PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?school WHERE {
  wd:Q4583 wdt:P69 ?school .
}

The 6th Montessori School Anne Frank (wd:Q19830060) is the school where Anne Frank went to school.

[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 did anne frank go to school?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
where was anne frank born?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q4583 wdt:P19 ?x .
}

Using entities:
Anne Frank, also known as Anne M. Frank, Anna Frank, Anne Maries Frank, Annelies Marie Frank, Anna M Frank (wd:Q4583): German-born Dutch Jewish diarist and Holocaust victim (1929–1945), diarist, writer

Using properties:
place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt): most specific known birth location of a person, animal or fictional character, location

Example 2:
Question:
where did anne frank live before the war?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q4583 p:P551 ?p .
  ?p ps:P551 ?x ; pq:P580 ?y ; pq:P582 ?z .
  wd:Q362 wdt:P580 ?w .
  FILTER ( ( ?y < ?w ) || ( ?z < ?w ) )
}

Using entities:
World War II, also known as 2nd World War, WWII, WW II, WW2, WW 2 (wd:Q362): 1939–1945 global conflict
Anne Frank, also known as Anne M. Frank, Anna Frank, Anne Maries Frank, Annelies Marie Frank, Anna M Frank (wd:Q4583): German-born Dutch Jewish diarist and Holocaust victim (1929–1945), diarist, writer

Using properties:
residence, also known as living in, place of residence, resided at, resided in, resident in (wd:P551 as ps/p): the place where the person is or has been, resident, location
start time, also known as start date, since, valid, join time, joined (wd:P580 as wdt/pq): time an entity begins to exist or a statement starts being valid, point in time
end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as pq): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time

Example 3:
Question:
where did helen keller go to school?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q38203 wdt:P69 ?x .
}

Using entities:
Helen Keller, also known as Helen Adams Keller (wd:Q38203): American author and activist (1880–1968), political activist, autobiographer, peace activist, trade unionist, suffragette, essayist, linguist, writer, orator

Using properties:
educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as wdt): educational institution attended by subject, affiliation

[Assistant] Based on the examples, we can see that the property "educated at" (P69) is used to indicate the schools someone attended. Let's use this property to find out where Anne Frank went to school.

[Tool]
Got 1 row and 1 column:
| school                                          |
| ----------------------------------------------- |
| 6th Montessori School Anne Frank (wd:Q19830060) |

[Assistant]
The SPARQL query returned the school where Anne Frank went to school. Now let's formulate the final answer.

The 6th Montessori School Anne Frank (wd:Q19830060) is the school where Anne Frank went to school.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?coordinates WHERE {
  wd:Q182139 wdt:P625 ?coordinates .
}

The Isthmus of Panama is located at approximately 9.000000 latitude and -79.000000 longitude.

[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 is isthmus of panama located on the map?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
where is isthmus of panama located?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q182139 wdt:P17 ?x .
}

Using entities:
Isthmus of Panama, also known as Istmo de Panama, Istmo de Panamá, Panama Isthmus (wd:Q182139): narrow landstrip in Panama

Using properties:
country, also known as sovereign state, state, land, host country (wd:P17 as wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity

Example 2:
Question:
where is the country of panama located?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q804 wdt:P30 ?x .
}

Using entities:
Panama, also known as pa, Republic of Panama (wd:Q804): sovereign state in Central America

Using properties:
continent (wd:P30 as wdt): continent of which the subject is a part, located in/on physical feature

Example 3:
Question:
where does the panama canal run through?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q7350 wdt:P131 ?x .
}

Using entities:
Panama Canal (wd:Q7350): large canal in Panama

Using properties:
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 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

[Assistant] From the examples, we can see that the Isthmus of Panama is represented by the entity `wd:Q182139`. We need to find the geographical coordinates of this entity to determine its location on the map. Let's search for the property that represents geographical coordinates.

[Tool]
Top 10 property alternatives:
1. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
2. this zoological name is coordinate with, also known as coordinate name (wd:P2743 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): links coordinate zoological names, different from
3. coordinates of depicted place, also known as depicted item geolocation, geolocation of object, object geolocation (wd:P9149 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): coordinates of the place depicted in the work (or Commons image)
4. coordinates of geographic center, also known as coordinates of geographic centre, geographic centre, geographic center, geographical midpoint, geographical centre (wd:P5140 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): coordinates of the center of an area. Use qualifier "determination method" (P459) to indicate how, coordinate location
5. time index, also known as time coordinate, timestamp, temporal coordinate, relative time (wd:P4895 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): indicate when something happens relative to its beginning
6. genomic start, also known as start coordinate, genomic from, Genloc From, from, Genloc Start (wd:P644 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): genomic starting coordinate of the biological sequence (e.g. a gene)
7. spatial reference system, also known as coordinate reference system, CRS, SRS (wd:P3037 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): frame of reference used to produce a map
8. coordinates of the point of view, also known as camera location, camera coordinates, viewpoint coordinates, coordinates of point of view, coordinates of pov (wd:P1259 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): point from which the scene depicted by the element is seen (element can be a photo, a painting, etc.)
9. occupant, also known as tenant, resident, renter, occupiers, lessee (wd:P466 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): person or organization occupying property, used by
10. named place on map, also known as name on map, place on map (wd:P9664 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): property linking a map to a place named on it

[Assistant] The property `coordinate location` (wd:P625) seems to be the correct one for finding the geographical coordinates of the Isthmus of Panama. Let's construct a SPARQL query to retrieve these coordinates.

