PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?country WHERE {
  ?cave wdt:P31 wd:Q35509 .
  ?cave wdt:P131 ?country .
  ?country wdt:P31 wd:Q6256 .
}
GROUP BY ?country
HAVING ( COUNT( ?cave ) > 10 )
ORDER BY DESC ( COUNT( ?cave ) )

Got 4 rows and 1 column:
| country              |
| -------------------- |
| Montenegro (wd:Q236) |
| Libya (wd:Q1016)     |
| Indonesia (wd:Q252)  |
| Kosovo (wd:Q1246)    |

The countries that have more than ten caves are Montenegro, Libya, Indonesia, and Kosovo.

[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 http://amur:7001

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 countries have more than ten caves?

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

[Tool]
Example 1:
Question:
Which countries have more than ten volcanoes?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  {
    ?volcano wdt:P31 wd:Q8072 .
  } UNION {
    ?volcano wdt:P31 ?type .
    ?type wdt:P279 * wd:Q8072 .
  }
  ?volcano wdt:P17 ?uri .
}
GROUP BY ?uri
HAVING ( COUNT( ?volcano ) > 10 )

Using entities:
volcano (wd:Q8072): natural, surface vent or fissure usually in a mountainous form

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
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:
Give me all South American countries.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q6256 .
  ?uri wdt:P30 wd:Q18 .
}

Using entities:
South America, also known as S America, S. America, South American continent (wd:Q18): continent
country, also known as countries (wd:Q6256): distinct territorial body or political entity

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

SPARQL:
SELECT DISTINCT * WHERE {
  ?uri wdt:P31 wd:Q6256 .
  ?uri wdt:P2046 ?area .
  ?uri rdfs:label ?label
}
ORDER BY DESC ( ?area )
LIMIT 1

Using entities:
country, also known as countries (wd:Q6256): distinct territorial body or political entity

Using properties:
area, also known as total area, surface area, surface, size, resolution (wd:P2046 as wdt): area occupied by an 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]
From the examples, we see that countries are identified as instances of wd:Q6256. We also see that counting instances of a certain type (like volcanoes) within a country can be done by grouping and counting with a HAVING clause.

Next, I need to identify the entity for "cave" and the property that links caves to countries. I will first search for the entity "cave" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. cave, also known as cavern (wd:Q35509): natural void under the Earth's surface
2. Cave (wd:Q177726): comune in Italy
3. Carlsbad Caverns National Park, also known as CAVE (wd:Q273195): United States National Park in the Guadalupe Mountains in southeastern New Mexico
4. Cave (wd:Q736010): single by Muse
5. The Cave, also known as Cave (wd:Q1027834): 2005 film directed by Bruce Hunt
6. Cave, also known as Cave, MO (wd:Q957976): village in Missouri
7. CAVE, also known as Cave Co., Ltd., Cave Interactive Co., Ltd. (wd:Q2495040): video game company
8. Cave (wd:Q18436524): human settlement in Italy
9. Cave, also known as Cave, New Zealand (wd:Q5054876): locality in Timaru District, Canterbury Region, New Zealand
10. Cave (wd:Q18506124)

[Assistant] The entity for "cave" as a natural void under the Earth's surface is wd:Q35509. Now I will search for properties that link caves to countries. I will search for properties of the cave entity related to country or location.

[Tool]
Top 10 property alternatives:
1. OpenStreetMap tag or key, also known as tag, OSM wiki tag or key, OpenStreetMap relation role, OSM tag or key, OSM tag (wd:P1282 as p): OpenStreetMap tagging schema (a Key:key, Tag:key=value, Relation:type, or Role:role) for classes, properties, and values
2. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
3. 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
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. spherical panorama image, also known as 360-degree panorama image, photosphere panoramic image, photosphere panorama, photosphere image, panorama view 360x180 degrees (wd:P4640 as wdt/p): image with the field of view 360×180 degrees oyiyi na ubi anya 360×180 degrees, panoramic view
6. studied in, also known as is studied by, studied by, science, that studies, researched in, researched by (wd:P2579 as wdt/p): subject is studied by this science or domain, field of work
7. properties for this type, also known as uses properties, Wikidata properties for this type, Wikidata properties for this class, uses property, things one could say about (wd:P1963 as wdt/p): when this subject is used as object of “instance of”, the following properties normally apply
8. has list, also known as list, topic's list, topic list, related list, list for this topic (wd:P2354 as wdt/p): Wikimedia list related to this subject
9. subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt/p): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
10. Freebase ID, also known as Freebase, MID, Freebase identifier, FID (wd:P646 as wdt/p): identifier for a page in the Freebase database. Format: "/m/0" f...r IDs starting with "/g/", use Google Knowledge Graph ID (P2671)

No other items found

[Assistant] The search for a direct property linking caves to countries did not return a clear property. I will try searching for properties related to location or country for caves.

[Tool]
Top 10 property alternatives:
1. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
2. Commons gallery, also known as gallery (wd:P935 as wdt/p): name of the Wikimedia Commons gallery page(s) related to this item (is suitable to allow multiple links to more gallery pages)
3. spherical panorama image, also known as 360-degree panorama image, photosphere panoramic image, photosphere panorama, photosphere image, panorama view 360x180 degrees (wd:P4640 as wdt/p): image with the field of view 360×180 degrees oyiyi na ubi anya 360×180 degrees, panoramic view
4. OpenStreetMap tag or key, also known as tag, OSM wiki tag or key, OpenStreetMap relation role, OSM tag or key, OSM tag (wd:P1282 as p): OpenStreetMap tagging schema (a Key:key, Tag:key=value, Relation:type, or Role:role) for classes, properties, and values
5. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as wdt/p): work where this item is described, attested in
6. properties for this type, also known as uses properties, Wikidata properties for this type, Wikidata properties for this class, uses property, things one could say about (wd:P1963 as wdt/p): when this subject is used as object of “instance of”, the following properties normally apply
7. Freebase ID, also known as Freebase, MID, Freebase identifier, FID (wd:P646 as wdt/p): identifier for a page in the Freebase database. Format: "/m/0" f...r IDs starting with "/g/", use Google Knowledge Graph ID (P2671)
8. GND ID, also known as Deutschen Nationalbibliothek ID, Universal Authority File, Integrated Authority File, IndividualisedGnd, GND-IDN (wd:P227 as wdt/p/wdtn): identifier from an international authority file of names, subjects, and organizations
9. PSH ID, also known as Czech Technical Library ID, PSH, PSH identifier (wd:P1051 as wdt/p): identifier in the authority database of the Czech Technical Library
10. FactGrid item ID, also known as FG ID, FactGrid ID (wd:P8168 as wdt/p/wdtn): identifier for an item in FactGrid

No other items found

[Assistant] The search for a property related to location for caves did not return a useful property either. I will try searching for properties related to "located in" or "country" in general to see if there is a common property used for geographic containment.

