PREFIX p: <http://www.wikidata.org/prop/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX wd: <http://www.wikidata.org/entity/>
ASK WHERE {
  wd:Q641 p:P361 ?statement .
  ?statement ps:P361 wd:Q131964 .
}

False

[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] Did Venice at any point belong to the Austrian Empire?

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

[Tool]
Example 1:
Question:
Who was the father of Queen Elizabeth II?

SPARQL:
SELECT ?uri WHERE {
  wd:Q9682 wdt:P22 ?uri .
}

Using entities:
Elizabeth II, also known as Her Royal Highness The Princess Elizabeth of the United Kingdom, HM Queen Elizabeth II, Lilibet, Princess Elizabeth, Duchess of Edinburgh, Princess Elizabeth of York (wd:Q9682): Queen of the United Kingdom from 1952 to 2022, monarch

Using properties:
father, also known as son of, child of, parent, is son of, is daughter of (wd:P22 as wdt): male parent of the subject. For stepfather, use "stepparent" (P3448), parent

Example 2:
Question:
Who wrote Harry Potter?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q8337 wdt:P50 ?uri
}

Using entities:
Harry Potter, also known as Harry Potter series (wd:Q8337): 1997–2007 fantasy book series by J. K. Rowling

Using properties:
author, also known as writer, written by, poet, playwright, maker (wd:P50 as wdt): main creator(s) of a written work (use on works, not humans); us...hor name string) when Wikidata item is unknown or does not exist, creator

Example 3:
Question:
Show me all museums in London.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q33506 .
  ?uri wdt:P276 wd:Q84 .
}

Using entities:
museum, also known as museal institution, museum-style institution (wd:Q33506): institution that holds artifacts and other objects of scientific, artistic, cultural, historical, or other importance
London, also known as Loniniensi, Trinovantum, the Big Smoke, Lundenwic, Lundenburh (wd:Q84): capital and largest city of England and the United Kingdom

Using properties:
location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as wdt): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

[Assistant] Based on the examples, we need to identify the relevant entities and properties for our question. We are looking for whether Venice ever belonged to the Austrian Empire. Let's start by searching for the entities "Venice" and "Austrian Empire".

[Tool]
Top 10 entity alternatives:
1. Venice, also known as Venice, Italy, Venezia, Venexia, Serenissima, Venetia (wd:Q641): capital city of Veneto, Italy
2. Republic of Venice, also known as The Serenissima, Duchy of Venetia, Venice Republic, Venice, Venezia Republic (wd:Q4948): former state in Northeastern Italy (697–1797)
3. Venice, also known as Venice, California, Venice, Los Angeles, Venice, CA (wd:Q773853): beachfront neighborhood in Los Angeles, California, USA
4. Venice, also known as Venice, Florida, Venice, FL (wd:Q57325): city in Sarasota County, Florida, United States
5. Venice, also known as IL, Venice, IL, Venice, Illinois (wd:Q579637): city in Illinois, United States
6. Venice, also known as Venice, LA, Venice, Louisiana (wd:Q962040): census designated place in Plaquemines Parish, Louisiana, United States
7. Venice, also known as Venice, Nebraska, Venice, NE (wd:Q6160341): census-designated place in Nebraska
8. Venice, also known as Venice, New York (wd:Q607094): town in Cayuga County, New York, United States
9. Venice, also known as Venice, UT, Venice, Utah (wd:Q7919964): unincorporated community in Sevier County, Utah, United States
10. Paolo Salviati, also known as P. Salviati, Venice (wd:Q58242413): Italian photographer, 1818-1894, photographer

[Tool]
Top 10 entity alternatives:
1. Austrian Empire, also known as Austria, Kaiserthum Österreich (wd:Q131964): Central European multinational Empire from 1804 to 1867
2. Austrian colonies, also known as Austrian colonial empire, Habsburg Monarchy colonies, List of former Austrian colonies (wd:Q303598): colonial attempts by the Austrian and later Austrian-Hungarian Empires
3. Imperial Crown of Austria, also known as Austrian Imperial Crown, Austrian Crown, Crown of the Austrian Empire, Crown of Rudolf II (wd:Q303507): Crown of the Emperor of Austria
4. Minister-President of Austria, also known as Minister-president of Austria, Minister-President of the Austrian Empire (wd:Q15902790): head of government of the Austrian Empire
5. economy of the Austrian Empire (wd:Q3718694): economy of the region
6. Constitutions of the Austrian Empire (wd:Q56364899)
7. ambassador to the Austrian Empire (wd:Q110636887): 1804-1867
8. ambassador of the Austrian Empire, also known as ambassador of Austria, Austrian ambassador (wd:Q106085599): 1804-1867
9. foreign minister of Austrian Empire (wd:Q130805004): position (–1867)
10. 1850 stamps of the Austrian Empire (wd:Q1447304)

[Assistant]
From the search results, we can see that the correct entities are:

- **Venice**: `wd:Q641` (capital city of Veneto, Italy)
- **Austrian Empire**: `wd:Q131964` (Central European multinational Empire from 1804 to 1867)

Next, we need to find a property that indicates whether Venice was part of the Austrian Empire at any point. A likely candidate is the "part of" property (`wdt:P361`).

Let's check if there are any statements indicating that Venice was part of the Austrian Empire.

[Tool]
Got 3 rows and 1 column:
| partOf                                    |
| ----------------------------------------- |
| Venice and its Lagoon (wd:Q11352141)      |
| Triveneto (wd:Q2641492)                   |
| Metropolitan City of Venice (wd:Q3678587) |

[Assistant]
The results show that Venice has been part of several entities, but none of them is the Austrian Empire. However, it's possible that the relationship is more indirect or involves a different property. Let's try another property, such as "located in the administrative territorial entity" (`wdt:P131`), to see if it provides any relevant information.

We'll also check if there are any historical events or periods where Venice was under the control of the Austrian Empire.

[Tool]
Got 1 row and 1 column:
| locatedIn                                 |
| ----------------------------------------- |
| Metropolitan City of Venice (wd:Q3678587) |

[Assistant]
The results show that Venice is currently located in the Metropolitan City of Venice, which doesn't provide any historical context. To find out if Venice was part of the Austrian Empire historically, we need to look for historical events or periods.

Let's search for properties related to historical control or governance of Venice.

[Tool]
Top 10 property alternatives:
1. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as p/wdt): time when an entity begins to exist; for date of official opening use P1619, start time
2. Library of Congress authority ID, also known as LCSH Authority File ID, LC Name Authority ID, LCSH ID, LCSH LCCN, LC Subject Heading ID (wd:P244 as wdtn/p/wdt): Library of Congress name authority (persons, families, corporate...lowed by 8-10 digits (see regex). For manifestations, use P1144]
3. significant event, also known as significant occurrence, significant incident, significant achievment, sign. event, outcome (wd:P793 as p/wdt): significant or notable events associated with the subject
4. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
5. NDL Authority ID, also known as NDLSH (NDL Subject Headings), NDLNA (NDL Name Authority), NDLNAId, NDL identifier, NDL ID (wd:P349 as wdtn/p/wdt): identifier for authority control per the National Diet Library of Japan
6. Dewey Decimal Classification, also known as DDC (wd:P1036 as p/wdt): use with qualifier "edition (P747)" with item value "DDC 23" or create new item to represent the corresponding DDC edition
7. X (Twitter) username, also known as twitter.com/, X username, X handle, x.com/, X account (wd:P2002 as p/wdt): username on X (formerly Twitter); do not include the '@' symbol, website username or ID
8. GND ID, also known as Deutschen Nationalbibliothek ID, Universal Authority File, Integrated Authority File, IndividualisedGnd, GND-IDN (wd:P227 as p/wdt/wdtn): identifier from an international authority file of names, subjects, and organizations
9. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as p/wdt): label for the items in their official language  or their original language, name
10. legislative body, also known as aboriginal council, Zila, Tehsil, rural council, representative body (wd:P194 as p/wdt): legislative body governing this entity; political institution wi...ted representatives, such as a parliament/legislature or council

No other items found

[Assistant]
The search for properties related to "historical control" of Venice did not yield any directly relevant properties. However, we can try a more specific approach by looking for historical events or periods where Venice was under the control of the Austrian Empire.

Let's search for historical events involving Venice and the Austrian Empire.

[Tool]
Top 10 entity alternatives:
1. Austrian Empire, also known as Austria, Kaiserthum Österreich (wd:Q131964): Central European multinational Empire from 1804 to 1867
2. Austrian colonies, also known as Austrian colonial empire, Habsburg Monarchy colonies, List of former Austrian colonies (wd:Q303598): colonial attempts by the Austrian and later Austrian-Hungarian Empires
3. Imperial Crown of Austria, also known as Austrian Imperial Crown, Austrian Crown, Crown of the Austrian Empire, Crown of Rudolf II (wd:Q303507): Crown of the Emperor of Austria
4. Minister-President of Austria, also known as Minister-president of Austria, Minister-President of the Austrian Empire (wd:Q15902790): head of government of the Austrian Empire
5. economy of the Austrian Empire (wd:Q3718694): economy of the region
6. Constitutions of the Austrian Empire (wd:Q56364899)
7. ambassador to the Austrian Empire (wd:Q110636887): 1804-1867
8. ambassador of the Austrian Empire, also known as ambassador of Austria, Austrian ambassador (wd:Q106085599): 1804-1867
9. foreign minister of Austrian Empire (wd:Q130805004): position (–1867)
10. 1850 stamps of the Austrian Empire (wd:Q1447304)

[Assistant]
The search for "Venice Austrian Empire" did not yield any specific historical events or periods where Venice was under the control of the Austrian Empire. However, we can try a more direct approach by checking if there are any statements indicating that Venice was part of the Austrian Empire during a specific period.

Let's use the "part of" property (`wdt:P361`) with a time constraint to see if there are any historical periods where Venice was part of the Austrian Empire.

[Tool]
Got 3 rows and 2 columns:
| partOf                                    | time |
| ----------------------------------------- | ---- |
| Venice and its Lagoon (wd:Q11352141)      |      |
| Triveneto (wd:Q2641492)                   |      |
| Metropolitan City of Venice (wd:Q3678587) |      |

[Assistant]
The results still do not show any indication that Venice was part of the Austrian Empire. However, it's possible that the relationship is more complex and involves a different property or a different way of representing historical control.

Let's try another approach by looking for historical events or periods where Venice was under the control of the Austrian Empire using the "significant event" property (`wdt:P793`).

[Tool]
Got 1 row and 1 column:
| event                       |
| --------------------------- |
| excommunication (wd:Q49822) |

[Assistant]
The result shows that one significant event related to Venice is "excommunication" (`wd:Q49822`), which is not relevant to our question about the Austrian Empire.

Given that we have not found any direct evidence that Venice was part of the Austrian Empire using the properties and approaches tried so far, let's try a more general search for historical events involving both Venice and the Austrian Empire.

We can use the `wdt:P1785` property, which represents "conflict," to see if there were any conflicts or historical events involving both Venice and the Austrian Empire.

[Tool] Got no rows and 1 columns

[Assistant]
The search for conflicts or historical events involving both Venice and the Austrian Empire did not yield any results. This suggests that there might not be a direct or well-documented relationship in the Wikidata knowledge graph indicating that Venice was part of the Austrian Empire.

To further confirm this, we can use an ASK query to check if there is any statement indicating that Venice was part of the Austrian Empire at any point in history.

Let's construct an ASK query to check this.

[Tool] False

[Assistant]
The ASK query returned `False`, confirming that there is no direct statement in the Wikidata knowledge graph indicating that Venice was part of the Austrian Empire at any point in history.

Therefore, based on the available data in Wikidata, the answer to the question "Did Venice at any point belong to the Austrian Empire?" is **False**.

Here is the final SPARQL query and answer:

```sparql
ASK WHERE { wd:Q641 p:P361 ?statement . ?statement ps:P361 wd:Q131964 . }
```

Answer: **False**

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

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
ASK WHERE {
  ?work wdt:P180 wd:Q1621261 .
  ?work wdt:P179 ?series .
  ?series wdt:P179 * wd:Q79037 .
}

False

[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 works that are based on Spider-Man has Venom been a part of?

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

[Tool]
Example 1:
Question:
Which German cities have more than 250000 inhabitants?

SPARQL:
SELECT ?s1 WHERE {
  ?s1 wdt:P17 wd:Q183 .
  ?s1 wdt:P31 wd:Q515 .
  ?s1 wdt:P1082 ?o1 .
  FILTER ( ?o1 > "250000" ^^ xsd:integer )
}

Using entities:
Germany, also known as BR Deutschland, Bundesrepublik Deutschland, Deutschland, Federal Republic of Germany (wd:Q183): country in Central Europe
city, also known as cities (wd:Q515): large human settlement

Using properties:
population, also known as inhabitants, human population (wd:P1082 as wdt): number of people inhabiting the place; number of people of subject
country, also known as sovereign state, state, land, host country (wd:P17 as wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 2:
Question:
Give me the birthdays of all actors of the television show Charmed.

SPARQL:
SELECT DISTINCT ?date WHERE {
  wd:Q162371 wdt:P161 / wdt:P569 ?date .
}

Using entities:
Charmed (wd:Q162371): American supernatural drama / fantasy television series (1998–2006)

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as wdt): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as wdt): date on which the subject was born, inception

Example 3:
Question:
Which airports does Yeti Airlines serve?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q1480118 wdt:P113 ?uri .
}

Using entities:
Yeti Airlines, also known as Yeti Airlines Domestic Pvt. Ltd. (wd:Q1480118): Airline based in Kathmandu, Nepal.

Using properties:
airline hub, also known as hub airport, hub (wd:P113 as wdt): airport that serves as a hub for an airline

[Assistant] Based on these examples, we need to identify the entities and properties relevant to our question. We are looking for works that feature Venom and are based on Spider-Man. Let's start by searching for the entities "Venom" and "Spider-Man".

[Tool]
Top 10 entity alternatives:
1. Venom (wd:Q23006268): 2018 American film directed by Ruben Fleischer
2. Venom (wd:Q192861): British heavy metal band
3. Venom (wd:Q1621261): fictional character in Marvel Comics
4. venom, also known as animal venom, venoms, zootoxin (wd:Q3386847): mixture of toxins and other substances secreted by an animal for the purpose of causing harm to another
5. UH-1Y Venom, also known as Venom, UH1Y Venom, UH-1Y Super Huey, UH-1 Venom, Super Huey (wd:Q2529305): military utility helicopter model by Bell
6. DH.112 Venom, also known as Venom, DH112, de Havilland Venom, de Havilland DH 112, de Havilland DH.112 Venom (wd:Q284767): 1949 fighter aircraft family by de Havilland
7. Michael Page, also known as MVP, the venenous cactus, Venom, Michael Jerome Reece-Page (wd:Q6833334): Brazilian jiu-jitsu practitioner, English mixed martial artist, mixed martial arts fighter, martial artist, kickboxer, karateka, boxer
8. Eddie Brock, also known as King in Black, Toxin, Venom, Edward Charles Brock, Anti-Venom (wd:Q2604715): fictional character in Marvel Comics, government agent, supervillain, superhero, vigilante, reporter
9. Venom, also known as Venom (Music from the Motion Picture) (wd:Q57326696): 2018 song by Eminem
10. Venom (wd:Q1757437): 1981 film by Tobe Hooper

[Tool]
Top 10 entity alternatives:
1. Spider-Man, also known as Wallcrawler, The Amazing Spider-Man, The Human Spider, The Fantastic Spider-Man, Web-slinger (wd:Q79037): fictional character in Marvel Comics, photographer, scientist, superhero, inventor, teacher
2. Spider-Man (wd:Q484442): 2002 American film directed by Sam Raimi
3. Spider-Man, also known as Marvel's Spider-Man (wd:Q25340029): 2018 video game developed by Insomniac Games
4. Spider-Man, also known as Spider-Man: The Animated Series (wd:Q569934): American animated television series from 1994–1998
5. Miles Morales, also known as Ultimate Spider-Man, Spider-Man, Miles Gonzalo Morales (wd:Q59826): fictional character in Marvel Comics, superhero, student
6. Spider-Man, also known as Spider-Man 2000 (wd:Q288296): 2000 video game
7. Peter Parker, also known as Peter #1, Peter 1, Peter One, Peter-One, Spider-Man (wd:Q23991129): fictional character from the Marvel Cinematic Universe
8. Marvel's Spider-Man, also known as Spider-Man (wd:Q28207200): American animated television series
9. Spider-Man, also known as Supaidāman (wd:Q2087538): Japanese-US late 1970's television series
10. Spider-Man (wd:Q2333456): US late 1960s animated television series

[Assistant]
From the search results, it looks like the correct entity for Venom is `wd:Q1621261` and for Spider-Man is `wd:Q79037`.

Next, we need to find out what properties might link works featuring Venom to works based on Spider-Man. A likely candidate is the "main subject" or "based on" property. Let's search for these properties.

[Tool]
Top 10 property alternatives:
1. main subject, also known as primary topic, primary subject, primary keyword, plot keyword, of (wd:P921 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): primary topic of a work (see also P180: depicts), depicts
2. facet of, also known as subitem of, topic of, subtopic of, subject in, section in (wd:P1269 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): topic of which this item is an aspect; item that offers a broader perspective on the same topic
3. category's main topic, also known as item for this category, cmt, main article in category, main category topic, main subject of category (wd:P301 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): primary topic of the subject Wikimedia category, main subject
4. academic major, also known as academic subject, college major, field of study, major, studied (wd:P812 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): major someone studied at college/university
5. depicts, also known as portrays, presents, preserves, quotes, represents (wd:P180 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): entity visually depicted in an image, literarily described in a ...o an audiovisual or other medium; see also P921,  'main subject', has part(s)
6. field of work, also known as scientific discipline, scientific area, responsible for, research on, research fields (wd:P101 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): specialization of a person or organization; see P106 for the occupation, interested in
7. curriculum topics, also known as included subject, included topic, subject included, syllabus includes, topic included (wd:P8263 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): topic or subject included in the curriculum
8. Wikidata item of this property, also known as associated item, Wikidata property subject item, Wikidata item for this property, subject of this property, subject of property (wd:P1629 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): item corresponding to the concept represented by the property
9. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): main Wikimedia category
10. statement is subject of, also known as statement is the subject of, subject of the statement, subject of the claim, subject of, related item of statement (wd:P805 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): (qualifying) item that describes the relation identified in this statement

[Tool]
Top 10 property alternatives:
1. based on, also known as modelled after, inspired by, iteration of, modeled after, fork of (wd:P144 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): the work(s) or inputs used as the basis for subject item; for fictional analog use P1074, references work, tradition or theory, inspired by
2. criterion used, also known as reason for distinction, with respect to, with reference to, respectively to, on the basis of (wd:P1013 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): property by which a distinction or classification is made
3. natural product of taxon, also known as produced by taxon, product of taxon, made from, fruit of (taxon), derived from (wd:P1582 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): links a natural product with its source (animal, plant, fungal, algal, etc.)
4. derived from lexeme, also known as derived from, etymology, history of a word, loaned from, origin of a word (wd:P5191 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): most direct lexeme(s) this one has developed from
5. after a work by, also known as inspirational artist, inspiring artist, copy of a work by, based on a work by, artist who inspired this (wd:P1877 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): artist whose work strongly inspired / was copied in this item, significant person
6. statement supported by, also known as supported by, statement is supported by, stated by, recognized by, per (wd:P3680 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): entity that supports a given statement
7. determination method or standard, also known as rationale, standard, methodology, method of determination, measured by (wd:P459 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): how a value is determined, or the standard by which it is declared
8. derivative work, also known as is source work of, is adapted as, is the basis for, iteration, reboot (wd:P4969 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): new work of art (film, book, software, etc.) derived from major part of this work
9. object sense, also known as sense derivation, derived from sense (wd:P5980 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): (qualifier) statement applies only to listed senses of statement's object
10. semantic derivation of, also known as derived from sense, sense derived from sense (wd:P12410 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): links a lexeme sense to a particular sense it is derived from

[Assistant]
The property "main subject" (`wd:P921`) seems appropriate for linking works to their main subjects, and "based on" (`wd:P144`) is suitable for linking works to the works they are based on.

Now, let's construct a SPARQL query to find works that feature Venom and are based on Spider-Man. We will use `wd:Q1621261` for Venom and `wd:Q79037` for Spider-Man.

Here is the initial query:

```sparql
SELECT ?work WHERE {
  ?work wdt:P921 wd:Q1621261 .
  ?work wdt:P144 wd:Q79037 .
}
```

Let's execute this query to see the results.

[Tool] Got no rows and 1 columns

[Assistant]
It seems that there are no works that directly feature Venom and are based on Spider-Man according to the current query. This could be due to the specific properties or the way the data is structured in Wikidata.

Let's try a different approach. Instead of using `wdt:P921` (main subject), we can use `wdt:P180` (depicts) to find works that depict Venom. We will also keep the `wdt:P144` (based on) property to ensure the works are based on Spider-Man.

Here is the revised query:

```sparql
SELECT ?work WHERE {
  ?work wdt:P180 wd:Q1621261 .
  ?work wdt:P144 wd:Q79037 .
}
```

Let's execute this query to see if we get any results.

[Tool] Got no rows and 1 columns

[Assistant]
It appears that even with the revised query using `wdt:P180` (depicts), there are still no works that directly depict Venom and are based on Spider-Man.

Given that Venom is a significant character in the Spider-Man universe, it's possible that the works featuring Venom are not directly linked to Spider-Man through the `wdt:P144` property. Instead, they might be part of a broader set of works that are part of the Spider-Man universe.

Let's try a more flexible approach by finding works that feature Venom and are part of the Spider-Man universe. We can use the `wdt:P179` property, which indicates that a work is part of a series or collection.

Here is the updated query:

```sparql
SELECT ?work WHERE {
  ?work wdt:P180 wd:Q1621261 .
  ?work wdt:P179 ?series .
  ?series wdt:P144 wd:Q79037 .
}
```

This query will look for works that depict Venom and are part of a series that is based on Spider-Man. Let's execute this query to see if we get any results.

[Tool] Got no rows and 1 columns

[Assistant]
It seems that even with the more flexible approach using the `wdt:P179` property, there are still no works that directly depict Venom and are part of a series based on Spider-Man.

Given the complexity of the data and the potential for indirect relationships, let's try one more approach. We can look for works that feature Venom and are part of the broader Spider-Man universe, which might be indicated by being part of a series or collection that is related to Spider-Man.

We can use the `wdt:P179` property to find works that are part of a series and then check if that series is related to Spider-Man in any way. We can also include the `rdfs:label` property to get the labels of the works for better readability.

Here is the updated query:

```sparql
SELECT ?work ?workLabel WHERE {
  ?work wdt:P180 wd:Q1621261 .
  ?work wdt:P179 ?series .
  ?series wdt:P144 wd:Q79037 .
  OPTIONAL { ?work rdfs:label ?workLabel . FILTER(LANG(?workLabel) = "en") }
}
```

Let's execute this query to see if we get any results.

[Tool] Got no rows and 2 columns

[Assistant]
It appears that even with the more detailed query, there are still no works that directly depict Venom and are part of a series based on Spider-Man. This suggests that the data in Wikidata might not be structured in a way that directly links these works in the manner we are querying.

Given the lack of results, let's take a step back and consider a different approach. We can look for works that feature Venom and are part of the broader Spider-Man universe by checking if they are part of any series or collection that is related to Spider-Man in any way, even if not directly through the `wdt:P144` property.

We can use the `wdt:P179` property to find works that are part of a series and then check if that series is related to Spider-Man in any way, such as being part of the same comic book universe.

Here is the updated query:

```sparql
SELECT ?work ?workLabel WHERE {
  ?work wdt:P180 wd:Q1621261 .
  ?work wdt:P179 ?series .
  ?series wdt:P179* wd:Q79037 .
  OPTIONAL { ?work rdfs:label ?workLabel . FILTER(LANG(?workLabel) = "en") }
}
```

This query will look for works that depict Venom and are part of a series that is part of the same broader series or collection as Spider-Man. Let's execute this query to see if we get any results.

[Tool] Got no rows and 2 columns

[Assistant]
It seems that even with the more comprehensive approach using the transitive property `wdt:P179*`, there are still no works that directly depict Venom and are part of the broader Spider-Man universe.

Given the lack of results, it's possible that the data in Wikidata is not structured in a way that allows us to directly link works featuring Venom to the Spider-Man universe. This could be due to the complexity of the relationships or the way the data is organized.

Since we have tried multiple approaches and still haven't found any results, it might be that there are no works in the dataset that meet the criteria we are looking for. In this case, the answer to the question "How many works that are based on Spider-Man has Venom been a part of?" is likely zero.

Let's confirm this with an ASK query to check if there are any such works at all.

Here is the ASK query:

```sparql
ASK WHERE {
  ?work wdt:P180 wd:Q1621261 .
  ?work wdt:P179 ?series .
  ?series wdt:P179* wd:Q79037 .
}
```

Let's execute this query to confirm our findings.

[Tool] False

[Assistant]
The ASK query confirms that there are no works in the dataset that depict Venom and are part of the broader Spider-Man universe.

Therefore, the answer to the question "How many works that are based on Spider-Man has Venom been a part of?" is zero.

Here is the final SPARQL query and answer:

```sparql
ASK WHERE {
  ?work wdt:P180 wd:Q1621261 .
  ?work wdt:P179 ?series .
  ?series wdt:P179* wd:Q79037 .
}
```

Answer: False

This means there are no such works in the dataset.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?predecessor WHERE {
  wd:Q1115291 wdt:P1365 ?predecessor .
}

The kingdom that preceded the Thonburi Kingdom is the Ayutthaya Kingdom.

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

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

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

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

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

[User] Which kingdom preceded the Thonburi Kingdom ?

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

[Tool]
Example 1:
Question:
What is the alma mater of the chancellor of Germany Angela Merkel?

SPARQL:
SELECT ?res WHERE {
  wd:Q567 wdt:P69 ?res .
  ?res wdt:P31 / wdt:P279 * wd:Q3918 .
}

Using entities:
university, also known as uni, universities (wd:Q3918): academic institution for further education
Angela Merkel, also known as Angela Dorothea Merkel, leader of the free world, Angela Kasner (wd:Q567): chancellor of Germany from 2005 to 2021, politician, physicist

Using properties:
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as wdt): educational institution attended by subject, affiliation

Example 2:
Question:
How many James Bond movies do exist?

SPARQL:
SELECT ( COUNT( ?s1 ) as ?c ) WHERE {
  ?s1 wdt:P31 wd:Q11424 .
  ?s1 ?p wd:Q2009573 .
  FILTER ( ?p = wdt:P144 || ?p = wdt:P674 )
}

Using entities:
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
James Bond, also known as Agent 007, double o seven, 007 (wd:Q2009573): secret agent, invented by novellist Ian Fleming, 00 Agent, spy

Using properties:
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 3:
Question:
How many people live in the capital of Australia?

SPARQL:
SELECT DISTINCT ?number WHERE {
  wd:Q408 wdt:P36 ?uri .
  ?uri wdt:P1082 ?number .
}

Using entities:
Australia, also known as AU, The Commonwealth of Australia, Stria, Straya, Stralia (wd:Q408): country in Oceania

Using properties:
population, also known as inhabitants, human population (wd:P1082 as wdt): number of people inhabiting the place; number of people of subject
capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as wdt): seat of government of a country, province, state or other type of administrative territorial entity

[Assistant] Based on these examples, we can see how to structure our SPARQL query. We need to identify the entity for the Thonburi Kingdom and then find the entity that precedes it. Let's start by searching for the Thonburi Kingdom.

[Tool]
Top 10 entity alternatives:
1. Thonburi Kingdom (wd:Q1115291): former country
2. kingdom, also known as regna, regnum (wd:Q36732): taxonomic rank
3. realm, also known as kingdom, kingdom (politics) (wd:Q1250464): denomination of a particular political entity, which is theoreti...ts political regime; but not necessarily identified with a state
4. The Kingdom, also known as Kingdom (wd:Q467582): 2007 film directed by Peter Berg
5. Kingdom (wd:Q30947892): 2019 South Korean TV series
6. kingdom, also known as realm (wd:Q417175): state over which a king or queen rules
7. Thonburi, also known as Thonburi Si Mahasamut (wd:Q6580711): area of Bangkok
8. Kingdom, also known as Kingudamu (wd:Q1058984): Japanese manga series
9. Kingdom (wd:Q18328031): 2014 TV series
10. Finnjet, also known as GTS Finnjet, IMO 7359632, Kingdom (wd:Q1418193): ship built in 1977

[Assistant] The correct entity for the Thonburi Kingdom is `wd:Q1115291`. Now, we need to find out which kingdom preceded it. To do this, we can look for properties related to succession or predecessor. Let's search for such properties.

[Tool]
Top 10 property alternatives:
1. follows, also known as prev, successor to, succeeds to, succeeds, split from (wd:P155 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): immediately prior item in a series of which the subject is a par... preceding item, e.g. political offices, use "replaces" (P1365)]
2. replaced by, also known as heir, superseded by, successor, succeeded by, next job holder (wd:P1366 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): other person or item which continues the item by replacing it in... nor identical, but adds to the series (e.g. books in a series)., followed by
3. followed by, also known as continued as, then, successor, succeeded by, sequel is (wd:P156 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): immediately following item in a series of which the subject is a...een replaced, e.g. political offices, use "replaced by" (P1366)]
4. replaces, also known as supersedes, succeeds, replaced, previous job holder, preceded by (wd:P1365 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): person, state or item replaced. Use "structure replaces" (P1398)...item was not replaced or predecessor and successor are identical, follows
5. named after, also known as toponym, namesake, named in honor of, named for, etymology (wd:P138 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): entity or event that inspired the subject's name, or namesake (i...fier "applies to name" (P5168) can be used to indicate which one
6. has heir or beneficiary, also known as heir, beneficiary (wd:P12002 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): people or organizations that received, or will receive, (all or part of) the subject's property or title
7. relative, also known as relatives, grandparent, relation, non-binary parent, niece (wd:P1038 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): family member (qualify with "kinship to subject", P1039; for direct family member please use specific property), significant person
8. owned by, also known as belongs to, stockholders, stockholder, shareholders, shareholder (wd:P127 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): owner of the subject
9. latest date, also known as terminus ante quem, prior to, on or before this date, no later than, max date (wd:P1326 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): latest possible time that something could have occurred. Use as qualifier for other date properties
10. appointed by, also known as named by (wd:P748 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): who appointed the person to the office, can be used as a qualifier

[Assistant]
The property `P1365` (replaces) seems to be the most appropriate for finding the predecessor of the Thonburi Kingdom. Let's use this property to find the kingdom that preceded the Thonburi Kingdom.

We'll construct a simple SPARQL query to find the entity that the Thonburi Kingdom replaced.

```sparql
SELECT ?predecessor WHERE {
  wd:Q1115291 wdt:P1365 ?predecessor .
}
```

Let's execute this query.

[Tool]
Got 1 row and 1 column:
| predecessor                    |
| ------------------------------ |
| Ayutthaya Kingdom (wd:Q841364) |

[Assistant]
The query returned the Ayutthaya Kingdom (wd:Q841364) as the predecessor of the Thonburi Kingdom.

To finalize the answer, we can provide the SPARQL query and the result.

Here is the final SPARQL query and the answer:

```sparql
SELECT ?predecessor WHERE {
  wd:Q1115291 wdt:P1365 ?predecessor .
}
```

The kingdom that preceded the Thonburi Kingdom is the Ayutthaya Kingdom.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?openingDate WHERE {
  wd:Q693956 wdt:P1619 ?openingDate .
}

The Hamburg S-Bahn was officially opened on January 1, 1906.

[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 the Hamburg S-Bahn officially opened?

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

[Tool]
Example 1:
Question:
How many people live in Poland?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q36 wdt:P1082 ?uri
}

Using entities:
Poland, also known as Republic of Poland (wd:Q36): country in Central Europe

Using properties:
population, also known as inhabitants, human population (wd:P1082 as wdt): number of people inhabiting the place; number of people of subject

Example 2:
Question:
Give me all writers that won the Nobel Prize in literature.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P106 wd:Q36180 ; wdt:P166 wd:Q37922 .
}

Using entities:
writer, also known as penwoman, writers, penwomen, penmen, penman (wd:Q36180): person who uses written words to communicate ideas and to produce literary works
Nobel Prize in Literature, also known as Nobel Literature Prize (wd:Q37922): one of five prizes established by Alfred Nobel

Using properties:
occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as wdt): award or recognition received by a person, organization or creative work

Example 3:
Question:
What is the area code of Berlin?

SPARQL:
SELECT DISTINCT ?string WHERE {
  wd:Q64 wdt:P473 ?string .
}

Using entities:
Berlin, also known as Berlin (Germany), Berlin, Germany, DE-BE (wd:Q64): federated state, capital and largest city of Germany

Using properties:
local dialing code, also known as area code, dialling code, local calling code, local dialling code, STD code (wd:P473 as wdt): identifier dedicated to subject city by the area communication network

[Assistant] Based on the examples, we need to identify the entity for "Hamburg S-Bahn" and the property for "official opening date". Let's first search for the entity "Hamburg S-Bahn".

[Tool]
Top 10 entity alternatives:
1. Hamburg S-Bahn (wd:Q693956): metro railway in Hamburg, Germany
2. Hamburg City S-Bahn, also known as City-S-Bahn, City-Tunnel (wd:Q321980): railway tunnel
3. S-Bahnhof Hamburg-Altona station, also known as Altona (S-Bahn), Hamburg-Altona(S), Hamburg-Altona (S-Bahn) (wd:Q70585725): railway station in Germany
4. S-Bahn Hamburg GmbH (wd:Q99869216): German railway company operating the Hamburg S-Bahn
5. Hamburg Airport S-Bahn line (wd:Q1430696): railway line in Germany
6. Train Simulator: Hamburg S1 S-Bahn Route Add-On (wd:Q108105621): Train Simulator DLC
7. 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
8. 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
9. Hamburg, also known as Hamburg, IA, Hamburg, Iowa (wd:Q998718): city in Fremont County, Iowa, United States
10. Hamburg, also known as Hamburg, AR, Hamburg, Arkansas (wd:Q79657): city in Ashley County, Arkansas, United States

[Assistant] The top result is the correct one: "Hamburg S-Bahn (wd:Q693956)". Now let's search for the property "official opening date".

[Tool]
Top 10 property alternatives:
1. date of official opening, also known as launch date, launched, officially opened on, official opening, official opening time (wd:P1619 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): date or point in time a place, organization, or event officially opened, start time, inception
2. officially opened by, also known as inaugurated by, opened by (wd:P542 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): person that officially opened the event or place
3. opening time, also known as hour opens, opens at, opening hour, open hour (wd:P8626 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): time when an establishment or attraction opens, qualifier for P3025
4. open days, also known as open on days, days open, opening days (wd:P3025 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): days in the week subject item is open within the opening season
5. open period from, also known as start of opening season, start opening season, opening season, opening month, opening day of the year (wd:P3027 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): qualifier to P3025 (open days) for season when open days apply
6. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): time when an entity begins to exist; for date of official opening use P1619, start time
7. announcement date, also known as released, date teased, made public on, public announcement date, published (wd:P6949 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): time of the first public presentation of a subject by the creator, of information by the media, point in time
8. start time, also known as start date, since, valid, join time, joined (wd:P580 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): time an entity begins to exist or a statement starts being valid, point in time
9. service entry, also known as commissioned, time of service entry, service introduction, launch date, in service (wd:P729 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): date or point in time on which a piece or class of equipment entered operational service, start time
10. UTC date of spacecraft launch, also known as time of spacecraft launch, spacecraft launch time, spacecraft launch date, launch time, launch date (wd:P619 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): date of spacecraft launch in UTC

[Assistant]
The property "date of official opening" (wd:P1619) seems to be the most appropriate. We will now construct a SPARQL query to find the official opening date of the Hamburg S-Bahn.

```sparql
SELECT ?openingDate WHERE {
  wd:Q693956 wdt:P1619 ?openingDate .
}
```

Let's execute this query.

[Tool]
Got 1 row and 1 column:
| openingDate                         |
| ----------------------------------- |
| 1906-01-01T00:00:00Z (xsd:dateTime) |

[Assistant]
The official opening date of the Hamburg S-Bahn is January 1, 1906.

Here is the final SPARQL query and answer:

```sparql
SELECT ?openingDate WHERE {
  wd:Q693956 wdt:P1619 ?openingDate .
}
```

Answer: The Hamburg S-Bahn was officially opened on January 1, 1906.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
ASK WHERE {
  wd:Q645476 wdt:P576 ?dissolvedDate .
}

False

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

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

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

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

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

[User] Is the production company of samurai champloo still existing?

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

[Tool]
Example 1:
Question:
How many James Bond movies do exist?

SPARQL:
SELECT ( COUNT( ?s1 ) as ?c ) WHERE {
  ?s1 wdt:P31 wd:Q11424 .
  ?s1 ?p wd:Q2009573 .
  FILTER ( ?p = wdt:P144 || ?p = wdt:P674 )
}

Using entities:
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
James Bond, also known as Agent 007, double o seven, 007 (wd:Q2009573): secret agent, invented by novellist Ian Fleming, 00 Agent, spy

Using properties:
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 2:
Question:
What country is Sitecore from?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q2663195 wdt:P17 ?uri
}

Using entities:
Sitecore (wd:Q2663195): company

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

Example 3:
Question:
Which states border Illinois?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q1204 wdt:P47 ?uri .
}

Using entities:
Illinois, also known as The Prairie State, Illinois, United States, The Land of Lincoln, US-IL, Prairie State (wd:Q1204): state of the United States of America

Using properties:
shares border with, also known as shares borders with, next to, bordered by, border, borders clockwise (wd:P47 as wdt): countries or administrative subdivisions, of equal level, that t...rders, either by land or water. A single common point is enough.

[Assistant] Based on the examples, we need to identify the production company of Samurai Champloo and check if it still exists. Let's first find the entity for Samurai Champloo.

[Tool]
Top 10 entity alternatives:
1. Samurai Champloo (wd:Q143276): Japanese anime television series
2. Samurai Champloo (wd:Q66138325): Japanese manga series
3. Samurai Champloo: Sidetracked, also known as Samurai Champloo HIPHOP Samurai Action (wd:Q3548610): 2006 video game
4. Samurai Champloo soundtrack releases, also known as Music of Samurai Champloo (wd:Q106856784): Wikipedia article covering multiple soundtrack releases
5. Samurai Champloo Music Record: Departure, also known as Departure (wd:Q7413091): 2004 soundtrack album by Nujabes / Fat Jon
6. Samurai Champloo Music Record: Impression, also known as Impression (wd:Q3149468): 2004 soundtrack album by Force of Nature / Nujabes / Fat Jon
7. Samurai Champloo Music Record: Masta, also known as Masta (wd:Q104829750): 2004 soundtrack album by FORCE OF NATURE / tsutchie
8. Samurai Champloo Music Record: Playlist (wd:Q104829743): 2004 soundtrack album by tsutchie
9. Postmodern Is Old Hat: Samurai Champloo (wd:Q56608596): article
10. samurai, also known as buke, bushi (wd:Q38142): military nobility of pre-industrial Japan

[Assistant] The top result is the correct one, which is the Japanese anime television series. Now let's find out what the production company of Samurai Champloo is.

[Tool]
Top 10 property alternatives:
1. production company, also known as broadcasting company, theatrical troupe, theatre company, theater company, studio (wd:P272 as p/wdt): company that produced this film, audio or performing arts work
2. director, also known as film director, movie director, game director, directed by (wd:P57 as p/wdt): director(s) of film, TV-series, stageplay, video game or similar, contributor to the creative work or subject, creator
3. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as p/wdt): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
4. derivative work, also known as is source work of, is adapted as, is the basis for, iteration, reboot (wd:P4969 as p/wdt): new work of art (film, book, software, etc.) derived from major part of this work
5. screenwriter, also known as story by, teleplay by, video game writer, writer (of screenplays), writing credits (wd:P58 as p/wdt): person(s) who wrote the script for subject item, film crew member, author
6. country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as p/wdt): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country
7. original language of film or TV show, also known as media language, original language, language of the original work, created on language (wd:P364 as p/wdt): language in which a film or a performance work was originally cr... works and songs; use P407 ("language of work or name") instead., language of work or name
8. Kinobox film ID, also known as www.kinobox.cz/film/, kinobox.cz/film/, https://www.kinobox.cz/film/ (wd:P12096 as p/wdt): identifier for a film on the Kinobox.cz website
9. distributed by, also known as distributor (wd:P750 as p/wdt): distributor of a creative work; distributor for a record label; news agency; film distributor
10. original broadcaster, also known as TV channel, television channel, radio station, radio network, original network (wd:P449 as p/wdt): network(s) or service(s) that originally broadcast a radio or television program, broadcast by

No other items found

[Assistant] The property `production company` (wd:P272) is the one we're looking for. Now, let's run a SPARQL query to find the production company of Samurai Champloo.

[Tool]
Got 1 row and 1 column:
| productionCompany     |
| --------------------- |
| Manglobe (wd:Q645476) |

[Assistant] The production company of Samurai Champloo is Manglobe. Next, we need to check if Manglobe still exists. We'll look for information about the current status of Manglobe.

[Tool]
Top 10 property alternatives:
1. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
2. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as p/wdt): time when an entity begins to exist; for date of official opening use P1619, start time
3. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as p/wdt): 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. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
5. dissolved, abolished or demolished date, also known as ended, publication end date, final issue, date repealed, final year (wd:P576 as p/wdt): point in time at which the subject (organisation, building) ceas...g equipment,  "discontinued date" (P2669) for stopping a product, end time
6. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as p/wdt): main Wikimedia category
7. replaced by, also known as heir, superseded by, successor, succeeded by, next job holder (wd:P1366 as p/wdt): other person or item which continues the item by replacing it in... nor identical, but adds to the series (e.g. books in a series)., followed by
8. location of formation, also known as place of incorporation, originates from, place of establishment, place of formation, place of foundation (wd:P740 as p/wdt): location where a group or organization was formed, location of creation
9. legal form, also known as legal structure, structured as (wd:P1454 as p/wdt): legal form of an entity, instance of
10. headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as p/wdt): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place

No other items found

[Assistant] The property `dissolved, abolished or demolished date` (wd:P576) seems relevant to check if Manglobe still exists. Let's run a SPARQL query to find this information.

[Tool]
Got 1 row and 1 column:
| dissolvedDate                       |
| ----------------------------------- |
| 2015-09-30T00:00:00Z (xsd:dateTime) |

[Assistant]
Manglobe, the production company of Samurai Champloo, dissolved on September 30, 2015. Therefore, the production company no longer exists.

To confirm this, we can use an ASK query to check if the dissolved date is present for Manglobe.

[Tool] True

[Assistant]
The ASK query confirms that Manglobe has a dissolved date, indicating that the production company no longer exists.

Therefore, the answer to the question "Is the production company of Samurai Champloo still existing?" is **False**.

Here is the final SPARQL query:

```sparql
ASK WHERE { wd:Q645476 wdt:P576 ?dissolvedDate . }
```

And the answer is **False**.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( ?part ) AS ?count ) WHERE {
  wd:Q208156 wdt:P527 ?part .
}

Got 1 row and 1 column:
| count       |
| ----------- |
| 2 (xsd:int) |

The Mongols tried to invade Japan 2 times.

[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 often did the Mongols try to invade Japan?

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

[Tool]
Example 1:
Question:
What country is Mount Everest in?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q513 wdt:P17 ?uri .
}

Using entities:
Mount Everest, also known as Chomolungma, Chomolangma, Zhumulangma, World highest peak, Sagarmāthā (wd:Q513): Earth's highest mountain above sea level, located in the Mahalangur Himal sub-range of the Himalayas

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

Example 2:
Question:
With how many countries Iran has borders?

SPARQL:
SELECT ?uri WHERE {
  wd:Q794 wdt:P47 ?uri .
}

Using entities:
Iran, also known as ir, IRI, IRN, Islamic Rep. Iran, Islamic Republic of Iran (wd:Q794): country in Western Asia

Using properties:
shares border with, also known as shares borders with, next to, bordered by, border, borders clockwise (wd:P47 as wdt): countries or administrative subdivisions, of equal level, that t...rders, either by land or water. A single common point is enough.

Example 3:
Question:
Who is starring in Spanish movies produced by Benicio del Toro?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?movie wdt:P31 wd:Q11424 ; wdt:P162 wd:Q193668 ; wdt:P495 wd:Q29 ; wdt:P161 ?uri .
}

Using entities:
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
Benicio del Toro, also known as Benicio Del Toro (wd:Q193668): Puerto Rican actor, television actor, film director, film producer, screenwriter, film actor, actor
Spain, also known as Kingdom of Spain (wd:Q29): country in southwestern Europe with territories in Africa

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as wdt): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
producer, also known as music producer, record producer, produced by, film producer, creative producer (wd:P162 as wdt): person(s) who produced the film, musical work, theatrical produc...etc.) [for production company, use P272, video games - use P178]
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as wdt): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country

[Assistant] Based on the examples, we need to identify the relevant entities and properties for our question. We are looking for the number of times the Mongols tried to invade Japan. Let's start by searching for the entity representing the Mongol invasions of Japan.

[Tool]
Top 10 entity alternatives:
1. Mongol invasions of Japan, also known as Attempted Mongol Invasions, 1274-1281, Japan--History--Attempted Mongol Invasions, 1274-1281 (wd:Q208156): attempts by the Mongol Empire to conquer Japan
2. Mongol invasions of Korea (wd:Q702266): Mongol Yuán Conquests of the Korean peninsula
3. Mongol invasions of Georgia, also known as Mongol conquests of Kingdom of Georgia (wd:Q2917513): 1220–1236 Mongol invasions of the Kingdom of Georgia
4. Mongol invasions of Vietnam (wd:Q2448644): 13th-century military campaigns of the Mongol Empire and Yuan-dynasty China in Vietnam
5. Mongol invasions of India (wd:Q2079940): history of Mongols with India
6. Mongol invasions of Sakhalin (wd:Q11344677): 1264 Invasions of the island Sakhalin by the Mongolian Yuan dynasty
7. Mongol invasions of Durdzuketi (wd:Q6899563): invasions of the territory of modern Chechnya and Ingushetia
8. Mongol invasions of Lithuania (wd:Q63859061)
9. Mongol invasions of Azerbaijan (wd:Q107354947)
10. Mongol invasions of Alania (wd:Q113130790)

[Assistant] The top result is the entity for the Mongol invasions of Japan (wd:Q208156). Now, let's check the properties associated with this entity to see if there is a property that indicates the number of invasions or attempts.

[Tool]
Top 10 property alternatives:
1. participant, also known as suspect, player, party, participants, has participant (wd:P710 as p/wdt): person, group of people or organization (object) that actively t...ct has role" (P3831). Use P1923 for participants that are teams., significant person
2. located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as p/wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
3. has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as p/wdt): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).
4. point in time, also known as at time, as of, year, when, time of event (wd:P585 as p/wdt): date something took place, existed or a statement was true; for providing time use the "refine date" property (P4241)
5. depicted by, also known as acted by, shown in, seen in, portrayed by, played by (wd:P1299 as p/wdt): object depicting this subject (object being creative works such as books, films, paintings)
6. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as p/wdt): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object

No other items found

[Assistant] It seems that there is no direct property indicating the number of invasions. However, we can look at the events or battles that were part of the Mongol invasions of Japan. Let's list the triples where the Mongol invasions of Japan (wd:Q208156) is the subject to see if there are any relevant properties or objects.

[Tool]
Got 293 rows and 3 columns, showing the first 10 rows below:
| subject                                | property                                                    | object                                                                                |
| -------------------------------------- | ----------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------ |
| Mongol invasions of Japan (wd:Q208156) | instance of (wdt:P31)                                       | conflict (wd:Q180684)                                                                                |
| Mongol invasions of Japan (wd:Q208156) | country (wdt:P17)                                           | Japan (wd:Q17)                                                                                |
| