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 ?item ?itemLabel ?coordinates WHERE {
  ?item wdt:P19 ?birthPlace .
  ?birthPlace wdt:P17 wd:Q20 .
  OPTIONAL {
    ?item wdt:P625 ?coordinates .
  }
  {
    ?item wdt:P27 wd:Q30 .
  } UNION {
    ?item wdt:P20 ?deathPlace .
    ?deathPlace wdt:P17 wd:Q30 .
  }
  OPTIONAL {
    ?item rdfs:label ?itemLabel FILTER ( LANG( ?itemLabel ) = "en" )
  }
}
LIMIT 100

Got 100 rows and 3 columns, showing the first 5 and last 5 rows below:
| item                                  | itemLabel                  | coordinates |
| ------------------------------------- | -------------------------- | ----------- |
| Gil Andersen (wd:Q1010446)            | Gil Andersen (en)          |             |
| Nels Johann Lennes (wd:Q102149248)    | Nels Johann Lennes (en)    |             |
| Ovidia Aas (wd:Q102296730)            | Ovidia Aas (en)            |             |
| Carl Sofus Lumholtz (wd:Q1040662)     | Carl Sofus Lumholtz (en)   |             |
| Sofie Magelssen Groth (wd:Q104591151) | Sofie Magelssen Groth (en) |             |
| ...                                   | ...                        | ...         |
| Serenus Halverson (wd:Q111228160)     | Serenus Halverson (en)     |             |
| Charles Halvorson (wd:Q111228161)     | Charles Halvorson (en)     |             |
| Gunder Halvorson (wd:Q111228162)      | Gunder Halvorson (en)      |             |
| Marcellus Halvorson (wd:Q111228163)   | Marcellus Halvorson (en)   |             |
| Otto Hansen (wd:Q111228178)           | Otto Hansen (en)           |             |

The query returns distinct items born in a place within Norway and either have the United States of America as their country of citizenship or died in a place within the United States of America. The results include the items' identifiers, labels, and coordinates (if available). Many items do not have coordinates listed.

[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 are the distinct items, along with their coordinates, that were born in a place within Norway and either have the United States of America as their country of citizenship or died in a place within the United States of America?

[Assistant]
To answer this question, I need to identify the following components:
1. Items that were born in a place within Norway.
2. Items that either have the United States of America as their country of citizenship or died in a place within the United States of America.
3. Retrieve the distinct items along with their coordinates.

Step 1: Identify the entity for Norway and the United States of America.
Step 2: Identify the property for place of birth, country of citizenship, place of death, and coordinates location.
Step 3: Construct a query to find items born in a place within Norway.
Step 4: Filter those items to have either the United States of America as their country of citizenship or died in a place within the United States of America.
Step 5: Retrieve the distinct items and their coordinates.

I will start by searching for the entities Norway and the United States of America.

[Tool]
Top 10 entity alternatives:
1. Norway, also known as Kingdom of Norway (wd:Q20): country in Northern Europe
2. Norway, also known as Norway, Iowa, Norway, IA (wd:Q1913264): city in Iowa, United States
3. Norway, also known as Norway, MI, Norway, Michigan (wd:Q2480177): city in Dickinson County, Michigan, United States
4. Norway, also known as Norway, SC, Norway, South Carolina (wd:Q3243583): town in South Carolina
5. Kingdom of Norway, also known as Norway, Norwegian Empire (wd:Q2196956): former Kingdom from 872 to 1397
6. Norway, also known as Norway, Maine, Norway, ME (wd:Q2734330): town in Maine, USA
7. Norway, also known as Norway, IN, Norway, Indiana (wd:Q2118814): census-designated place in Indiana
8. Kingdom of Norway, also known as Norway, Norwegian Kingdom (wd:Q2597352): short-lived monarchy in Northern Europe (1814)
9. Norway, also known as Norway, New York, Norway, NY (wd:Q944765): town in New York, USA
10. Norway, also known as Norway, WI (wd:Q3046928): town in Wisconsin, USA

[Tool]
Top 10 entity alternatives:
1. United States, also known as the U.S. of A, United States of America, the US of America, United States of North America, U. S. (wd:Q30): country primarily located in North America
2. Istadus Unidus the America, also known as United States of America (wd:Q29045433): Wikimedia permanent duplicate item
3. United States of America (wd:Q100270731): scholarly article
4. United States of America (wd:Q103971355): encyclopedic article; Grove Art Online
5. United States of America (wd:Q105870683): vocal track by Kikki Danielsson; 1980 studio recording
6. United States of America (wd:Q105870692): song written and composed by Donna Fargo, originally recorded by Donna Fargo and released in 1974
7. United States of America (wd:Q106315054): vocal track by Donna Fargo; 1974 studio recording
8. United States of America, also known as Star Trek USA, USA (wd:Q99281400): country of the United States of America as depicted in Star Trek
9. United States of America (wd:L350484-S1)
10. United States (of America) (wd:L399000-S1)

[Assistant]
I have identified the entities for Norway (wd:Q20) and the United States of America (wd:Q30).

Next, I will identify the properties for:
- Place of birth
- Country of citizenship
- Place of death
- Coordinates location

I will search for the properties related to "place of birth" first.

[Tool]
Top 10 property alternatives:
1. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): most specific known birth location of a person, animal or fictional character, location
2. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): date on which the subject was born, inception
3. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): the object is a country that recognizes the subject as its citizen, country
4. birthday, also known as b-day, bday, birth day (wd:P3150 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): item for day and month on which the subject was born. Used when full "date of birth" (P569) isn't known., date of birth
5. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): full name of a person at birth, if different from their current, generally used name, name
6. category for people born here, also known as category for place of birth, category of people born here (wd:P1464 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): category item that groups people born in this place, related category
7. valid in place, also known as applies to country, applies to location, applies to place, country, true in (wd:P3005 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): place where a statement is valid, applies to part
8. country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country
9. country, also known as sovereign state, state, land, host country (wd:P17 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
10. commemorates, also known as monument to, memorial to, memorializes, marks, in memory of (wd:P547 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): what the place, monument, memorial, or holiday, commemorates, main subject

[Assistant]
I have identified the following relevant properties:
- Place of birth: wdt:P19
- Country of citizenship: wdt:P27

Next, I will search for the property related to "place of death."

