PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?location ?locationLabel WHERE {
  wd:Q214524 wdt:P276 ?location .
  OPTIONAL {
    ?location rdfs:label ?locationLabel .
    FILTER ( LANG( ?locationLabel ) = 'en' )
  }
}

Got 1 row and 2 columns:
| location                | locationLabel   |
| ----------------------- | --------------- |
| Gettysburg (wd:Q694550) | Gettysburg (en) |

The Gettysburg Address took place in Gettysburg.

[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 the gettysburg address?

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

[Tool]
Example 1:
Question:
where was the gettysburg war located?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q33132 wdt:P276 ?x .
}

Using entities:
Battle of Gettysburg (wd:Q33132): 1863 battle of the American Civil War

Using properties:
location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as wdt): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object

Example 2:
Question:
where did chancellorsville battle take place?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q745979 wdt:P276 ?x .
}

Using entities:
Battle of Chancellorsville (wd:Q745979): 1863 major battle of the American Civil War

Using properties:
location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as wdt): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object

Example 3:
Question:
in what state did the bloody battle of antietam take place?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q719252 wdt:P276 ?p .
  ?p wdt:P131 + ?x .
  ?x wdt:P31 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
Battle of Antietam, also known as Battle of Sharpsburg (wd:Q719252): 1862 major battle of the American Civil War

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
location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as wdt): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
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 these examples, it seems like we need to find the location where the Gettysburg Address took place. Let's first search for the entity "Gettysburg Address".

[Tool]
Top 10 entity alternatives:
1. Gettysburg Address (wd:Q214524): speech by U.S. President Abraham Lincoln
2. Gettysburg Address (wd:Q19046068): version of the text inscribed on the walls at the Lincoln Memorial in Washington, D.C.
3. The Gettysburg Address, also known as Gettysburg Address (wd:Q17097518): 2017 film directed by Sean Conant
4. A Gettysburg Address (wd:Q4656986): episode of Homeland (S2 E6)
5. Address at Gettysburg, also known as The Gettysburg Address (wd:Q56524787): version of Lincoln's speech, 1898 publication
6. Lincoln's Gettysburg Address (wd:Q3832569): 1912 short film
7. The Gettysburg Address (wd:Q14752119): live album by Moon Safari
8. Lincoln's Gettysburg Address (wd:Q76440716): print in the National Gallery of Art (NGA 144034)
9. Lincoln's Gettysburg Address (wd:Q100307054): newspaper published in New York, New York
10. The Gettysburg Address (wd:Q87280588): episode of In Our Time

[Assistant]
The top result is the correct one, "Gettysburg Address" (wd:Q214524). Now let's find the location where this speech took place. We can use the property `location` (P276) as seen in the examples.

Let's construct a simple SPARQL query to find the location of the Gettysburg Address.

[Tool]
Got 1 row and 1 column:
| location                |
| ----------------------- |
| Gettysburg (wd:Q694550) |

[Assistant]
The location where the Gettysburg Address took place is Gettysburg (wd:Q694550).

To provide a more complete answer, let's also include the label of the location in the query.

[Tool]
Got 1 row and 2 columns:
| location                | locationLabel   |
| ----------------------- | --------------- |
| Gettysburg (wd:Q694550) | Gettysburg (en) |

[Assistant]
The Gettysburg Address took place in Gettysburg (wd:Q694550).

Now, 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 DISTINCT ?x WHERE {
  wd:Q5702260 wdt:P106 ?x .
}

Helen Flanagan is a film actor, actor, and model.

[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 does helen flanagan do?

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

[Tool]
Example 1:
Question:
what did florence sabin do?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q449487 wdt:P106 ?x .
}

Using entities:
Florence R. Sabin, also known as Florence Rena Sabin, Florence Sabin (wd:Q449487): American medical scientist (1871–1953), university teacher, physician, scientist, anatomist

Using properties:
occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)

Example 2:
Question:
what does annie leibovitz do?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q225283 wdt:P106 ?x .
}

Using entities:
Annie Leibovitz, also known as Anna-Lou Leibovitz (wd:Q225283): American photographer (born 1949), fashion photographer, film director, photographer

Using properties:
occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)

[Assistant] Based on the examples, we need to find Helen Flanagan's entity ID first.

[Tool]
Top 10 entity alternatives:
1. Helen Flanagan (wd:Q5702260): English actress, film actor, model, actor
2. Helen Anna Flanagan (wd:Q108477380): performance artist, visual artist, video artist, artist
3. Helen of Troy, also known as Helen, Helen of Argos, Helen of Sparta (wd:Q164061): daughter of Zeus in Greek mythology
4. Helen, also known as Helen, GA, Helen, Georgia (wd:Q1601823): city in White County, Georgia, United States
5. Helen, also known as Helen Khan, Helen Richardson Khan, Helen Jairag Richardson, Helen Ann Richardson Khan (wd:Q467223): Indian film actress and dancer of Anglo-Burmese descent, television actor, film actor, dancer
6. Flanagan, also known as Flanagan, Illinois (wd:Q1929330): human settlement in Illinois, United States of America
7. Helen, also known as Eur. Hel. (wd:Q1248812): ancient Greek tragedy by Euripides
8. Nakajima Ki-49 Donryu, also known as Helen bomber, Type 100 Heavy Bomber, Storm Dragon, Ki49, Ki-49 (wd:Q1393091): Japanese bomber aircraft
9. Helen, also known as Helen, West Virginia, Helen, WV (wd:Q511980): census designated place in Raleigh County, West Virginia, United States
10. Helen, also known as Helen (first name), Helen (given name) (wd:Q13376892): female given name

[Assistant] From the search results, it seems that the correct entity for Helen Flanagan is wd:Q5702260. Now let's check her occupations using the property P106 (occupation).