[Tool]
Got 1 row and 1 column:
| coordinates                                 |
| ------------------------------------------- |
| POINT(-79.000000 9.000000) (geo:wktLiteral) |

[Assistant]
The coordinates of the Isthmus of Panama are approximately 9.000000 latitude and -79.000000 longitude. These coordinates can be used to locate the Isthmus of Panama on a map.

Now, let's finalize the SPARQL query and provide the answer.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?government WHERE {
  wd:Q183 wdt:P122 ?government .
}

Got 4 rows and 1 column:
| government                                   |
| -------------------------------------------- |
| parliamentary republic (wd:Q4198907)         |
| federation (wd:Q43702)                       |
| federal parliamentary republic (wd:Q5440547) |
| republic (wd:Q7270)                          |

The type of government in Germany now is a federal parliamentary republic.

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

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

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

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

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

[User] what type of government does germany have now?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
what form of government does germany use?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q183 wdt:P122 ?x .
}

Using entities:
Germany, also known as BR Deutschland, Bundesrepublik Deutschland, Deutschland, Federal Republic of Germany (wd:Q183): country in Central Europe

Using properties:
basic form of government, also known as form of government, government, type of government (wd:P122 as wdt): subject's government

Example 2:
Question:
what is the government structure of germany?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q183 wdt:P122 ?x .
}

Using entities:
Germany, also known as BR Deutschland, Bundesrepublik Deutschland, Deutschland, Federal Republic of Germany (wd:Q183): country in Central Europe

Using properties:
basic form of government, also known as form of government, government, type of government (wd:P122 as wdt): subject's government

Example 3:
Question:
what kind of government does spain have now?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q29 wdt:P122 ?x .
}

Using entities:
Spain, also known as Kingdom of Spain (wd:Q29): country in southwestern Europe with territories in Africa

Using properties:
basic form of government, also known as form of government, government, type of government (wd:P122 as wdt): subject's government

[Assistant]
From the examples, we can see that the property `wdt:P122` (form of government) is used to find the type of government for a country. We will use this property along with the entity for Germany (`wd:Q183`) to construct our SPARQL query.

Let's execute the SPARQL query to find the type of government for Germany.

[Tool]
Got 4 rows and 1 column:
| government                                   |
| -------------------------------------------- |
| parliamentary republic (wd:Q4198907)         |
| federation (wd:Q43702)                       |
| federal parliamentary republic (wd:Q5440547) |
| republic (wd:Q7270)                          |

[Assistant]
The results show multiple types of government for Germany, which can be combined to describe the current governmental system. To provide a clear and concise answer, we can combine these terms.

However, for the purpose of the SPARQL query, we will return the specific types of government directly. Here is the final SPARQL query and the answer:

```sparql
SELECT DISTINCT ?government WHERE {
  wd:Q183 wdt:P122 ?government .
}
```

The type of government in Germany now is a **federal parliamentary republic**.

Let's finalize this with the `answer` function.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?state WHERE {
  wd:Q1265 wdt:P131 + ?state .
  ?state wdt:P31 / wdt:P279 * wd:Q107390 .
}

Got 7 rows and 1 column:
| state                       |
| --------------------------- |
| Nevada (wd:Q1227)           |
| Colorado (wd:Q1261)         |
| Sonora (wd:Q46422)          |
| Baja California (wd:Q58731) |
| Arizona (wd:Q816)           |
| Utah (wd:Q829)              |
| California (wd:Q99)         |

The Colorado River runs through the following states: Nevada, Colorado, Arizona, Utah, California, Sonora (Mexico), and Baja California (Mexico).

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

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

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

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

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

[User] which states does the colorado river run through?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
which states does the connecticut river flow through?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q379648 wdt:P131 + ?x .
  ?x wdt:P31 / wdt:P279 * wd:Q107390 .
}

Using entities:
federated state, also known as state in a federation, state of a federation, state, federal state, constituent state (wd:Q107390): territorial and constitutional community forming part of a federal union
Connecticut River, also known as Connecticut River Estuary and Tidal River Wetlands Complex (wd:Q379648): river in the New England region of the United States

Using properties:
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 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
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 2:
Question:
what states does the connecticut river flow through?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q379648 wdt:P131 + ?x .
  ?x wdt:P31 / wdt:P279 * wd:Q107390 .
}

Using entities:
federated state, also known as state in a federation, state of a federation, state, federal state, constituent state (wd:Q107390): territorial and constitutional community forming part of a federal union
Connecticut River, also known as Connecticut River Estuary and Tidal River Wetlands Complex (wd:Q379648): river in the New England region of the United States

Using properties:
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 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
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 3:
Question:
which states does the mississippi river pass through?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q1497 wdt:P131 + ?x .
  ?x wdt:P31 / wdt:P279 * wd:Q107390 .
}

Using entities:
federated state, also known as state in a federation, state of a federation, state, federal state, constituent state (wd:Q107390): territorial and constitutional community forming part of a federal union
Mississippi River, also known as Mississippi, The Mississippi (wd:Q1497): primary river of the largest drainage basin in the United States

Using properties:
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 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
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

[Assistant]
Based on the examples, we can see that the SPARQL query to find the states a river runs through generally involves the following steps:

1. Identify the river entity.
2. Use the `wdt:P131` property to find the administrative territorial entities (states) the river is located in.
3. Filter these entities to ensure they are states (using `wdt:P31` and `wdt:P279`).

First, let's identify the Colorado River entity.

[Tool]
Top 10 entity alternatives:
1. Colorado River, also known as Rio de Buena Guia, Rio Colorado, Rio Colorado del Norte, Rio Colorado Del Norte, Rio Cosnina (wd:Q1265): major river in the western United States and Mexico
2. Colorado River (wd:Q270627): river in Argentina
3. Brazos River, also known as Los Brazos de Dios, Uhkto'wusi'yohe, Tokonohono, The River of the Arms of God, Rio Trinidad (wd:Q903306): river in Texas, United States
4. Colorado River (wd:Q847785): river in Texas, United States
5. Colorado River (wd:Q2984377): river in Costa Rica
6. Colorado River (wd:Q5148881): river in Bolivia
7. Colorado River (wd:Q5148884)
8. Colorado River, also known as Colorado River (Maipo) (wd:Q5148879): tributary of Maipo River in RM, Chile
9. Colorado river (wd:Q23649107): watercourse in Chile
10. Colorado River, also known as Rio Colorado (wd:Q5148883): river in Rondônia, Brazil

[Assistant]
The top result for "Colorado River" is `wd:Q1265`, which refers to the major river in the western United States and Mexico. We will use this entity in our SPARQL query.

Next, we need to find the states that the Colorado River runs through. We will use the `wdt:P131` property to find the administrative territorial entities (states) and filter them to ensure they are states using `wdt:P31` and `wdt:P279`.

Let's construct the SPARQL query:

```sparql
SELECT DISTINCT ?state WHERE {
  wd:Q1265 wdt:P131 + ?state .
  ?state wdt:P31 / wdt:P279 * wd:Q107390 .
}
```

This query will find the states where the Colorado River is located and ensure they are states.

Let's execute this query.

[Tool]
Got 7 rows and 1 column:
| state                       |
| --------------------------- |
| Nevada (wd:Q1227)           |
| Colorado (wd:Q1261)         |
| Sonora (wd:Q46422)          |
| Baja California (wd:Q58731) |
| Arizona (wd:Q816)           |
| Utah (wd:Q829)              |
| California (wd:Q99)         |

[Assistant]
The SPARQL query has returned the states through which the Colorado River runs. These states include:

- Nevada (wd:Q1227)
- Colorado (wd:Q1261)
- Sonora (wd:Q46422)
- Baja California (wd:Q58731)
- Arizona (wd:Q816)
- Utah (wd:Q829)
- California (wd:Q99)

Since the user asked for the states, and the results include both U.S. states and Mexican states, we can provide the answer as follows:

The Colorado River runs through the following states:
- Nevada
- Colorado
- Arizona
- Utah
- California
- Sonora (Mexico)
- Baja California (Mexico)

Let's finalize the answer with the SPARQL query and the list of states.

[Tool] Stopped generation process


PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?character WHERE {
  wd:Q5930 p:P725 ?p .
  ?p ps:P725 wd:Q37628 ; pq:P453 ?character .
}

Mila Kunis plays the character Meg Griffin in Family Guy.

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

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

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

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

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

[User] who does mila kunis play on family guy?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
what character does mila kunis play on family guy?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q5930 p:P725 ?p .
  ?p ps:P725 wd:Q37628 ; pq:P453 ?x .
}

Using entities:
Mila Kunis, also known as Milena Markivna Kunis, Milena Markovna (wd:Q37628): Ukrainian-American actress, television producer, television actor, child actor, voice actor, film actor, model, actor
Family Guy (wd:Q5930): American adult animated sitcom

Using properties:
character role, also known as role, plays, performer of, as, acting role (wd:P453 as pq): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)
voice actor, also known as voice actors, voice dubber, voice actress, voice actresses, voiced by (wd:P725 as ps/p): performer of a spoken role in a creative work such as animation,... (P453) as qualifier] [use "cast member" (P161) for live acting], film crew member, cast member

Example 2:
Question:
who plays lois in family guy?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q5930 p:P725 ?p .
  ?p ps:P725 ?x ; pq:P453 wd:Q853073 .
}

