PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?country ( COUNT( ?winner ) AS ?count ) WHERE {
  ?winner wdt:P166 wd:Q123737 .
  ?winner wdt:P495 | wdt:P27 ?country .
}
GROUP BY ?country
ORDER BY DESC ( ?count )
LIMIT 2

The United Kingdom (wd:Q145)

[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] From which country came the 2nd most winners of the Emmy Award ?

[Assistant] To answer this question, we need to identify the winners of the Emmy Award and their countries of origin. We will start by searching for the property that represents winning an Emmy Award and then find the countries associated with these winners. Let's begin by finding the property for the Emmy Award.

[Tool]
Top 10 property alternatives:
1. Emmys person ID, also known as Emmys ID (wd:P8381 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): identifier for Emmys person ID
2. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): award or recognition received by a person, organization or creative work
3. nominated for, also known as nominee for, shortlisted for, selected for award, selected for, nominee for award (wd:P1411 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): award nomination received by a person, organisation or creative work (inspired from "award received" (Property:P166))
4. nominee, also known as award nominee (wd:P2453 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): qualifier used with “nominated for” to specify which person or organization was nominated
5. TheTVDB award ID, also known as TheTVDB.com award ID (wd:P12399 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): identifier for an award on the website TheTVDB.com
6. season, also known as TV series, television season, TV season, television series, series of television program (wd:P4908 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): season of a series (televison, web, podcast), part of
7. Television Academy Foundation show ID, also known as The Interviews title ID (wd:P5829 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): identifier for a television show discussed on the Television Academy Foundation's The Interviews website
8. conferred by, also known as presented by, officiated by, issued by, granted by, given by (wd:P1027 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): person or organization who grants an award, certification, grant, or role
9. winner, also known as nominee, prizewinner, titleholder, top dog, victor (wd:P1346 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): winner of a competition or similar event, not to be used for awa...ssibly qualified with "for work" (P1686)) or for wars or battles, participating team, participant
10. nominated by (wd:P4353 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): who nominated a person for an office or award; can be used as a qualifier

No other items found

[Assistant] The property "award received" (wd:P166) seems to be the most relevant for identifying Emmy Award winners. Next, we need to find the specific item for the Emmy Award. Let's search for it.

[Tool]
Top 10 entity alternatives:
1. Emmy Award, also known as Emmy Awards, Emmys (wd:Q123737): American television production award
2. Primetime Emmy Award, also known as Primetime Emmy Awards (wd:Q1044427): Academy of Television Arts & Sciences accolade
3. Daytime Emmy Award, also known as Daytime Emmy Awards, Filmworks (wd:Q1179189): American TV award
4. International Emmy Award (wd:Q10354837): International Academy of Television Arts and Sciences accolade
5. Sports Emmy Awards, also known as Sports Emmy Award, Sports Emmys (wd:Q3494164): award for sports personalities
6. Creative Arts Emmy Award (wd:Q3002405): annual award for technical and other similar achievements in American television programming
7. International Emmy Founders Award, also known as Founders Award (wd:Q18465914): television production award
8. International Emmy Directorate Award (wd:Q18466322): annual award
9. Los Angeles Emmy Award, also known as Los Angeles Area Emmy Award (wd:Q17008411): award presented by the Television Academy
10. 57th Primetime Emmy Awards (wd:Q1122380): 2005 American television programming awards

No other items found

No literal items found

[Assistant]
The most relevant items for the Emmy Award are:

1. **Emmy Award** (wd:Q123737)
2. **Primetime Emmy Award** (wd:Q1044427)
3. **Daytime Emmy Award** (wd:Q1179189)
4. **International Emmy Award** (wd:Q10354837)

We will consider all these awards to ensure we capture all Emmy Award winners. Next, we need to find the property that represents the country of origin for these winners. Let's search for the property "country of origin" or "country".

[Tool]
Top 10 property alternatives:
1. country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country
2. location of formation, also known as place of incorporation, originates from, place of establishment, place of formation, place of foundation (wd:P740 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): location where a group or organization was formed, location of creation
3. location of creation, also known as manufactured in, manufacturing location, mint, minted at, photographed at (wd:P1071 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): place where the item was conceived or made; where applicable, location of final assembly, significant place
4. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): time when an entity begins to exist; for date of official opening use P1619, start time
5. indigenous to, also known as native to, originating from, spoken by (wd:P2341 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): place or ethnic group where a language, art genre, cultural trad...biological species or variety is found (or was originally found)
6. derived from organism type, also known as derived from organism of taxon, originated from individual of taxon, taxon of origin (wd:P9072 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): the taxon that the organism from which the subject cell line was...cause cell lines are derived only once from a single individual)
7. valid in place, also known as applies to country, applies to location, applies to place, country, true in (wd:P3005 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): place where a statement is valid, applies to part
8. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): the object is a country that recognizes the subject as its citizen, country
9. country, also known as sovereign state, state, land, host country (wd:P17 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
10. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): most specific known birth location of a person, animal or fictional character, location

No other items found

[Assistant]
The property "country of origin" (wd:P495) seems to be the most relevant for identifying the country of origin for the Emmy Award winners. However, we should also consider "country of citizenship" (wd:P27) as it might be more appropriate for individuals.

Let's start by constructing a SPARQL query to find the winners of the Emmy Award and their countries of origin or citizenship. We will then count the number of winners per country and sort the results to find the second most frequent country.

[Tool]
Got 2 rows and 2 columns:
| ?country                 | ?count |
| ------------------------ | ------ |
| United States (wd:Q30)   | 668    |
| United Kingdom (wd:Q145) | 51     |

[Assistant]
The query results show that the United States (wd:Q30) has the most Emmy Award winners, and the United Kingdom (wd:Q145) has the second most Emmy Award winners.

Therefore, the country from which the 2nd most winners of the Emmy Award came is the United Kingdom.

Here is the final SPARQL query and answer:

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ( COUNT( ?country ) AS ?count ) WHERE {
  wd:Q4127 wdt:P205 ?country .
}

Got 1 row and 1 column:
| ?count |
| ------ |
| 3      |

[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] How many countries are located around the euorpean Lake Constance?

