countries and today's Russia
6. Cosmonaut (wd:Q5174345): 2010 studio album by Bump of Chicken
7. COSMONAUT (wd:Q122343082): 2018 video game
8. cosmonaut (wd:L493546-S2)
9. cosmonaut (wd:L30879)
10. cosmonaut (wd:L30879-F1)

[Assistant] The entity "cosmonaut" is best represented by wd:Q12634815 which is described as "cosmonaut, also known as Russian astronaut." This is the most specific entity for cosmonauts. Now I will query for all individuals who have the occupation "cosmonaut" (wd:Q12634815).

[Tool]
Got 8 rows and 2 columns:
| cosmonaut                                       | cosmonautLabel                       |
| ----------------------------------------------- | ------------------------------------ |
| Void (wd:Q106373153)                            | Void (en)                            |
| Svetlana Oktyabrevna Omelchenko (wd:Q108169808) | Svetlana Oktyabrevna Omelchenko (en) |
| Aleksandr Gorbunov (wd:Q109493064)              | Aleksandr Gorbunov (en)              |
| Marina Vasilevskaya (wd:Q118185958)             | Marina Vasilevskaya (en)             |
| Ural Sultanov (wd:Q15210574)                    | Ural Sultanov (en)                   |
| Anna Kikina (wd:Q18352451)                      | Anna Kikina (en)                     |
| Vladimír Remek (wd:Q254985)                     | Vladimír Remek (en)                  |
| Arnaldo Tamayo Méndez (wd:Q362902)              | Arnaldo Tamayo Méndez (en)           |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly retrieves cosmonauts by occupation (wdt:P106 wd:Q12634815), which is appropriate. However, the query returns only 8 results, which is a very small subset and not exhaustive. The user asked for all cosmonauts, so the query should not limit results and should ideally retrieve all items with occupation cosmonaut. Also, the label retrieval is done correctly with an OPTIONAL clause and language filter. The presence of 'Void' (wd:Q106373153) as a cosmonaut seems suspicious and might be an error or a misclassification in Wikidata. It would be good to check for and filter out such irrelevant or erroneous entries if possible. Overall, the approach is correct but the result is incomplete and may contain irrelevant items. The system should refine the query or check for data quality issues to improve the answer completeness and accuracy.

[Assistant] Thank you for the feedback. I will refine the query to remove the LIMIT clause to retrieve all cosmonauts. Additionally, I will add a filter to exclude any obviously irrelevant or suspicious entries such as "Void" by filtering out entities with labels like "Void." This should improve the completeness and accuracy of the results. I will now execute the refined query.

[Tool]
Got 8 rows and 2 columns:
| cosmonaut                                       | cosmonautLabel                       |
| ----------------------------------------------- | ------------------------------------ |
| Void (wd:Q106373153)                            | Void (en)                            |
| Svetlana Oktyabrevna Omelchenko (wd:Q108169808) | Svetlana Oktyabrevna Omelchenko (en) |
| Aleksandr Gorbunov (wd:Q109493064)              | Aleksandr Gorbunov (en)              |
| Marina Vasilevskaya (wd:Q118185958)             | Marina Vasilevskaya (en)             |
| Ural Sultanov (wd:Q15210574)                    | Ural Sultanov (en)                   |
| Anna Kikina (wd:Q18352451)                      | Anna Kikina (en)                     |
| Vladimír Remek (wd:Q254985)                     | Vladimír Remek (en)                  |
| Arnaldo Tamayo Méndez (wd:Q362902)              | Arnaldo Tamayo Méndez (en)           |

[Assistant] The filter to exclude "Void" by label did not work as expected because the label is still present. This might be due to the OPTIONAL clause and the label being retrieved after the filter. I will try a different approach by filtering out the entity itself (wd:Q106373153) explicitly. Also, the number of results is still 8, which suggests that there might be only a few entities with occupation cosmonaut in Wikidata or some data quality issue. I will now refine the query to exclude the entity wd:Q106373153 explicitly and remove the LIMIT clause.

[Tool]
Got 7 rows and 2 columns:
| cosmonaut                                       | cosmonautLabel                       |
| ----------------------------------------------- | ------------------------------------ |
| Svetlana Oktyabrevna Omelchenko (wd:Q108169808) | Svetlana Oktyabrevna Omelchenko (en) |
| Aleksandr Gorbunov (wd:Q109493064)              | Aleksandr Gorbunov (en)              |
| Marina Vasilevskaya (wd:Q118185958)             | Marina Vasilevskaya (en)             |
| Ural Sultanov (wd:Q15210574)                    | Ural Sultanov (en)                   |
| Anna Kikina (wd:Q18352451)                      | Anna Kikina (en)                     |
| Vladimír Remek (wd:Q254985)                     | Vladimír Remek (en)                  |
| Arnaldo Tamayo Méndez (wd:Q362902)              | Arnaldo Tamayo Méndez (en)           |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves all cosmonauts by their occupation (wdt:P106 wd:Q12634815) and excludes the irrelevant entity 'Void' (wd:Q106373153). The query also optionally retrieves English labels for better readability. The answer lists the cosmonauts found in the query result, which is consistent with the data returned. The approach is appropriate and the answer is complete and accurate given the data available in Wikidata. No further refinement is necessary.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?immediateOwner ?immediateOwnerLabel ?ultimateOwner ?ultimateOwnerLabel WHERE {
  wd:Q125141709 wdt:P127 ?immediateOwner .
  OPTIONAL {
    ?immediateOwner wdt:P127 ?ultimateOwner .
    OPTIONAL {
      ?ultimateOwner rdfs:label ?ultimateOwnerLabel FILTER ( LANG( ?ultimateOwnerLabel ) = "en" )
    }
  }
  OPTIONAL {
    ?immediateOwner rdfs:label ?immediateOwnerLabel FILTER ( LANG( ?immediateOwnerLabel ) = "en" )
  }
}

The immediate owner of the Rolls-Royce car brand is Rolls-Royce Motor Cars. The ultimate owner of Rolls-Royce Motor Cars is BMW.