Using entities:
Family Guy (wd:Q5930): American adult animated sitcom
Lois Griffin, also known as Lois Pewterschmidt Griffin, Lois Pewterschmidt, Lois Patrice Pewterschmidt, Lois Patrice Griffin (wd:Q853073): fictional character from the Family Guy franchise, housewife

Using properties:
character role, also known as role, plays, performer of, as, acting role (wd:P453 as pq): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)
voice actor, also known as voice actors, voice dubber, voice actress, voice actresses, voiced by (wd:P725 as ps/p): performer of a spoken role in a creative work such as animation,... (P453) as qualifier] [use "cast member" (P161) for live acting], film crew member, cast member

Example 3:
Question:
who plays lois griffin in family guy?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q5930 p:P725 ?p .
  ?p ps:P725 ?x ; pq:P453 wd:Q853073 .
}

Using entities:
Family Guy (wd:Q5930): American adult animated sitcom
Lois Griffin, also known as Lois Pewterschmidt Griffin, Lois Pewterschmidt, Lois Patrice Pewterschmidt, Lois Patrice Griffin (wd:Q853073): fictional character from the Family Guy franchise, housewife

Using properties:
character role, also known as role, plays, performer of, as, acting role (wd:P453 as pq): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)
voice actor, also known as voice actors, voice dubber, voice actress, voice actresses, voiced by (wd:P725 as ps/p): performer of a spoken role in a creative work such as animation,... (P453) as qualifier] [use "cast member" (P161) for live acting], film crew member, cast member

[Assistant]
Based on the examples, we can see that the relevant entities and properties for our question are:

- **Entities**:
  - Mila Kunis (wd:Q37628)
  - Family Guy (wd:Q5930)

- **Properties**:
  - Voice actor (wd:P725)
  - Character role (wd:P453)

We need to find the character that Mila Kunis voices in Family Guy. Let's construct a SPARQL query to get this information.

[Tool]
Got 1 row and 1 column:
| character                |
| ------------------------ |
| Meg Griffin (wd:Q908772) |

[Assistant]
The SPARQL query has returned that Mila Kunis plays the character Meg Griffin in Family Guy.

Let's finalize the answer.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?placeOfDeath WHERE {
  wd:Q1203 wdt:P20 ?placeOfDeath .
}

Got 1 row and 1 column:
| placeOfDeath           |
| ---------------------- |
| New York City (wd:Q60) |

New York City (wd:Q60)

[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 do john lennon die?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
where was john lennon standing when he was shot?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q1203 wdt:P20 ?x .
}

Using entities:
John Lennon, also known as John Winston Ono Lennon, John Ono Lennon (wd:Q1203): British musician (1940–1980), political activist, singer-songwriter, recording artist, record producer, peace activist, public figure, film director, film producer, prose writer, film actor, guitarist, composer, painter, pianist, singer, writer, actor, poet

Using properties:
place of death, also known as POD, location of death, killed in, deathplace, died in (wd:P20 as wdt): most specific known (e.g. city instead of country, or hospital i... city) death location of a person, animal or fictional character, location

Example 2:
Question:
who shot j lennon?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q1203 wdt:P157 ?x .
}

Using entities:
John Lennon, also known as John Winston Ono Lennon, John Ono Lennon (wd:Q1203): British musician (1940–1980), political activist, singer-songwriter, recording artist, record producer, peace activist, public figure, film director, film producer, prose writer, film actor, guitarist, composer, painter, pianist, singer, writer, actor, poet

Using properties:
killed by, also known as slaughtered by, slain by, shot dead by, murderer, murdered by (wd:P157 as wdt): person or organization who killed the subject, significant person

Example 3:
Question:
where did reagan die?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q9960 wdt:P20 ?x .
}

Using entities:
Ronald Reagan, also known as Ronald W Reagan, Ronald W. Reagan, R. W. Reagan, President Reagan, President Ronald Reagan (wd:Q9960): president of the United States from 1981 to 1989 and actor, television actor, military officer, character actor, game show host, autobiographer, anti-communist, trade unionist, art collector, statesperson, screenwriter, voice actor, film actor, politician, announcer, lifeguard, diarist, actor

Using properties:
place of death, also known as POD, location of death, killed in, deathplace, died in (wd:P20 as wdt): most specific known (e.g. city instead of country, or hospital i... city) death location of a person, animal or fictional character, location

[Assistant] From the examples, we can see that the property `wdt:P20` (place of death) is used to find where a person died. Let's confirm this by searching for the property.

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

[Assistant] The property `wdt:P20` (place of death) is indeed the correct property to use. Now let's search for John Lennon's entity to construct our query.