[Tool]
Got 3 rows and 1 column:
| x                         |
| ------------------------- |
| film actor (wd:Q10800557) |
| actor (wd:Q33999)         |
| model (wd:Q4610556)       |

[Assistant] Helen Flanagan is a film actor, actor, and model. Let's provide this information in the final answer.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX p: <http://www.wikidata.org/prop/>
SELECT DISTINCT ?senator WHERE {
  ?senator p:P39 ?positionStatement .
  ?positionStatement ps:P39 wd:Q4416090 ; pq:P768 ?district .
  ?district wdt:P131 wd:Q1400 .
  FILTER NOT EXISTS {
    ?positionStatement pq:P582 ?endTime .
  }
}

The current U.S. Senators of Pennsylvania are John Fetterman and Bob Casey.

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

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

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

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

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

[User] who are the u s senators of pennsylvania?

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

[Tool]
Example 1:
Question:
who are senators from new jersey?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x p:P39 ?p .
  ?p ps:P39 wd:Q4416090 .
  ?p pq:P768 ?y .
  ?y wdt:P131 wd:Q1408 .
  FILTER NOT EXISTS {
    ?p pq:P582 ?z .
  }
}

Using entities:
New Jersey, also known as Garden State, US-NJ, the State of New Jersey, the Garden State, State of New Jersey (wd:Q1408): state of the United States of America
United States senator, also known as U.S. senator, US senator (wd:Q4416090): member of the United States Senate

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
position held, also known as function, held position, holds position, job, office held (wd:P39 as ps/p): subject currently or formerly holds the object position or public office
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
electoral district, also known as riding, seat, ward, electoral area, electorate (wd:P768 as pq): electoral district this person is representing, or of the office... or "office contested" (P541) or "candidacy in election" (P3602)

Example 2:
Question:
who are the current maryland senators?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x p:P39 ?p .
  ?p ps:P39 wd:Q4416090 .
  ?p pq:P768 ?y .
  ?y wdt:P131 wd:Q1391 .
  FILTER NOT EXISTS {
    ?p pq:P582 ?z .
  }
}

Using entities:
Maryland, also known as Maryland, United States, Md., MD, US-MD, Old Line State (wd:Q1391): state of the United States of America
United States senator, also known as U.S. senator, US senator (wd:Q4416090): member of the United States Senate

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
position held, also known as function, held position, holds position, job, office held (wd:P39 as ps/p): subject currently or formerly holds the object position or public office
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
electoral district, also known as riding, seat, ward, electoral area, electorate (wd:P768 as pq): electoral district this person is representing, or of the office... or "office contested" (P541) or "candidacy in election" (P3602)

Example 3:
Question:
who is the senator of the united states 2010?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x p:P39 ?p .
  ?p ps:P39 wd:Q4416090 ; pq:P580 ?y ; pq:P582 ?z .
  FILTER ( ( ?y < "2011-01-01T00:00:00Z" ^^ xsd:dateTime ) && ( ?z >= "2010-01-01T00:00:00Z" ^^ xsd:dateTime ) )
}

Using entities:
United States senator, also known as U.S. senator, US senator (wd:Q4416090): member of the United States Senate

Using properties:
position held, also known as function, held position, holds position, job, office held (wd:P39 as ps/p): subject currently or formerly holds the object position or public office
start time, also known as start date, since, valid, join time, joined (wd:P580 as 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

[Assistant]
Based on these examples, we can see that the SPARQL query to find the U.S. Senators of Pennsylvania would involve the following steps:

1. Identify the entity for Pennsylvania.
2. Identify the entity for U.S. Senator.
3. Use the `position held` property (`wdt:P39`) to find individuals who hold the position of U.S. Senator.
4. Use the `electoral district` property (`wdt:P768`) to ensure the senator represents Pennsylvania.
5. Ensure the position is currently held by checking that there is no `end time` (`wdt:P582`).

Let's start by identifying the entity for Pennsylvania.

[Tool]
Top 10 entity alternatives:
1. Pennsylvania, also known as PA, Pa., US-PA, State of Pennsylvania, Pennsylvania, United States (wd:Q1400): state of the United States of America
2. Pennsylvania, also known as US-PA, State of Pennsylvania, Pennsylvania, United States, Penna., Pa. (wd:Q1400): state of the United States of America
3. Province of Pennsylvania, also known as Colony of Pennsylvania, Pennsylvania, Pennsylvania Colony (wd:Q2475732): former colony in North America, part of Great Britain
4. Pennsylvania, also known as Pennsylvania, AL (wd:Q18392474): unincorporated community in Alabama
5. Pennsylvania (wd:Q3960056): state song of Pennsylvania, United States
6. Pennsylvania (wd:Q7163626): suburb in Exeter, Devon, England, UK
7. Pennsylvania (wd:Q1777290): steamboat
8. Pennsylvania (wd:Q7163634): album by Pere Ubu
9. Pennsylvania (wd:Q23863889): article in Otto's encyclopedia
10. Pennsylvania, also known as IMO 9486958 (wd:Q83651224): ship built in 2012

[Assistant] The correct entity for Pennsylvania is `wd:Q1400`. Next, let's identify the entity for U.S. Senator.

[Tool]
Top 10 entity alternatives:
1. United States senator, also known as U.S. senator, US senator (wd:Q4416090): member of the United States Senate
2. state senator, also known as United States state senator, state senator of the United States, US state senator, U.S. state senator (wd:Q7603534): member of an upper house of a U.S. state legislature
3. U.S. senator bibliography (wd:Q7863481): overview of United States congressional memoirs
4. John Walker, also known as John Walker, U.S. Senator (wd:Q450549): American politician (1744–1809), politician, lawyer
5. John Hemphill, also known as John Hemphill (U.S. Senator) (wd:Q456208): American politician (1803-1862), politician, lawyer, judge
6. Isham Talbot, also known as Isham Talbot, U.S. Senator (wd:Q1673872): American politician (1773-1837), politician, lawyer
7. U.S. Senator champions PET (wd:Q74623916): scientific article published on 01 March 1999
8. David J. Baker, also known as David Jewett Baker, David J. Baker, U.S. Senator (wd:Q435105): American politician (1792–1869), politician, lawyer, judge
9. William H. Wells, also known as William Hill Wells, U.S. Senator, William Hill Wells (wd:Q666838): American politician (1769-1829), politician, lawyer
10. U.S. Senator Tim Johnson hospitalized (wd:Q17667741): Wikinews article

[Assistant]
The correct entity for U.S. Senator is `wd:Q4416090`.