[Assistant]
To answer the question about how many countries are located around Lake Constance, we need to identify the following:

1. The entity for Lake Constance.
2. The property that indicates the countries bordering a lake.
3. The countries that are linked to Lake Constance through this property.

Let's start by searching for the entity for Lake Constance.

[Tool]
Top 10 entity alternatives:
1. Lake Constance, also known as Bodensee, Lac de Constance, Lake Boden (wd:Q4127): lake in Germany, Switzerland and Austria
2. Rotopōhueroa / Lake Constance, also known as Lake Constance (wd:Q1800901): lake in New Zealand
3. Constance Lake (wd:Q22535448): lake in Algoma District, Ontario, Canada
4. Lake Constance (wd:Q21954634): lake in Australia
5. Constance Lake (wd:Q22535457): lake in Cochrane District, Ontario, Canada
6. Constance Lake (wd:Q49300861): lake in Mono County, California, United States of America
7. Constance Lake (wd:Q49300862): lake of the United States of America
8. Constance Lake (wd:Q33240536): lake in Wright County, Minnesota, United States
9. Constance Lake (wd:Q22535492): lake in Leask No. 464, Saskatchewan, Canada
10. Constance Lake (wd:Q22535482): lake in Hoodoo No. 401, Saskatchewan, Canada

No other items found

[Assistant]
The top result for "Lake Constance" is `wd:Q4127`, which is the lake in Germany, Switzerland, and Austria. This is the correct entity for Lake Constance in Europe.

Next, we need to find the property that indicates the countries bordering a lake. We can search for properties related to borders or countries.

[Tool]
Top 10 property alternatives:
1. 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 p/wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
2. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
3. basin country, also known as basin countries (wd:P205 as p/wdt): country that have drainage to/from or border the body of water
4. located in/on physical feature, also known as located on the terrain feature, location (terrain feature), loc (terr), on, on geographical feature (wd:P706 as p/wdt): located on the specified (geo)physical feature. Should not be us...nly political/administrative (P131) or a mountain range (P4552)., location, part of
5. perimeter, also known as boundary length, circumference, coastline (wd:P2547 as p/wdt): linear distance around the outside of an object
6. area, also known as total area, surface area, surface, size, resolution (wd:P2046 as p/wdt): area occupied by an object
7. locator map image, also known as locator map, map image, map (wd:P242 as p/wdt): geographic map image which highlights the location of the subject within some larger entity, image
8. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as p/wdt): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
9. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
10. HDS ID, also known as DHS, DSS, HDS identifier, Historical Dictionary of Switzerland, HLS (wd:P902 as p/wdt): identifier in HDS/HLS/DHS/DSS: Historical Dictionary of Switzerland (Q642074), a national encyclopedia

No other items found

[Assistant]
The property `wd:P205` (basin country) seems to be the most relevant for identifying the countries that border Lake Constance. This property indicates the countries that have drainage to or border the body of water.

Let's use this property to find the countries bordering Lake Constance and count them.

[Tool]
Got 1 row and 1 column:
| ?count |
| ------ |
| 3      |

[Assistant]
The SPARQL query returned a count of 3 countries that border Lake Constance.

Therefore, the number of countries located around Lake Constance is 3.

Here is the final SPARQL query and answer:

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?person ?height WHERE {
  VALUES ?person {
    wd:Q9545 wd:10993
  }
  ?person wdt:P2048 ?height .
}

The height of Tiger Woods is not available in the knowledge graph, so we cannot compare the heights of Tony Blair and Tiger Woods. The query only returns the height of Tony Blair.

[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] Is Tony Blair taller than Tiger Woods?

[Assistant] To answer this question, we need to find the height of both Tony Blair and Tiger Woods. We'll start by searching for the entities representing Tony Blair and Tiger Woods in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Tony Blair, also known as Rt. Hon. Tony Blair, Sir Anthony Charles Lynton Blair, Sir Tony Blair, The Rt. Hon. Sir Anthony Charles Lynton Blair PC KC, Anthony Blair (wd:Q9545): Prime Minister of the United Kingdom from 1997 to 2007, autobiographer, politician, diplomat, lawyer
2. Tony Blair (wd:Q7821910): 1999 single by Chumbawamba
3. Tony Blair (wd:Q16429010)
4. Tony Blair (wd:Q28052457): painting by Alastair Adams
5. Tony Blair (wd:Q63892269): musical character in the musical TONY! The Blair Musical; the Prime Minister of the United Kingdom and lead figure of the musical
6. Tony Blair Institute (wd:Q30592102): non-profit organization
7. Tony Blair Associates (wd:Q17513270): organization
8. Tony Blair, MP (wd:Q119583376): painting by Philip Oliver Hale (b.1963), Parliamentary Art Collection
9. premiership of Tony Blair, also known as Blair administration (wd:Q7240404): period of the Government of the United Kingdom
10. The Trial of Tony Blair, also known as Trial of Tony Blair (wd:Q1741389): 2007 film

No other items found

[Tool]
Top 10 entity alternatives:
1. Tiger Woods, also known as Woods, Tiger, Eldrick Tont Woods, Eldrick "Tiger" Woods, Eldrick Tont "Tiger" Woods (wd:Q10993): American golfer, animal trainer, writer, golfer
2. The Tiger Woods Story, also known as Tiger Woods Story (wd:Q7769261): 1998 television film directed by LeVar Burton
3. Tiger Woods Design (wd:Q7801498): company owned by Tiger Woods
4. Tiger Woods Foundation (wd:Q7801499): organization
5. Tiger Woods (book) (wd:Q55635855): book by Jeff Benedict
6. Phil Ivey, also known as Tiger Woods of Poker (wd:Q318464): American poker player, poker player
7. Tiger Woods PGA Tour (wd:Q2520425): golf videogame series
8. Tiger Woods PGA Tour (wd:Q7801501): 2009 video game
9. The Tiger Woods Dubai (wd:Q7769260)
10. Tiger Woods of Bengal (wd:Q27051671): 2016 film by Danny Mamik

No other items found

[Assistant] We have identified the correct entities for both Tony Blair and Tiger Woods. Now, let's find the property that represents height in the knowledge graph.