[Tool]
Top 10 property alternatives:
1. place of death, also known as POD, location of death, killed in, deathplace, died in (wd:P20 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): most specific known (e.g. city instead of country, or hospital i... city) death location of a person, animal or fictional character, location
2. place of burial, also known as interment, interment location, interment place, interred at, location of burial (wd:P119 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): location of grave, resting place, place of ash-scattering, etc. ...veral places: e.g., re-burials, parts of body buried separately., location
3. date of death, also known as DOD, deathdate, died, died on, year of death (wd:P570 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): dissolved, abolished or demolished date, date on which the subject died, end time
4. category for people who died here, also known as category for place of death, category of people who died here (wd:P1465 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): category item for people who died in this location, related category
5. manner of death, also known as type of death, nature of death, death manner, death type, circumstance of death (wd:P1196 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): general circumstances of a person's death; e.g. natural causes, ...ysiological mechanism, e.g. heart attack, trauma, pneumonia etc.
6. number of deaths, also known as dead, qty fatalities, qty deaths, number of fatalities, fatalities (wd:P1120 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): total (cumulative) number of people who died since start as a direct result of an event or cause
7. category for people buried here, also known as buried here: Wikimedia category for, category of people buried here, category for place of burial, category for burials (wd:P1791 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): Wikimedia category for people with a burial site within this area, related category
8. cause of death, also known as death cause, murder method, method of murder, die of, die from (wd:P509 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): underlying or immediate cause of death.  Underlying cause (e.g. ...adest category, e.g. natural causes, accident, homicide, suicide
9. date of burial or cremation, also known as burial date, cremation date, date of cremation, funeral date (wd:P4602 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): date on which the person was buried or cremated soon after death, point in time
10. commemorates, also known as monument to, memorial to, memorializes, marks, in memory of (wd:P547 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): what the place, monument, memorial, or holiday, commemorates, main subject

[Assistant]
I have identified the property for place of death: wdt:P20.

Next, I will identify the property for coordinates location.

[Tool]
Top 10 property alternatives:
1. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
2. this zoological name is coordinate with, also known as coordinate name (wd:P2743 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): links coordinate zoological names, different from
3. coordinates of depicted place, also known as depicted item geolocation, geolocation of object, object geolocation (wd:P9149 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): coordinates of the place depicted in the work (or Commons image)
4. coordinates of geographic center, also known as coordinates of geographic centre, geographic centre, geographic center, geographical midpoint, geographical centre (wd:P5140 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): coordinates of the center of an area. Use qualifier "determination method" (P459) to indicate how, coordinate location
5. location map (wd:P1943 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): blank geographic map image suitable for overlaying coordinate points, as defined at c:Category:Location maps, image
6. occupant, also known as tenant, resident, renter, occupiers, lessee (wd:P466 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): person or organization occupying property, used by
7. location of discovery, also known as found in, location of discovered object, place of discovery, site of discovery, source (wd:P189 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): where the item was located when discovered, significant place
8. named place on map, also known as name on map, place on map (wd:P9664 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): property linking a map to a place named on it
9. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
10. genomic start, also known as start coordinate, genomic from, Genloc From, from, Genloc Start (wd:P644 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): genomic starting coordinate of the biological sequence (e.g. a gene)

[Assistant]
I have identified the property for coordinates location: wdt:P625.

Now I will construct a SPARQL query to find distinct items born in a place within Norway (wd:Q20) and either have the United States of America (wd:Q30) as their country of citizenship or died in a place within the United States of America. I will also retrieve their coordinates.

[Tool]
Got 100 rows and 3 columns, showing the first 5 and last 5 rows below:
| item                                  | itemLabel                  | coordinates |
| ------------------------------------- | -------------------------- | ----------- |
| Gil Andersen (wd:Q1010446)            | Gil Andersen (en)          |             |
| Nels Johann Lennes (wd:Q102149248)    | Nels Johann Lennes (en)    |             |
| Ovidia Aas (wd:Q102296730)            | Ovidia Aas (en)            |             |
| Carl Sofus Lumholtz (wd:Q1040662)     | Carl Sofus Lumholtz (en)   |             |
| Sofie Magelssen Groth (wd:Q104591151) | Sofie Magelssen Groth (en) |             |
| ...                                   | ...                        | ...         |
| Serenus Halverson (wd:Q111228160)     | Serenus Halverson (en)     |             |
| Charles Halvorson (wd:Q111228161)     | Charles Halvorson (en)     |             |
| Gunder Halvorson (wd:Q111228162)      | Gunder Halvorson (en)      |             |
| Marcellus Halvorson (wd:Q111228163)   | Marcellus Halvorson (en)   |             |
| Otto Hansen (wd:Q111228178)           | Otto Hansen (en)           |             |

[Assistant]
I have retrieved distinct items born in a place within Norway and either have the United States of America as their country of citizenship or died in a place within the United States of America. The query also attempts to retrieve their coordinates, but many items do not have coordinates listed.

Here is the SPARQL query I used:

SELECT DISTINCT ?item ?itemLabel ?coordinates WHERE {
  ?item wdt:P19 ?birthPlace .
  ?birthPlace wdt:P17 wd:Q20 .  # birthPlace located in Norway
  OPTIONAL { ?item wdt:P625 ?coordinates . }
  {
    ?item wdt:P27 wd:Q30 .  # country of citizenship United States
  } UNION {
    ?item wdt:P20 ?deathPlace .
    ?deathPlace wdt:P17 wd:Q30 .  # deathPlace located in United States
  }
  OPTIONAL { ?item rdfs:label ?itemLabel FILTER (LANG(?itemLabel) = "en") }
} LIMIT 100

If you want, I can provide the results or refine the query further.

[Tool] Stopped generation process


PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
SELECT ?revenue ?revenueUnit ?revenueUnitLabel WHERE {
  wd:Q516755 p:P2139 ?statement .
  ?statement ps:P2139 ?revenue .
  OPTIONAL {
    ?statement pq:P585 ?date .
    FILTER ( YEAR( ?date ) = 2019 )
  }
  OPTIONAL {
    ?statement pq:P518 ?revenueUnit .
  }
  OPTIONAL {
    ?revenueUnit rdfs:label ?revenueUnitLabel FILTER ( LANG( ?revenueUnitLabel ) = "en" )
  }
}
LIMIT 10

SPARQL execution failed:
HTTPSConnectionPool(host='qlever.cs.uni-freiburg.de', port=443): Read timed out. (read timeout=30)

The total revenue and revenue unit of the German nature conservation organization Naturschutzbund Deutschland on January 1, 2019, could not be retrieved from Wikidata due to lack of available data or query timeouts.

[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 was the total revenue (and revenue unit) of the German nature conservation organization Naturschutzbund Deutschland on January 1, 2019?

[Assistant] To answer this question, I need to find the entity for the German nature conservation organization Naturschutzbund Deutschland in Wikidata. Then, I need to find the property related to total revenue or income and check if there is a qualifier or statement for the date January 1, 2019. I will start by searching for the entity Naturschutzbund Deutschland.

[Tool]
Top 10 entity alternatives:
1. Naturschutzbund Deutschland, also known as NABU (wd:Q516755): German nature conservation organization
2. Germany, also known as BR Deutschland, Bundesrepublik Deutschland, Deutschland, Federal Republic of Germany (wd:Q183): country in Central Europe
3. German cruiser Deutschland, also known as Deutschland (wd:Q158427): 1931 Deutschland-class heavy cruiser
4. Deutschland (wd:Q662230): 1916 Type U 151 submarine
5. Deutschland (wd:Q62565775): 2019 song by Rammstein
6. SS Deutschland, also known as Deutschland, Deutschland IV (wd:Q323005): German ocean liner steamship (1923-45)
7. Deutschland (wd:Q949364): ship launched in 1905
8. Deutschland, also known as IMO 7129922 (wd:Q1206244): motor ship built in 1972
9. Deutschland, also known as IMO 5089269, Renetta, Nissos (wd:Q1206239): Train ferry, built in 1953
10. Deutschland (wd:Q1206242): scrapped German passenger ship

[Assistant] I found the entity for Naturschutzbund Deutschland as wd:Q516755, which is a German nature conservation organization. Next, I will search for properties related to revenue or income for this entity to find the relevant property that might contain the total revenue information.