Now, let's construct the SPARQL query to find the current U.S. Senators of Pennsylvania. We will use the `position held` property (`wdt:P39`), the `electoral district` property (`wdt:P768`), and ensure there is no `end time` (`wdt:P582`).

Here is the initial SPARQL query:

```sparql
SELECT DISTINCT ?senator WHERE {
  ?senator p:P39 ?positionStatement .
  ?positionStatement ps:P39 wd:Q4416090 ;
                     pq:P768 ?district .
  ?district wdt:P131 wd:Q1400 .
  FILTER NOT EXISTS {
    ?positionStatement pq:P582 ?endTime .
  }
}
```

Let's execute this query to see the results.

[Tool]
Got 2 rows and 1 column:
| senator                      |
| ---------------------------- |
| John Fetterman (wd:Q3181500) |
| Bob Casey (wd:Q887841)       |

[Assistant]
The SPARQL query has successfully returned the current U.S. Senators of Pennsylvania:

- John Fetterman (wd:Q3181500)
- Bob Casey (wd:Q887841)

Here is the final SPARQL query and the answer:

```sparql
SELECT DISTINCT ?senator WHERE {
  ?senator p:P39 ?positionStatement .
  ?positionStatement ps:P39 wd:Q4416090 ;
                     pq:P768 ?district .
  ?district wdt:P131 wd:Q1400 .
  FILTER NOT EXISTS {
    ?positionStatement pq:P582 ?endTime .
  }
}
```

The current U.S. Senators of Pennsylvania are John Fetterman and Bob Casey.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX p: <http://www.wikidata.org/prop/>
SELECT DISTINCT ?character WHERE {
  ?film wdt:P8345 wd:Q462 ; p:P161 ?castMember .
  ?castMember ps:P161 wd:Q358345 ; pq:P453 ?character .
}

Lando Calrissian

[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 character did billy d williams play in star wars?

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

[Tool]
Example 1:
Question:
what was liam neeson's character in star wars?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?p wdt:P8345 wd:Q462 ; p:P161 ?y .
  ?y ps:P161 wd:Q58444 ; pq:P453 ?x .
}

Using entities:
Star Wars, also known as 1977 Star Wars (wd:Q462): epic space opera multimedia franchise created by George Lucas
Liam Neeson, also known as William John Neeson (wd:Q58444): Northern Irish actor, television actor, voice actor, stage actor, film actor, actor

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as ps/p): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
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)
media franchise, also known as franchise, mass media franchise, media mix, presented in media franchise (wd:P8345 as wdt): this creative work belongs to this media franchise

Example 2:
Question:
who play luke skywalker?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?p p:P161 ?y .
  ?y ps:P161 ?x ; pq:P453 wd:Q51746 .
}

Using entities:
Luke Skywalker, also known as Luke Starkiller (wd:Q51746): fictional character from Star Wars, starship pilot, mechanic, rebel, Jedi

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as ps/p): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
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)

Example 3:
Question:
who was the voice of darth vader in episode iii?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q42051 p:P161 ?y .
  ?y ps:P161 ?x ; pq:P453 wd:Q51752 .
}

Using entities:
Star Wars: Episode III – Revenge of the Sith, also known as Star Wars Episode III, Star Wars: Episode III -- Revenge of the Sith, Star Wars: Revenge of the Sith (wd:Q42051): 2005 American epic space opera film directed by George Lucas
Anakin Skywalker, also known as Anakin, Ani, General Skywalker, The Chosen One (wd:Q51752): fictional character from Star Wars, Jedi

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as ps/p): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
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)

[Assistant]
Based on the examples, we need to identify the following:

1. **Billy Dee Williams** - The actor.
2. **Star Wars** - The franchise.
3. **Character Role** - The specific role played by Billy Dee Williams.

Let's start by searching for the entity representing Billy Dee Williams.

[Tool]
Top 10 entity alternatives:
1. Billy Dee Williams, also known as William December Williams Jr., William December "Billy Dee" Williams Jr. (wd:Q358345): American actor (born 1937), recording artist, television actor, screenwriter, voice actor, film actor, novelist, painter, writer, singer, actor
2. Billy Drease Williams, also known as Edreys, Edreys Wajed (wd:Q4912488): record producer, American rapper, songwriter, rapper, singer
3. Billy Williams, also known as William Dennis "Billy" Williams, William Dennis Williams (wd:Q4913466): association football player, footballer, born 1905
4. Billy Dee Williams Self-Portrait (wd:Q47513010): painting by Billy Dee Williams
5. Bill Maynard, also known as Billy Williams (wd:Q3736724): English comedian and actor (1928–2018), association football player, stand-up comedian, television actor, stage actor, actor
6. Billy Williams (wd:Q123745): British cinematographer, camera operator, cinematographer, film actor, actor
7. Billy Williams, also known as Billy Leo Williams (wd:Q4913471): American former professional baseball outfielder, baseball player
8. David Williams, also known as D. Williams (wd:Q1177203): Welsh mathematician working in probability theory, university teacher, mathematician
9. Billy Williams, also known as Wilfred Williams (wd:Q3640062): American basketball player, basketball player
10. Billy Williams, also known as Wilfred Williams (wd:Q863272): African-American singer (1910-1972), singer

[Assistant]
The correct entity for Billy Dee Williams is `wd:Q358345`.

Next, let's search for the entity representing the Star Wars franchise.

[Tool]
Top 10 entity alternatives:
1. Star Wars, also known as 1977 Star Wars (wd:Q462): epic space opera multimedia franchise created by George Lucas
2. Star Wars: Episode IV – A New Hope, also known as 1977 Star Wars, A New Hope, Star Wars, Star Wars: A New Hope, Star Wars: Episode IV (wd:Q17738): 1977 film directed by George Lucas
3. Star Wars, also known as Star Wars: The Arcade Game (wd:Q54317): 1983 video game
4. Star Wars, also known as Star Wars (Original Motion Picture Soundtrack), Star Wars soundtrack (wd:Q2715371): 1977 soundtrack album
5. Star Wars, also known as 1991 Star Wars, Game Boy Star Wars, NES Star Wars (wd:Q54320): 1991 video game
6. Star Wars (wd:Q30597407): 1977 composition by John Williams
7. Star Wars: Starfighter (wd:Q55225): 2001 video game
8. Star Wars, also known as 1987 Star Wars (wd:Q54319): 1987 video game
9. Star Wars (wd:Q20720789): album by Wilco
10. Star Wars (wd:Q3180475): Japanese manga series

[Assistant]
The correct entity for the Star Wars franchise is `wd:Q462`.

Now, we need to find the character role played by Billy Dee Williams in the Star Wars franchise. We will use the properties `P161` (cast member) and `P453` (character role) to find this information.

Let's construct a SPARQL query to find the character role played by Billy Dee Williams in the Star Wars franchise.

```sparql
SELECT DISTINCT ?character WHERE {
  ?film wdt:P8345 wd:Q462 ; p:P161 ?castMember .
  ?castMember ps:P161 wd:Q358345 ; pq:P453 ?character .
}
```

This query will find the films that belong to the Star Wars franchise (`wdt:P8345 wd:Q462`), then find the cast members (`p:P161`) where Billy Dee Williams (`wd:Q358345`) is the actor, and finally extract the character role (`pq:P453`).

Let's execute this query.

[Tool]
Got 1 row and 1 column:
| character                    |
| ---------------------------- |
| Lando Calrissian (wd:Q51799) |

[Assistant]
The character played by Billy Dee Williams in the Star Wars franchise is Lando Calrissian.

Here is the final SPARQL query and answer:

```sparql
SELECT DISTINCT ?character WHERE {
  ?film wdt:P8345 wd:Q462 ; p:P161 ?castMember .
  ?castMember ps:P161 wd:Q358345 ; pq:P453 ?character .
}
```

Answer: Lando Calrissian

Let's finalize this with the answer function.

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?school ?schoolLabel WHERE {
  wd:Q9123 wdt:P69 ?school .
  OPTIONAL {
    ?school rdfs:label ?schoolLabel .
    FILTER ( LANG( ?schoolLabel ) = 'en' )
  }
}

Got 4 rows and 2 columns:
| school                                | schoolLabel                   |
| ------------------------------------- | ----------------------------- |
| Nelson College (wd:Q1976962)          | Nelson College (en)           |
| Trinity College (wd:Q332342)          | Trinity College (en)          |
| University of Cambridge (wd:Q35794)   | University of Cambridge (en)  |
| University of Canterbury (wd:Q432475) | University of Canterbury (en) |

Sir Ernest Rutherford attended the following schools: Nelson College (wd:Q1976962), Trinity College (wd:Q332342), University of Cambridge (wd:Q35794), and University of Canterbury (wd:Q432475).

[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 school did sir ernest rutherford go to?

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

[Tool]
Example 1:
Question:
what school did sir isaac newton go to?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q935 wdt:P69 ?x .
}

Using entities:
Isaac Newton (wd:Q935): English mathematician and physicist (1642–1727), mathematician, philosopher

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 2:
Question:
where did isaac newton go to high school?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q935 wdt:P69 ?x .
  ?x wdt:P31 / wdt:P279 * wd:Q9826 .
}

Using entities:
Isaac Newton (wd:Q935): English mathematician and physicist (1642–1727), mathematician, philosopher
high school, also known as H.S., upper middle school, senior high school, HS (wd:Q9826): institution which provides all or part of secondary education

Using properties:
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)
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 primary school did sir isaac newton go to?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q935 wdt:P69 ?x .
  ?x wdt:P31 / wdt:P279 * wd:Q967098 .
}

Using entities:
Isaac Newton (wd:Q935): English mathematician and physicist (1642–1727), mathematician, philosopher
grammar school (wd:Q967098): type of school in the United Kingdom and some other countries

Using properties:
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)
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]
From the examples, we can see that the property `educated at` (P69) is used to link a person to the schools they attended. We need to identify Sir Ernest Rutherford and then use this property to find the schools he attended.

First, let's search for Sir Ernest Rutherford.

[Tool]
Top 10 entity alternatives:
1. Ernest Rutherford, Baron Rutherford of Nelson, Fellow and Physicist, also known as Ernest Rutherford (1871–1937), B... of Nelson, Fellow and Physicist, Sir Ernest Rutherford (wd:Q117280779): painting by Philip de László
2. Sir Ernest Victor Buckley Rutherford (wd:Q76061425): Peerage person ID=503509
3. Ernest Rutherford, also known as Ernest Rutherford, primer barón Rutherford. de Nelson, E. Rutherford, Ernest Lord Rutherford, Ernest, Lord Rutherford (wd:Q9123): New Zealand physicist (1871–1937), university teacher, nuclear physicist, politician, professor, physicist, chemist
4. Ernest Rutherford (wd:Q41065867): scientific article
5. Ernest Rutherford (wd:Q67472783): scientific article published on April 12, 1976
6. Rutherford, Ernest (wd:Q103848810): encyclopedia article
7. Ernest Marsden, also known as Sir Ernest Marsden (wd:Q714452): British–New Zealand physicist (1889–1970), nuclear physicist, physicist
8. Ernest Oppenheimer, also known as Sir Ernest Oppenheimer (wd:Q819374): South African businessman (1880-1957), businessperson, entrepreneur, politician, financier, banker
9. Ernest Barker, also known as Sir Ernest Barker (wd:Q5392730): British political scientist (1874-1960), political scientist, politician, historian
10. Ernest Scott, also known as Sir Ernest Scott (wd:Q1356521): Australian historian (1867-1939), biographer, journalist, historian, writer

[Assistant]
The correct entity for Sir Ernest Rutherford is `wd:Q9123`. Now, let's use the property `educated at` (P69) to find the schools he attended.

