PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( DISTINCT ?airport ) AS ?count ) WHERE {
  ?airport wdt:P31 wd:Q644371 .
  ?airport wdt:P131 / wdt:P131 * wd:Q1055 .
}

Got 1 row and 1 column:
| count       |
| ----------- |
| 1 (xsd:int) |

There is 1 international airport located within the city of Hamburg.

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

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

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

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

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

[User] How many international airports are located within the city of Hamburg ?

[Assistant]
To answer the question "How many international airports are located within the city of Hamburg?", I need to identify the following:

1. The entity representing the city of Hamburg.
2. The entity or class representing international airports.
3. The property that relates airports to their location (specifically within Hamburg).
4. A way to filter airports that are international.

Step 1: Search for the entity representing the city of Hamburg.

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

[Assistant]
The entity representing the city of Hamburg is wd:Q1055 (Free and Hanseatic City of Hamburg, Hamburg, Germany).

Step 2: Identify the property that relates airports to their location. I will search for properties related to location for the entity Hamburg (wd:Q1055).

[Tool]
Top 10 property alternatives:
1. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as wdt/p): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
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 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
3. geoshape, also known as Commons map data, geographic data, geographic shape, .map, map data (wd:P3896 as wdt/p): geographic data from Wikimedia Commons
4. locator map image, also known as locator map, map image, map (wd:P242 as wdt/p): geographic map image which highlights the location of the subject within some larger entity, image
5. location map (wd:P1943 as wdt/p): blank geographic map image suitable for overlaying coordinate points, as defined at c:Category:Location maps, image
6. 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
7. 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
8. area, also known as total area, surface area, surface, size, resolution (wd:P2046 as wdt/p): area occupied by an object
9. located in or next to body of water, also known as located on body of water, ocean, on bay, next to lake, on coast of (wd:P206 as wdt/p): body of water on or next to which a place is located, location
10. 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)

No other items found

[Assistant]
The property "located in the administrative territorial entity" (wdt:P131) is the most suitable to relate airports to their location within Hamburg.

Step 3: Identify the entity or class representing international airports. I will search for the entity "international airport".

[Tool]
Top 10 entity alternatives:
1. international airport (wd:Q644371): airport serving international destinations
2. International Airport (wd:Q55614529): 1985 film directed by Don Chaffey
3. Domodedovo International Airport, also known as Moscow-Domodedovo Airport, UUDD, Moscow International Airport, Moscow Domodedovo Airport, Moscow Airport (wd:Q186614): international airport serving Moscow, Russia
4. John F. Kennedy International Airport, also known as Kennedy International Airport, New York International Airport, KJFK, JFK International Airport, Kennedy International (wd:Q8685): international airport in New York, United States
5. John F. Kennedy International Airport, also known as Idlewild Airport, Kennedy International, JFK International Airport, KJFK, JFK Airport (wd:Q8685): international airport in New York, United States
6. Sheremetyevo International Airport, also known as Moscow Airport, Moscow International Airport, Sheremetyevo Airport, SVO, UUEE (wd:Q192733): international airport serving Moscow, Russia
7. Istanbul-Atatürk, also known as LTBA, Istanbul Atatürk Airport, Istanbul Ataturk Airport, ISL, Atatürk International Airport (wd:Q86473): international airport in Istanbul, Turkey
8. Dubai International Airport, also known as DXB, OMDB (wd:Q193439): international airport in Dubai, United Arab Emirates
9. Singapore Changi Airport, also known as WSSS, Changi Airport Singapore, SIN, Changi Airport, Changi International Airport (wd:Q32159): international airport in Singapore
10. Tokyo International Airport, also known as Haneda Airport, HND, RJTT (wd:Q204853): international airport serving Tokyo, Japan

[Assistant]
The entity representing "international airport" is wd:Q644371.

Step 4: I will now build a SPARQL query to count the number of airports that are instances of or subclasses of international airports (wd:Q644371) and are located in the administrative territorial entity Hamburg (wd:Q1055).

I will first check for airports that are instances of international airports and located in Hamburg.

[Tool] Got no rows and 1 columns

[Assistant]
No airports were found that are directly instances of international airports (wd:Q644371) and located in Hamburg (wd:Q1055).

Step 5: I will now try to find airports that are instances of airport (wd:Q1248784) and located in Hamburg, and then check if they have the property of being international. I will first search for the entity "airport".

[Tool]
Top 10 entity alternatives:
1. airport, also known as aerodrome, air port, airports (wd:Q1248784): location where aircraft take off and land with extended support facilities, mostly for commercial air transport
2. Airport (wd:Q409022): 1970 film directed by George Seaton
3. AirPort, also known as Apple AirPort (wd:Q697292): brand of wifi router equipment made by Apple Inc.
4. Airport, also known as Airport, CA, Airport, California (wd:Q4698872): census-designated place in Stanislaus County, California, USA
5. Airport (wd:Q2604087): 1968 novel by Arthur Hailey
6. Kasese Airport, also known as Airport, HUKS, KSE (wd:Q6374123): airport in Uganda
7. Basongo Airport, also known as airport, BAN, FZVR (wd:Q3339360): airport in Democratic Republic of the Congo
8. Bambili-Dingila Airport, also known as airport, FZKB, Aéroport de Bambili-Dingila (wd:Q3206837): airport in Democratic Republic of the Congo
9. Bokungu Airport, also known as Airport, FZGF (wd:Q4938837): airport in Democratic Republic of the Congo
10. Airport, also known as Rapid Airport (wd:Q11289474): Rapid trains in Hokkaido, Japan

[Assistant]
The entity representing "airport" is wd:Q1248784.

Step 6: I will now build a SPARQL query to find airports (instances of wd:Q1248784) located in Hamburg (wd:Q1055) and check if they have a qualifier or property indicating they are international. Since there might not be a direct property for "international," I will first just list airports located in Hamburg.

[Tool] Got no rows and 2 columns

[Assistant]
No airports were found that are instances of airport (wd:Q1248784) and located in Hamburg (wd:Q1055).

Step 7: I will try a different approach. I will find entities that are airports (wd:Q1248784) or subclasses of airports and located in Hamburg or its administrative parts. I will check if there are any airports located in Hamburg by querying for entities that are instances of airport or subclasses of airport and have Hamburg as their location or located in the administrative territorial entity Hamburg or its parts.

I will first find parts of Hamburg (wd:Q1055) using the property "located in the administrative territorial entity" (wdt:P131).

[Tool]
Got 2,924 rows and 2 columns, showing the first 5 and last 5 rows below:
| part                                     | partLabel                      |
| ---------------------------------------- | ------------------------------ |
| TSC Wellingsbüttel (wd:Q100276526)       | TSC Wellingsbüttel (en)        |
| Poggenmühlenbrücke (wd:Q100320780)       | Poggenmühlenbrücke (en)        |
| Wiemeldorfer Moorgraben (wd:Q100322444)  | Wiemeldorfer Moorgraben (en)   |
| Moorflagengraben (wd:Q100322690)         | Moorflagengraben (en)          |
| Hamburg-Ottensen station (wd:Q100326416) | Hamburg-Ottensen station (en)  |
| ...                                      | ...                            |
| Phoenixhof (wd:Q99735910)                | Phoenixhof (en)                |
| Schule Rhiemsweg (wd:Q99769207)          | Schule Rhiemsweg (en)          |
| Schule Hauskoppelstieg (wd:Q99769241)    | Schule Hauskoppelstieg (en)    |
| Schule Möllner Landstraße (wd:Q99769685) | Schule Möllner Landstraße (en) |
| VfL Lohbrügge (wd:Q998636)               | VfL Lohbrügge (en)             |

[Assistant]
There are many parts located in the administrative territorial entity Hamburg (wd:Q1055).

Step 8: I will now search for airports (instances of wd:Q1248784) that are located in Hamburg or any of its parts. To do this, I will check for airports with the property "located in the administrative territorial entity" (wdt:P131) being Hamburg or any of its parts.

I will write a query to find airports located in Hamburg or its parts using a property path.

[Tool] Got no rows and 2 columns

[Assistant]
No airports were found that are instances of airport (wd:Q1248784) and located in Hamburg or its parts using the property path.

Step 9: I will try to find airports by checking if Hamburg is the "location" (wdt:P276) of the airport instead of "located in the administrative territorial entity" (wdt:P131). I will query for airports with location Hamburg (wd:Q1055).

[Tool] Got no rows and 2 columns

[Assistant]
No airports were found that are instances of airport (wd:Q1248784) and have Hamburg (wd:Q1055) as their location (wdt:P276).

Step 10: I will try to find airports by checking if Hamburg is the "headquarters location" (wdt:P159) of the airport instead. I will query for airports with headquarters location Hamburg (wd:Q1055).

[Tool] Got no rows and 2 columns

[Assistant]
No airports were found that are instances of airport (wd:Q1248784) and have Hamburg (wd:Q1055) as their headquarters location (wdt:P159).

Step 11: I will try to find airports by checking if Hamburg is the "located in or next to body of water" (wdt:P206) of the airport instead. I will query for airports with located in or next to body of water Hamburg (wd:Q1055).

[Tool] Got no rows and 2 columns

[Assistant]
No airports were found that are instances of airport (wd:Q1248784) and have Hamburg (wd:Q1055) as their location in or next to body of water (wdt:P206).

Step 12: I will try to find airports by checking if Hamburg is the "located in time zone" (wdt:P421) of the airport instead. I will query for airports with located in time zone Hamburg (wd:Q1055). This is less likely but worth checking.

[Tool] Got no rows and 2 columns

[Assistant]
No airports were found that are instances of airport (wd:Q1248784) and have Hamburg (wd:Q1055) as their located in time zone (wdt:P421).

Step 13: I will try to find airports by checking if Hamburg is the "located in the administrative territorial entity" (wdt:P131) of the airport, but this time I will search for subclasses of airport (wd:Q1248784) and instances of those subclasses located in Hamburg. This might help if the airport is classified under a more specific subclass.

I will first find subclasses of airport (wd:Q1248784).

[Tool]
Got 10 rows and 2 columns:
| subclass                                   | subclassLabel                   |
| ------------------------------------------ | ------------------------------- |
| airport straddling borders (wd:Q104905692) | airport straddling borders (en) |
| wd:Q10536263                               |                                 |
| federal aeroport (wd:Q106643740)           | federal aeroport (en)           |
| Outstation (wd:Q109558168)                 | Outstation (en)                 |
| wd:Q11560400                               |                                 |
| vertiport (wd:Q117475712)                  | vertiport (en)                  |
| unfinished airport (wd:Q124363875)         | unfinished airport (en)         |
| special airport (wd:Q1479818)              | special airport (en)            |
| departure airport (wd:Q15733670)           | departure airport (en)          |
| destination airport (wd:Q15733672)         | destination airport (en)        |

[Assistant]
There are subclasses of airport such as "airport straddling borders" (wd:Q104905692), "federal aeroport" (wd:Q106643740), "vertiport" (wd:Q117475712), "unfinished airport" (wd:Q124363875), "special airport" (wd:Q1479818), "departure airport" (wd:Q15733670), and "destination airport" (wd:Q15733672).

Step 14: I will now check if there are any airports that are instances of these subclasses and located in Hamburg (wd:Q1055) using the property "located in the administrative territorial entity" (wdt:P131). I will check for instances of any subclass of airport located in Hamburg.

[Tool] Got no rows and 2 columns

[Assistant]
No airports were found that are instances of airport or its subclasses and located in Hamburg (wd:Q1055).

Step 15: I will try to find airports by checking if Hamburg is the "located in the administrative territorial entity" (wdt:P131) of the airport, but this time I will check for entities that are instances of "airport" or have the property "instance of" (wdt:P31) airport (wd:Q1248784) or international airport (wd:Q644371).

I will query for entities that are instances of either airport or international airport and located in Hamburg.

[Tool] Got no rows and 2 columns

[Assistant]
No airports were found that are instances of either airport (wd:Q1248784) or international airport (wd:Q644371) and located in Hamburg (wd:Q1055).

Step 16: I will try to find airports by checking if Hamburg is the "location" (wdt:P276) of the airport, and the airport is an instance of airport or international airport.

I will query for entities that are instances of either airport or international airport and have Hamburg as their location.

[Tool] Got no rows and 2 columns

[Assistant]
No airports were found that are instances of either airport (wd:Q1248784) or international airport (wd:Q644371) and have Hamburg (wd:Q1055) as their location (wdt:P276).

Step 17: I will try to find airports by checking if Hamburg is the "located in or next to body of water" (wdt:P206) of the airport, and the airport is an instance of airport or international airport.

I will query for entities that are instances of either airport or international airport and have Hamburg as their location in or next to body of water.