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

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

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

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

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

[User] Who is the owner of Rolls-Royce?

[Assistant]
To answer the question "Who is the owner of Rolls-Royce?", I need to clarify whether the user refers to the company Rolls-Royce Holdings plc (the aerospace and defense company) or Rolls-Royce Motor Cars (the luxury automobile manufacturer). Both are distinct entities with different ownership.

Step 1: Search for the entity "Rolls-Royce" to identify the relevant entities and distinguish between them.

[Tool]
Top 10 entity alternatives:
1. Rolls-Royce, also known as Rolls-Royce Holdings plc (wd:Q243278): British multinational public holding company
2. Rolls-Royce (wd:Q125141709): car brand
3. Rolls-Royce, also known as Rolls-Royce plc (wd:Q85623218): British company
4. Rolls-Royce Limited, also known as Rolls Royce Limited (wd:Q679888): 1906-1987 automobile and aerospace manufacturer in the United Kingdom
5. Merlin, also known as Merlin engine, Rolls-Royce Merlin, RR Merlin (wd:Q1412885): 12-cylinder V piston engine family by Rolls-Royce
6. The Yellow Rolls-Royce, also known as Yellow Rolls-Royce (wd:Q2474758): 1964 film by Anthony Asquith
7. Rolls-Royce Ghost (wd:Q1510648): car model
8. Rolls-Royce Trent (wd:Q1738127): turbofan aircraft engine family
9. Rolls-Royce Griffon (wd:Q2164325): 1930s British piston aircraft engine
10. Rolls-Royce RB211, also known as RB211 (wd:Q1636078): 1960s British turbofan aircraft engine

[Assistant]
There are multiple entities related to "Rolls-Royce." The two most relevant for ownership are:
1. Rolls-Royce Holdings plc (wd:Q243278), a British multinational public holding company.
2. Rolls-Royce (car brand) (wd:Q125141709).

I will now check the owners or parent companies of these two entities to determine who owns them. I will start with Rolls-Royce Holdings plc (wd:Q243278).

[Tool] Got no rows and 3 columns

[Assistant]
There is no direct parent company (wdt:P749) listed for Rolls-Royce Holdings plc (wd:Q243278), which makes sense as it is a public holding company.

Next, I will check the owner or parent company of the Rolls-Royce car brand (wd:Q125141709).

[Tool]
Got 1 row and 3 columns:
| subject                     | property            | object                              |
| --------------------------- | ------------------- | ----------------------------------- |
| Rolls-Royce (wd:Q125141709) | owned by (wdt:P127) | Rolls-Royce Motor Cars (wd:Q234803) |

[Assistant] The Rolls-Royce car brand (wd:Q125141709) is owned by Rolls-Royce Motor Cars (wd:Q234803). I will now check the owner or parent company of Rolls-Royce Motor Cars (wd:Q234803).

[Tool]
Got 1 row and 3 columns:
| subject                             | property            | object          |
| ----------------------------------- | ------------------- | --------------- |
| Rolls-Royce Motor Cars (wd:Q234803) | owned by (wdt:P127) | BMW (wd:Q26678) |

[Assistant]
Rolls-Royce Motor Cars (wd:Q234803) is owned by BMW (wd:Q26678).

Summary:
- Rolls-Royce car brand is owned by Rolls-Royce Motor Cars.
- Rolls-Royce Motor Cars is owned by BMW.

I will now provide the final answer with this information.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly identifies Rolls-Royce Motor Cars as the owner of the Rolls-Royce car brand and that Rolls-Royce Motor Cars is owned by BMW. However, the query returns the label 'BMW' as the ownerLabel for Rolls-Royce Motor Cars, which is misleading because the direct owner of the brand is Rolls-Royce Motor Cars, not BMW. The query should be refined to clearly distinguish between the immediate owner (Rolls-Royce Motor Cars) and the ultimate owner (BMW). For example, the query could separately retrieve the immediate owner of Rolls-Royce and then the owner of that owner, to clarify the ownership hierarchy. Also, the label retrieval for the owner should correspond to the immediate owner entity, not the ultimate owner. This will improve clarity and accuracy of the answer.

[Assistant] Thank you for the feedback. I will refine the SPARQL query to clearly distinguish between the immediate owner of the Rolls-Royce car brand (Rolls-Royce Motor Cars) and the ultimate owner (BMW). The query will retrieve both owners separately with their labels for clarity.

[Tool]
Got 1 row and 4 columns:
| immediateOwner                      | immediateOwnerLabel         | ultimateOwner   | ultimateOwnerLabel |
| ----------------------------------- | --------------------------- | --------------- | ------------------ |
| Rolls-Royce Motor Cars (wd:Q234803) | Rolls-Royce Motor Cars (en) | BMW (wd:Q26678) | BMW (en)           |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves both the immediate owner and the ultimate owner of the Rolls-Royce car brand, returning their identifiers and English labels. The answer is accurate and complete, clearly stating that Rolls-Royce Motor Cars is the immediate owner and BMW is the ultimate owner. The query uses appropriate properties and entities, and the result matches the expected ownership hierarchy. No further refinement is necessary.