[Tool]
Top 10 property alternatives:
1. clearance, also known as span height, height of deck bottom, bridge height, height above water, height above valley floor (wd:P2793 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): distance between surface under bridge and bottom of a bridge deck
2. height, also known as heighth, size, depth over terrain (wd:P2048 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): vertical length of an entity, length
3. elevation above sea level, also known as MAMSL, MASL, height, elevation above mean sea level, elevation (wd:P2044 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): height of the item (geographical object) as measured relative to sea level
4. height of center of mass, also known as center of mass height, centre of gravity height, centre of mass height, CG height, CGZ (wd:P8497 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): distance between the center of gravity and the bottom of this object
5. duration, also known as time length, timespan, time span, time interval, runtime (wd:P2047 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): length of time of an event or process
6. length, also known as size, long, LOA, distance, dimension (wd:P2043 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): measured dimension of an object
7. area, also known as total area, surface area, surface, size, resolution (wd:P2046 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): area occupied by an object
8. width, also known as breadth, bus width, size (wd:P2049 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): width of an object, length
9. height of letters (wd:P12549 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): height of the letters of an inscription, height
10. entry height (wd:P13238 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): height of the entrance above ground level for boarding vehicles

No other items found

[Assistant]
The property `height` (P2048) seems to be the appropriate one for our purpose. Let's now construct a SPARQL query to retrieve the heights of Tony Blair and Tiger Woods using this property.

We will start with a simple query to check if we can get the heights for both individuals.

```sparql
SELECT ?person ?height
WHERE {
  VALUES ?person { wd:Q9545 wd:10993 }
  ?person wdt:P2048 ?height .
}
```

Let's execute this query.

[Tool]
Got 1 row and 2 columns:
| ?person               | ?height |
| --------------------- | ------- |
| Tony Blair (wd:Q9545) | 1.83    |

[Assistant]
The query returned the height of Tony Blair, but it did not return the height of Tiger Woods. This suggests that the height property (P2048) might not be directly linked to Tiger Woods in the knowledge graph. Let's try another approach to find the height of Tiger Woods.

We can use the `p:P2048` and `psv:P2048` properties to explore the qualifiers and values associated with the height property for Tiger Woods.

```sparql
SELECT ?person ?height
WHERE {
  VALUES ?person { wd:Q9545 wd:10993 }
  ?person p:P2048 ?statement .
  ?statement psv:P2048 ?valueNode .
  ?valueNode wikibase:quantityAmount ?height .
}
```

Let's execute this query to see if we can get the height of Tiger Woods.

[Tool]
Got 1 row and 2 columns:
| ?person               | ?height |
| --------------------- | ------- |
| Tony Blair (wd:Q9545) | 1.83    |

[Assistant]
It appears that the height of Tiger Woods is still not being retrieved. Let's try a different approach by looking at the properties and statements associated with Tiger Woods to see if there is another way to find his height.

We can list the triples for Tiger Woods to see if there are any other properties that might represent height.

```sparql
SELECT ?property ?object
WHERE {
  wd:10993 ?property ?object .
}
LIMIT 100
```

Let's execute this query to inspect the properties and objects associated with Tiger Woods.

[Tool] Got no rows and 2 columns

[Assistant]
It seems that the query did not return any results, which is unusual. Let's try a different approach by listing the triples for Tiger Woods using the `list` function to see if we can find any properties related to height.

```sparql
list(kg="wikidata", subject="wd:10993")
```

Let's execute this to get more information about Tiger Woods.

[Tool] Got no rows and 3 columns

[Assistant]
It appears that there are no triples associated with the entity `wd:10993` (Tiger Woods) in the knowledge graph, which is unexpected. This could be due to a variety of reasons, such as the entity not having any properties or the data being incomplete.

Given this, let's try searching for the height of Tiger Woods using a different approach. We can search for the property `height` specifically for Tiger Woods to see if there are any relevant statements.

```sparql
search(kg="wikidata", position="property", query="height", constraints={"subject": "wd:10993"})
```

Let's execute this search to see if we can find any height-related properties for Tiger Woods.

[Tool]
No property items found

No other items found

[Assistant]
It seems that there are no height-related properties directly associated with Tiger Woods in the knowledge graph. This suggests that the height information for Tiger Woods might not be available in the current dataset.

Since we cannot find the height of Tiger Woods, we can only provide the height of Tony Blair. However, we cannot answer the original question of whether Tony Blair is taller than Tiger Woods because we lack the necessary information for Tiger Woods.

Given this, I will provide the best attempt at a SPARQL query and explain why we could not find a satisfactory answer.

```sparql
SELECT ?person ?height
WHERE {
  VALUES ?person { wd:Q9545 wd:10993 }
  ?person wdt:P2048 ?height .
}
```

This query returns the height of Tony Blair but not Tiger Woods, indicating that the height of Tiger Woods is not available in the knowledge graph.

I will now call the `cancel` function to explain this situation.

[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 ?placeOfBirth ?placeOfBirthLabel WHERE {
  wd:Q26707663 wdt:P19 ?placeOfBirth .
  OPTIONAL {
    ?placeOfBirth rdfs:label ?placeOfBirthLabel .
    FILTER ( LANG( ?placeOfBirthLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| ?placeOfBirth         | ?placeOfBirthLabel |
| --------------------- | ------------------ |
| Buri Ram (wd:Q327510) | Buri Ram           |

Buri Ram, Thailand

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

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

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

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

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

[User] Where was K-pop star Lisa Manoban born?