[Tool]
Top 10 property alternatives:
1. total revenue, also known as turnover, sales, revenue, income, gross revenue (wd:P2139 as wdt/p): income gained by an organization during a given time frame. Not to be confused with fiscal revenue
2. has goal, also known as intention, mission, objective, objective of project or action, project of (wd:P3712 as wdt/p): desired result or outcome
3. total assets, also known as assets, balance sheet total (wd:P2403 as wdt/p): value of assets held by a private or public entity
4. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
5. 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.
6. industry, also known as branch, economic branch, field of action, field of exercise, sector (wd:P452 as wdt/p): specific industry of company or organization, part of
7. bequest income (wd:P13171 as wdt/p): the sum a organisations receives from bequests/legacies in a timeframe
8. donations, also known as donations received (wd:P8093 as wdt/p): sum of donations an organization receives
9. motto text, also known as mission statement, travel slogan, tourism slogan, tagline, strapline (wd:P1451 as wdt/p): short motivation sentence associated to item
10. field of work, also known as scientific discipline, scientific area, responsible for, research on, research fields (wd:P101 as wdt/p): specialization of a person or organization; see P106 for the occupation, interested in

No other items found

[Assistant] The property for total revenue is wd:P2139. Now I will check if there is a statement for the total revenue of Naturschutzbund Deutschland (wd:Q516755) with a qualifier for the date January 1, 2019. I will write a query to retrieve the total revenue and the unit of revenue for that date.

[Tool] Got no rows and 3 columns

[Assistant] There is no direct statement for total revenue of Naturschutzbund Deutschland on exactly January 1, 2019. I will try to relax the date constraint to just the year 2019 to see if there is any revenue information for that year.

[Tool]
SPARQL execution failed:
HTTPSConnectionPool(host='qlever.cs.uni-freiburg.de', port=443): Read timed out.

[Assistant] The query to find total revenue for the year 2019 timed out. I will try a simpler query without the revenue unit and date label to reduce complexity and try again.

[Tool]
SPARQL execution failed:
HTTPSConnectionPool(host='qlever.cs.uni-freiburg.de', port=443): Read timed out. (read timeout=30)

[Assistant] The query still times out when trying to get revenue for 2019. I will try a different approach by listing all revenue statements for Naturschutzbund Deutschland and then filter manually if any are for 2019.

[Tool]
Failed to list triples with error:
HTTPSConnectionPool(host='qlever.cs.uni-freiburg.de', port=443): Read timed out. (read timeout=30)

[Assistant] The listing of triples for total revenue also times out. It seems the data for total revenue with date qualifiers for Naturschutzbund Deutschland is not readily accessible or too large to query directly. I will try to find if there is any general revenue information for Naturschutzbund Deutschland without date constraints.

[Tool]
SPARQL execution failed:
HTTPSConnectionPool(host='qlever.cs.uni-freiburg.de', port=443): Read timed out. (read timeout=30)

[Assistant] It seems that the data for total revenue of Naturschutzbund Deutschland is either not present or not accessible within the query time limits. Given these limitations, I cannot provide the total revenue and revenue unit for Naturschutzbund Deutschland on January 1, 2019. I will now finalize my response.

[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 ?person ?personLabel ?voiceType ?voiceTypeLabel WHERE {
  ?person wdt:P412 ?voiceType .
  VALUES ?voiceType {
    wd:Q30903 wd:Q186506 wd:Q37137 wd:Q223166 wd:Q27914 wd:Q31687 wd:Q27911
  }
  FILTER NOT EXISTS {
    ?person wdt:P106 ?occupation
  }
  OPTIONAL {
    ?person rdfs:label ?personLabel FILTER ( LANG( ?personLabel ) = "en" )
  }
  OPTIONAL {
    ?voiceType rdfs:label ?voiceTypeLabel FILTER ( LANG( ?voiceTypeLabel ) = "en" )
  }
}

Got 11,701 rows and 4 columns, showing the first 5 and last 5 rows below:
| person                          | personLabel           | voiceType                  | voiceTypeLabel     |
| ------------------------------- | --------------------- | -------------------------- | ------------------ |
| wd:Q55003172                    |                       | mezzo-soprano (wd:Q186506) | mezzo-soprano (en) |
| Leokadja Begbick (wd:Q54913414) | Leokadja Begbick (en) | mezzo-soprano (wd:Q186506) | mezzo-soprano (en) |
| Venus (wd:Q55010077)            | Venus (en)            | mezzo-soprano (wd:Q186506) | mezzo-soprano (en) |
| Djamileh (wd:Q55023462)         | Djamileh (en)         | mezzo-soprano (wd:Q186506) | mezzo-soprano (en) |
| wd:Q55010449                    |                       | mezzo-soprano (wd:Q186506) | mezzo-soprano (en) |
| ...                             | ...                   | ...                        | ...                |
| Huntsman (wd:Q63527879)         | Huntsman (en)         | contralto (wd:Q37137)      | contralto (en)     |
| Diana (wd:Q63526877)            | Diana (en)            | contralto (wd:Q37137)      | contralto (en)     |
| Alcione (wd:Q63526495)          | Alcione (en)          | contralto (wd:Q37137)      | contralto (en)     |
| Arthur of Cleves (wd:Q63522293) | Arthur of Cleves (en) | contralto (wd:Q37137)      | contralto (en)     |
| Third actor (wd:Q63522277)      | Third actor (en)      | contralto (wd:Q37137)      | contralto (en)     |

The query retrieves individuals who have a specified voice type (soprano, mezzo-soprano, contralto, countertenor, tenor, baritone, bass) but do not have a defined occupation. For each individual, their voice type and labels (if available) are included.

[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 are the individuals with a specified voice type (such as soprano, mezzo-soprano, contralto, countertenor, tenor, baritone, bass, and their derivatives) but do not have a defined occupation? For each individual,  include their voice type.

[Assistant]
To answer this question, I need to identify individuals with a specified voice type but without a defined occupation. The voice types mentioned are soprano, mezzo-soprano, contralto, countertenor, tenor, baritone, bass, and their derivatives.

Step 1: Identify the entities for the voice types.
Step 2: Identify the property for voice type.
Step 3: Identify the property for occupation.
Step 4: Query individuals who have a voice type but no occupation.

I will start by searching for the property related to voice type.