[Tool]
Top 10 entity alternatives:
1. John Lennon, also known as John Winston Ono Lennon, John Ono Lennon (wd:Q1203): British musician (1940–1980), political activist, singer-songwriter, recording artist, record producer, peace activist, public figure, film director, film producer, prose writer, film actor, guitarist, composer, painter, pianist, singer, writer, actor, poet
2. Liverpool John Lennon Airport, also known as John Lennon, John Lennon airport, Liverpool Airport, Liverpool (John Lennon), LPL (wd:Q8727): airport in Liverpool, England
3. John Lennon Silva Santos, also known as John Lennon (wd:Q6244563): association football player, Brazilian footballer
4. John Brown Lennon, also known as John B. Lennon, John Lennon (wd:Q6223555): American labor leader (1850–1923), trade unionist
5. John Lennon, also known as J. John Lennon, Justin John Lennon (wd:Q11979004): Scottish tourism researcher, university teacher, tourism scholar
6. John Lennon (wd:Q65548791): Irish hurler born 1996
7. John Lennon (wd:Q6244553): British naval captain, military personnel
8. John Lennon (wd:Q12871620): 1855 - 3 Aug 1921
9. John Lennon (wd:Q125643070): 2005 edition of written work by Jordi Sierra i Fabra
10. John Lennon (wd:Q106781630): 2015 song by SCH

[Assistant]
The correct entity for John Lennon is `wd:Q1203`. Now we can construct a SPARQL query to find the place of his death using the property `wdt:P20`.

Let's execute the query.

[Tool]
Got 1 row and 1 column:
| placeOfDeath           |
| ---------------------- |
| New York City (wd:Q60) |

[Assistant]
The place where John Lennon died is New York City.

Here is the final SPARQL query and answer:

```sparql
SELECT ?placeOfDeath WHERE {
  wd:Q1203 wdt:P20 ?placeOfDeath .
}
```

Answer: New York City (wd:Q60)

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?team WHERE {
  wd:Q221048 wdt:P54 ?team .
}

Jackie Robinson played for the Los Angeles Dodgers.

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

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

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

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

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

[User] what baseball team was jackie robinson on?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
what years did jackie robinson play baseball?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q221048 wdt:P2031 | wdt:P2032 ?x .
}

Using entities:
Jackie Robinson, also known as Jack Roosevelt "Jackie" Robinson (wd:Q221048): American baseball player, athletics competitor, military officer, basketball coach, baseball player, vice president

Using properties:
work period (start), also known as start working, flourished (start), start time for work, start date of activity, fl. (start) (wd:P2031 as wdt): start of period during which a person or group flourished (fl. = "floruit") in their professional activity, start time, floruit
work period (end), also known as floruit end, floruit (end of work), flourished (end), retirement, work ends (wd:P2032 as wdt): end of period during which a person or group flourished (fl. = "floruit") in their professional activity, end time, floruit

Example 2:
Question:
where did jackie robinson go to school?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q221048 wdt:P69 ?x .
}

Using entities:
Jackie Robinson, also known as Jack Roosevelt "Jackie" Robinson (wd:Q221048): American baseball player, athletics competitor, military officer, basketball coach, baseball player, vice president

Using properties:
educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as wdt): educational institution attended by subject, affiliation

Example 3:
Question:
what team did albert pujols play for?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q148726 wdt:P54 ?x .
}

Using entities:
Albert Pujols, also known as Jose Alberto Pujols Alcantara, José Alberto Pujols Alcántara, Alberto Pujols Alcántara, Alberto Pujols Alcantara, Alberto Alcántara (wd:Q148726): Dominican-American baseball player, baseball player

Using properties:
member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as wdt): sports teams or clubs that the subject represents or represented, member of

[Assistant] From the examples, we can see that the property `member of sports team` (P54) is used to indicate the team a player belongs to. We will use this property to find out what baseball team Jackie Robinson was on.

[Tool]
Got 1 row and 1 column:
| team                             |
| -------------------------------- |
| Los Angeles Dodgers (wd:Q334634) |

[Assistant]
The SPARQL query has returned the team that Jackie Robinson played for, which is the Los Angeles Dodgers.

Now, let's provide the final answer.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?party WHERE {
  wd:Q91 wdt:P102 ?party .
}

Got 3 rows and 1 column:
| party                            |
| -------------------------------- |
| Republican Party (wd:Q29468)     |
| Whig Party (wd:Q42183)           |
| National Union Party (wd:Q80719) |

Abraham Lincoln was a member of the Republican Party, the Whig Party, and the National Union Party.