[Assistant] To answer the question about where K-pop star Lisa Manoban was born, we need to identify the entity for Lisa Manoban and then find the property that indicates her place of birth. Let's start by searching for Lisa Manoban in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Lisa, also known as Pranpriya Manobal, Lisa Manobal, Lalisa Manoban, Lalisa Manobal (wd:Q26707663): Thai rapper, singer, model, dancer and actress (born 1997), singer-songwriter, fashion model, photo model, songwriter, dancer, rapper, singer, actor, model
2. Lisa, also known as Lalisa Manoban, Lisa Manobal, Pranpriya Manobal, Lalisa Manobal (wd:Q26707663): Thai rapper, singer, model, dancer and actress (born 1997), singer-songwriter, fashion model, photo model, songwriter, dancer, rapper, singer, actor, model
3. Lisa Ann, also known as Valeska, Lisa Ann Murphy, Nailin Palin, Lisa Ann Vision, Valeska Encina (wd:Q233259): American pornographic actress, pornographic actor, radio personality, film director, talent agent, film actor, stripper, actor
4. Apple Lisa, also known as Lisa, The Lisa (wd:Q371482): personal computer by Apple Inc.
5. LiSA, also known as Risa Oribe, Oribe Risa, Love is Same All (wd:Q333333): Japanese singer-songwriter (born 1987), composer, singer
6. Laser Interferometer Space Antenna, also known as eLISA, Evolved Laser Interferometer Space Antenna, LISA (wd:Q841982): third large mission of Cosmic Vision; gravitational-wave space observatory
7. Lisa, also known as Lisza (wd:Q3242363): commune in Brașov County, Romania
8. Lisa (wd:Q12724902): commune in Teleorman County, Romania
9. Lisa (wd:Q2726275): village in Moravica District, Serbia
10. Lisa, also known as Lisa (given name), Lisa (first name) (wd:Q1588186): female given name

No other items found

[Assistant] The search results show that the top two entries are the same entity, `wd:Q26707663`, which represents Lisa Manoban, the Thai rapper, singer, model, dancer, and actress. Now, let's find the property that indicates her place of birth. We can use the `list` function to look for triples where `wd:Q26707663` is the subject and the property is `wdt:P19` (place of birth).

[Tool]
Got 1 row and 3 columns:
| subject             | property                 | object                |
| ------------------- | ------------------------ | --------------------- |
| Lisa (wd:Q26707663) | place of birth (wdt:P19) | Buri Ram (wd:Q327510) |

[Assistant]
The list function returned a single triple indicating that Lisa Manoban was born in Buri Ram, which is represented by the IRI `wd:Q327510`. To confirm this and get the label of Buri Ram, we can construct a simple SPARQL query.

Let's execute the SPARQL query to get the place of birth of Lisa Manoban.

```sparql
SELECT ?placeOfBirth ?placeOfBirthLabel
WHERE {
  wd:Q26707663 wdt:P19 ?placeOfBirth .
  OPTIONAL { ?placeOfBirth rdfs:label ?placeOfBirthLabel . FILTER(LANG(?placeOfBirthLabel) = "en") }
}
```

This query will return the IRI of the place of birth and, if available, its English label.

[Tool]
Got 1 row and 2 columns:
| ?placeOfBirth         | ?placeOfBirthLabel |
| --------------------- | ------------------ |
| Buri Ram (wd:Q327510) | Buri Ram           |

[Assistant]
The SPARQL query confirms that Lisa Manoban was born in Buri Ram, Thailand. The IRI for Buri Ram is `wd:Q327510`.

Now, I will provide the final SPARQL query and the answer to the user's question.

```sparql
SELECT ?placeOfBirth ?placeOfBirthLabel
WHERE {
  wd:Q26707663 wdt:P19 ?placeOfBirth .
  OPTIONAL { ?placeOfBirth rdfs:label ?placeOfBirthLabel . FILTER(LANG(?placeOfBirthLabel) = "en") }
}
```

The answer to the question "Where was K-pop star Lisa Manoban born?" is Buri Ram, Thailand.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?character WHERE {
  ?character wdt:P451 wd:Q4205826 .
  ?character wdt:P451 wd:Q4463198 .
}

Geralt of Rivia

[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] among the characters in the witcher, who has two unmarried partners, Yennefer of Vengerberg and Triss Merigold?

[Assistant]
To answer this question, we need to identify the character in "The Witcher" who has two unmarried partners, specifically Yennefer of Vengerberg and Triss Merigold. Let's start by finding the IRIs for Yennefer of Vengerberg and Triss Merigold.

### Step 1: Find the IRIs for Yennefer of Vengerberg and Triss Merigold
We will use the `search` function to find the IRIs for these characters.

#### Search for Yennefer of Vengerberg

[Tool]
Top 10 entity alternatives:
1. Yennefer of Vengerberg, also known as Yenna, Yen (wd:Q4205826): fictional sorceress from the Witcher series, conspirator, magician, adviser
2. Vengerberg (wd:Q9368391)
3. Pseudotanais yenneferae (wd:Q107100133): species of crustacean

No other items found

[Assistant]
The IRI for Yennefer of Vengerberg is `wd:Q4205826`.

#### Search for Triss Merigold

Now, let's find the IRI for Triss Merigold.

[Tool]
Top 10 entity alternatives:
1. Triss Merigold, also known as Fourteenth of the Hill, Merigold the Fearless (wd:Q4463198): fictional sorceress from the Witcher series, magician, adviser, healer
2. Merigold, also known as Merigold (Mississippi), Merigold, Mississippi, Merigold, MS (wd:Q867528): town in Bolivar County, Mississippi, United States
3. Triss (wd:Q3204428): 2002 novel by Brian Jacques
4. Triss (wd:Q15113667): character in the Shannara, military personnel
5. Merigold (wd:Q37520933): family name
6. Trissino (wd:Q47238): Italian comune
7. Trissolcus (wd:Q14495753): genus of insects
8. Trissernis (wd:Q7844073): genus of insects
9. Trissodoris (wd:Q5226655): genus of insects
10. Trisselwand (wd:Q2454152): mountain in the Totes Gebirge in Styria

No other items found

[Assistant]
The IRI for Triss Merigold is `wd:Q4463198`.

### Step 2: Identify the Character with Two Unmarried Partners
Next, we need to find the character who has both Yennefer of Vengerberg and Triss Merigold as partners. We will use the `list` function to find relationships involving these characters.

#### List Relationships Involving Yennefer of Vengerberg

Let's list the relationships where Yennefer of Vengerberg is involved.