[Tool]
Top 10 property alternatives:
1. voice type, also known as range of voice, register, tessitura, type of voice, vocal type (wd:P412 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): person's voice type. expected values: soprano, mezzo-soprano, contralto, countertenor, tenor, baritone, bass (and derivatives)
2. audio recording of the subject's spoken voice, also known as voice recording, audio clip, spoken voice, speaking voice, recording of the subject's spoken voice (wd:P990 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): audio file representing the speaking voice of a person; or of an animated cartoon or other fictitious character, audio
3. tone or pitch accent class, also known as pitch accent type, tone type, tone class, pitch accent class (wd:P5426 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): type of an tone or pitch accent of a lexeme with respect to the classifications for a given tonal or pitch accented language
4. voice actor, also known as voice actors, voice dubber, voice actress, voice actresses, voiced by (wd:P725 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): performer of a spoken role in a creative work such as animation,... (P453) as qualifier] [use "cast member" (P161) for live acting], film crew member, cast member
5. 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 pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): language associated with this creative work (such as books, show...guage" (P103) and "languages spoken, written or signed" (P1412))
6. class, also known as type (wd:P2308 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): qualifier to define a property constraint in combination with "property constraint" (P2302)
7. taxonomic type, also known as genotype, species typica, type, type genus, type species (wd:P427 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): type genus or species: [in zoology:] nominal genus or species th...t is the name-bearing type of this nominal species or subspecies
8. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
9. pronunciation variety, also known as language variant, with pronunciation, with dialect, pronunciation, dialect (wd:P5237 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): qualifier for IPA transcription (P898), pronunciation audio (P44... audio (P989) to indicate the associated spoken language variant
10. audio system, also known as audio format (wd:P7501 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): audio system hardware used in the item

[Assistant]
The property "voice type" (wdt:P412) is the relevant property for the voice types such as soprano, mezzo-soprano, contralto, countertenor, tenor, baritone, bass, and their derivatives.

Next, I will identify the property for occupation to filter out individuals who do not have a defined occupation.

[Tool]
Top 10 property alternatives:
1. occupation, also known as job, work, vocation, profession, employment (wd:P106 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
2. field of this occupation, also known as practice, works in, profession's field, practices, field of this profession (wd:P425 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): field corresponding to this occupation or profession (use only f...fessions - for people use Property:P101, for companies use P452)
3. members have occupation, also known as profession of members, organization of, organization for, organisation of, organisation for (wd:P3989 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): some or all members of this group share the occupation
4. practiced by, also known as proponent, studied by, practitioners, practioner, occupation of this field (wd:P3095 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): type of agents that study this subject or work in this field
5. position held, also known as function, held position, holds position, job, office held (wd:P39 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): subject currently or formerly holds the object position or public office
6. employer, also known as working at, working for, working place, works at, works for (wd:P108 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): person or organization for which the subject works or worked, affiliation
7. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): the object is a country that recognizes the subject as its citizen, country
8. occupant, also known as tenant, resident, renter, occupiers, lessee (wd:P466 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): person or organization occupying property, used by
9. field of work, also known as scientific discipline, scientific area, responsible for, research on, research fields (wd:P101 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): specialization of a person or organization; see P106 for the occupation, interested in
10. work location, also known as work place, working from, working at, worked from, worked at (wd:P937 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): location where persons or organisations were actively participating in employment, business or other work, significant place, location

[Assistant]
The property "occupation" (wdt:P106) is the relevant property for occupation.

Now I will build a SPARQL query to find individuals (?person) who have a voice type (?voiceType) but do not have an occupation. I will use the property wdt:P412 for voice type and wdt:P106 for occupation. I will also include the label for the voice type for better readability.

I will start with a query that selects individuals with a voice type and no occupation.

[Tool]
SPARQL execution failed:
HTTPSConnectionPool(host='qlever.cs.uni-freiburg.de', port=443): Read timed out. (read timeout=30)

[Assistant]
The query execution timed out, likely due to the large dataset and complexity of the query. To improve performance, I will remove the SERVICE wikibase:label clause and instead use optional rdfs:label for labels. I will also limit the results to 10 for testing.

I will retry the query with these adjustments.

[Tool]
SPARQL execution failed:
HTTPSConnectionPool(host='qlever.cs.uni-freiburg.de', port=443): Read timed out. (read timeout=30)

[Assistant]
The query still times out, likely due to the large number of individuals with voice types and the complexity of the query.

To reduce the complexity, I will first check how many individuals have a voice type to get an estimate of the data size. Then I will try to find individuals with voice type and no occupation in smaller batches or with additional constraints.

I will run a count query for individuals with a voice type.

[Tool]
SPARQL execution failed:
HTTPSConnectionPool(host='qlever.cs.uni-freiburg.de', port=443): Read timed out. (read timeout=30)

[Assistant]
The count query also times out, indicating that the dataset for individuals with voice types is quite large or the endpoint is under heavy load.

As an alternative approach, I will try to find some example individuals with a specific voice type, e.g., "soprano," and check if they have an occupation or not. This will help to understand the data distribution and refine the query.

I will first search for the entity "soprano" to get its identifier.

[Tool]
Top 10 entity alternatives:
1. soprano, also known as soprano lirica (wd:Q30903): type of singing voice with the highest vocal range
2. Soprano, also known as Saïd M'Roumbaba (wd:Q1372291): French rapper, singer and songwriter, singer-songwriter, singer, rapper, actor
3. Soprano, also known as KDE (wd:Q3110464): free software
4. Soprano, also known as Soprano Oyj (wd:Q11894120): business enterprise in Helsinki, Finland
5. Soprano, also known as Francis Xavery Ndumbaro (wd:Q47513883): Tanzanian musician, musician
6. Soprano (wd:Q37553758): family name
7. Soprano, also known as IMO 1013133 (wd:Q84727182): yacht built in 2017
8. Soprano (wd:Q103909217): shipwreck off the Scottish coast
9. soprano (wd:Q63518855): operatic character in the opera In seinem Garten liebt Don Perlimplin Belisa by Wolfgang Fortner
10. soprano (wd:L13256-F1)

[Assistant]
The entity "soprano" as a type of singing voice with the highest vocal range is wd:Q30903.

I will now query individuals with voice type "soprano" (wd:Q30903) and check if they have an occupation or not. I will limit the results to 10 for testing.

[Tool]
SPARQL execution failed:
HTTPSConnectionPool(host='qlever.cs.uni-freiburg.de', port=443): Read timed out. (read timeout=30)

[Assistant]
The query for individuals with the voice type "soprano" and no occupation also times out.

Given the repeated timeouts, it seems the endpoint struggles with queries involving voice type and occupation filters, possibly due to the large data volume or complexity.

As a workaround, I will try to find individuals with any voice type and then filter out those with occupation in a separate step or limit the query further by adding a constraint on the number of results or specific voice types.

I will try to list some individuals with voice types without filtering occupation first, limiting to 10 results.

[Tool]
SPARQL execution failed:
HTTPSConnectionPool(host='qlever.cs.uni-freiburg.de', port=443): Read timed out. (read timeout=30)

[Assistant]
Even the query to list individuals with voice types without filtering occupation times out.

Due to the repeated timeouts, it appears that the dataset or the endpoint cannot handle queries involving the voice type property efficiently.

I will try a different approach by searching for individuals with a voice type among a smaller subset of voice types, e.g., only "soprano" and "tenor," and limit the results to 5. This might reduce the query complexity.

I will run this query next.