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

[Assistant] The property "located in the administrative territorial entity" (wdt:P131) seems to be the most appropriate for linking caves to countries or administrative regions. I will now try to write a SPARQL query that counts caves (wd:Q35509) located in countries (wd:Q6256) using this property and filters for countries with more than ten caves.

[Tool]
Got 4 rows and 2 columns:
| country              | caveCount     |
| -------------------- | ------------- |
| Montenegro (wd:Q236) | 161 (xsd:int) |
| Libya (wd:Q1016)     | 80 (xsd:int)  |
| Indonesia (wd:Q252)  | 17 (xsd:int)  |
| Kosovo (wd:Q1246)    | 15 (xsd:int)  |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?city ?cityLabel ?population WHERE {
  VALUES ?county {
    wd:Q112915 wd:Q128077 wd:Q138141 wd:Q490505 wd:Q495974 wd:Q495998 wd:Q496862 wd:Q496886 wd:Q497795 wd:Q497810 wd:Q497812 wd:Q497813 wd:Q497814 wd:Q497815 wd:Q497816 wd:Q497817 wd:Q497818 wd:Q497819 wd:Q497820 wd:Q502459 wd:Q502463 wd:Q502468 wd:Q502564 wd:Q502587
  }
  ?city wdt:P31 wd:Q515 ; wdt:P1082 ?population ; wdt:P131 ?county .
  FILTER ( ?population > 100000 ) OPTIONAL {
    ?city rdfs:label ?cityLabel FILTER ( LANG( ?cityLabel ) = "en" )
  }
}
ORDER BY DESC ( ?population )

No cities in New Jersey with more than 100000 inhabitants were found in Wikidata using the given criteria.

[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 http://amur:7001

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

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

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

[User] Give me all cities in New Jersey with more than 100000 inhabitants.

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

[Tool]
Example 1:
Question:
Show me all U.S. states.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q35657 .
}

Using entities:
U.S. state, also known as U.S. states, US state, USA state, U.S.A. state, United States states (wd:Q35657): constituent political entity of the United States of America

Using properties:
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:
Give me all soccer clubs in the Premier League.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q476028 .
  ?uri wdt:P118 wd:Q9448 .
}

Using entities:
association football club, also known as association soccer club, F.C., FC, football club, soccer club (wd:Q476028): sports club devoted to association football (soccer)
Premier League, also known as England Premier League, English Premier League, English Premiership, EPL, PL (wd:Q9448): English men's association football top league

Using properties:
league or competition, also known as tournament, sports league, division, cup, competition (wd:P118 as wdt): league or competition in which team or player has played, or in which an event occurs, participant in
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:
What are the five boroughs of New York?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q408804 .
}

Using entities:
borough of New York City, also known as Five Boroughs, borough of the City of New York (wd:Q408804): administrative division of New York City, United States of America, administrative division of New York City, USA

Using properties:
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]
From the examples, we see that to find cities in a specific state, we need to use the property "instance of" (wdt:P31) for cities and the property "located in the administrative territorial entity" (wdt:P131) for the state. We also need to filter by population using the property "population" (wdt:P1082).

Next, I will search for the entity representing New Jersey to use it in the query.

[Tool]
Top 10 entity alternatives:
1. 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
2. Newark, also known as Brick City, City of Newark, Newark, New Jersey, Newark, NJ (wd:Q25395): city in Essex County, New Jersey, United States
3. Newton, also known as Newton, New Jersey, Newton, NJ (wd:Q1089234): town in Sussex County, New Jersey, United States
4. Newfield, also known as Newfield, NJ, Newfield, New Jersey (wd:Q931145): borough in New Jersey
5. New Jersey (wd:Q779923): 1988 studio album by Bon Jovi
6. Province of New Jersey, also known as New Jersey, New Jersey Colony, Colony of New Jersey (wd:Q2335128): former colony in North America, part of Great Britain
7. Newfoundland, also known as Newfoundland, New Jersey (wd:Q7017818): unincorporated community in New Jersey, United States
8. Newtonville, also known as Newtonville, New Jersey, Newtonville, NJ (wd:Q14705810): unincorporated community in Atlantic County, New Jersey, United States
9. Newport, also known as Newport, New Jersey (wd:Q7018698): human settlement in Downe Township, New Jersey, United States of America
10. Newtown, also known as Newtown, New Jersey (wd:Q20657441): human settlement in Piscataway, New Jersey, United States of America

[Assistant] The entity representing the state of New Jersey is wd:Q1408. Next, I will search for the property that represents population to confirm its identifier.

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

[Assistant] The property representing population is wdt:P1082. Next, I will search for the entity representing "city" to use it as the instance type in the query.

[Tool]
Top 10 entity alternatives:
1. city, also known as cities (wd:Q515): large human settlement
2. Manchester City F.C., also known as The Sky Blues, City, The Citizens, The Blues, Sky Blues (wd:Q50602): association football club in Manchester, England
3. Leicester City F.C., also known as The Foxes, Leicester Fosse Football Club, Leicester Fosse FC, Leicester Fosse, Leicester City (wd:Q19481): association football club in Leicester, England
4. Swansea City A.F.C., also known as Swansea City Association Football Club, The Swans, The Jacks, Swansea City AFC, Swansea City (wd:Q18659): association football club in Swansea, Wales
5. Stoke City F.C., also known as City, SCFC, Stoke, Stoke City, Stoke City FC (wd:Q18736): association football club in Stoke-on-Trent, England
6. Birmingham City F.C., also known as BCFC, City, Blues, Birmingham City Football Club, Birmingham City (wd:Q19444): association football club in Birmingham, England
7. Norwich City F.C., also known as Norwich City FC, The Canaries, Norwich City Football Club, Norwich City, Norwich (wd:Q18721): association football club in Norwich, England
8. Cardiff City F.C., also known as Cardiff, The Bluebirds, City, CCFC, Cardiff City Football Club (wd:Q18662): association football club in Cardiff, Wales
9. Hull City A.F.C., also known as City, HCAFC, Hull, Hull City, Hull City AFC (wd:Q19477): association football club in Hull, England
10. Coventry City F.C., also known as Coventry City FC, Sky Blues, Coventry City Football Club, Coventry City, Coventry (wd:Q19580): association football club in Coventry, England

[Assistant] The entity representing city is wd:Q515. Now I will write a SPARQL query to get all cities (wd:Q515) located in New Jersey (wd:Q1408) with a population greater than 100000 (wdt:P1082 > 100000). I will also include the city label and population in the results.

[Tool] Got no rows and 3 columns

[Assistant] The query returned no results, which might be because some cities in New Jersey are not directly linked with "located in the administrative territorial entity" (wdt:P131) to New Jersey but rather to counties or other subdivisions. I will try to use the property "located in the administrative territorial entity" (wdt:P131) recursively to include cities located in subdivisions of New Jersey.

[Tool] Got no rows and 3 columns

[Assistant] The recursive query also returned no results. It is possible that the classification of cities in New Jersey is not strictly under the entity "city" (wd:Q515) but might be under other subclasses like "human settlement" or "town". I will try to broaden the instance of (wdt:P31) to include "human settlement" (wd:Q486972) instead of just "city".

[Tool] Got no rows and 3 columns

[Assistant] The broader class "human settlement" also returned no results. I will now try to find all entities that are located in New Jersey (wd:Q1408) and have population greater than 100000 without restricting the instance type to see what kind of entities are returned. This might help identify the correct classification for cities in New Jersey.

[Tool]
Got 10 rows and 3 columns:
| entity                                                       | entityLabel                                       | population            |
| ------------------------------------------------------------ | ------------------------------------------------- | --------------------- |
| Delaware Valley (wd:Q1925894)                                | Delaware Valley (en)                              | 6245051 (xsd:decimal) |
| Roman Catholic Archdiocese of Newark (wd:Q1365140)           | Roman Catholic Archdiocese of Newark (en)         | 3250000 (xsd:decimal) |
| Roman Catholic Diocese of Trenton (wd:Q877475)               | Roman Catholic Diocese of Trenton (en)            | 2039060 (xsd:decimal) |
| Roman Catholic Diocese of Metuchen (wd:Q646346)              | Roman Catholic Diocese of Metuchen (en)           | 1410087 (xsd:decimal) |
| Roman Catholic Diocese of Paterson (wd:Q164614)              | Roman Catholic Diocese of Paterson (en)           | 1156880 (xsd:decimal) |
| Bergen County (wd:Q112915)                                   | Bergen County (en)                                | 955732 (xsd:decimal)  |
| Essex County (wd:Q128077)                                    | Essex County (en)                                 | 863728 (xsd:decimal)  |
| Middlesex County (wd:Q496862)                                | Middlesex County (en)                             | 863162 (xsd:decimal)  |
| Allentown-Bethlehem-Easton metropolitan area (wd:Q113137311) | Allentown-Bethlehem-Easton metropolitan area (en) | 861889 (xsd:decimal)  |
| Hudson County (wd:Q490505)                                   | Hudson County (en)                                | 724854 (xsd:decimal)  |

[Assistant]
The results show that entities located in New Jersey with population over 100000 include counties and dioceses, but no cities. This suggests that cities might not be directly linked to New Jersey or its subdivisions with the property "located in the administrative territorial entity" (wdt:P131).

I will now try to find cities in New Jersey by checking for entities that are instance of "city" (wd:Q515) and have "located in the administrative territorial entity" (wdt:P131) New Jersey (wd:Q1408) directly, without the population filter, to see if any cities are linked this way.

[Tool] Got no rows and 2 columns

[Assistant] There are no cities directly linked to New Jersey (wd:Q1408) with the property "located in the administrative territorial entity" (wdt:P131). I will now try to find cities in New Jersey by checking for entities that are instance of "city" (wd:Q515) and have "located in the administrative territorial entity" (wdt:P131) a county in New Jersey. I will first find counties in New Jersey.

[Tool] Got no rows and 2 columns

[Assistant] There are no counties directly linked to New Jersey (wd:Q1408) with the property "located in the administrative territorial entity" (wdt:P131). I will try to find counties that are instance of "county of the United States" (wd:Q131569) and located in New Jersey using the property "located in or next to body of water" (wdt:P206) or other location properties.

[Tool]
Top 10 property alternatives:
1. located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as wdt/p): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
2. contains the administrative territorial entity, also known as has shires, has rural cities, has regions, has municipalities, has members (wd:P150 as wdt/p): (list of) direct subdivisions of an administrative territorial entity, has part(s)
3. capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as wdt/p): seat of government of a country, province, state or other type of administrative territorial entity
4. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
5. legislative body, also known as aboriginal council, Zila, Tehsil, rural council, representative body (wd:P194 as wdt/p): legislative body governing this entity; political institution wi...ted representatives, such as a parliament/legislature or council
6. highest judicial authority, also known as supreme court, judiciary, judicial branch, has supreme court, court (wd:P209 as wdt/p): supreme judicial body within a country, administrative division, or other organization

No other items found

[Assistant] The property "located in the administrative territorial entity" (wdt:P131) is the correct property to use for location, but it seems that counties are not directly linked to New Jersey with this property. I will try to find counties that have New Jersey as their "country" (wdt:P17) or "state" (wdt:P131) to see if there is a different way to link them.

[Tool]
Got 10 rows and 2 columns:
| county                                                           | countyLabel                                           |
| ---------------------------------------------------------------- | ----------------------------------------------------- |
| Treaty of New Echota (wd:Q1049395)                               | Treaty of New Echota (en)                             |
| Great Treaty of 1722 (wd:Q107722799)                             | Great Treaty of 1722 (en)                             |
| Treaty with the Winnebago (wd:Q108203604)                        | Treaty with the Winnebago (en)                        |
| Treaty of Tripoli (wd:Q108427838)                                | Treaty of Tripoli (en)                                |
| Millennium Challenge Corporation's Nepal Compact (wd:Q108619583) | Millennium Challenge Corporation's Nepal Compact (en) |
| Treaty of Castor Hill (wd:Q109536004)                            | Treaty of Castor Hill (en)                            |
| Treaty with the Delawares, 1854 (wd:Q111530447)                  | Treaty with the Delawares, 1854 (en)                  |
| Treaty with the Wyandot, 1855 (wd:Q111540375)                    | Treaty with the Wyandot, 1855 (en)                    |
| Treaty with the Shawnee, 1854 (wd:Q111540627)                    | Treaty with the Shawnee, 1854 (en)                    |
| Treaty with the Kickapoo, 1854 (wd:Q111540860)                   | Treaty with the Kickapoo, 1854 (en)                   |

[Assistant] The query returned treaties instead of counties, which means the instance of county (wd:Q131569) might not be correctly used or counties in New Jersey are not classified under this entity. I will try to find all entities that are instance of "county" or subclass of "county" to identify the correct entity for counties in New Jersey.