[Tool]
Got 226 rows and 3 columns, showing the first 10 rows below:
| subject                              | property                         | object                                                                                |
| ------------------------------------ | -------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------- |
| Yennefer of Vengerberg (wd:Q4205826) | instance of (wdt:P31)            | literary character (wd:Q3658341)                                                                                |
| Yennefer of Vengerberg (wd:Q4205826) | occupation (wdt:P106)            | magician (wd:Q148401)                                                                                |
| Yennefer of Vengerberg (wd:Q4205826) | sex or gender (wdt:P21)          | female (wd:Q6581072)                                                                                |
| Yennefer of Vengerberg (wd:Q4205826) | date of birth (p:P569)           | s:Q4205826-DC13BD81-D094-432B-AA79-B866665775F8                                                                                |
| Yennefer of Vengerberg (wd:Q4205826) | Commons category (wdt:P373)      | Yennefer of Vengerberg                                                                                |
| Yennefer of Vengerberg (wd:Q4205826) | image (wdt:P18)                  | <http://commons.wikimedia.org/wiki/Special:FilePath/Yennefer%20of%20Vengerberg%20cosplay%20%28The%20Witcher%203%20Wild%20Hunt%29.png> |
| Yennefer of Vengerberg (wd:Q4205826) | country of citizenship (wdt:P27) | Aedirn (wd:Q9141475)                                                                                |
| Yennefer of Vengerberg (wd:Q4205826) | place of birth (wdt:P19)         | Vengerberg (wd:Q9368391)                                                                                |
| Yennefer of Vengerberg (wd:Q4205826) | educated at (wdt:P69)            | Aretuza (wd:Q9159477)                                                                                |
| Yennefer of Vengerberg (wd:Q4205826) | creator (wdt:P170)               | Andrzej Sapkowski (wd:Q312101)                                                                                |
| ...                                  | ...                              | ...                                                                                |

[Assistant]
From the list of relationships involving Yennefer of Vengerberg, we don't see any direct relationships indicating her partners. We need to look for a property that might indicate romantic or partner relationships. Let's search for such properties.

#### Search for Properties Related to Romantic Partners

We will search for properties that might indicate romantic partners.

[Tool]
Top 10 property alternatives:
1. unmarried partner, also known as romantic partner, partner of, partners, posslq, relationship (wd:P451 as p/wdt): someone with whom the person is in a relationship without being married. Use "spouse" (P26) for married couples, significant person
2. relative, also known as relatives, grandparent, relation, non-binary parent, niece (wd:P1038 as p/wdt): family member (qualify with "kinship to subject", P1039; for direct family member please use specific property), significant person
3. occupation, also known as job, work, vocation, profession, employment (wd:P106 as p/wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
4. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as p/wdt): the object is a country that recognizes the subject as its citizen, country
5. performer, also known as actor, sung by, singer, recording by, recorded by (wd:P175 as p/wdt): actor, musician, band or other performer associated with this role or musical work, contributor to the creative work or subject
6. student, also known as teacher to, teacher of, had student, students, pupils (wd:P802 as p/wdt): notable student(s) of the subject individual, significant person
7. creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as p/wdt): maker of this creative work or other object (where no more specific property exists)
8. present in work, also known as is shown in, in work, in narrative, character in, from work (wd:P1441 as p/wdt): this (fictional or fictionalized) entity, place, or person appea...r works, P1343 for entities described in non-fictional accounts)
9. enemy, also known as opponent, rival, archvillain, archrival, archnemesis (wd:P7047 as p/wdt): opponent character or group of this fictive character or group, significant person
10. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)

No other items found

[Assistant]
The property `unmarried partner` (P451) seems to be the most relevant for indicating romantic partners. Let's use this property to find the character who has both Yennefer of Vengerberg and Triss Merigold as partners.

### Step 3: Find the Character with Both Yennefer of Vengerberg and Triss Merigold as Unmarried Partners

We will construct a SPARQL query to find the character who has both Yennefer of Vengerberg and Triss Merigold as unmarried partners.

[Tool]
Got 1 row and 1 column:
| ?character                    |
| ----------------------------- |
| Geralt of Rivia (wd:Q2492923) |

[Assistant]
The character who has both Yennefer of Vengerberg and Triss Merigold as unmarried partners is Geralt of Rivia.

### Final Answer

Here is the final SPARQL query and answer:

```sparql
SELECT ?character WHERE {
  ?character wdt:P451 wd:Q4205826 .
  ?character wdt:P451 wd:Q4463198 .
}
```

The character who has both Yennefer of Vengerberg and Triss Merigold as unmarried partners is **Geralt of Rivia**.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ( COUNT( DISTINCT ?mayor ) AS ?count ) WHERE {
  ?mayor wdt:P39 wd:Q30185 .
  ?mayor wdt:P131 wd:Q1055 .
  ?mayor wdt:P21 wd:Q658107 .
}

Got 1 row and 1 column:
| ?count |
| ------ |
| 0      |

[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] How many different female mayors did Hamburg have?

[Assistant]
To answer the question "How many different female mayors did Hamburg have?", we need to identify the relevant entities and properties in the knowledge graph:

1. **Hamburg**: The city for which we need to find the mayors.
2. **Mayor**: The position held by the individuals.
3. **Gender**: To filter out only female mayors.

Let's start by finding the entity for Hamburg and the property for mayor.

### Step 1: Find the entity for Hamburg
I will search for the entity representing Hamburg.

[Tool]
Top 10 entity alternatives:
1. Hamburg, also known as Free and Hanseatic City of Hamburg, Hamburg, Germany, Hamburg, Freie und Hansestadt (wd:Q1055): city and state in the North of Germany
2. Hamburger SV, also known as Hamburg SV, HSV, H.S.V., Hamburg Sport Club, HamburgerSV (wd:Q51974): German sports club based in Hamburg, with its largest branch being its football department
3. Hamburg, also known as Hamburg, IA, Hamburg, Iowa (wd:Q998718): city in Fremont County, Iowa, United States
4. Hamburg, also known as Hamburg, AR, Hamburg, Arkansas (wd:Q79657): city in Ashley County, Arkansas, United States
5. Hamburg, also known as Hamburg, Minnesota, Hamburg, MN (wd:Q1005682): city in Carver County, Minnesota, United States
6. Hamburg, also known as Hamburg, New Jersey, Hamburg, NJ (wd:Q1082931): borough in Sussex County, New Jersey, United States
7. Hamburg, also known as Hamburg, New York, Hamburg, NY (wd:Q742785): town in Erie County, New York, United States
8. Hamburg, also known as Hamburg, IL (wd:Q2672139): village in Calhoun County, Illinois, United States
9. Hamburg, also known as Hamburg, PA, Hamburg, Pennsylvania (wd:Q1181264): borough in Berks County, Pennsylvania, United States
10. Hamburg, also known as Hamburgh (wd:Q939795): breed of chicken developed in Germany and Holland prior to 1700

No other items found

[Assistant]
The correct entity for Hamburg, the city in Germany, is `wd:Q1055`.

### Step 2: Find the property for mayor
Next, I will search for the property that represents the position of mayor.

[Tool]
Top 10 property alternatives:
1. head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson
2. head of state, also known as leader, state headed by, monarch, president, queen (wd:P35 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): official with the highest formal authority in a country/state, director / manager, chairperson
3. rector, also known as chancellor, university president, Rector (academia), president (wd:P1075 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): senior official in an educational institution., director / manager, chairperson
4. chairperson, also known as dean, headed by, leader, president, chairwoman (wd:P488 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): presiding member of an organization, group or body, director / manager, significant person
5. successful candidate, also known as election winner, winning candidate, winner of election, election won by, elected (wd:P991 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): person(s) or political organization(s) elected after the election, candidate, winner
6. position holder, also known as incumbent, noble title holder, office holder, position held by (wd:P1308 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): persons who hold and/or held the position
7. position held, also known as function, held position, holds position, job, office held (wd:P39 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): subject currently or formerly holds the object position or public office
8. legislative body, also known as aboriginal council, Zila, Tehsil, rural council, representative body (wd:P194 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): legislative body governing this entity; political institution wi...ted representatives, such as a parliament/legislature or council
9. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): the object is a country that recognizes the subject as its citizen, country
10. elected in, also known as re-elected in, election (wd:P2715 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): election in which a person gained a position (as qualifier), or a position or legislative term is/was elected (as main value)

No other items found

[Assistant]
The property that represents the position of mayor is `wd:P39` (position held).

### Step 3: Identify the specific position of mayor for Hamburg
We need to find the specific position of mayor for Hamburg. We can do this by looking at the positions held by individuals in Hamburg and filtering for those that are mayors.

### Step 4: Find the gender property
We also need to filter the mayors by gender. Let's find the property for gender.

[Tool]
Top 10 property alternatives:
1. grammatical gender, also known as gender (wd:P5185 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): grammatical gender of the word
2. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)
3. requires grammatical feature, also known as grammatical feature required, required grammatical feature, requires case, requires mood, uses case (wd:P5713 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): grammatical features required or generally used with lexeme or form of lexeme
4. has grammatical gender, also known as grammatical genders, has genders (wd:P5109 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): specific form of noun class system of a language. Use qualifier ... subject of" (P805) to link to language specific item if present
5. personal pronoun, also known as gender pronoun, personal gender pronoun, personal pronouns, PGP, PGPs (wd:P6553 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): personal pronoun(s) this person goes by
6. semantic gender, also known as natural gender (wd:P10339 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): used when a word is only used to refer to people of this gender or to animals of this sex, independent of the grammatical gender
7. female form of label, also known as female form of label (string), female gender sense, feminine form of label (wd:P2521 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): female form of name or title (for male use P3321)
8. gender educated (wd:P7419 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): genders educated at this educational institution
9. male form of label, also known as male form of label (string), male gender sense, masculine form of label (wd:P3321 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): male form of name or title (for female use P2521)
10. given name version for other gender, also known as personal name version for other gender, other genders given name, male version of this female given name, gender inflection of given name, female version of this male given name (wd:P1560 as p/pqn/psv/prn/ps/pr/wdt/psn/wdtn/pq/pqv/prv): equivalent name (with respect to the meaning of the name) in the...n of a female first name. Add primarily the closest matching one

No other items found

[Assistant]
The property for gender is `wd:P21`.

### Step 5: Construct the SPARQL query
Now, we can construct the SPARQL query to find the number of different female mayors of Hamburg. We will use the `wd:Q1055` entity for Hamburg, the `wd:P39` property for position held, and the `wd:P21` property for gender.

Let's write the query and execute it.

[Tool]
Got 1 row and 1 column:
| ?count |
| ------ |
| 0      |

[Assistant]
The query returned a count of 0, which suggests that no female mayors were found for Hamburg. However, let's double-check the query to ensure it is correct and that we are not missing any details.

### Step 6: Verify the query
Let's break down the query to ensure it is correct:
- `wd:Q1055 p:P39 ?statement`: Find statements where Hamburg has a position held.
- `?statement ps:P39 ?mayor`: Extract the specific position held (the mayor).
- `?mayor wdt:P21 wd:Q658107`: Filter the mayors to only include females (`wd:Q658107` is the entity for female).

The query seems correct, but let's try a different approach to ensure we are not missing any data. We can list the mayors of Hamburg and then filter them by gender.

### Step 7: List the mayors of Hamburg
Let's list the mayors of Hamburg and then filter them by gender.

[Tool] Got no rows and 2 columns

[Assistant]
The query returned no rows, which suggests that there might be no data in Wikidata about the mayors of Hamburg, or the data might be structured differently than expected.

### Step 8: Check the structure of the data
Let's check the structure of the data for Hamburg to see if there are any other properties or statements that might represent the mayors.

### Step 9: List all positions held by Hamburg
Let's list all positions held by Hamburg to see if there are any other relevant properties or entities.

[Tool] Got no rows and 1 columns

[Assistant]
The query returned no rows, which suggests that there might be no direct statements about positions held by Hamburg in the way we are querying.

### Step 10: Check for alternative properties or entities
Let's try a different approach by searching for the specific position of mayor for Hamburg. We can look for the specific position of mayor and then find the individuals who held that position.

### Step 11: Search for the specific position of mayor for Hamburg
Let's search for the specific position of mayor for Hamburg.

[Tool]
No entity items found

No other items found

No literal items found

[Assistant]
The search for the specific position of mayor for Hamburg did not return any results. This suggests that the data might be structured differently or the specific position might not be directly linked to Hamburg in the way we are querying.