[Tool]
Got 5 rows and 4 columns:
| person                            | personLabel              | voiceType           | voiceTypeLabel |
| --------------------------------- | ------------------------ | ------------------- | -------------- |
| Florencia Fabris (wd:Q14892712)   | Florencia Fabris (en)    | soprano (wd:Q30903) | soprano (en)   |
| Mercedes Capsir (wd:Q1464447)     | Mercedes Capsir (en)     | soprano (wd:Q30903) | soprano (en)   |
| Bernadett Wiedemann (wd:Q1464722) | Bernadett Wiedemann (en) | soprano (wd:Q30903) | soprano (en)   |
| Margit Schramm (wd:Q1464824)      | Margit Schramm (en)      | soprano (wd:Q30903) | soprano (en)   |
| Fritzi Jokl (wd:Q1469225)         | Fritzi Jokl (en)         | soprano (wd:Q30903) | soprano (en)   |

[Assistant]
I found 5 individuals with the voice type "soprano" (wd:Q30903). Now I will check if these individuals have an occupation or not. This will help me understand if filtering by occupation is feasible.

I will query the occupations of these 5 individuals.

[Tool]
Got 5 rows and 4 columns:
| person                            | personLabel              | occupation                 | occupationLabel   |
| --------------------------------- | ------------------------ | -------------------------- | ----------------- |
| Mercedes Capsir (wd:Q1464447)     | Mercedes Capsir (en)     | opera singer (wd:Q2865819) | opera singer (en) |
| Bernadett Wiedemann (wd:Q1464722) | Bernadett Wiedemann (en) | opera singer (wd:Q2865819) | opera singer (en) |
| Margit Schramm (wd:Q1464824)      | Margit Schramm (en)      | opera singer (wd:Q2865819) | opera singer (en) |
| Fritzi Jokl (wd:Q1469225)         | Fritzi Jokl (en)         | opera singer (wd:Q2865819) | opera singer (en) |
| Florencia Fabris (wd:Q14892712)   | Florencia Fabris (en)    | opera singer (wd:Q2865819) | opera singer (en) |

[Assistant]
All 5 individuals with the voice type "soprano" have an occupation defined as "opera singer."

This suggests that individuals with a specified voice type often have an occupation defined, at least for soprano.

I will now try to find individuals with other voice types (mezzo-soprano, contralto, countertenor, tenor, baritone, bass) and check if any of them do not have an occupation.

First, I need to find the Wikidata entities for these voice types. I will search for "tenor" as an example.

[Tool]
Top 10 entity alternatives:
1. tenor, also known as tenor (singer), tenor voice (wd:Q27914): voice type, male singing voice
2. Tenor (wd:Q48817537): search engine
3. Tenor (wd:Q111754419): 2022 film directed by Claude Zidi Jr.
4. Tenor (wd:Q7700558): linguistics term
5. Tenor (wd:Q19897929): 1976 live album by Joe McPhee
6. Tenor (wd:Q37571096): family name
7. Tenor (wd:Q4021291): album
8. Tenor (wd:Q48774408): Cameroonian rapper, rapper
9. Tenor, also known as IMO 8709846 (wd:Q52509468): research/survey vessel built in 1988
10. Tenör (wd:Q6020554): Turkish term from mining

[Assistant]
The entity for the voice type "tenor" (male singing voice) is wd:Q27914.

I will now search for the entities of the other voice types: mezzo-soprano, contralto, countertenor, baritone, and bass.

[Tool]
Top 10 entity alternatives:
1. mezzo-soprano, also known as mezzosoprán, mezzo-soprano voice, mezzosoprano, mezzo (wd:Q186506): type of classical female singing voice whose vocal range lies between the soprano and the contralto voice
2. mezzo-soprano (wd:Q108404711): singer with a mezzo-soprano voice
3. oboe d'amore, also known as hautbois d'amour, mezzo-soprano oboe (wd:Q8380): double reed woodwind musical instrument
4. mezzo-soprano saxophone, also known as F alto saxophone (wd:Q1926466): instrument in the saxophone family
5. mezzo-soprano clef (wd:Q2175897): C-clef placed on the second line of the stave
6. lyric mezzo-soprano (wd:Q1878954): Mezzo-soprano voice subtype
7. dramatic mezzo-soprano, also known as dramatic mezzo (wd:Q6012297): type of singing voice
8. light mezzo-soprano (wd:Q6012300)
9. character mezzo-soprano (wd:Q54634862)
10. coloratura mezzo-soprano (wd:Q54634572)

[Tool]
Top 10 entity alternatives:
1. contralto (wd:Q37137): type of classical female singing voice
2. ContrAlto (wd:Q55770874): Alto emulator
3. contralto (wd:L318577)
4. contralto (wd:L335604-F1)
5. contralto (wd:L335604)
6. contralto (wd:L318577-F1)
7. deep contralto (wd:Q54635335)
8. contra-alto clarinet, also known as E-flat contrabass clarinet, contralto clarinet, contrabass clarinet (E♭), E♭ contrabass clarinet (wd:Q6517474): bass-contrabass member of the clarinet family
9. contra-alto flute, also known as contr'alto flute, contralto flute (wd:Q5165592): large flute pitched in G between the bass and contrabass
10. dramatic contralto (wd:Q5785183)

[Tool]
Top 10 entity alternatives:
1. countertenor, also known as angelical, contra tenor, counter-tenor, countertenor voice, tenor angelical (wd:Q223166): high classical male singing voice
2. countertenor (wd:L318755-F1)
3. countertenor (wd:L318755)
4. countertenor (wd:L335679)
5. countertenor (wd:L335679-F1)
6. countertenors (wd:L318755-F2)
7. Twentieth‐Century Countertenor Repertoire (wd:Q58506543)
8. Intelligibility of vowels sung by a countertenor (wd:Q30531300): scientific article
9. James Bowman, Who Helped Resurrect the Countertenor, Dies at 81 (wd:Q123756592): The New York Times article (April 7, 2023)
10. Russell Oberlin, 88, Dies; Led Renaissance of Countertenor in U.S. (wd:Q123589220): The New York Times article (November 29, 2016)

[Tool]
Top 10 entity alternatives:
1. baritone, also known as baryton (wd:Q31687): vocal and pitch range above bass and below tenor
2. baritone, also known as baritone instrument (wd:Q15212740): instrumental part between the tenor and bass lines
3. baritone (wd:Q63518848): operatic character in the opera In seinem Garten liebt Don Perlimplin Belisa by Wolfgang Fortner
4. baritone (wd:L737003-S1)
5. baritone (wd:L334749-F1)
6. baritone (wd:L334749)
7. baritone (wd:L1336054-S1)
8. baritone (wd:L13254-F1)
9. baritone (wd:L13254)
10. baritone horn, also known as baritonhorn, bombardino (wd:Q790468): low-pitched brass instrument

[Tool]
Top 10 entity alternatives:
1. bass guitar, also known as bass (wd:Q46185): electric or acoustic bass instrument
2. bass guitar, also known as bass (wd:Q46185): electric or acoustic bass instrument
3. bass, also known as bas, bass voice (wd:Q27911): type of classical male singing voice
4. bass, also known as bas, bass voice (wd:Q27911): type of classical male singing voice
5. Bulgarian Academy of Sciences, also known as БЪЛГАРСКА АКАДЕМИЯ НА НАУКИТЕ, Bulgarian Academy of Sciences，簡稱：BAS, BASS, BAS, Balgarska Akademiya na Naukite (wd:Q1003730): academy of sciences
6. bass (wd:Q810451): sound, tone of low frequency or range
7. bass, also known as bass instrument (wd:Q810447): any of a number of music instruments which produce low pitched tones
8. Bassa Vah, also known as Bassa alphabet, Bassa script, Bassa Vah script, Bass (wd:Q810458): writing system
9. bass, also known as Bass (wd:Q1224135): name of various types of fish
10. 120074 Bass, also known as (120074) 2003 EA, Bass (wd:Q8257348): asteroid

[Assistant]
The Wikidata entities for the voice types are:
- mezzo-soprano: wd:Q186506
- contralto: wd:Q37137
- countertenor: wd:Q223166
- tenor: wd:Q27914
- baritone: wd:Q31687
- bass: wd:Q27911

I will now query individuals with these voice types and check if they have an occupation or not. I will limit the results to 10 for testing.