I will construct a simple SPARQL query to retrieve the schools Sir Ernest Rutherford attended.

[Tool]
Got 4 rows and 1 column:
| school                                |
| ------------------------------------- |
| Nelson College (wd:Q1976962)          |
| Trinity College (wd:Q332342)          |
| University of Cambridge (wd:Q35794)   |
| University of Canterbury (wd:Q432475) |

[Assistant]
The SPARQL query has returned the schools that Sir Ernest Rutherford attended. To provide a complete and clear answer, I will include the labels of these schools in the final query.

Here is the final SPARQL query:

```sparql
SELECT DISTINCT ?school ?schoolLabel WHERE {
  wd:Q9123 wdt:P69 ?school .
  OPTIONAL { ?school rdfs:label ?schoolLabel . FILTER(LANG(?schoolLabel) = 'en') }
}
```

This query will return the schools along with their English labels.

Now, let's execute this final query.

[Tool]
Got 4 rows and 2 columns:
| school                                | schoolLabel                   |
| ------------------------------------- | ----------------------------- |
| Nelson College (wd:Q1976962)          | Nelson College (en)           |
| Trinity College (wd:Q332342)          | Trinity College (en)          |
| University of Cambridge (wd:Q35794)   | University of Cambridge (en)  |
| University of Canterbury (wd:Q432475) | University of Canterbury (en) |

[Assistant]
The final SPARQL query has successfully retrieved the schools that Sir Ernest Rutherford attended, along with their English labels.

Here is the answer to the question:

Sir Ernest Rutherford attended the following schools:
- Nelson College (wd:Q1976962)
- Trinity College (wd:Q332342)
- University of Cambridge (wd:Q35794)
- University of Canterbury (wd:Q432475)

Now, I will 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 ?school WHERE {
  wd:Q2190766 wdt:P69 ?school .
}

Got 3 rows and 1 column:
| school                                   |
| ---------------------------------------- |
| Juneau-Douglas High School (wd:Q6312473) |
| Wasilla High School (wd:Q7972657)        |
| West Anchorage High School (wd:Q7984309) |

Bristol Palin went to school at Juneau-Douglas High School, Wasilla High School, and West Anchorage High 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 bristol palin go to school?

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

[Tool]
Example 1:
Question:
where did barack obama went to school?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q76 wdt:P69 ?x .
}

Using entities:
Barack Obama, also known as Honorable Barack Obama, BHO, Obama, Barry O Bomber, President Obama (wd:Q76): president of the United States from 2009 to 2017, community organizer, political writer, statesperson, politician, podcaster, memoirist, academic, lawyer, jurist

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 2:
Question:
where did barack obama attend school?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q76 wdt:P69 ?x .
}

Using entities:
Barack Obama, also known as Honorable Barack Obama, BHO, Obama, Barry O Bomber, President Obama (wd:Q76): president of the United States from 2009 to 2017, community organizer, political writer, statesperson, politician, podcaster, memoirist, academic, lawyer, jurist

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:
where did pres. obama go to school?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q76 wdt:P69 ?x .
}

Using entities:
Barack Obama, also known as Honorable Barack Obama, BHO, Obama, Barry O Bomber, President Obama (wd:Q76): president of the United States from 2009 to 2017, community organizer, political writer, statesperson, politician, podcaster, memoirist, academic, lawyer, jurist

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 need to identify Bristol Palin and the property for 'educated at'. Let's start by searching for Bristol Palin.

[Tool]
Top 10 entity alternatives:
1. Bristol Palin, also known as Bristol Sheeran Marie Palin (wd:Q2190766): reality television participant, daughter of Sarah Palin, real estate agent, politician, writer
2. Bristol Palin: Life's a Tripp (wd:Q4968974): television series
3. Bristol, also known as Bristol, UK, Bristol, England, Bristol, Gloucestershire (wd:Q23154): city in South West England, United Kingdom
4. Bristol, also known as Bristol, CT, Bristol, Connecticut (wd:Q755149): city in Hartford County, Connecticut, United States
5. Bristol, also known as Bristol, Tennessee, Bristol, TN (wd:Q917821): city in Sullivan County, Tennessee, United States
6. Bristol Airport, also known as Bristol (Lulsgate) Airport, EGGD, BRS, Bristol International Airport, Bristol (wd:Q8725): commercial airport serving the city of Bristol, England
7. Bristol, also known as Bristol, VA, Bristol, Virginia (wd:Q503366): independent city in Virginia, United States
8. Bristol, also known as Bristol, Florida, Bristol, FL (wd:Q568950): city in and the county seat of Liberty County, Florida, United States
9. Bristol Airport, also known as EGGD, Bristol, Bristol International Airport, Bristol (Lulsgate) Airport, BRS (wd:Q8725): commercial airport serving the city of Bristol, England
10. Bristol, also known as Bristol, Rhode Island, Bristol, RI (wd:Q917809): town in Rhode Island, United States

[Assistant] The correct entity for Bristol Palin is `wd:Q2190766`. Next, let's confirm the property for 'educated at'.