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

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

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

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

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

[User] what party was abe lincoln part of?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
which party was lincoln?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q91 wdt:P102 ?x .
}

Using entities:
Abraham Lincoln, also known as President Lincoln, Uncle Abe, Honest Abe, Abe Lincoln (wd:Q91): president of the United States from 1861 to 1865, military officer, statesperson, postmaster, politician, farmer, writer, lawyer

Using properties:
member of political party, also known as political party member, political party, party membership, party, member of party (wd:P102 as wdt): the political party of which a person is or has been a member or otherwise affiliated, member of

Example 2:
Question:
what political party was lincoln?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q91 wdt:P102 ?x .
}

Using entities:
Abraham Lincoln, also known as President Lincoln, Uncle Abe, Honest Abe, Abe Lincoln (wd:Q91): president of the United States from 1861 to 1865, military officer, statesperson, postmaster, politician, farmer, writer, lawyer

Using properties:
member of political party, also known as political party member, political party, party membership, party, member of party (wd:P102 as wdt): the political party of which a person is or has been a member or otherwise affiliated, member of

Example 3:
Question:
what party was lincoln affiliated with?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q91 wdt:P102 ?x .
}

Using entities:
Abraham Lincoln, also known as President Lincoln, Uncle Abe, Honest Abe, Abe Lincoln (wd:Q91): president of the United States from 1861 to 1865, military officer, statesperson, postmaster, politician, farmer, writer, lawyer

Using properties:
member of political party, also known as political party member, political party, party membership, party, member of party (wd:P102 as wdt): the political party of which a person is or has been a member or otherwise affiliated, member of

[Assistant] Based on the examples, we can see that the property `wdt:P102` is used to represent the political party affiliation of a person. Let's confirm the entity for Abraham Lincoln.

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

[Assistant]
The correct entity for Abraham Lincoln is `wd:Q91`. Now let's use the property `wdt:P102` to find out what political party he was a member of.

I will now construct and execute the SPARQL query.

[Tool]
Got 3 rows and 1 column:
| party                            |
| -------------------------------- |
| Republican Party (wd:Q29468)     |
| Whig Party (wd:Q42183)           |
| National Union Party (wd:Q80719) |

[Assistant]
Abraham Lincoln was a member of multiple parties during his lifetime, including the Republican Party, the Whig Party, and the National Union Party.

To provide a concise answer, I will format the response to list these parties clearly.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?productOrService WHERE {
  wd:Q95 wdt:P1056 ?productOrService .
  FILTER ( ?productOrService != wd:Q4182287 ) FILTER ( ?productOrService != wd:Q111897729 )
}

Got 6 rows and 1 column:
| productOrService          |
| ------------------------- |
| Google Maps (wd:Q12013)   |
| Google Pay (wd:Q19834616) |
| Google Ads (wd:Q271982)   |
| Google Voice (wd:Q51712)  |
| Gmail (wd:Q9334)          |
| Google Search (wd:Q9366)  |

Google offers the following products and services: Google Maps, Google Pay, Google Ads, Google Voice, Gmail, and Google Search.

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

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

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

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

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

[User] what products and\/or services does google offer customers?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
what all does google have?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q95 wdt:P1830 ?x .
}

Using entities:
Google, also known as Big G, google.com, Google Inc., Google LLC, Google, Inc. (wd:Q95): American multinational technology company, a subsidiary of Alphabet Inc.

Using properties:
owner of, also known as owns, owns property, shareholder of (wd:P1830 as wdt): entities owned by the subject

Example 2:
Question:
who started google?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q9366 wdt:P112 ?x .
}

Using entities:
Google Search, also known as BackRub, goo.gle, Google, google.com, Google homepage (wd:Q9366): search engine by Google LLC

Using properties:
founded by, also known as starter, co-founded by, started by, institutor, instituted by (wd:P112 as wdt): founder or co-founder of this organization, religion, place or entity, creator

Example 3:
Question:
where are google headquarters located?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q694178 wdt:P131 ?x .
}

Using entities:
Googleplex (wd:Q694178): building complex in California, United States

Using properties:
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 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

[Assistant] Based on the examples, it seems like we need to look at the entity for Google and then find the properties that relate to the products and services it offers. Let's first identify the correct entity for Google.

[Tool]
Top 10 entity alternatives:
1. Google, also known as google.com, Google LLC, Google, Inc., Google Inc., Big G (wd:Q95): American multinational technology company, a subsidiary of Alphabet Inc.
2. Google, also known as Big G, google.com, Google Inc., Google LLC, Google, Inc. (wd:Q95): American multinational technology company, a subsidiary of Alphabet Inc.
3. Google Search, also known as BackRub, goo.gle, Google, google.com, Google homepage (wd:Q9366): search engine by Google LLC
4. Alphabet Inc., also known as Alphabet, Alphabet company, Alphabet Inc, Alphabet, Inc, Alphabet, Inc. (wd:Q20800404): American multinational technology conglomerate
5. Google+, also known as G+, Google Plus (wd:Q356): social networking service
6. .google, also known as dot google (wd:Q20573262): top-level Internet domain
7. google, also known as to google, googling (wd:Q1156923): transitive verb, meaning to search for something using the Google search engine
8. Google Google (wd:Q123412777): Tamil song from Thuppakki movie
9. Archaeology & Language, also known as Google (wd:Q23301814): 1998 Pimlico edition
10. Google Canada, also known as Google, Google Kitchener-Waterloo, Google Waterloo (wd:Q30338099)

[Assistant]
The correct entity for Google is `wd:Q95`. Now let's find the properties that relate to the products and services offered by Google. We can use the `P1830` property (owner of) as seen in Example 1, but we should also explore other relevant properties.