[Tool] Got no rows and 2 columns

[Assistant]
No airports were found that are instances of either airport (wd:Q1248784) or international airport (wd:Q644371) and have Hamburg (wd:Q1055) as their location in or next to body of water (wdt:P206).

Step 18: Since direct queries for airports located in Hamburg did not yield results, I will try to find airports by searching for airports with the label "Hamburg" to see if there are airports named after Hamburg or related to Hamburg in some way.

I will search for entities with the label "Hamburg Airport".

[Tool]
Top 10 entity alternatives:
1. Hamburg Airport, also known as Hamburg-Fuhlsbüttel Airport, Hamburg Airport “Helmut Schmidt”, EDDH, HAM (wd:Q27706): airport in Fuhlsbüttel, Hamburg, Germany
2. Hamburg Finkenwerder Airport, also known as Airbus Hamburg-Finkenwerder, EDHI, Finkenwerder Airport, XFW (wd:Q663819): aircraft manufacturing plant and associated private airport in the Finkenwerder quarter of southwest Hamburg, Germany
3. Hamburg Airport station (wd:Q5644290): railway station in Germany
4. Hamburg Airport Classics (wd:Q1572874)
5. Hamburg Inc Airport, also known as 4G2, Hamburg Inc Aerodrome (wd:Q34959585)
6. Hamburg : Airport, also known as A9 n35_Sm2 (wd:Q104725193): folder of the 20th Century Press Archives
7. Hamburg Airport S-Bahn line (wd:Q1430696): railway line in Germany
8. Novo Hamburgo Airport, also known as SSNH (wd:Q12694211): Brazilian airport
9. Hamburg : Airport, individual, also known as A9 n35_Sm2.II (wd:Q104725196): folder of the 20th Century Press Archives
10. Hamburg : Airport, general, also known as A9 n35_Sm2.I (wd:Q104725195): folder of the 20th Century Press Archives

[Assistant]
There are two airports related to Hamburg:
1. Hamburg Airport (wd:Q27706), also known as Hamburg-Fuhlsbüttel Airport, located in Fuhlsbüttel, Hamburg, Germany.
2. Hamburg Finkenwerder Airport (wd:Q663819), an aircraft manufacturing plant and associated private airport in the Finkenwerder quarter of southwest Hamburg, Germany.

Step 19: I will check if these airports are classified as international airports (wd:Q644371) or have the property of being international.

I will check the instance of (wdt:P31) for Hamburg Airport (wd:Q27706).

[Tool]
Got 2 rows and 2 columns:
| type                               | typeLabel                  |
| ---------------------------------- | -------------------------- |
| commercial airport (wd:Q21836433)  | commercial airport (en)    |
| international airport (wd:Q644371) | international airport (en) |

[Assistant]
Hamburg Airport (wd:Q27706) is classified as both a commercial airport (wd:Q21836433) and an international airport (wd:Q644371).

Step 20: I will check the instance of (wdt:P31) for Hamburg Finkenwerder Airport (wd:Q663819).

[Tool]
Got 2 rows and 2 columns:
| type                                  | typeLabel                    |
| ------------------------------------- | ---------------------------- |
| German special airfield (wd:Q2301048) | German special airfield (en) |
| factory (wd:Q83405)                   | factory (en)                 |

[Assistant]
Hamburg Finkenwerder Airport (wd:Q663819) is classified as a German special airfield (wd:Q2301048) and a factory (wd:Q83405), but not as an international airport.

Step 21: I will count how many airports are classified as international airports (wd:Q644371) and located in Hamburg (wd:Q1055) or have "Hamburg" in their label to cover any other possible airports.

I will query for airports that are instances of international airports and have Hamburg as their location or have "Hamburg" in their label.

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

[Assistant]
The query to count international airports located in Hamburg or having "Hamburg" in their label timed out. I will simplify the query to only count international airports located in Hamburg (wd:Q1055).

I will query for the count of airports that are instances of international airports and located in Hamburg.

[Tool]
Got 1 row and 1 column:
| count       |
| ----------- |
| 0 (xsd:int) |

[Assistant]
There are 0 international airports that are directly located in the administrative territorial entity Hamburg (wd:Q1055) according to the property wdt:P131.

Step 22: Since Hamburg Airport (wd:Q27706) is known to be an international airport and is located in Fuhlsbüttel, which is a part of Hamburg, I will check the location of Hamburg Airport (wd:Q27706) to confirm its administrative territorial entity.

I will query for the administrative territorial entity (wdt:P131) of Hamburg Airport (wd:Q27706).

[Tool]
Got 1 row and 2 columns:
| location                | locationLabel     |
| ----------------------- | ----------------- |
| Hamburg-Nord (wd:Q1627) | Hamburg-Nord (en) |

[Assistant]
Hamburg Airport (wd:Q27706) is located in Hamburg-Nord (wd:Q1627), which is a part of Hamburg.

Step 23: I will check if Hamburg-Nord (wd:Q1627) is located in the administrative territorial entity Hamburg (wd:Q1055).

[Tool]
Got 1 row and 2 columns:
| parentLocation     | parentLocationLabel |
| ------------------ | ------------------- |
| Hamburg (wd:Q1055) | Hamburg (en)        |

[Assistant]
Hamburg-Nord (wd:Q1627) is located in the administrative territorial entity Hamburg (wd:Q1055).

Step 24: I will count the number of international airports (wd:Q644371) located in any part of Hamburg (wd:Q1055) by checking for airports located in administrative territorial entities that are part of Hamburg or Hamburg itself.

I will query for international airports located in Hamburg or its parts using a property path.

[Tool]
Got 1 row and 1 column:
| count       |
| ----------- |
| 1 (xsd:int) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly counts the number of international airports (wd:Q644371) located within the administrative territorial entity of Hamburg (wd:Q1055) using the property 'located in the administrative territorial entity' (wdt:P131) with recursive traversal. The query returns the count as 1, which matches the human-readable answer provided. The query follows the rules by returning the count directly and does not perform any post-processing outside SPARQL. The answer is complete and correct for the user's question.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?timeOfDiscovery WHERE {
  wd:Q15787 wdt:P575 ?timeOfDiscovery .
}

HIV was first identified in the year 1983.

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

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

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

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

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

[User] When was HIV first identified?

[Assistant]
To answer the question "When was HIV first identified?", I need to find the entity for HIV and then find the property related to the date or year of its identification or discovery.