[Tool]
Top 10 property alternatives:
1. educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): educational institution attended by subject, affiliation
2. conferred by, also known as presented by, officiated by, issued by, granted by, given by (wd:P1027 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): person or organization who grants an award, certification, grant, or role
3. student of, also known as professor, studied under, pupil of, tutor, mentor (wd:P1066 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): person who has taught this person, significant person
4. student, also known as teacher to, teacher of, had student, students, pupils (wd:P802 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): notable student(s) of the subject individual, significant person
5. studied in, also known as is studied by, studied by, science, that studies, researched in, researched by (wd:P2579 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): subject is studied by this science or domain, field of work
6. gender educated (wd:P7419 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): genders educated at this educational institution
7. academic major, also known as academic subject, college major, field of study, major, studied (wd:P812 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): major someone studied at college/university
8. has role in modeling, also known as has role in modelling, used for investigating, used for researching, used for studying, used to investigate (wd:P6530 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): relation between a research artefact and an entity that is used ... its replicating or approximating features of the studied entity
9. academic degree, also known as academic diploma, degree, diploma (wd:P512 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): academic degree that the person holds
10. influenced by, also known as favorite player, has influence, informed by, role model (wd:P737 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): this person, idea, etc. is informed by that other person, idea, etc., e.g. “Heidegger was influenced by Aristotle”

[Assistant]
The correct property for 'educated at' is `wdt:P69`. Now, let's construct a SPARQL query to find out where Bristol Palin went to school.

```sparql
SELECT DISTINCT ?school WHERE {
  wd:Q2190766 wdt:P69 ?school .
}
```

I'll execute this query now.

[Tool]
Got 3 rows and 1 column:
| school                                   |
| ---------------------------------------- |
| Juneau-Douglas High School (wd:Q6312473) |
| Wasilla High School (wd:Q7972657)        |
| West Anchorage High School (wd:Q7984309) |

[Assistant]
The SPARQL query returned three schools where Bristol Palin went to school:

- Juneau-Douglas High School (wd:Q6312473)
- Wasilla High School (wd:Q7972657)
- West Anchorage High School (wd:Q7984309)

Here is the final SPARQL query and the answer:

```sparql
SELECT DISTINCT ?school WHERE {
  wd:Q2190766 wdt:P69 ?school .
}
```

Answer: Bristol Palin went to school at Juneau-Douglas High School, Wasilla High School, and West Anchorage High School.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?occupation ?placeOfBirth ?dateOfBirth ?dateOfDeath ?countryOfCitizenship WHERE {
  wd:Q9200 wdt:P106 ?occupation .
  wd:Q9200 wdt:P19 ?placeOfBirth .
  wd:Q9200 wdt:P569 ?dateOfBirth .
  wd:Q9200 wdt:P570 ?dateOfDeath .
  wd:Q9200 wdt:P27 ?countryOfCitizenship .
}

Saint Paul the Apostle, also known as Saul of Tarsus, was a significant figure in early Christianity. He was born around 5 AD in Tarsus, which is now in modern-day Turkey, and died around 66 AD. His country of citizenship was Ancient Rome. His occupations included: Theologian (wd:Q1234713), Artisan (wd:Q1294787), Rabbi (wd:Q133485), Missionary (wd:Q219477), Traveler (wd:Q22813352), Writer (wd:Q36180), and Religious figure (wd:Q4504549).

[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 was saint paul the apostle?

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

[Tool]
Example 1:
Question:
who was the apostle paul considered to be?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q9200 wdt:P1559 ?x .
}

Using entities:
Paul the Apostle, also known as Saul of Tarsus, Saulus, Šā'ûl, Saul, Saint Paulus (wd:Q9200): Early Christian apostle and missionary (c. AD 5 – c. 64/65), religious figure, missionary, theologian, traveler, artisan, writer, rabbi

Using properties:
name in native language, also known as native name (wd:P1559 as wdt): name of a person in their native language, name

Example 2:
Question:
who is paul revere and what did he do?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q327071 wdt:P106 ?x .
}

Using entities:
Paul Revere, also known as Paul Revere, Jr. (wd:Q327071): American silversmith and Patriot in the American Revolution, military personnel, entrepreneur, silversmith, Minutemen

Using properties:
occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)

Example 3:
Question:
what did st. matthew do?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q43600 wdt:P106 ?x .
}

Using entities:
Matthew the Apostle, also known as Saint Matthew, Matthew the Evangelist, Matthew (wd:Q43600): Christian evangelist and apostle, tax collector, presbyter, publican

Using properties:
occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)

[Assistant] From the examples, we can see that the first example is the most relevant to our question about Saint Paul the Apostle. It provides a query that retrieves alternative names for Paul the Apostle. However, we want to know more about who he was, including his roles and contributions. Let's start by searching for the entity "Saint Paul the Apostle" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Paul the Apostle, also known as Saul of Tarsus, Saulus, Šā'ûl, Saul, Saint Paulus (wd:Q9200): Early Christian apostle and missionary (c. AD 5 – c. 64/65), religious figure, missionary, theologian, traveler, artisan, writer, rabbi
2. San Paolo convent, also known as Saint Paul the Apostle, San Paolo (Ferrara) - Convent (wd:Q124151525): convent at the church of San Paolo, Ferrara, Italy
3. San Paolo al Cimitero, also known as Saint Paul the Apostle (wd:Q123987072): religious building at the cemetery of Sassari, Italy
4. San Paolo, also known as Saint Paul the Apostle (wd:Q118516744): religious building in Biancareddu, Sassari, Italy
5. Saint Paul the Apostle (wd:Q19859112): painting by José Ferraz de Almeida Júnior
6. Saint Paul the Apostle (wd:Q118591287): painting by Spanish School, Wellcome Collection
7. The apostle Saint Paul (wd:Q121546195): painting by Anthony van Dyck
8. St. Paul the Apostle Church, also known as Saint Paul the Apostle Church (wd:Q7591285): church in New York, United States
9. Saint Paul the Apostle writing (wd:Q123163634): painting by Lambert Jacobsz
10. Church of St Paul, 1651 Shettleston Road, Glasgow, also known as 1651 Shettleston Road, Church Of St Paul, Church of Saint Paul the Apostle (wd:Q17815655): church building in Glasgow, Scotland, UK

[Assistant] The top result is the entity we're looking for: Paul the Apostle, also known as Saul of Tarsus, Saulus, Šā'ûl, Saul, Saint Paulus (wd:Q9200). Now, let's gather more information about him, such as his roles, contributions, and other significant details. We'll start by listing the triples associated with this entity to get an overview of the available information.