[Tool]
Top 10 entity alternatives:
1. county, also known as County (wd:Q28575): geographical and administrative region in some countries
2. county of the United States, also known as county of a state of the United States of America, county of the United States of America, county (United States), U.S. county, US county (wd:Q47168): subdivision used by most states in the United States of America
3. Derby County F.C., also known as The Rams, Derby County FC, Derby, DCFC, Derby County (wd:Q19470): association football club in Derby, England
4. county of England, also known as counties of England, Counties of England, County, English county (wd:Q171809): administrative, geographical and political demarcation of England, United Kingdom, England's administrative, geographical and political demarcation
5. Notts County F.C., also known as Notts, The Magpies, Notts County Football Club, Notts County FC, Notts County (wd:Q19598): association football club in Nottingham, England
6. county of China, also known as counties of China, county, county in China, county-level division, county-level division of China (wd:Q1289426): People's Republic of China county-level subdivision
7. Stockport County F.C., also known as County, The Hatters, Stockport County Football Club, Stockport County FC, Stockport (wd:Q18526): association football club in Stockport, England
8. Newport County A.F.C., also known as The Exiles, NCAFC, Newport County Association Football Club, Newport County AFC, Newport (wd:Q18523): association football club in Newport, Wales
9. shire, also known as county (wd:Q662296): traditional term for a division of land, found in some English-speaking countries
10. county (wd:Q1776764): first level administrative division of Romania

[Assistant] The entity for county of the United States is wd:Q47168. I will now try to find counties (wd:Q47168) located in New Jersey (wd:Q1408) using the property "located in the administrative territorial entity" (wdt:P131).

[Tool] Got no rows and 2 columns

[Assistant] There are no counties of the United States (wd:Q47168) directly linked to New Jersey (wd:Q1408) with the property "located in the administrative territorial entity" (wdt:P131). I will try to find counties that have New Jersey as their "state" using the property "state" (wdt:P131) or "located in the administrative territorial entity" (wdt:P131) recursively.

[Tool] Got no rows and 2 columns

[Assistant] There are no counties of the United States (wd:Q47168) linked to New Jersey (wd:Q1408) even with recursive location property. I will try a different approach: I will search for cities in New Jersey by searching for entities that have "located in the administrative territorial entity" (wdt:P131) New Jersey (wd:Q1408) and are instance of any subclass of "city" or "human settlement". I will first find subclasses of city (wd:Q515).

[Tool]
Got 10 rows and 2 columns:
| subclass                             | subclassLabel                |
| ------------------------------------ | ---------------------------- |
| city of the Philippines (wd:Q104157) | city of the Philippines (en) |
| 100 percent corner (wd:Q104414508)   | 100 percent corner (en)      |
| wd:Q10499171                         |                              |
| wd:Q10500900                         | fortress city (en)           |
| national central city (wd:Q1066538)  | national central city (en)   |
| wd:Q10717529                         |                              |
| half million city (wd:Q108454687)    | half million city (en)       |
| circular city (wd:Q108525740)        | circular city (en)           |
| state city of Latvia (wd:Q109329953) | state city of Latvia (en)    |
| wd:Q109357164                        |                              |

[Assistant] There are some subclasses of city, but they seem to be very specific or not relevant for New Jersey. I will try to find subclasses of "human settlement" (wd:Q486972) instead.

[Tool]
Got 10 rows and 2 columns:
| subclass                          | subclassLabel           |
| --------------------------------- | ----------------------- |
| wd:Q100588007                     |                         |
| wd:Q1006421                       |                         |
| wd:Q101627493                     |                         |
| seaside resort (wd:Q1021711)      | seaside resort (en)     |
| rural settlement (wd:Q10354598)   | rural settlement (en)   |
| Water town (China) (wd:Q10377997) | Water town (China) (en) |
| wd:Q10425988                      |                         |
| vicus (wd:Q104530309)             | vicus (en)              |
| wd:Q104641871                     |                         |
| wd:Q105085639                     |                         |

[Assistant] The subclasses of human settlement do not seem to include common city types for New Jersey. I will try a different approach: I will search for cities in New Jersey by searching for entities that have "located in the administrative territorial entity" (wdt:P131) New Jersey (wd:Q1408) and have a population (wdt:P1082) greater than 100000, without restricting the instance type. Then I will check their labels and types to identify cities.

[Tool]
Got 10 rows and 5 columns:
| entity                                                       | entityLabel                                       | population            | type                                         | typeLabel                           |
| ------------------------------------------------------------ | ------------------------------------------------- | --------------------- | -------------------------------------------- | ----------------------------------- |
| Delaware Valley (wd:Q1925894)                                | Delaware Valley (en)                              | 6245051 (xsd:decimal) | metropolitan statistical area (wd:Q1768043)  | metropolitan statistical area (en)  |
| Roman Catholic Diocese of Trenton (wd:Q877475)               | Roman Catholic Diocese of Trenton (en)            | 2039060 (xsd:decimal) | diocese of the Catholic Church (wd:Q3146899) | diocese of the Catholic Church (en) |
| Roman Catholic Diocese of Metuchen (wd:Q646346)              | Roman Catholic Diocese of Metuchen (en)           | 1410087 (xsd:decimal) | diocese of the Catholic Church (wd:Q3146899) | diocese of the Catholic Church (en) |
| Roman Catholic Diocese of Paterson (wd:Q164614)              | Roman Catholic Diocese of Paterson (en)           | 1156880 (xsd:decimal) | diocese of the Catholic Church (wd:Q3146899) | diocese of the Catholic Church (en) |
| Bergen County (wd:Q112915)                                   | Bergen County (en)                                | 955732 (xsd:decimal)  | county of New Jersey (wd:Q13414754)          | county of New Jersey (en)           |
| Essex County (wd:Q128077)                                    | Essex County (en)                                 | 863728 (xsd:decimal)  | county of New Jersey (wd:Q13414754)          | county of New Jersey (en)           |
| Middlesex County (wd:Q496862)                                | Middlesex County (en)                             | 863162 (xsd:decimal)  | county of New Jersey (wd:Q13414754)          | county of New Jersey (en)           |
| Allentown-Bethlehem-Easton metropolitan area (wd:Q113137311) | Allentown-Bethlehem-Easton metropolitan area (en) | 861889 (xsd:decimal)  | metropolitan statistical area (wd:Q1768043)  | metropolitan statistical area (en)  |
| Hudson County (wd:Q490505)                                   | Hudson County (en)                                | 724854 (xsd:decimal)  | county of New Jersey (wd:Q13414754)          | county of New Jersey (en)           |
| Monmouth County (wd:Q502424)                                 | Monmouth County (en)                              | 643615 (xsd:decimal)  | county of New Jersey (wd:Q13414754)          | county of New Jersey (en)           |

[Assistant] The results show counties and metropolitan areas but no cities. It seems that cities in New Jersey are not directly linked to New Jersey with the property "located in the administrative territorial entity" (wdt:P131). I will try to find cities in New Jersey by searching for entities that are instance of "city" (wd:Q515) and have a population greater than 100000, without restricting the location, and then check if any of them are located in New Jersey by their label or other properties.

[Tool]
Got 20 rows and 3 columns, showing the first 5 and last 5 rows below:
| city                 | cityLabel      | population             |
| -------------------- | -------------- | ---------------------- |
| Chengdu (wd:Q30002)  | Chengdu (en)   | 20937757 (xsd:decimal) |
| Shenzhen (wd:Q15174) | Shenzhen (en)  | 17681600 (xsd:decimal) |
| Shenzhen (wd:Q15174) | Shenzhen (en)  | 17494398 (xsd:decimal) |
| Dhaka (wd:Q1354)     | Dhaka (en)     | 16800000 (xsd:decimal) |
| Mumbai (wd:Q1156)    | Mumbai (en)    | 15414288 (xsd:decimal) |
| ...                  | ...            | ...                    |
| São Paulo (wd:Q174)  | São Paulo (en) | 11316149 (xsd:decimal) |
| São Paulo (wd:Q174)  | São Paulo (en) | 11253503 (xsd:decimal) |
| Lahore (wd:Q11739)   | Lahore (en)    | 11126285 (xsd:decimal) |
| São Paulo (wd:Q174)  | São Paulo (en) | 10886534 (xsd:decimal) |
| Harbin (wd:Q42956)   | Harbin (en)    | 10635971 (xsd:decimal) |

[Assistant] The query returned cities with population greater than 100000 globally, but none of the top results are cities in New Jersey. I will now try to find cities in New Jersey by searching for entities that have "located in the administrative territorial entity" (wdt:P131) New Jersey (wd:Q1408) and are instance of "municipality" (wd:Q15284) or "city" (wd:Q515). I will try both instance types separately. First, I will try "municipality".

[Tool] Got no rows and 3 columns

[Assistant] There are no municipalities (wd:Q15284) directly linked to New Jersey (wd:Q1408) with population greater than 100000. I will now try the same query but for cities (wd:Q515).

[Tool] Got no rows and 3 columns

[Assistant] There are no cities (wd:Q515) directly linked to New Jersey (wd:Q1408) with population greater than 100000. I will now try to find cities in New Jersey by searching for entities that are instance of "city" (wd:Q515) and have a population greater than 100000, and then filter those whose label contains "New Jersey" or "NJ" as a heuristic to identify cities in New Jersey.

[Tool]
Got 9 rows and 3 columns:
| city                      | cityLabel         | population             |
| ------------------------- | ----------------- | ---------------------- |
| Tianjin (wd:Q11736)       | Tianjin (en)      | 13866009 (xsd:decimal) |
| Tianjin (wd:Q11736)       | Tianjin (en)      | 13245000 (xsd:decimal) |
| Nanjing (wd:Q16666)       | Nanjing (en)      | 9314685 (xsd:decimal)  |
| Nanjing (wd:Q16666)       | Nanjing (en)      | 8187800 (xsd:decimal)  |
| Malanje (wd:Q621001)      | Malanje (en)      | 604215 (xsd:decimal)   |
| Ichalkaranji (wd:Q583818) | Ichalkaranji (en) | 287570 (xsd:decimal)   |
| Jinja (wd:Q501709)        | Jinja (en)        | 279184 (xsd:decimal)   |
| Thanjavur (wd:Q41496)     | Thanjavur (en)    | 222943 (xsd:decimal)   |
| Banja Luka (wd:Q131127)   | Banja Luka (en)   | 185042 (xsd:decimal)   |

[Assistant]
The heuristic filter for city labels containing "New Jersey" or "NJ" did not return any cities in New Jersey. It seems that the data for cities in New Jersey is not directly linked or labeled in a way that is easily queryable with the properties and entities we tried.

Given the difficulty in finding cities in New Jersey with population over 100000 using direct properties, I will now try to find cities in New Jersey by searching for cities that have a "located in the administrative territorial entity" (wdt:P131) some entity that is a subdivision of New Jersey (wd:Q1408). I will first find subdivisions of New Jersey.

[Tool] Got no rows and 2 columns

[Assistant] There are no subdivisions of New Jersey (wd:Q1408) with instance of "subdivision of the United States" (wd:Q10864048) directly linked with the property "located in the administrative territorial entity" (wdt:P131). I will try to find subdivisions of New Jersey using the property "contains the administrative territorial entity" (wdt:P150) instead.

[Tool]
Got 10 rows and 2 columns:
| subdivision                    | subdivisionLabel       |
| ------------------------------ | ---------------------- |
| Bergen County (wd:Q112915)     | Bergen County (en)     |
| Essex County (wd:Q128077)      | Essex County (en)      |
| Burlington County (wd:Q138141) | Burlington County (en) |
| Hudson County (wd:Q490505)     | Hudson County (en)     |
| Passaic County (wd:Q495974)    | Passaic County (en)    |
| Sussex County (wd:Q495998)     | Sussex County (en)     |
| Middlesex County (wd:Q496862)  | Middlesex County (en)  |
| Mercer County (wd:Q496886)     | Mercer County (en)     |
| Cape May County (wd:Q497795)   | Cape May County (en)   |
| Camden County (wd:Q497810)     | Camden County (en)     |

[Assistant] I found subdivisions of New Jersey (wd:Q1408) which are counties. Now I will find cities (wd:Q515) located in these counties with population greater than 100000.

[Tool] Got no rows and 3 columns

[Assistant]
There are no cities (wd:Q515) with population greater than 100000 located in counties that are subdivisions of New Jersey (wd:Q1408) using the property "located in the administrative territorial entity" (wdt:P131).

I will now try to find cities located in these counties using a broader property "part of" (wdt:P361) instead of "located in the administrative territorial entity" (wdt:P131).

[Tool] Got no rows and 3 columns

[Assistant]
There are no cities (wd:Q515) with population greater than 100000 that are part of counties which are subdivisions of New Jersey (wd:Q1408) using the property "part of" (wdt:P361).

Given the difficulty in finding cities in New Jersey with population over 100000 using direct properties, I will now try to find cities in New Jersey by searching for entities that are instance of "city" (wd:Q515) and have a population greater than 100000, and then filter those whose administrative territorial entity (wdt:P131) is any of the counties of New Jersey. I will first get the list of counties of New Jersey.

[Tool]
Got 21 rows and 1 column, showing the first 5 and last 5 rows below:
| county                         |
| ------------------------------ |
| Bergen County (wd:Q112915)     |
| Essex County (wd:Q128077)      |
| Burlington County (wd:Q138141) |
| Hudson County (wd:Q490505)     |
| Passaic County (wd:Q495974)    |
| ...                            |
| Union County (wd:Q502459)      |
| Gloucester County (wd:Q502463) |
| Warren County (wd:Q502468)     |
| Ocean County (wd:Q502564)      |
| Salem County (wd:Q502587)      |

[Assistant] I have the list of counties of New Jersey. Now I will find cities (wd:Q515) with population greater than 100000 that have one of these counties as their administrative territorial entity (wdt:P131).

[Tool] Got no rows and 3 columns

[Assistant]
There are no cities (wd:Q515) with population greater than 100000 that have one of the counties of New Jersey as their administrative territorial entity (wdt:P131).

Given the difficulty in finding cities in New Jersey with population over 100000 using direct properties, it is possible that the data is not modeled in a way that allows a straightforward query for this information in Wikidata.

I will now provide a final answer stating that no such cities were found with the given criteria in Wikidata.

[Tool] Stopped generation process


PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?date WHERE {
  wd:Q211 p:P463 ?statement .
  ?statement ps:P463 wd:Q458 .
  ?statement pq:P580 ?date .
}

Latvia joined the European Union on May 1, 2004.

[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 http://amur:7001

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

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

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

[User] When did Latvia join the EU?

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

[Tool] No examples found

[Assistant] There are no direct example queries for this question, so I will proceed by identifying the entity for Latvia and the property related to joining the European Union. Then I will build a query to find the date Latvia joined the EU. First, I will search for the entity "Latvia" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Latvia, also known as Latvija, Republic of Latvia, LVA, lv, Leţmо̄ Vabāmо̄ (wd:Q211): sovereign state in northeastern Europe
2. 1284 Latvia, also known as Latvia (wd:Q137583): asteroid
3. RAF-977, also known as Latvia, RAF-977D (wd:Q2425377): soviet bustype
4. RAF-2203, also known as Latvia (wd:Q1065645): van and minibus manufactured by Rīgas Autobusu Fabrika in Latvia
5. Latvia (wd:Q6497226): constituency of the European Parliament
6. Latvia (wd:Q104537040)
7. Latvia (wd:Q104892776): scientific article published in December 2012
8. Latvia (wd:Q58040021)
9. Latvia (wd:Q103948319): encyclopedia article
10. Latvia (wd:L254271)

[Assistant] The entity for Latvia as a sovereign state in northeastern Europe is wd:Q211. Next, I will search for properties related to joining the European Union for this entity. I will search for properties of Latvia with the query "European Union".

[Tool]
Top 10 property alternatives:
1. Encyclopedia of the History of Ukraine ID, also known as EHU, EIY, history.org.ua, ЕІУ (wd:P8935 as wdt/p): ID for an entry on the official website of the Encyclopedia of the History of Ukraine
2. legislative body, also known as aboriginal council, Zila, Tehsil, rural council, representative body (wd:P194 as wdt/p): legislative body governing this entity; political institution wi...ted representatives, such as a parliament/legislature or council
3. subreddit, also known as r/, reddit, Reddit community ID, Reddit forum, Reddit sub ID (wd:P3984 as wdt/p): name of the Reddit forum associated to this subject
4. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as wdt/p): URL of the official page of an item (current or former). Usage: ...but see the "Hijacked or dead websites" section of the Talk page, URL
5. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as wdt/p): work where this item is described, attested in
6. Enzyklopädie des europäischen Ostens ID (wd:P9498 as wdt/p): identifier for an article in the Enzyklopädie des europäischen Ostens
7. EU Knowledge Graph item ID, also known as EU Knowledge Graph item identifier (wd:P11012 as wdt/p/wdtn): identifier for the corresponding entity in the EU Knowledge Graph
8. contains the administrative territorial entity, also known as has shires, has rural cities, has regions, has municipalities, has members (wd:P150 as wdt/p): (list of) direct subdivisions of an administrative territorial entity, has part(s)
9. member of, also known as band member of, membership, member of musical group, in musical group, be member of (wd:P463 as wdt/p): organization, club or musical group to which the subject belongs...ical position, such as a member of parliament (use P39 for that), part of
10. basic form of government, also known as form of government, government, type of government (wd:P122 as wdt/p): subject's government

No other items found

[Assistant] The property "member of" (wdt:P463) seems relevant as it indicates membership in an organization, which can include the European Union. I will now query the date when Latvia (wd:Q211) became a member of the European Union using this property. The date of joining is likely recorded as a qualifier or statement related to this membership. I will write a query to find the date when Latvia became a member of the European Union (wd:Q458).

[Tool]
Got 1 row and 1 column:
| date                                |
| ----------------------------------- |
| 2004-05-01T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?chancellor ?chancellorLabel WHERE {
  ?chancellor wdt:P39 wd:Q4970706 .
  OPTIONAL {
    ?chancellor rdfs:label ?chancellorLabel FILTER ( LANG( ?chancellorLabel ) = "en" )
  }
}

Got 10 rows and 2 columns:
| chancellor                      | chancellorLabel           |
| ------------------------------- | ------------------------- |
| Konrad Adenauer (wd:Q2492)      | Konrad Adenauer (en)      |
| Ludwig Erhard (wd:Q2496)        | Ludwig Erhard (en)        |
| Kurt Georg Kiesinger (wd:Q2512) | Kurt Georg Kiesinger (en) |
| Willy Brandt (wd:Q2514)         | Willy Brandt (en)         |
| Helmut Schmidt (wd:Q2516)       | Helmut Schmidt (en)       |
| Helmut Kohl (wd:Q2518)          | Helmut Kohl (en)          |
| Gerhard Schröder (wd:Q2530)     | Gerhard Schröder (en)     |
| Walter Scheel (wd:Q2571)        | Walter Scheel (en)        |
| Angela Merkel (wd:Q567)         | Angela Merkel (en)        |
| Olaf Scholz (wd:Q61053)         | Olaf Scholz (en)          |

The federal chancellors of Germany are Konrad Adenauer, Ludwig Erhard, Kurt Georg Kiesinger, Willy Brandt, Helmut Schmidt, Helmut Kohl, Gerhard Schröder, Walter Scheel, Angela Merkel, and Olaf Scholz.

[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 http://amur:7001

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

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

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

[User] Give me all federal chancellors of Germany.

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

[Tool]
Example 1:
Question:
Give me all federal chancellors of Germany.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P39 wd:Q4970706 .
}

Using entities:
Federal Chancellor of Germany, also known as German Federal Chancellor, prime minister of Germany, German Chancellor, Federal Chancellor of the Federal Republic of Germany, Federal Chancellor (wd:Q4970706): head of government of the Federal Republic of Germany (1949–present)

Using properties:
position held, also known as function, held position, holds position, job, office held (wd:P39 as wdt): subject currently or formerly holds the object position or public office

Example 2:
Question:
Show me all U.S. states.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q35657 .
}

Using entities:
U.S. state, also known as U.S. states, US state, USA state, U.S.A. state, United States states (wd:Q35657): constituent political entity of the United States of America

Using properties:
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:
Give me all soccer clubs in the Premier League.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q476028 .
  ?uri wdt:P118 wd:Q9448 .
}

Using entities:
association football club, also known as association soccer club, F.C., FC, football club, soccer club (wd:Q476028): sports club devoted to association football (soccer)
Premier League, also known as England Premier League, English Premier League, English Premiership, EPL, PL (wd:Q9448): English men's association football top league

Using properties:
league or competition, also known as tournament, sports league, division, cup, competition (wd:P118 as wdt): league or competition in which team or player has played, or in which an event occurs, participant in
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]
From the similar example found, the federal chancellor of Germany corresponds to the entity wd:Q4970706 and the property "position held" corresponds to wd:P39. We can use these to construct a query that retrieves all entities that held the position of federal chancellor of Germany.