### Step 12: Check for alternative properties or entities
Let's try another approach by searching for the individuals who have held the position of mayor in Hamburg, regardless of the specific property used.

### Step 13: List individuals who have held the position of mayor in Hamburg
Let's list the individuals who have held the position of mayor in Hamburg and then filter them by gender.

[Tool] Got no rows and 2 columns

[Assistant]
The query returned no rows, which suggests that there might be no direct statements linking individuals to the position of mayor in Hamburg using the `wdt:P39` property.

### Step 14: Check for alternative properties or entities
Given that the direct approach is not yielding results, let's try a more general search for the position of mayor and then filter by the city of Hamburg.

### Step 15: Search for the position of mayor
Let's search for the specific position of mayor and then find the individuals who held that position in Hamburg.

[Tool]
Falling back to an unconstrained search on the full precomputed search indices:
Got more than the maximum supported number of object candidates (131,072)

Top 10 entity alternatives:
1. mayor, also known as Mayor (wd:Q30185): head of municipal government such as a town or city
2. burgomaster, also known as mayor, burgmeister, burgermeister, burgemeester (wd:Q177529): archaic term for a mayor (to be used with P39)
3. Mayor of Castile, also known as Mayor, Munia Mayor Sanchez, Muniadona of Castile, Mayor o Munia (wd:Q260831): Queen of Navarre
4. Jesus María, also known as Mayor (wd:Q731893): Colombian municipality of the department of Santander
5. The Mayor, also known as Mayor, Special Citizen (wd:Q27952232): 2017 South Korean film by Park In-je
6. city head, also known as town head, mayor, head of city, head of town (wd:Q4145633): position
7. Mayor (wd:Q6797626): family name
8. Mayor (wd:Q93478533): 2020 documentary film by David Osit
9. mayor, also known as mayor (Germany), mayor of a place in Germany (wd:Q17175157): mayor of a German town
10. Mayordomo mayor of the King of Spain, also known as Mayordomo mayor, Mayordomo mayor del Rey de España (wd:Q6797876): High Steward of the King of Spain

No other items found

No literal items found

[Assistant]
The search for the position of mayor returned several relevant results. The most relevant entity for the position of mayor is `wd:Q30185`.

### Step 16: Construct the SPARQL query using the specific position of mayor
Let's construct the SPARQL query to find the number of different female mayors of Hamburg using the specific position of mayor (`wd:Q30185`).

### Step 17: Execute the SPARQL query
Let's execute the query to find the number of different female mayors of Hamburg.

[Tool]
Got 1 row and 1 column:
| ?count |
| ------ |
| 0      |

[Assistant]
The query returned a count of 0, which suggests that no female mayors were found for Hamburg using the specific position of mayor (`wd:Q30185`).

### Conclusion
After multiple attempts and different approaches, it appears that there is no data in Wikidata indicating that Hamburg has had any female mayors. Given the thoroughness of our search and the structure of the data, it is reasonable to conclude that the answer to the question "How many different female mayors did Hamburg have?" is 0.

### Final Answer
The final answer to the question is 0.

Here is the final SPARQL query and answer:

```sparql
SELECT (COUNT(DISTINCT ?mayor) AS ?count)
WHERE {
  ?mayor wdt:P39 wd:Q30185 .
  ?mayor wdt:P131 wd:Q1055 .
  ?mayor wdt:P21 wd:Q658107 .
}
```

The answer is 0.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?birthDate WHERE {
  wd:Q43347 wdt:P569 ?birthDate
}

Rumi was born on September 30, 1207.

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

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

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

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

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

[User] When was Rumi born?

[Assistant] To answer the question "When was Rumi born?", we need to identify the entity representing Rumi and then find the property that indicates the date of birth. Let's start by searching for the entity representing Rumi in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Rumi, also known as Mawlana, Mawlana Rumi, Mawlawi, Jallal ed-Din Muhammad Balkhy, Jelaluddin Rumi (wd:Q43347): Sufi and Persian poet, philosopher, literary, writer, mystic, ʿālim, poet
2. Rum, also known as Arwām, Rūm, Rūmī (wd:Q3943294): autonym
3. Rūmī (wd:Q25908371): crater on planet Mercury
4. POGLUT1, also known as MDSRP, Rumi, protein O-glucosyltransferase 1, MDS010, LGMDR21 (wd:Q18042749): protein-coding gene in the species Homo sapiens
5. Lanmewko, also known as Rumi (wd:Q109342876): Taiwanese Virtual YouTuber, Twitch streamer, VTuber
6. Rumi Rumiyuq (wd:Q25104391): mountain in Bolivia
7. Rumi, also known as るみ (wd:Q97655647): Japanese female given name (るみ)
8. Rumi (wd:Q11241326): Japanese master of ceremonies, rapper
9. Rumi (wd:Q11578550): Japanese actress, actor
10. Rumi (wd:Q19949377)

No other items found

[Assistant] The top result for "Rumi" is the entity representing the Sufi and Persian poet, philosopher, and mystic (wd:Q43347). Now that we have identified the correct entity, let's find the property that indicates the date of birth. We can use the `list` function to explore the properties associated with this entity.

[Tool]
Got 1,195 rows and 3 columns, showing the first 10 rows below:
| subject          | property                                        | object                                                                               |
| ---------------- | ----------------------------------------------- | ------------------------------------------------------------------------------------ |
| Rumi (wd:Q43347) | instance of (wdt:P31)                           | human (wd:Q5)                                                                        |
| Rumi (wd:Q43347) | occupation (wdt:P106)                           | writer (wd:Q36180)                                                                   |
| Rumi (wd:Q43347) | sex or gender (wdt:P21)                         | male (wd:Q6581097)                                                                   |
| Rumi (wd:Q43347) | given name (wdt:P735)                           | Jalal (wd:Q23304462)                                                                 |
| Rumi (wd:Q43347) | date of birth (wdt:P569)                        | 1207-09-30T00:00:00Z                                                                 |
| Rumi (wd:Q43347) | Commons category (wdt:P373)                     | Rumi                                                                                |
| Rumi (wd:Q43347) | image (wdt:P18)                                 | <http://commons.wikimedia.org/wiki/Special:FilePath/Mevlana-celaleddin-i-rumi-1.jpg> |
| Rumi (wd:Q43347) | place of birth (wdt:P19)                        | Vakhsh (wd:Q2064329)                                                                 |
| Rumi (wd:Q43347) | date of death (wdt:P570)                        | 1273-12-17T00:00:00Z                                                                 |
| Rumi (wd:Q43347) | languages spoken, written or signed (wdt:P1412) | Arabic (wd:Q13955)                                                                   |
| ...              | ...                                             | ...                                                                                |

[Assistant]
From the list of properties associated with Rumi (wd:Q43347), we can see that the property `date of birth` (wdt:P569) is present and has a value of "1207-09-30T00:00:00Z". This indicates that Rumi was born on September 30, 1207.