Step 1: Search for the entity "HIV" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. HIV, also known as AIDS virus, human immunodeficiency virus (wd:Q15787): human retrovirus, cause of AIDS
2. Hiv (wd:Q5959052): village in Iran
3. .hiv (wd:Q20573587): top level domain
4. human immunodeficiency virus infectious disease, also known as HIV+, HIV infection, HIV infections, HIV-positive (wd:Q18556697): disease affecting the human immune system
5. HIV/AIDS in Ethiopia, also known as HIV (wd:Q65409016): Ethiopia faces an epidemic among sub-populations and geographic areas
6. HyperChem Input File, also known as HIV, .hin, HyperChem molecule file format, HIV molecule file format (wd:Q28530466): file format
7. HIV (wd:Q87558374): scientific article published on 01 August 2014
8. HIV (wd:Q93531156)
9. HIV. (wd:Q43247940): scientific article published in February 1998
10. HIV. (wd:Q45982420): scientific article published in February 2001

[Assistant] The entity for HIV as the human retrovirus causing AIDS is wd:Q15787. Now I need to find the property related to the date or year of its identification or discovery for this entity. I will search for properties of the entity wd:Q15787 related to "discovery" or "identified".

[Tool]
Top 10 property alternatives:
1. time of discovery or invention, also known as invented in, time of invention, time of discovery, invention time, invented on (wd:P575 as wdt/p): date or point in time when the item was discovered or invented
2. 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
3. has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as wdt/p): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).
4. has effect, also known as has symptom, implies, leads to, led to, outcome (wd:P1542 as wdt/p): effect of this item, followed by
5. ScienceDirect topic ID, also known as Science Direct topic ID, Science Direct topic identifier, ScienceDirect topic identifier (wd:P10376 as wdt/p): identifier for a topic on the research publication website ScienceDirect
6. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
7. external data available at URL, also known as data, external data URL, URL with external data (wd:P1325 as wdt/p): URL where external data on this item can be found
8. 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)
9. pronunciation audio, also known as listen, audio pronunciation (wd:P443 as wdt/p): audio file with pronunciation, audio
10. prevalence (wd:P1193 as wdt/p): portion in percent of a population with a given disease or disorder

No other items found

[Assistant] The property "time of discovery or invention" (wdt:P575) seems to be the most relevant to find when HIV was first identified. I will now query the time of discovery or invention for the entity HIV (wd:Q15787).

[Tool]
Got 1 row and 1 column:
| timeOfDiscovery                     |
| ----------------------------------- |
| 1983-01-01T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the time of discovery (P575) for HIV (Q15787) from Wikidata. The answer '1983' matches the retrieved date '1983-01-01T00:00:00Z'. The query follows the rules by returning the identifier and the relevant property without unnecessary labels or services. The output is correct and complete.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?person ?personLabel ?role WHERE {
  {
    wd:Q533822 wdt:P178 ?person .
    BIND( "developer" AS ?role )
  } UNION {
    wd:Q533822 wdt:P170 ?person .
    BIND( "creator" AS ?role )
  }
  OPTIONAL {
    ?person rdfs:label ?personLabel FILTER ( LANG( ?personLabel ) = "en" )
  }
}

The SPARQL query returns Christiane Fellbaum as the developer of WordNet with her identifier (wd:Q4558744) and label for readability. The original creator, George A. Miller, is historically significant but is not explicitly listed as a creator or developer of WordNet in Wikidata. The query distinguishes between developer (wdt:P178) and creator (wdt:P170) properties to capture all relevant contributors.

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

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

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

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

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

[User] Who developed WordNet?

[Assistant] To answer the question "Who developed WordNet?", I need to identify the entity "WordNet" in Wikidata and then find the property that relates it to its developer or creator. I will start by searching for the entity "WordNet" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. WordNet, also known as Princeton WordNet (wd:Q533822): Princeton University's computational lexicon of English, a seman...nodes connected by hypernymy, hyponymy, holonymy, meronymy, etc.
2. word net, also known as wordnet (wd:Q2594143): network of words connected by semantic relationships (synonyms, antonyms, hypernyms, hyponyms, meronyms, holonyms)
3. WordNet (wd:Q125949755)
4. WordNet (wd:Q98000414): chapter in book from 2010
5. WordNet: An Electronic Lexical Database, also known as WordNet, WordNet.  An  Electronic Lexical Database (wd:Q35839029): book edition published in 1998 with Fellbaum as editor
6. Arabic WordNet, also known as AWN (wd:Q28136431)
7. Estonian Wordnet (wd:Q31277898)
8. Malayalam WordNet (wd:Q25112033): WordNet for Malayalam language by CUSAT
9. Chinese WordNet, also known as CWN (wd:Q65924663): Huang et al. wordnet in Chinese
10. GF WordNet (wd:Q112258758): a lexical resource which combines WordNet resources from many languages and makes them compatible within GF

[Assistant] The entity "WordNet" is identified as wd:Q533822 in Wikidata, which is Princeton University's computational lexicon of English. Now, I will look for the property that relates WordNet to its developer or creator. Common properties to check are "developer," "creator," or "author." I will search for properties related to "developer" or "creator" for the entity WordNet (wd:Q533822).

[Tool]
Top 10 property alternatives:
1. developer, also known as written by, video game developer, video game dev, game developer, game dev (wd:P178 as wdt/p): organization or person that developed the item, creator
2. software version identifier, also known as software release number, software version number, software release version, software update identifier, software update number (wd:P348 as wdt/p): numeric or nominal identifier of a version of a software program or file format, current or past, has edition or translation, edition number
3. used by, also known as armiger, user, played by, of (wd:P1535 as wdt/p): item or concept that makes use of the subject (use sub-properties when appropriate)
4. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as wdt/p): time when an entity begins to exist; for date of official opening use P1619, start time
5. copyright license, also known as content licence, content license, copyright licence, licence, license (wd:P275 as wdt/p): license under which this copyrighted work is released
6. language of work or name, also known as language of the reference, language of URL, language of website, language of work, named in language (wd:P407 as wdt/p): language associated with this creative work (such as books, show...guage" (P103) and "languages spoken, written or signed" (P1412))
7. 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
8. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

No other items found

[Assistant] The property "developer" (wdt:P178) is the most relevant property for finding who developed WordNet. I will now construct a SPARQL query to find the developer of WordNet (wd:Q533822) using this property.

[Tool]
Got 1 row and 2 columns:
| developer                         | developerLabel           |
| --------------------------------- | ------------------------ |
| Christiane Fellbaum (wd:Q4558744) | Christiane Fellbaum (en) |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly identifies Christiane Fellbaum as a developer of WordNet, which is accurate. However, WordNet was originally developed by George A. Miller and his team at Princeton University. Christiane Fellbaum is known for her significant contributions and maintenance of WordNet, but not as the original developer. The query should be refined to include all developers or creators associated with WordNet, possibly by checking other relevant properties such as 'creator' (wdt:P170) or considering multiple developers. This will provide a more complete and historically accurate answer.

[Assistant] Thank you for the feedback. To provide a more complete and historically accurate answer, I will refine the query to include both developers (wdt:P178) and creators (wdt:P170) of WordNet. This way, we can capture all relevant people associated with the development and creation of WordNet. I will now update the SPARQL query accordingly.

[Tool]
Got 1 row and 2 columns:
| person                            | personLabel              |
| --------------------------------- | ------------------------ |
| Christiane Fellbaum (wd:Q4558744) | Christiane Fellbaum (en) |

[Assistant] The refined query still returns only Christiane Fellbaum as the developer or creator of WordNet. To ensure completeness, I will also check for statements about WordNet that mention George A. Miller or other possible developers in the references or qualifiers. I will search for statements about WordNet with the property "creator" or "developer" and see if George A. Miller is mentioned in any related statements or references.

[Tool] Got no rows and 3 columns

[Tool]
Got 1 row and 3 columns:
| subject              | property             | object                            |
| -------------------- | -------------------- | --------------------------------- |
| WordNet (wd:Q533822) | developer (wdt:P178) | Christiane Fellbaum (wd:Q4558744) |

[Assistant] There are no entries for the property "creator" (wdt:P170) for WordNet, and only Christiane Fellbaum is listed as the developer (wdt:P178). Since George A. Miller is known historically as the original developer, it might be that this information is not explicitly stated in the properties "creator" or "developer" for WordNet in Wikidata. I will now search for any statements or references mentioning George A. Miller in relation to WordNet by searching for entities related to WordNet and George A. Miller.

[Tool]
Top 10 entity alternatives:
1. George Armitage Miller, also known as George A. Miller, George Miller (wd:Q670658): American psychologist (1920–2012), university teacher, psychologist
2. George Arthur Miller (wd:Q2495778): British polo player (1867–1935), polo player
3. George Abram Miller, also known as G. A. Miller (wd:Q1506815): American mathematician (1863–1951), historian of mathematics, university teacher, mathematician
4. Alf Miller, also known as Alfred George Abraham Miller (wd:Q23461809): association football player (1917-1999), association football player
5. George Miller Andrews, also known as George Andrews (wd:Q75636713): Peerage person ID=262014
6. George Miller Armstrong, also known as G. M. Armstrong, G.M.Armstr. (wd:Q21505333): American botanist and plant pathologist (1893-1986), botanical collector, phytopathologist, botanist
7. George A. Miller (1920-2012). (wd:Q30353436): scientific article
8. George Alfred Miller (wd:Q118153037): graduated from University of Washington with a Ph. D. in Sociology
9. George Albert Miller (wd:Q94487076)
10. George Augustus Miller Jr. (wd:Q62592140): 1894-1983 , armorer, engineer, armourer, inventor

[Assistant] The entity George Armitage Miller (wd:Q670658) corresponds to George A. Miller, the American psychologist known for his work related to WordNet. I will now check if there is any property or statement linking George A. Miller (wd:Q670658) to WordNet (wd:Q533822) as a creator or developer.

[Tool]
Got 406 rows and 3 columns, showing the first 10 rows below:
| subject                             | property                         | object                                    |
| ----------------------------------- | -------------------------------- | ----------------------------------------- |
| George Armitage Miller (wd:Q670658) | instance of (wdt:P31)            | human (wd:Q5)                             |
| George Armitage Miller (wd:Q670658) | occupation (wdt:P106)            | psychologist (wd:Q212980)                 |
| George Armitage Miller (wd:Q670658) | sex or gender (wdt:P21)          | male (wd:Q6581097)                        |
| George Armitage Miller (wd:Q670658) | given name (wdt:P735)            | George (wd:Q15921732)                     |
| George Armitage Miller (wd:Q670658) | date of birth (wdt:P569)         | 1920-02-03T00:00:00Z (xsd:dateTime)       |
| George Armitage Miller (wd:Q670658) | country of citizenship (wdt:P27) | United States (wd:Q30)                    |
| George Armitage Miller (wd:Q670658) | family name (wdt:P734)           | Miller (wd:Q1605060)                      |
| George Armitage Miller (wd:Q670658) | place of birth (wdt:P19)         | Charleston (wd:Q44564)                    |
| George Armitage Miller (wd:Q670658) | date of death (wdt:P570)         | 2012-07-22T00:00:00Z (xsd:dateTime)       |
| George Armitage Miller (wd:Q670658) | educated at (wdt:P69)            | George Washington University (wd:Q432637) |
| ...                                 | ...                              | ...                                       |

[Assistant] There is no direct property linking George A. Miller (wd:Q670658) to WordNet (wd:Q533822) in the first 10 rows of his statements. I will now specifically check if there is any property linking George A. Miller to WordNet as a creator or developer by querying for statements where George A. Miller is the subject and WordNet is the object.

[Tool] Got no rows and 3 columns

[Assistant] There are no direct statements in Wikidata linking George A. Miller (wd:Q670658) to WordNet (wd:Q533822) as a creator or developer. The only developer listed for WordNet is Christiane Fellbaum. Given this, I will provide the answer based on the available data in Wikidata, mentioning Christiane Fellbaum as the developer and noting that George A. Miller is historically known as the original developer but not explicitly listed in Wikidata.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly retrieves Christiane Fellbaum as a developer of WordNet from Wikidata, which matches the execution result. However, the answer should clarify that George A. Miller, the original creator of WordNet, is historically significant but not explicitly listed in Wikidata as a developer or creator. To improve completeness, the query could be refined to also check for the property 'creator' (wdt:P170) alone, since 'developer' (wdt:P178) might not capture the original creator. Additionally, the answer should explicitly mention that the query returns identifiers as required and that the label is optional but included for readability. Overall, the output is sensible but could be improved by refining the query to better capture the original creator and by clarifying the distinction between developer and creator in the answer.

[Assistant] Thank you for the detailed feedback. To improve the completeness and clarity of the answer, I will refine the SPARQL query to separately retrieve both developers (wdt:P178) and creators (wdt:P170) of WordNet. This will help capture the original creator (George A. Miller) if listed under creator, and developers like Christiane Fellbaum under developer. I will also clarify in the answer that the query returns the identifiers of the persons and optionally their labels for readability, and explain the distinction between developer and creator based on the data available in Wikidata. I will now refine the query accordingly.

[Tool]
Got 1 row and 3 columns:
| person                            | personLabel              | role      |
| --------------------------------- | ------------------------ | --------- |
| Christiane Fellbaum (wd:Q4558744) | Christiane Fellbaum (en) | developer |

[Assistant] The refined query still returns only Christiane Fellbaum as the developer or creator of WordNet in Wikidata. George A. Miller is not explicitly listed under either property for WordNet in Wikidata. I will now provide the final answer with this clarification and mention that the query returns the identifiers and optionally labels for readability.

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?highestPoint ?highestPointLabel WHERE {
  wd:Q20 wdt:P610 ?highestPoint .
  OPTIONAL {
    ?highestPoint rdfs:label ?highestPointLabel FILTER ( LANG( ?highestPointLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| highestPoint              | highestPointLabel |
| ------------------------- | ----------------- |
| Galdhøpiggen (wd:Q203942) | Galdhøpiggen (en) |

The highest point of Norway is Galdhøpiggen.

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

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

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

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

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

[User] What is the highest point of Norway?

[Assistant]
To answer the question "What is the highest point of Norway?", I need to find the entity representing Norway and then find the highest point (usually a mountain or peak) associated with it.

Step 1: Search for the entity representing Norway in Wikidata.

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

[Assistant] The entity representing the country Norway is wd:Q20. Next, I need to find the highest point of Norway. Typically, the highest point of a country is represented by a property like "highest point" (P610) in Wikidata. I will check if Norway (wd:Q20) has a property for the highest point.

[Tool]
Got 1 row and 3 columns:
| subject         | property                 | object                    |
| --------------- | ------------------------ | ------------------------- |
| Norway (wd:Q20) | highest point (wdt:P610) | Galdhøpiggen (wd:Q203942) |

[Assistant] The highest point of Norway (wd:Q20) is Galdhøpiggen (wd:Q203942). I will now provide this as the final answer.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the highest point of Norway using the property 'highest point' (wdt:P610) for the entity Norway (wd:Q20). The query returns the identifier and English label of the highest point, which is Galdhøpiggen. The answer is accurate and complete. The query follows best practices by including the label as an optional clause with a language filter. No further refinement is necessary.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?inceptionDate WHERE {
  wd:Q41304 wdt:P571 ?inceptionDate .
}

The Weimar Republic started on November 9, 1918.

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

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

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

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

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

[User] When did the Weimar Republic start?

[Assistant]
The question asks for the starting date of the Weimar Republic. The Weimar Republic is a historical German state, so I need to find the entity representing the Weimar Republic in Wikidata and then find the property that indicates its start date.

Step 1: Search for the entity "Weimar Republic" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Weimar Republic, also known as German Republic, Weimar Germany, Republic of Germany, Germany, German Reich (wd:Q41304): Germany in the years 1918/1919–1933
2. flag of the Weimar Republic, also known as the Weimar Republic flag, Weimar Republic flag (wd:Q4485721): flag
3. Landtag (Weimar Republic) (wd:Q1453030): federated state parliament in German Weimar Republic (1919—1934)
4. history of the Weimar Republic, also known as the Weimar Republic history, Weimar Republic history (wd:Q104731094): aspect of German history
5. historian of the Weimar Republic, also known as historian of Weimar Republic, Weimar Republic historian (wd:Q104730830): historian specializing in history of the Weimar Republic
6. hyperinflation in the Weimar Republic (wd:Q695052): occurrence of hyperinflation in early 20th century Germany
7. states of the Weimar Republic (wd:Q3712151): federated states of the Weimar Republic
8. States of the Weimar Republic (wd:Q3712151): federated states of the Weimar Republic
9. Reichsadler of the Weimar Republic, also known as coat of arms of the Weimar Republic (wd:Q25401250)
10. Landtag of Bavaria (Weimar Republic) (wd:Q812353): Parliament of the Free State of Bavaria during the period of the Weimar Republic

[Assistant]
The entity for the Weimar Republic is wd:Q41304. Now I need to find the property that indicates the start date of the Weimar Republic. Typically, the property for the start date of an entity like a country or historical state is "inception" (P571).

Step 2: Query the inception date (P571) of the Weimar Republic (wd:Q41304).

[Tool]
Got 1 row and 1 column:
| inceptionDate                       |
| ----------------------------------- |
| 1918-11-09T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the inception date (P571) of the Weimar Republic (Q41304) from Wikidata. The returned date, November 9, 1918, is accurate and matches the historical start date of the Weimar Republic. The query is simple, precise, and returns the expected result without unnecessary complexity. The answer is clear and complete.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?employees ?pointInTime WHERE {
  wd:Q1027807 wdt:P1128 ?employees .
  OPTIONAL {
    wd:Q1027807 p:P1128 ?statement .
    ?statement pq:P585 ?pointInTime .
  }
}

The Port of Rotterdam (Q1027807) has an employee count of 385,000 according to data available for the years 2016 and 2018. The number is the same for both years. This figure likely represents the total workforce related to port activities rather than direct employees of a single organization managing the port.

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

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

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

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

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

[User] How many perople do the Port of Rotterdam employ?

[Assistant]
To answer the question "How many people do the Port of Rotterdam employ?" I need to find the entity for "Port of Rotterdam" and then find the property related to the number of employees or staff for that entity.

Step 1: Search for the entity "Port of Rotterdam" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Port of Rotterdam (wd:Q1027807): largest port in Europe, located in the city of Rotterdam, Netherlands
2. Port of Rotterdam Authority, also known as Directie bedrijfsvoering Havenbedrijf   etc. (wd:Q2187039): manager of Rotterdam's port and industrial area in the Netherlands
3. The Port of Rotterdam (wd:Q59543911): painting by Eugène Boudin
4. Portrait of Erasmus of Rotterdam (wd:Q107122548)
5. Portrait of Erasmus of Rotterdam (wd:Q110572054): painting by Hans Holbein the Younger and workshop (David Owsley Museum)
6. Portrait of Erasmus of Rotterdam (wd:Q116966868): painting by Workshop Lucas Cranach the Elder (Landesmuseum für Kunst und Kulturgeschichte Oldenburg)
7. Portrait of Erasmus of Rotterdam (wd:Q116968152): painting by Copy after Lucas Cranach the Elder or Workshop Lucas Cranach the Elder (Sammlung Würth)
8. Portrait of Erasmus of Rotterdam (wd:Q20809158): painting by Hans Holbein the Younger
9. Portrait of Erasmus of Rotterdam (wd:Q110571788): painting by Hans Holbein the Younger and workshop
10. Portrait of Erasmus of Rotterdam writing (wd:Q105684225): painting by Hans Holbein

[Assistant]
There are two relevant entities related to the Port of Rotterdam:
1. Port of Rotterdam (wd:Q1027807) - the largest port in Europe, located in Rotterdam.
2. Port of Rotterdam Authority (wd:Q2187039) - the manager of Rotterdam's port and industrial area.

Since the question is about the number of people employed by the Port of Rotterdam, it is more likely referring to the managing organization, which is the Port of Rotterdam Authority (wd:Q2187039).

Step 2: Search for properties related to the number of employees for the entity "Port of Rotterdam Authority" (wd:Q2187039).

[Tool]
Top 10 property alternatives:
1. headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as wdt/p): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place
2. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as wdt/p): time when an entity begins to exist; for date of official opening use P1619, start time
3. has works in the collection, also known as has items in the collection, works in collection, work in collection, museum housing this person's work, items in the collection (wd:P6379 as wdt/p): collection that has works of this person or organisation (use archives at [P485] for archives)
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. 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
6. legal form, also known as legal structure, structured as (wd:P1454 as wdt/p): legal form of an entity, instance of
7. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

No other items found

[Assistant]
The search for properties related to the number of employees for the entity "Port of Rotterdam Authority" (wd:Q2187039) did not return a direct property for the number of employees.

Step 3: I will try a more general search for properties related to "employees" or "staff" for the entity "Port of Rotterdam Authority" (wd:Q2187039).

[Tool]
Top 10 property alternatives:
1. headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as wdt/p): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place
2. has works in the collection, also known as has items in the collection, works in collection, work in collection, museum housing this person's work, items in the collection (wd:P6379 as wdt/p): collection that has works of this person or organisation (use archives at [P485] for archives)
3. 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
4. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as wdt/p): time when an entity begins to exist; for date of official opening use P1619, start time
5. 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
6. legal form, also known as legal structure, structured as (wd:P1454 as wdt/p): legal form of an entity, instance of
7. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

No other items found

[Assistant]
There are no direct properties related to the number of employees or staff for the entity "Port of Rotterdam Authority" (wd:Q2187039).

Step 4: I will try to find the number of employees for the more general entity "Port of Rotterdam" (wd:Q1027807) instead, by searching for properties related to "employees" or "staff".

[Tool]
Top 10 property alternatives:
1. employees, also known as workers, staff, personnel, number of employees, employee count (wd:P1128 as wdt/p): total number of employees of a company at a given "point in time...not deprecated rank). Add data for recent years, don't overwrite
2. operator, also known as offered by, operated by, provided by, run by, service operator (wd:P137 as wdt/p): person, profession, organization or entity that operates the equipment, facility, or service, used by
3. 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
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. has facility, also known as has amenity, has feature, features, amenity, facility (wd:P912 as wdt/p): the subject item has this type of facility, e.g. toilet, car park, has part(s) of the class
6. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as wdt/p): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
7. has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as wdt/p): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).
8. 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)
9. 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
10. 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

No other items found

[Assistant]
For the entity "Port of Rotterdam" (wd:Q1027807), there is a property "employees" (wdt:P1128) which represents the total number of employees of a company at a given point in time.

Step 5: I will now write a SPARQL query to get the number of employees for the Port of Rotterdam (wd:Q1027807) using the property wdt:P1128. I will also try to get the point in time qualifier if available to know the date of the employee count.

[Tool]
Got 2 rows and 2 columns:
| employees            | pointInTime                         |
| -------------------- | ----------------------------------- |
| 385000 (xsd:decimal) | 2016-01-01T00:00:00Z (xsd:dateTime) |
| 385000 (xsd:decimal) | 2018-01-01T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly retrieves the number of employees and the corresponding points in time for the Port of Rotterdam. However, the answer states that the Port of Rotterdam employs 385,000 people, which seems unusually high for a port itself and might be a confusion with the number of employees of a company or organization related to the port. The query returns two identical employee counts for 2016 and 2018, which is consistent but should be clarified in the answer. It would be helpful to verify if the entity Q1027807 (Port of Rotterdam) indeed represents the port authority or the port as a location, as the number of employees might differ significantly. Also, the answer should mention the years explicitly to avoid confusion. Suggestion: clarify the entity and the context of the employee count, and present the answer as "The Port of Rotterdam employed 385,000 people in 2016 and 2018 according to the data."

[Assistant]
The entity Q1027807 represents the Port of Rotterdam as the largest port in Europe, which is more of a location or infrastructure rather than a single employing organization. The number of employees 385,000 seems unusually high for the port itself and might represent the workforce related to the port activities or a related organization. The data points are from 2016 and 2018, and both show the same employee count.

I will refine the answer to clarify the entity and the years explicitly.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly retrieves the number of employees and the point in time for the Port of Rotterdam. However, the answer states that 385,000 people were employed, which seems very high for a single organization and likely represents the workforce related to port activities rather than direct employees of the Port of Rotterdam entity. The query and answer should clarify this distinction. Additionally, the answer could be improved by explicitly mentioning the years for which the data is available (2016 and 2018) and noting that the number is the same for both years. This would provide a clearer and more precise response to the user's question.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ( COUNT( ?film ) AS ?count ) WHERE {
  wd:Q267721 wdt:P577 ?greaseDate .
  BIND( YEAR( ?greaseDate ) AS ?greaseYear ) .
  ?film wdt:P136 wd:Q842256 ; wdt:P577 ?date .
  FILTER ( YEAR( ?date ) = ?greaseYear ) .
  FILTER ( ?film != wd:Q267721 ) .
}

There are 156 other musical films launched in the same year as Grease.

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

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

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

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

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

[User] How many other musical films were launched the same year as Grease?

[Assistant]
Step 1: Identify the entity "Grease" in the knowledge graph to get its launch year.
I will search for the entity "Grease" in the wikidata knowledge graph.

[Tool]
Top 10 entity alternatives:
1. fat, also known as grease, fats and oils, fat or oil, dietary fats, dietary fat (wd:Q127980): esters of three fatty acid chains and the alcohol glycerol, one of the three main macronutrients, also known as triglycerides
2. Grease (wd:Q267721): 1978 film by Randal Kleiser
3. grease, also known as lubricating grease, grease lubricant (wd:Q629823): semi-solid, oily lubricant
4. Grease (wd:Q611626): 1972 musical
5. Grease (wd:Q728791): original song written and composed by Barry Gibb; from the 1978 film "Grease", performed by Frankie Valli
6. Grease (wd:Q3776108): 2010 video game
7. Grease (wd:Q104861673): American media franchise
8. Grease (wd:Q114518793): episode of Cheers (S9 E6)
9. Grease (wd:Q116013684): sardana by Martí de Joan
10. Grease (wd:Q126836847): vocal track by Mina; 1986 studio recording; cover version

[Assistant] The entity "Grease" as a 1978 film is identified as wd:Q267721. Next, I will find the launch year (publication or release date) of this film.

[Tool]
Got 2 rows and 3 columns:
| subject             | property                    | object                              |
| ------------------- | --------------------------- | ----------------------------------- |
| Grease (wd:Q267721) | publication date (wdt:P577) | 1978-06-13T00:00:00Z (xsd:dateTime) |
| Grease (wd:Q267721) | publication date (wdt:P577) | 1978-09-28T00:00:00Z (xsd:dateTime) |

[Assistant]
The film "Grease" (wd:Q267721) was launched in the year 1978 (two publication dates in 1978). Now I will find other musical films launched in the same year 1978.

Step 2: Identify the property for "musical film" and filter films by the year 1978. I will search for the property "genre" and the entity "musical film" to use them in the query.

[Tool]
Top 10 entity alternatives:
1. musical film, also known as film musical, musical movie (wd:Q842256): film genre
2. musical film (wd:L428534-S1)
3. Musical Films (wd:Q121091316): production company
4. Theorising the film musical (wd:Q57622181): doctoral thesis
5. College Course Film: THE HOLLYWOOD MUSICAL (wd:Q108309950): journal article from 'Journal of the University Film and Video Association' published in 1983
6. The Beatles. Una filmografía musical (wd:Q125618465): 1995 edition of written work by Magí Crusells
7. The Beatles. Una filmografía musical (wd:Q125618437): written work by Magí Crusells
8. High School Musical: El Desafio (Mexican film), also known as High School Musical: el desafío (wd:Q2636649): 2008 film directed by Eduardo Ripari
9. Rock This Town Musical Film Fest Pau (wd:Q125736952)
10. film, also known as cinematic work, moving picture, movie, motion pictures, motion picture (wd:Q11424): sequence of images that give the impression of movement, stored on film stock

[Assistant] The entity for "musical film" is wd:Q842256. Now I will find the property for "genre" to filter films by this genre.

[Tool]
Top 10 property alternatives:
1. radio format, also known as format, radio station format, genre (wd:P415 as psv/wdtn/pqv/pr/prn/wdt/pqn/pq/prv/ps/p/psn): describes the overall content broadcast on a radio station
2. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as psv/wdtn/pqv/pr/prn/wdt/pqn/pq/prv/ps/p/psn): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
3. subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as psv/wdtn/pqv/pr/prn/wdt/pqn/pq/prv/ps/p/psn): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
4. form of creative work, also known as work type, work form, type of work, artform, type of reference work (wd:P7937 as psv/wdtn/pqv/pr/prn/wdt/pqn/pq/prv/ps/p/psn): structure of a creative work
5. Every Noise at Once ID, also known as Spotify genre, Every Noise at Once identifier, everynoise.com identifier (wd:P9881 as psv/wdtn/pqv/pr/prn/wdt/pqn/pq/prv/ps/p/psn): identifier of a music genre, style, or scene on the Every Noise at Once website
6. MusicBrainz genre ID, also known as MB genre ID (wd:P8052 as psv/wdtn/pqv/pr/prn/wdt/pqn/pq/prv/ps/p/psn): identifier for a genre on the MusicBrainz open music encyclopedia
7. for color scheme, also known as color mode, uses colour scheme, uses color scheme, theme, prefers colour scheme (wd:P8798 as psv/wdtn/pqv/pr/prn/wdt/pqn/pq/prv/ps/p/psn): which color scheme this statement is designed for
8. based on, also known as modelled after, inspired by, iteration of, modeled after, fork of (wd:P144 as psv/wdtn/pqv/pr/prn/wdt/pqn/pq/prv/ps/p/psn): the work(s) or inputs used as the basis for subject item; for fictional analog use P1074, references work, tradition or theory, inspired by
9. main subject, also known as primary topic, primary subject, primary keyword, plot keyword, of (wd:P921 as psv/wdtn/pqv/pr/prn/wdt/pqn/pq/prv/ps/p/psn): primary topic of a work (see also P180: depicts), depicts
10. AllMusic genre/style ID, also known as AllMusic style identifier, AllMusic theme identifier, AllMusic theme ID, AllMusic style ID, AllMusic style/genre ID (wd:P9185 as psv/wdtn/pqv/pr/prn/wdt/pqn/pq/prv/ps/p/psn): ID of a music genre or style in AllMusic

[Assistant] The property for "genre" is wdt:P136. Now I will write a SPARQL query to count the number of musical films (wd:Q842256) launched in the year 1978. I will use the property "publication date" (wdt:P577) to filter by year.

[Tool]
Got 1 row and 1 column:
| count        |
| ------------ |
| 80 (xsd:int) |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly counts musical films released in 1978, the same year as Grease. However, it does not explicitly verify the release year of Grease within the query, assuming it is 1978. To improve accuracy and generality, the query should first retrieve the release year of Grease (wd:Q1049) and then count musical films released in that year. This ensures the answer is dynamically based on Grease's actual release year rather than hardcoding 1978. Additionally, the query currently counts Grease itself among the musical films; if the question implies 'other' musical films, the query should exclude Grease from the count.

[Assistant] Thank you for the feedback. I will improve the query by dynamically retrieving the release year of Grease (wd:Q267721) within the query and then counting the musical films released in that year, excluding Grease itself from the count. This will ensure the answer is accurate and general. I will now write and execute the improved query.

[Tool]
Got 1 row and 1 column:
| count         |
| ------------- |
| 156 (xsd:int) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly identifies the release year of the film 'Grease' and counts the number of other musical films released in the same year, excluding 'Grease' itself. The use of the genre property (wdt:P136) to filter musical films and the publication date property (wdt:P577) to match the year is appropriate. The query returns the count as requested, and the answer is consistent with the query result. No further refinement is necessary.