I will now write a SPARQL query to get all federal chancellors of Germany using these identifiers.

[Tool]
Got 10 rows and 2 columns:
| chancellor                      | chancellorLabel           |
| ------------------------------- | ------------------------- |
| Konrad Adenauer (wd:Q2492)      | Konrad Adenauer (en)      |
| Ludwig Erhard (wd:Q2496)        | Ludwig Erhard (en)        |
| Kurt Georg Kiesinger (wd:Q2512) | Kurt Georg Kiesinger (en) |
| Willy Brandt (wd:Q2514)         | Willy Brandt (en)         |
| Helmut Schmidt (wd:Q2516)       | Helmut Schmidt (en)       |
| Helmut Kohl (wd:Q2518)          | Helmut Kohl (en)          |
| Gerhard Schröder (wd:Q2530)     | Gerhard Schröder (en)     |
| Walter Scheel (wd:Q2571)        | Walter Scheel (en)        |
| Angela Merkel (wd:Q567)         | Angela Merkel (en)        |
| Olaf Scholz (wd:Q61053)         | Olaf Scholz (en)          |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?actor ?actorLabel ?birthday WHERE {
  wd:Q162371 wdt:P161 ?actor .
  ?actor wdt:P569 ?birthday .
  OPTIONAL {
    ?actor rdfs:label ?actorLabel FILTER ( LANG( ?actorLabel ) = "en" )
  }
}

The birthdays of the actors of the television show Charmed are:
- Holly Marie Combs: December 3, 1973
- Alyssa Milano: December 19, 1972
- Shannen Doherty: April 12, 1971
- Rose McGowan: September 5, 1973

[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 http://amur:7001

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

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

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

[User] Give me the birthdays of all actors of the television show Charmed.

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

[Tool] No examples found

[Assistant] No similar examples found. Next, I will search for the entity "Charmed" to identify the television show in Wikidata. Then I will find the actors of this show and their birthdays.

[Tool]
Top 10 entity alternatives:
1. Charmed (wd:Q162371): American supernatural drama / fantasy television series (1998–2006)
2. Charmed (wd:Q53162693): American television series, reboot of Charmed (1998–2006)
3. Charmed (wd:Q1067576): Norwegian musical group
4. Charmed, also known as Charmed (comics) (wd:Q2564039): comic book that is an officially licensed continuation of the popular The WB television series of the same name
5. Charmed (wd:Q11963476): 2000 self-titled debut studio album by Charmed
6. Charmed (wd:Q5086449): video game based on the fourth season of the television series of the same name
7. Charmed (wd:Q133201824)
8. Charmed (wd:Q128008863): episode of The Little Mermaid (S1 E7)
9. charmed (wd:L8016-F3)
10. charmed (wd:L8016-F5)

[Assistant] The television show "Charmed" is identified as wd:Q162371 in Wikidata. Next, I will find the actors of this television show. Typically, actors are linked with the property "cast member" (wdt:P161) for a television show. I will query the cast members of Charmed (wd:Q162371).

[Tool]
Got 4 rows and 2 columns:
| actor                          | actorLabel             |
| ------------------------------ | ---------------------- |
| Holly Marie Combs (wd:Q162578) | Holly Marie Combs (en) |
| Alyssa Milano (wd:Q189067)     | Alyssa Milano (en)     |
| Shannen Doherty (wd:Q207598)   | Shannen Doherty (en)   |
| Rose McGowan (wd:Q211040)      | Rose McGowan (en)      |

[Assistant] I found four actors of the television show Charmed: Holly Marie Combs, Alyssa Milano, Shannen Doherty, and Rose McGowan. Now, I will find the birthdays of these actors. The property for date of birth in Wikidata is P569. I will query the birthdays of these actors.

[Tool]
Got 4 rows and 3 columns:
| actor                          | actorLabel             | birthday                            |
| ------------------------------ | ---------------------- | ----------------------------------- |
| Holly Marie Combs (wd:Q162578) | Holly Marie Combs (en) | 1973-12-03T00:00:00Z (xsd:dateTime) |
| Alyssa Milano (wd:Q189067)     | Alyssa Milano (en)     | 1972-12-19T00:00:00Z (xsd:dateTime) |
| Shannen Doherty (wd:Q207598)   | Shannen Doherty (en)   | 1971-04-12T00:00:00Z (xsd:dateTime) |
| Rose McGowan (wd:Q211040)      | Rose McGowan (en)      | 1973-09-05T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?lake ?lakeLabel ?country ?countryLabel WHERE {
  VALUES ?lake {
    wd:Q6386177 wd:Q49303749 wd:Q22434937
  }
  ?lake wdt:P17 ?country .
  OPTIONAL {
    ?lake rdfs:label ?lakeLabel FILTER ( LANG( ?lakeLabel ) = "en" )
  }
  OPTIONAL {
    ?country rdfs:label ?countryLabel FILTER ( LANG( ?countryLabel ) = "en" )
  }
}

Got 3 rows and 4 columns:
| lake                         | lakeLabel          | country                | countryLabel       |
| ---------------------------- | ------------------ | ---------------------- | ------------------ |
| Limerick Lake (wd:Q22434937) | Limerick Lake (en) | Canada (wd:Q16)        | Canada (en)        |
| Limerick Lake (wd:Q6386177)  | Limerick Lake (en) | Canada (wd:Q16)        | Canada (en)        |
| Lake Limerick (wd:Q49303749) | Lake Limerick (en) | United States (wd:Q30) | United States (en) |

There are three lakes named Limerick Lake or Lake Limerick. Two of them are in Canada and one is in the United States. Could you please specify which Limerick Lake you are referring to, or do you want the countries for all of them?

[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 http://amur:7001

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] In which country is the Limerick Lake?

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

[Tool] No examples found

[Assistant] There are no similar example questions available. Next, I will search for the entity "Limerick Lake" in Wikidata to find its identifier.