[Tool]
Got 10 rows and 4 columns:
| person                                | personLabel                 | voiceType                  | voiceTypeLabel     |
| ------------------------------------- | --------------------------- | -------------------------- | ------------------ |
| Roßweiße (wd:Q55013466)               | Roßweiße (en)               | mezzo-soprano (wd:Q186506) | mezzo-soprano (en) |
| Adriano (wd:Q55021992)                | Adriano (en)                | mezzo-soprano (wd:Q186506) | mezzo-soprano (en) |
| a maidservant (wd:Q55001886)          | a maidservant (en)          | mezzo-soprano (wd:Q186506) | mezzo-soprano (en) |
| Naina (wd:Q55018239)                  | Naina (en)                  | mezzo-soprano (wd:Q186506) | mezzo-soprano (en) |
| Grimgerde (wd:Q55013473)              | Grimgerde (en)              | mezzo-soprano (wd:Q186506) | mezzo-soprano (en) |
| wd:Q55022022                          |                             | mezzo-soprano (wd:Q186506) | mezzo-soprano (en) |
| Marina Mniszech (wd:Q55003472)        | Marina Mniszech (en)        | mezzo-soprano (wd:Q186506) | mezzo-soprano (en) |
| wd:Q55022041                          |                             | mezzo-soprano (wd:Q186506) | mezzo-soprano (en) |
| wd:Q55001967                          |                             | mezzo-soprano (wd:Q186506) | mezzo-soprano (en) |
| Two Servants of Aithra (wd:Q54999800) | Two Servants of Aithra (en) | mezzo-soprano (wd:Q186506) | mezzo-soprano (en) |

[Assistant]
I found 10 individuals with voice types (all mezzo-soprano in this sample) who do not have a defined occupation. Some of these individuals have labels, while others do not.

I will now provide the final SPARQL query that retrieves individuals with a specified voice type (among the given voice types) but without a defined occupation, including their voice type and labels where available.

[Tool] Stopped generation process


PREFIX wikibase: <http://wikiba.se/ontology#>
PREFIX p: <http://www.wikidata.org/prop/>
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#>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
SELECT ?entity ?entityLabel ?idescatCode ?population ?area ?coatOfArmsImage WHERE {
  ?entity wdt:P4335 ?idescatCode .
  FILTER ( STRSTARTS( ?idescatCode , "25" ) ) ?entity wdt:P131 * wd:Q5705 .
  OPTIONAL {
    ?entity p:P1082 ?populationStatement .
    ?populationStatement ps:P1082 ?population ; wikibase:rank wikibase:PreferredRank .
  }
  OPTIONAL {
    ?entity wdt:P2046 ?area .
  }
  OPTIONAL {
    ?entity wdt:P94 ?coatOfArmsImage .
  }
  OPTIONAL {
    ?entity rdfs:label ?entityLabel FILTER ( LANG( ?entityLabel ) = "en" )
  }
}
ORDER BY ?entityLabel
LIMIT 100

There are multiple municipalities or territorial entities in Catalonia, Spain, with an IDESCAT territorial code starting with "25". For these entities, I retrieved their most recent population using the preferred rank (if available), area (if available), and coat of arms image (if available). The query results include entities like Abella d'Adons, Abella de la Conca, Ardòvol, and others with their respective data when available.

[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 are the municipalities of Catalonia, Spain, with an IDESCAT territorial code starting with "25"? Include their most recent population using their preferred rank (if available), area (if available), and coat of arms image (if available).

[Assistant]
To answer this question, I need to find municipalities of Catalonia, Spain, that have an IDESCAT territorial code starting with "25". Then, I need to retrieve their most recent population using their preferred rank (if available), area (if available), and coat of arms image (if available).

Step 1: Identify the entity for Catalonia, Spain.
Step 2: Identify the property for IDESCAT territorial code.
Step 3: Identify the property for population with preferred rank.
Step 4: Identify the property for area.
Step 5: Identify the property for coat of arms image.
Step 6: Construct a query to find municipalities of Catalonia with IDESCAT code starting with "25" and retrieve the requested information.

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

[Tool]
Top 10 entity alternatives:
1. Catalonia, also known as Autonomous Community of Catalonia, Cat., Catalonha, Cataluña, Catalunya (wd:Q5705): autonomous community and nationality of Spain
2. Principality of Catalonia, also known as Principality, Principality and Counties, Catalonia (wd:Q15581): principality in the northeastern Iberian Peninsula between the 12th century and 1714
3. 13868 Catalonia, also known as Catalonia (wd:Q2355989): asteroid
4. Catalonia, also known as IMO 9176046 (wd:Q5635911): catamaran launched in 1998
5. Old Catalonia, also known as Catalonia (wd:Q3754835)
6. New Catalonia, also known as Catalonia (wd:Q3751449)
7. Catalonia (wd:Q96374545)
8. Catalonia (wd:Q113834065): cultural region
9. Catalonia Hotels & Resorts, also known as Catalonia (wd:Q126180437): chain of hotels in Spain
10. Catalònia (wd:Q115997507): sardana by Josep Sancho i Marraco

[Assistant]
The entity for Catalonia as an autonomous community and nationality of Spain is wd:Q5705.

Next, I will search for the property related to the IDESCAT territorial code. I will search for properties with the keyword "IDESCAT".

[Tool]
Top 10 property alternatives:
1. IDESCAT territorial code in Catalonia (wd:P4335 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): official identifier for a Catalonian territorial unit, from Institut Estadístic de Catalunya (IDESCAT)
2. ISOCAT ID, also known as ISO 12620 ID, ISOCAT (wd:P2263 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): numeric ID from the Data Category Registry
3. Commons category, also known as category on Wikimedia Commons, Wikimedia Commons category, Wikimedia Commons cat, Commons cat, commonscat (wd:P373 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): name of the Wikimedia Commons category containing files related to this item (without the prefix "Category:")
4. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): main Wikimedia category
5. IndexCat ID (wd:P10662 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): ID in the IndexCat database of historical medical publications
6. ideographic description sequence, also known as ideographic description sequences, IDS, IDSes (wd:P5753 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): method to describe composition of Han characters using ideographic description characters and character or stroke components
7. IdRef ID, also known as SUDOC, SUDOC authorities ID, SUDOC authority ID, Système Universitaire de Documentation authorities ID, IdRef (wd:P269 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): identifier for authority control in the French collaborative lib...og (see also P1025). Format: 8 digits followed by a digit or "X"
8. endangeredlanguages.com ID, also known as Catalogue of Endangered Languages ID, ELCat ID (wd:P2192 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): identifier of a language on the website endangeredlanguages.com
9. Istituto Italiano di Tecnologia author ID, also known as IIT ID (wd:P11896 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): identifier for an author in Istituto Italiano di Tecnologia
10. Bugs! track ID (wd:P10384 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): identifier for a track on the South Korean music streaming site Bugs!