[Tool]
Got 1,388 rows and 3 columns, showing the first 10 rows below:
| subject                     | property                         | object                                                                                |
| --------------------------- | -------------------------------- | ----------------------------------------------------------------------------------------------------------- |
| Paul the Apostle (wd:Q9200) | instance of (wdt:P31)            | human (wd:Q5)                                                                                |
| Paul the Apostle (wd:Q9200) | occupation (wdt:P106)            | writer (wd:Q36180)                                                                                |
| Paul the Apostle (wd:Q9200) | sex or gender (wdt:P21)          | male (wd:Q6581097)                                                                                |
| Paul the Apostle (wd:Q9200) | given name (wdt:P735)            | Saul (wd:Q9302723)                                                                                |
| Paul the Apostle (wd:Q9200) | date of birth (wdt:P569)         | 0005-01-01T00:00:00Z (xsd:dateTime)                                                                         |
| Paul the Apostle (wd:Q9200) | Commons category (wdt:P373)      | Saint Paul                                                                                |
| Paul the Apostle (wd:Q9200) | image (wdt:P18)                  | <http://commons.wikimedia.org/wiki/Special:FilePath/Giovanni%20Francesco%20Barbieri%20-%20Saint%20Paul.jpg> |
| Paul the Apostle (wd:Q9200) | country of citizenship (wdt:P27) | Ancient Rome (wd:Q1747689)                                                                                |
| Paul the Apostle (wd:Q9200) | place of birth (wdt:P19)         | Tarsus (wd:Q134287)                                                                                |
| Paul the Apostle (wd:Q9200) | date of death (wdt:P570)         | 0066-01-01T00:00:00Z (xsd:dateTime)                                                                         |
| ...                         | ...                              | ...                                                                                |

[Assistant]
The list of triples provides a wealth of information about Saint Paul the Apostle. We can see his occupations, birth and death dates, place of birth, and other details. To provide a comprehensive answer, we can construct a SPARQL query that retrieves key information such as his occupations, place of birth, and other significant details.

Let's start with a basic query to retrieve his occupations and place of birth:

```sparql
SELECT ?occupation ?placeOfBirth WHERE {
  wd:Q9200 wdt:P106 ?occupation .
  wd:Q9200 wdt:P19 ?placeOfBirth .
}
```

We can then expand this query to include more details as needed. Let's execute this initial query to see the results.

[Tool]
Got 7 rows and 2 columns:
| occupation                     | placeOfBirth        |
| ------------------------------ | ------------------- |
| theologian (wd:Q1234713)       | Tarsus (wd:Q134287) |
| artisan (wd:Q1294787)          | Tarsus (wd:Q134287) |
| rabbi (wd:Q133485)             | Tarsus (wd:Q134287) |
| missionary (wd:Q219477)        | Tarsus (wd:Q134287) |
| traveler (wd:Q22813352)        | Tarsus (wd:Q134287) |
| writer (wd:Q36180)             | Tarsus (wd:Q134287) |
| religious figure (wd:Q4504549) | Tarsus (wd:Q134287) |

[Assistant]
The initial query has provided us with Saint Paul the Apostle's occupations and place of birth. To give a more comprehensive answer, we can include additional details such as his date of birth, date of death, and country of citizenship. Let's expand the query to include these details:

```sparql
SELECT ?occupation ?placeOfBirth ?dateOfBirth ?dateOfDeath ?countryOfCitizenship WHERE {
  wd:Q9200 wdt:P106 ?occupation .
  wd:Q9200 wdt:P19 ?placeOfBirth .
  wd:Q9200 wdt:P569 ?dateOfBirth .
  wd:Q9200 wdt:P570 ?dateOfDeath .
  wd:Q9200 wdt:P27 ?countryOfCitizenship .
}
```

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

[Tool]
Got 7 rows and 5 columns:
| occupation                     | placeOfBirth        | dateOfBirth                         | dateOfDeath                         | countryOfCitizenship       |
| ------------------------------ | ------------------- | ----------------------------------- | ----------------------------------- | -------------------------- |
| theologian (wd:Q1234713)       | Tarsus (wd:Q134287) | 0005-01-01T00:00:00Z (xsd:dateTime) | 0066-01-01T00:00:00Z (xsd:dateTime) | Ancient Rome (wd:Q1747689) |
| artisan (wd:Q1294787)          | Tarsus (wd:Q134287) | 0005-01-01T00:00:00Z (xsd:dateTime) | 0066-01-01T00:00:00Z (xsd:dateTime) | Ancient Rome (wd:Q1747689) |
| rabbi (wd:Q133485)             | Tarsus (wd:Q134287) | 0005-01-01T00:00:00Z (xsd:dateTime) | 0066-01-01T00:00:00Z (xsd:dateTime) | Ancient Rome (wd:Q1747689) |
| missionary (wd:Q219477)        | Tarsus (wd:Q134287) | 0005-01-01T00:00:00Z (xsd:dateTime) | 0066-01-01T00:00:00Z (xsd:dateTime) | Ancient Rome (wd:Q1747689) |
| traveler (wd:Q22813352)        | Tarsus (wd:Q134287) | 0005-01-01T00:00:00Z (xsd:dateTime) | 0066-01-01T00:00:00Z (xsd:dateTime) | Ancient Rome (wd:Q1747689) |
| writer (wd:Q36180)             | Tarsus (wd:Q134287) | 0005-01-01T00:00:00Z (xsd:dateTime) | 0066-01-01T00:00:00Z (xsd:dateTime) | Ancient Rome (wd:Q1747689) |
| religious figure (wd:Q4504549) | Tarsus (wd:Q134287) | 0005-01-01T00:00:00Z (xsd:dateTime) | 0066-01-01T00:00:00Z (xsd:dateTime) | Ancient Rome (wd:Q1747689) |

[Assistant]
The expanded query has provided us with a comprehensive set of details about Saint Paul the Apostle, including his occupations, place of birth, date of birth, date of death, and country of citizenship.