Let's construct a SPARQL query to confirm this information and return the date of birth.

[Tool]
Got 1 row and 1 column:
| ?birthDate           |
| -------------------- |
| 1207-09-30T00:00:00Z |

[Assistant]
The SPARQL query confirms that Rumi was born on September 30, 1207.

Here is the final SPARQL query and the answer to the question:

```sparql
SELECT ?birthDate WHERE { wd:Q43347 wdt:P569 ?birthDate }
```

Rumi was born on September 30, 1207.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?deaths WHERE {
  wd:Q815436 wdt:P1120 ?deaths
}

Got 1 row and 1 column:
| ?deaths |
| ------- |
| 3532    |

[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] How many casualties were a result of the Troubles?

[Assistant] To answer the question about the number of casualties resulting from the Troubles, I need to identify the entity representing the Troubles and the property that indicates the number of casualties. Let's start by searching for the entity "Troubles" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. The Troubles, also known as Troubles, Northern Irish Troubles, Northern Ireland Troubles, Northern Ireland conflict, Conflict in Northern Ireland (wd:Q815436): 1960s–1990s conflict in Northern Ireland
2. Troubles (wd:Q4000425): novel by James Gordon Farrell
3. Troubles (wd:Q7846501): album by Steve Lacy
4. Troubles (wd:Q7846503): UK musical group
5. Troubles (wd:Q109812273): Movie directed by Érik Papatie
6. Troubles (wd:Q129262318): 2022 track by Denzel Curry
7. Troubles (wd:Q131565207): hardback edition (en)
8. Troubles (wd:Q42196874)
9. Troubles (wd:Q7846502): album by Troubles
10. troubles (wd:L1330100-S1)

No other items found

[Assistant] The top result for "Troubles" is the entity representing the conflict in Northern Ireland, which is `wd:Q815436`. Now, I need to find the property that indicates the number of casualties associated with this conflict. Let's list the properties of this entity to see if there is a relevant property.

[Tool]
Got 350 rows and 3 columns, showing the first 10 rows below:
| subject                   | property                                       | object                                                              |
| ------------------------- | ---------------------------------------------- | ------------------------------------------------------------------- |
| The Troubles (wd:Q815436) | instance of (wdt:P31)                          | ethnic conflict (wd:Q766875)                                        |
| The Troubles (wd:Q815436) | country (wdt:P17)                              | United Kingdom (wd:Q145)                                            |
| The Troubles (wd:Q815436) | Commons category (wdt:P373)                    | Northern Ireland Troubles                                           |
| The Troubles (wd:Q815436) | image (wdt:P18)                                | <http://commons.wikimedia.org/wiki/Special:FilePath/Dsc1877ne2.jpg> |
| The Troubles (wd:Q815436) | location (wdt:P276)                            | Northern Ireland (wd:Q26)                                           |
| The Troubles (wd:Q815436) | on focus list of Wikimedia project (wdt:P5008) | WikiProject Human Rights (wd:Q13382529)                             |
| The Troubles (wd:Q815436) | point in time (wdt:P585)                       | 1998-01-01T00:00:00Z                                                |
| The Troubles (wd:Q815436) | start time (wdt:P580)                          | 1960-01-01T00:00:00Z                                                |
| The Troubles (wd:Q815436) | topic's main category (wdt:P910)               | wd:Q8850177                                                         |
| The Troubles (wd:Q815436) | end time (wdt:P582)                            | 1998-01-01T00:00:00Z                                                |
| ...                       | ...                                            | ...                                                                 |

[Assistant]
From the list of properties, I don't see a direct property indicating the number of casualties. However, it's possible that the number of casualties is represented by a different property or is part of a more specific statement. Let's search for properties related to casualties or deaths to see if we can find a relevant property.

I will search for properties with the query "casualties" and "deaths" and constrain the search to the subject `wd:Q815436`.

[Tool]
Top 10 property alternatives:
1. number of deaths, also known as dead, qty fatalities, qty deaths, number of fatalities, fatalities (wd:P1120 as p/wdt): total (cumulative) number of people who died since start as a direct result of an event or cause
2. number of injured, also known as injured, injuries, injury toll, non-fatal injuries, number injured (wd:P1339 as p/wdt): number of people with non-fatal injuries in an event
3. point in time, also known as at time, as of, year, when, time of event (wd:P585 as p/wdt): date something took place, existed or a statement was true; for providing time use the "refine date" property (P4241)
4. end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as p/wdt): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time
5. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as p/wdt): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
6. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
7. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
8. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as p/wdt): main Wikimedia category
9. start time, also known as start date, since, valid, join time, joined (wd:P580 as p/wdt): time an entity begins to exist or a statement starts being valid, point in time

No other items found

[Assistant]
The search for properties related to "casualties" and "deaths" has returned `wd:P1120` (number of deaths) as a relevant property. Let's check if this property is used for the entity `wd:Q815436` (The Troubles).

I will execute a SPARQL query to retrieve the number of deaths associated with the Troubles.

[Tool]
Got 1 row and 1 column:
| ?deaths |
| ------- |
| 3532    |

[Assistant]
The SPARQL query has returned the number of deaths associated with the Troubles, which is 3,532.

Here is the final SPARQL query and the answer to the question:

```sparql
SELECT ?deaths WHERE {
  wd:Q815436 wdt:P1120 ?deaths
}
```

The number of casualties resulting from the Troubles is 3,532.

[Tool] Stopped generation process