[Assistant]
The property for the IDESCAT territorial code in Catalonia is wd:P4335.

Next, I will search for the property related to population with preferred rank. I will search for properties with the keyword "population".

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

[Assistant]
The property for population is wd:P1082.

Next, I will search for the property related to area. I will search for properties with the keyword "area".

[Tool]
Top 10 property alternatives:
1. area, also known as total area, surface area, surface, size, resolution (wd:P2046 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): area occupied by an object
2. field of work, also known as scientific discipline, scientific area, responsible for, research on, research fields (wd:P101 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): specialization of a person or organization; see P106 for the occupation, interested in
3. applies to part, also known as when viewed as, valid for part, section, region, per (wd:P518 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): part, aspect, or form of the item to which the claim applies
4. applies to jurisdiction, also known as belongs to jurisdiction, applies to territorial jurisdiction, applies to region, applies to place, applies to geographic place (wd:P1001 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): the item (institution, law, public office, public register...) o...a territorial jurisdiction: a country, state, municipality, ...), significant place, characteristic of, operating area
5. operating area, also known as province served, serves jurisdiction, serves geographic region, serves geographic area, serves area (wd:P2541 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): geographic area or jurisdiction an organisation or industry operates in, serves, or has responsibility for, location
6. water area (wd:P8887 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): area/surface of a geographical entity that is covered by water, area
7. interested in, also known as area of interest, area of research, field of interest, field of research, field of study (wd:P2650 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): item of special or vested interest to this person or organisation
8. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
9. 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 pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
10. electoral district, also known as riding, seat, ward, electoral area, electorate (wd:P768 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): electoral district this person is representing, or of the office... or "office contested" (P541) or "candidacy in election" (P3602)

[Assistant]
The property for area is wd:P2046.

Next, I will search for the property related to coat of arms image. I will search for properties with the keyword "coat of arms".

[Tool]
Top 10 property alternatives:
1. coat of arms (wd:P237 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): subject's coat of arms
2. coat of arms image, also known as symbol, representation (heraldic), image of coat of arms, emblem, heraldic, CoA image (wd:P94 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): image of the item's coat of arms - for the shield part only use P4004, image
3. symbol of, also known as emblem of, flag of, logo of, seal of, symbolises (wd:P8058 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): item of which the image is a symbol
4. official symbol, also known as symbol, state tartan, official tartan, floral emblem, official emblem (wd:P2238 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): official symbol of an organisation
5. seal image, also known as emblem, emblem image, seal (wd:P158 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): image of subject's seal (emblem), image
6. heraldic attitude (wd:P8503 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): the attitude or posture of a charge on a coat of arms (e.g. lion rampant)
7. flag, also known as flag description (wd:P163 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): subject's flag
8. flag image, also known as image flag, image of flag (wd:P41 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): image of the item's flag, image, flag
9. logo image, also known as masthead, wordmark, trademark, trade mark, sign (wd:P154 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): graphic mark or emblem commonly used by commercial enterprises, organizations and products, icon
10. escutcheon image, also known as shield, shield image (wd:P4004 as pq/pqn/psv/p/wdt/pqv/prv/wdtn/pr/ps/psn/prn): use for the shield part only: use P94 for a coat of arms

[Assistant]
The property for coat of arms image is wd:P94.

Now I will construct a SPARQL query to find municipalities of Catalonia (wd:Q5705) with an IDESCAT territorial code (wdt:P4335) starting with "25". I will retrieve their most recent population (wdt:P1082) using preferred rank, area (wdt:P2046), and coat of arms image (wdt:P94) if available. I will also ensure the entities are instances of municipality (wd:Q3314687) or a subclass of municipality.

I will now write the SPARQL query.

[Tool] Got no rows and 6 columns

[Assistant] The query returned no results, which might be due to the strict filtering on the instance of municipality or the location hierarchy. I will relax the instance of municipality condition to just instance of municipality (wd:Q3314687) without subclasses and check again.

[Tool] Got no rows and 6 columns

[Assistant] No results were returned again. It might be that the municipalities in Catalonia are not directly instances of municipality (wd:Q3314687) or the location property chain is different. I will try to find municipalities located in Catalonia by checking if they have Catalonia as their "located in the administrative territorial entity" (wdt:P131) directly without the recursive path.

[Tool] Got no rows and 6 columns

[Assistant] No results again. It seems that municipalities in Catalonia might not be directly located in Catalonia (wd:Q5705) but rather in smaller administrative divisions within Catalonia. I will try to find municipalities that are located in any administrative territorial entity that is itself located in Catalonia. I will use a two-level location chain for this.

[Tool] Got no rows and 6 columns

[Assistant] Still no results. It might be that the municipalities are located in administrative entities that are located in other entities before reaching Catalonia. I will try a recursive location chain again but with a different approach: I will first find all entities with IDESCAT code starting with "25" and then check if they are located in Catalonia or its subdivisions.

[Tool] Got no rows and 6 columns

[Assistant]
No results again. It seems that the instance of municipality (wd:Q3314687) might not be the correct classification for these entities or the IDESCAT code property is not used as expected.

I will try to find entities with IDESCAT code starting with "25" and check their instance of property to see what types they have. This will help understand the classification of these entities.

[Tool]
Got 27 rows and 2 columns, showing the first 5 and last 5 rows below:
| instanceOf                                            | instanceOfLabel                            |
| ----------------------------------------------------- | ------------------------------------------ |
| casal (wd:Q11912920)                                  | casal (en)                                 |
| populated place nucleus (wd:Q11939023)                | populated place nucleus (en)               |
| municipality capital (wd:Q121289819)                  | municipality capital (en)                  |
| neighborhood (wd:Q123705)                             | neighborhood (en)                          |
| nucleus of singular population entity (wd:Q127386657) | nucleus of singular population entity (en) |
| ...                                                   | ...                                        |
| decentralized municipal entity (wd:Q6554043)          | decentralized municipal entity (en)        |
| old town (wd:Q676050)                                 | old town (en)                              |
| fortified town (wd:Q677678)                           | fortified town (en)                        |
| pene-exclave (wd:Q8273909)                            | pene-exclave (en)                          |
| comarca of Catalonia (wd:Q937876)                     | comarca of Catalonia (en)                  |

[Assistant]
The entities with IDESCAT code starting with "25" have various instance types, including "casal", "populated place nucleus", "municipality capital", "neighborhood", "decentralized municipal entity", "old town", "fortified town", and "comarca of Catalonia". The expected "municipality" instance is not directly seen here.

I will check if there are any entities with instance of "municipality" (wd:Q3314687) in Catalonia with an IDESCAT code at all, to verify if the property is used for municipalities.

[Tool] Got no rows and 3 columns

[Assistant]
There are no entities that are instances of municipality (wd:Q3314687) in Catalonia with an IDESCAT code. This suggests that the municipalities in Catalonia might be classified differently or the IDESCAT code is assigned to other types of entities.

I will now check the instance types of municipalities in Catalonia without filtering by IDESCAT code to understand their classification.

[Tool]
Got 20 rows and 2 columns, showing the first 5 and last 5 rows below:
| instanceOf                                              | instanceOfLabel                              |
| ------------------------------------------------------- | -------------------------------------------- |
| parish (wd:Q102496)                                     | parish (en)                                  |
| rural settlement (wd:Q10354598)                         | rural settlement (en)                        |
| Roman Catholic metropolitan archdiocese (wd:Q105390172) | Roman Catholic metropolitan archdiocese (en) |
| autonomous community of Spain (wd:Q10742)               | autonomous community of Spain (en)           |
| historic site (wd:Q1081138)                             | historic site (en)                           |
| ...                                                     | ...                                          |
| comarca (wd:Q12829)                                     | comarca (en)                                 |
| ski resort (wd:Q130003)                                 | ski resort (en)                              |
| Catalan historical locality (wd:Q130261443)             | Catalan historical locality (en)             |
| second-level administrative division (wd:Q13220204)     | second-level administrative division (en)    |
| wd:Q133503733                                           |                                              |

[Assistant]
The instance types of entities in Catalonia with population include various types such as parish, rural settlement, comarca, second-level administrative division, and others. The typical "municipality" instance is not prominent here.

Given this, I will try to find entities with IDESCAT code starting with "25" that are located in Catalonia or its subdivisions, without restricting to municipality instance, and retrieve their population, area, and coat of arms image. This might give a broader set of relevant territorial entities in Catalonia with the requested data.

[Tool]
Got 100 rows and 6 columns, showing the first 5 and last 5 rows below:
| entity                                                 | entityLabel                                 | idescatCode   | population        | area               | coatOfArmsImage                                                                               |
| ------------------------------------------------------ | ------------------------------------------- | ------------- | ----------------- | ------------------ | --------------------------------------------------------------------------------------------- |
| Abella d'Adons (wd:Q9138196)                           | Abella d'Adons (en)                         | 2517340001700 | 1 (xsd:decimal)   |                    |                                                                                |
| Abella de la Conca (wd:Q18257)                         | Abella de la Conca (en)                     | 250019        | 158 (xsd:decimal) | 78.3 (xsd:decimal) | <http://commons.wikimedia.org/wiki/Special:FilePath/Escut%20d%27Abella%20de%20la%20Conca.svg> |
| Abella de la Conca (wd:Q24003963)                      | Abella de la Conca (en)                     | 2500190001700 |                   |                    |                                                                                |
| Abellar (wd:Q67147089)                                 | Abellar (en)                                | 2514250002200 |                   |                    |                                                                                |
| Acadèmia General Bàsica de Suboficials (wd:Q126642002) | Acadèmia General Bàsica de Suboficials (en) | 2523470028700 |                   |                    |                                                                                |
| ...                                                    | ...                                         | ...           | ...               | ...                | ...                                                                                |
| Ardèvol (wd:Q8203867)                                  | Ardèvol (en)                                | 2516730001700 |                   |                    |                                                                                |
| Ardòvol (wd:Q9159374)                                  | Ardòvol (en)                                | 2517900001700 | 6 (xsd:decimal)   |                    |                                                                                |
| Arduix (wd:Q11686676)                                  | Arduix (en)                                 | 2523980003800 |                   |                    |                                                                                |
| Arestui (wd:Q8203983)                                  | Arestui (en)                                | 2512660002200 |                   | 9.7 (xsd:decimal)  |                                                                                |
| Àreu (wd:Q17181945)                                    | Àreu (en)                                   | 2501750004300 |                   |                    |                                                                                |

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?item ?itemLabelEN WHERE {
  ?item rdfs:label "Madonna and Child" @en .
  FILTER NOT EXISTS {
    ?item rdfs:label ?itemLabelFR FILTER ( LANG( ?itemLabelFR ) = "fr" )
  }
  OPTIONAL {
    ?item rdfs:label ?itemLabelEN FILTER ( LANG( ?itemLabelEN ) = "en" )
  }
}

Got 210 rows and 2 columns, showing the first 5 and last 5 rows below:
| item                              | itemLabelEN            |
| --------------------------------- | ---------------------- |
| Madonna and Child (wd:Q101085785) | Madonna and Child (en) |
| Madonna and Child (wd:Q103888170) | Madonna and Child (en) |
| Madonna and Child (wd:Q105490754) | Madonna and Child (en) |
| Madonna and Child (wd:Q105495932) | Madonna and Child (en) |
| Madonna and Child (wd:Q107437222) | Madonna and Child (en) |
| ...                               | ...                    |
| Madonna and Child (wd:Q80006189)  | Madonna and Child (en) |
| Madonna and Child (wd:Q80006203)  | Madonna and Child (en) |
| Madonna and Child (wd:Q88800712)  | Madonna and Child (en) |
| Madonna and Child (wd:Q90260785)  | Madonna and Child (en) |
| Madonna and Child (wd:Q99454457)  | Madonna and Child (en) |

The items labeled "Madonna and Child" in English but do not have a label in French are returned by the query. The query finds items with the English label "Madonna and Child" and filters out those that have a French label.

[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 items are labeled "Madonna and Child" in English but do not have a label in French?

[Assistant]
To answer this question, I need to find items that have an English label "Madonna and Child" but do not have a French label.

Step 1: Identify items with the English label "Madonna and Child."
Step 2: Filter out items that have a French label.

I will start by writing a SPARQL query to find items with the English label "Madonna and Child" and check if they have a French label or not.

[Tool]
Got 812 rows and 3 columns, showing the first 5 and last 5 rows below:
| item                              | itemLabelEN | itemLabelFR            |
| --------------------------------- | ----------- | ---------------------- |
| Madonna and Child (wd:Q101085785) |             |                        |
| Madonna and Child (wd:Q102166981) |             | Vierge à l'Enfant (fr) |
| Madonna and Child (wd:Q103304807) |             | Vierge à l'Enfant (fr) |
| Madonna and Child (wd:Q103858810) |             | Vierge à l'Enfant (fr) |
| Madonna and Child (wd:Q103888170) |             |                        |
| ...                               | ...         | ...                    |
| Madonna and Child (wd:Q96185495)  |             | Vierge à l'Enfant (fr) |
| Madonna and Child (wd:Q96812877)  |             | Vierge à l'Enfant (fr) |
| Madonna and Child (wd:Q97552353)  |             | Vierge à l'Enfant (fr) |
| Madonna and Child (wd:Q97686883)  |             | Vierge à l'Enfant (fr) |
| Madonna and Child (wd:Q99454457)  |             |                        |

[Assistant] I found 812 items labeled "Madonna and Child" in English. Some of them have a French label, but some do not. Now I will refine the query to only return items that do not have a French label.

[Tool] Stopped generation process