To finalize the answer, we can format the results into a readable form. Here is the final SPARQL query and the corresponding answer:

```sparql
SELECT ?occupation ?placeOfBirth ?dateOfBirth ?dateOfDeath ?countryOfCitizenship WHERE {
  wd:Q9200 wdt:P106 ?occupation .
  wd:Q9200 wdt:P19 ?placeOfBirth .
  wd:Q9200 wdt:P569 ?dateOfBirth .
  wd:Q9200 wdt:P570 ?dateOfDeath .
  wd:Q9200 wdt:P27 ?countryOfCitizenship .
}
```

Answer:
Saint Paul the Apostle, also known as Saul of Tarsus, was a significant figure in early Christianity. He was born around 5 AD in Tarsus, which is now in modern-day Turkey, and died around 66 AD. His country of citizenship was Ancient Rome. His occupations included:
- Theologian (wd:Q1234713)
- Artisan (wd:Q1294787)
- Rabbi (wd:Q133485)
- Missionary (wd:Q219477)
- Traveler (wd:Q22813352)
- Writer (wd:Q36180)
- Religious figure (wd:Q4504549)

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 ?highSchool WHERE {
  wd:Q182658 wdt:P69 ?highSchool .
  ?highSchool wdt:P31 / wdt:P279 * wd:Q9826 .
}

Monroe County High 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 harper lee attend high school?

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

[Tool]
Example 1:
Question:
where did richard nixon go to high school?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q9588 wdt:P69 ?x .
  ?x wdt:P31 / wdt:P279 * wd:Q9826 .
}

Using entities:
Richard Nixon, also known as Richard M. Nixon, R. M. Nixon, Tricky Dick, Richard Milhous Nixon, R. Nixon (wd:Q9588): President of the United States from 1969 to 1974, military officer, autobiographer, statesperson, politician, lawyer
high school, also known as H.S., upper middle school, senior high school, HS (wd:Q9826): institution which provides all or part of secondary education

Using properties:
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)
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 2:
Question:
what high school did president bill clinton attend?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q1124 wdt:P69 ?x .
  ?x wdt:P31 / wdt:P279 * wd:Q9826 .
}

Using entities:
Bill Clinton, also known as William Jefferson Blythe, William Jefferson Blythe III, William Jefferson "Bill" Clinton, William Jefferson Clinton, WJC (wd:Q1124): President of the United States from 1993 to 2001, autobiographer, statesperson, saxophonist, politician, governor, diplomat, teacher, jurist, lawyer, writer
high school, also known as H.S., upper middle school, senior high school, HS (wd:Q9826): institution which provides all or part of secondary education

Using properties:
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)
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:
where did charles drew go to high school?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q1065848 wdt:P69 ?x .
  ?x wdt:P31 / wdt:P279 * wd:Q9826 .
}

Using entities:
Charles Drew, also known as Charles Drew, Charles R. Drew (wd:Q1065848): American surgeon and medical researcher (1904–1950), university teacher, physician, surgeon
high school, also known as H.S., upper middle school, senior high school, HS (wd:Q9826): institution which provides all or part of secondary education

Using properties:
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)
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 these examples, we can see that the pattern to find where someone attended high school involves using the `educated at` property (P69) and filtering the results to only include high schools, which are instances of or subclasses of the high school entity (Q9826).

First, let's identify the entity for Harper Lee.

[Tool]
Top 10 entity alternatives:
1. Harper Lee, also known as Nelle Harper Lee (wd:Q182658): American author, prose writer, screenwriter, poet lawyer, novelist, musician, writer, actor
2. Lee Harper, also known as Lee Charles Philip Harper (wd:Q6513809): Footballer and manager (born 1971), association football manager, association football player
3. Lee Harper (wd:Q1811814): American musician (1945–2010), jazz guitarist, musician
4. Ron Harper, also known as Ronald Lee Harper (wd:Q7363883): Canadian politician, politician
5. Harper B. Lee, also known as Harper Baylor Lee, James Harper Gillett (wd:Q3127694): American matador (1884-1941), matador
6. Harper Lee Award (wd:Q107354207): award for Alabama writers
7. Harper Lee Kaye (wd:Q88315759): researcher
8. Jonathan Lee Harper (wd:Q102342439): Ph.D. Montana State University 2007
9. Eric Harper, also known as Eric Lee Harper (wd:Q116510885): guitarist, composer, musician
10. Gloria Harper Lee (wd:Q117517845): Cousin of Monica Hargrove, interviewee of Dartmouth Black Lives

[Assistant]
The correct entity for Harper Lee is `wd:Q182658`. Now, let's construct the SPARQL query to find out where she attended high school.

We will use the `educated at` property (P69) and filter the results to only include high schools, which are instances of or subclasses of the high school entity (Q9826).

Here is the SPARQL query:

```sparql
SELECT DISTINCT ?highSchool WHERE {
  wd:Q182658 wdt:P69 ?highSchool .
  ?highSchool wdt:P31 / wdt:P279* wd:Q9826 .
}
```

Let's execute this query.

[Tool]
Got 1 row and 1 column:
| highSchool                              |
| --------------------------------------- |
| Monroe County High School (wd:Q6902164) |

[Assistant]
The SPARQL query has returned the high school that Harper Lee attended, which is Monroe County High School (wd:Q6902164).

Therefore, the answer to the question "Where did Harper Lee attend high school?" is:

Monroe County High School.

Let's finalize the answer with the SPARQL query and the result.

[Tool] Stopped generation process