[Tool]
Top 10 entity alternatives:
1. Limerick Lake (wd:Q6386177): lake in Hastings Country, Ontario, Canada
2. Lake Limerick (wd:Q49303749): lake in Mason County, Washington state, United States of America
3. Limerick Lake (wd:Q22434937): lake in Algoma District, Ontario, Canada
4. Lake Limerick Dam (wd:Q48991830): dam impounding Cranberry Creek in Mason County, Washington state, United States of America
5. lake, also known as Lake, lakes (wd:Q23397): body of relatively still water, localized in a basin
6. Limerick, also known as Limerick City, Limrick, Limmerick (wd:Q133315): city in Ireland in the province of Munster
7. County Limerick, also known as Limerick, County Limerick, Ireland (wd:Q178283): county in Ireland
8. limerick, also known as Limerick (wd:Q204698): form of poetry
9. Lake, also known as Lake, Mississippi, Lake, MS (wd:Q2087707): town in Newton and Scott counties, Mississippi, United States
10. Limerick F.C., also known as LFC, Limerick, Limerick FC, Limerick Football Club (wd:Q1552212): association football club in Limerick, Ireland

[Assistant]
There are multiple lakes named Limerick Lake. The top results show three lakes named Limerick Lake:
1. Limerick Lake in Hastings County, Ontario, Canada (wd:Q6386177)
2. Lake Limerick in Mason County, Washington state, United States of America (wd:Q49303749)
3. Limerick Lake in Algoma District, Ontario, Canada (wd:Q22434937)

I will now check the countries for these lakes to confirm the countries they are located in.

[Tool]
Got 3 rows and 4 columns:
| lake                         | lakeLabel          | country                | countryLabel       |
| ---------------------------- | ------------------ | ---------------------- | ------------------ |
| Limerick Lake (wd:Q22434937) | Limerick Lake (en) | Canada (wd:Q16)        | Canada (en)        |
| Limerick Lake (wd:Q6386177)  | Limerick Lake (en) | Canada (wd:Q16)        | Canada (en)        |
| Lake Limerick (wd:Q49303749) | Lake Limerick (en) | United States (wd:Q30) | United States (en) |

[Assistant] There are three lakes named Limerick Lake or Lake Limerick. Two of them are in Canada and one is in the United States. Could you please specify which Limerick Lake you are referring to, or do you want the countries for all of them?


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
ASK WHERE {
  wd:Q1144302 wdt:P171 + wd:Q10908
}

Yes, tree frogs are a type of amphibian as they have a taxonomic parent that is an amphibian.

[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 http://amur:7001

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] Are tree frogs a type of amphibian?

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

[Tool] No examples found

[Assistant] There are no direct example queries for this question, so I will proceed by identifying the entity "tree frog" and the entity "amphibian" in Wikidata. Then I will check if "tree frog" is an instance or subclass of "amphibian" or if it has a taxonomic parent that is an amphibian.

[Tool]
Top 10 entity alternatives:
1. Hylidae, also known as Hylid, Tree frog (wd:Q53696): family of amphibians
2. tree frog (wd:Q1144302): any species of frog that spends a major portion of its lifespan in trees
3. Bokermannohyla izecksohni, also known as Bokermannohyla izeckshoni, Tree frog (wd:Q308753): species of amphibian
4. Rhacophorus lateralis, also known as Small Tree Frog, Tree frog (wd:Q2707407): species of amphibian
5. Leptopelis fiziensis, also known as Tree frog (wd:Q1946641): species of amphibian
6. Tree frog (wd:Q110818899)
7. Hyla arborea, also known as Common Tree Frog, European Tree Frog (wd:Q2142057): species of amphibian
8. red-eyed tree frog, also known as Agalychnis callidryas (wd:Q337616): species of amphibian
9. Australian green tree frog, also known as White's tree frog, Litoria caerulea, green tree frog, Ranoidea caerulea (wd:Q654682): species of amphibian
10. Common tree frog, also known as Polypedates leucomystax (wd:Q2277171): species of amphibian

[Assistant]
I found multiple entities for "tree frog." The most general one seems to be "tree frog" as any species of frog that spends a major portion of its lifespan in trees (wd:Q1144302). There is also a family called Hylidae (wd:Q53696) which is a family of amphibians known as tree frogs.

Next, I will check the entity "amphibian" to confirm its identifier in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Amphibia, also known as amphibian, amphibians (wd:Q10908): class of tetrapods, whose living forms include frogs, toads, salamanders, newts and caecilians
2. amphibious vehicle, also known as amphibian (wd:Q474698): means of transport, viable on land as well as on (or under) water
3. amphibious aircraft, also known as amphibian (wd:Q474709): aircraft that can routinely both operate in water and in land
4. Amphibian (wd:Q15924195): 2005 studio album by Tanya Chua
5. Amphibian, also known as Kingsley Rice (wd:Q4748176): fictional character in Marvel Comics
6. Amphibian (wd:Q125685669): journal article from 'The Global South' published in 2022
7. amphibian (wd:L334419-F1)
8. amphibian (wd:L334419)
9. amphibian (wd:L229297-F1)
10. amphibian (wd:L229297)

[Assistant]
The entity for amphibian as a class of tetrapods including frogs is "Amphibia" with the identifier wd:Q10908.

Now, I will check if "tree frog" (wd:Q1144302) is a subclass or instance of "amphibian" (wd:Q10908).

[Tool] False

[Assistant]
The query checking if "tree frog" (wd:Q1144302) is a subclass of "amphibian" (wd:Q10908) returned false.

I will now check if "tree frog" is an instance (wdt:P31) of "amphibian" or if it has a taxonomic parent that is an amphibian.

[Tool] False

[Assistant]
"Tree frog" (wd:Q1144302) is not directly an instance of "amphibian" (wd:Q10908).

I will check if "tree frog" is a subclass of or instance of a taxonomic group that is a subclass or instance of amphibian. Since the family Hylidae (wd:Q53696) is described as a family of amphibians, I will check if "tree frog" is related to Hylidae or if Hylidae is a subclass of amphibian.

[Tool] False

[Assistant]
The family Hylidae (wd:Q53696) is not a subclass of amphibian (wd:Q10908) according to the subclass property (wdt:P279).

I will check if Hylidae is an instance of amphibian or if it has a taxonomic parent that is an amphibian.

[Tool] False

[Assistant]
Hylidae (wd:Q53696) is not directly an instance of amphibian (wd:Q10908).

I will now check if "tree frog" (wd:Q1144302) or Hylidae (wd:Q53696) have a taxonomic parent (property wdt:P171) that is an amphibian (wd:Q10908). I will start with "tree frog" (wd:Q1144302).

[Tool] True

[Assistant]
The query checking if "tree frog" (wd:Q1144302) has a taxonomic parent that is an amphibian (wd:Q10908) returned true.

This means tree frogs are a type of amphibian.

I will now provide the final answer with the SPARQL query.

[Tool] Stopped generation process