Let's list the properties of `wd:Q95` to see what might be relevant.

[Tool]
Got 2,096 rows and 3 columns, showing the first 10 rows below:
| subject         | property                        | object                                                                                |
| --------------- | ------------------------------- | ---------------------------------------------------------------------------------------- |
| Google (wd:Q95) | instance of (wdt:P31)           | business (wd:Q4830453)                                                                   |
| Google (wd:Q95) | country (wdt:P17)               | United States (wd:Q30)                                                                   |
| Google (wd:Q95) | Commons category (wdt:P373)     | Google                                                                                |
| Google (wd:Q95) | image (wdt:P18)                 | <http://commons.wikimedia.org/wiki/Special:FilePath/Googleplex%20HQ%20%28cropped%29.jpg> |
| Google (wd:Q95) | part of (wdt:P361)              | Alphabet Inc. (wd:Q20800404)                                                             |
| Google (wd:Q95) | inception (wdt:P571)            | 1998-09-04T00:00:00Z (xsd:dateTime)                                                      |
| Google (wd:Q95) | described at URL (wdt:P973)     | <https://about.google/>                                                                  |
| Google (wd:Q95) | short name (wdt:P1813)          | Google (en)                                                                              |
| Google (wd:Q95) | described by source (wdt:P1343) | Lentapedia (wd:Q17290934)                                                                |
| Google (wd:Q95) | official name (wdt:P1448)       | Google LLC (en)                                                                          |
| ...             | ...                             | ...                                                                                |

[Assistant]
From the list of properties, we don't see any direct properties that indicate the products and services offered by Google. However, we can try searching for properties related to "products" or "services" specifically for the Google entity.

Let's use the `search_property_of_entity` function to find properties related to products and services for Google.

[Tool]
Top 10 property alternatives:
1. product, material, or service produced or provided, also known as products, product or service provided, product, material, or service produced or provided, product, output (wd:P1056 as wdt/p): material or product produced or sold by an organization, industry, facility, or process, material or product produced by an organization, industry, facility, or process, immediate cause of
2. official shop URL, also known as online store, shop, shop URL, store, store URL (wd:P10225 as wdt/p): official URL where the agent sells products/merchandise, official website
3. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
4. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as wdt/p): main Wikimedia category
5. parent organization, also known as parent company, parent institution, parent organisation, parent unit, part of (wd:P749 as wdt/p): parent organization of an organization, opposite of subsidiaries (P355), owned by, part of
6. uses, also known as uses trope, used, using, wielded, wields (wd:P2283 as wdt/p): item or concept used by the subject or in the operation (see also instrument [P1303] and armament [P520])
7. industry, also known as branch, economic branch, field of action, field of exercise, sector (wd:P452 as wdt/p): specific industry of company or organization, part of
8. operating area, also known as province served, serves jurisdiction, serves geographic region, serves geographic area, serves area (wd:P2541 as wdt/p): geographic area or jurisdiction an organisation or industry operates in, serves, or has responsibility for, location
9. partnership with, also known as works with, collaborates with, collaboration with (wd:P2652 as wdt/p): partnership (commercial or/and non-commercial) between this organization and another organization or institution
10. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as wdt/p): work where this item is described, attested in

No other items found

[Assistant]
The property `P1056` (product, material, or service produced or provided) seems to be the most relevant for finding the products and services offered by Google. Let's use this property in a SPARQL query to find the products and services of Google.

Here is the initial SPARQL query:

```sparql
SELECT ?productOrService WHERE {
  wd:Q95 wdt:P1056 ?productOrService .
}
```

Let's execute this query to see the results.

[Tool]
Got 8 rows and 1 column:
| productOrService               |
| ------------------------------ |
| Software tools (wd:Q111897729) |
| Google Maps (wd:Q12013)        |
| Google Pay (wd:Q19834616)      |
| Google Ads (wd:Q271982)        |
| search engine (wd:Q4182287)    |
| Google Voice (wd:Q51712)       |
| Gmail (wd:Q9334)               |
| Google Search (wd:Q9366)       |

[Assistant]
The initial query has returned a list of products and services offered by Google. However, some of these results are quite general (like "Software tools" and "search engine"). To get more specific and detailed results, we can try to filter out these general terms and focus on specific products and services.

Let's refine the query to exclude general terms and focus on specific products and services. We can do this by adding a filter to exclude certain general terms.

Here is the refined SPARQL query:

```sparql
SELECT ?productOrService WHERE {
  wd:Q95 wdt:P1056 ?productOrService .
  FILTER NOT EXISTS {
    ?productOrService wdt:P31 wd:Q4182287 .  # Exclude "search engine"
  }
  FILTER NOT EXISTS {
    ?productOrService wdt:P31 wd:Q111897729 .  # Exclude "Software tools"
  }
}
```

Let's execute this refined query to see the results.

[Tool]
Got 7 rows and 1 column:
| productOrService               |
| ------------------------------ |
| Software tools (wd:Q111897729) |
| Google Maps (wd:Q12013)        |
| Google Pay (wd:Q19834616)      |
| Google Ads (wd:Q271982)        |
| search engine (wd:Q4182287)    |
| Google Voice (wd:Q51712)       |
| Gmail (wd:Q9334)               |

[Assistant]
It seems that the filters did not work as expected, and the general terms are still included in the results. Let's try a different approach by explicitly excluding the general terms using their IRIs.

Here is the revised SPARQL query:

```sparql
SELECT ?productOrService WHERE {
  wd:Q95 wdt:P1056 ?productOrService .
  FILTER (?productOrService != wd:Q4182287)  # Exclude "search engine"
  FILTER (?productOrService != wd:Q111897729)  # Exclude "Software tools"
}
```

Let's execute this revised query to see the results.

[Tool]
Got 6 rows and 1 column:
| productOrService          |
| ------------------------- |
| Google Maps (wd:Q12013)   |
| Google Pay (wd:Q19834616) |
| Google Ads (wd:Q271982)   |
| Google Voice (wd:Q51712)  |
| Gmail (wd:Q9334)          |
| Google Search (wd:Q9366)  |

[Assistant]
The revised query has successfully excluded the general terms and returned a list of specific products and services offered by Google. Here are the results:

- Google Maps (wd:Q12013)
- Google Pay (wd:Q19834616)
- Google Ads (wd:Q271982)
- Google Voice (wd:Q51712)
- Gmail (wd:Q9334)
- Google Search (wd:Q9366)

These are the specific products and services that Google offers to its customers.

Let's provide the final answer using the `answer` function.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?team WHERE {
  wd:Q1374361 wdt:P54 ?team .
}

Tom Landry played for the New York Giants and the Texas Longhorns football team.

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

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

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

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

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

[User] who did tom landry play for?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
who did mike tomlin play for?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q371118 wdt:P54 ?x .
}

Using entities:
Mike Tomlin, also known as Michael Tomlin, Michael Pettaway Tomlin (wd:Q371118): American football coach (born 1972), American football coach, head coach

Using properties:
member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as wdt): sports teams or clubs that the subject represents or represented, member of

Example 2:
Question:
who has tom brady played for?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q313381 wdt:P54 ?x .
}

Using entities:
Tom Brady, also known as Thomas Edward Patrick Brady, Jr., Thomas Edward Brady, Jr., Thomas Edward Patrick Brady Jr., Thomas Edward Patrick Brady, Thomas Brady (wd:Q313381): American football player (born 1977), American football player

Using properties:
member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as wdt): sports teams or clubs that the subject represents or represented, member of

Example 3:
Question:
who did tyson chandler play for?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q297146 wdt:P54 ?x .
}

Using entities:
Tyson Chandler, also known as Tyson Cleotis Chandler (wd:Q297146): American basketball player, basketball player

Using properties:
member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as wdt): sports teams or clubs that the subject represents or represented, member of

[Assistant] Based on these examples, it seems like we need to find the entity for Tom Landry and then use the `P54` property to find out which team he played for. Let's first search for Tom Landry.

[Tool]
Top 10 entity alternatives:
1. Tom Landry, also known as Thomas Wade Landry (wd:Q1374361): American football coach and player (1924–2000), American football player, American football coach, aircraft pilot
2. Tom Landry (wd:Q108629583): statue in Arlington, United States of America - Robert Summers - 2001
3. Landry Tomb (wd:Q4856268): historic place
4. Tom Landry Strategy Football (wd:Q108536207)
5. Landry, Tom (1924-2000), football coach (wd:Q103866595): encyclopedia article
6. 75th US Colored Infantry: Landry, Tom (wd:Q107830161): file unit in the National Archives and Records Administration's holdings (NAID 170728667)
7. 84th US Colored Infantry: Landry, Tom (wd:Q107699626): file unit in the National Archives and Records Administration's holdings (NAID 107157520)
8. A personal tribute to Tom Landry (wd:Q93705732)
9. Art Garfunkel, also known as Arthur Ira Garfunkel, Arthur Ira "Art" Garfunkel, Tom, Arthur Garfunkel (wd:Q4039): American singer (born 1941), singer-songwriter, television actor, street artist, songwriter, teacher, singer, actor, poet
10. Tom, also known as Tom River (wd:Q216188): river in Khakassia, Kemerovo Oblast, and Tomsk Oblast, Russia

[Assistant]
The correct entity for Tom Landry is `wd:Q1374361`. Now let's use the `P54` property to find out which team he played for.

I will now construct and execute the SPARQL query.

[Tool]
Got 2 rows and 1 column:
| team                                   |
| -------------------------------------- |
| New York Giants (wd:Q190618)           |
| Texas Longhorns football (wd:Q7707821) |

[Assistant]
The SPARQL query returned two teams that Tom Landry played for: the New York Giants and the Texas Longhorns football team.

To provide a clear and concise answer, I will format the response accordingly.

[Tool] Stopped generation process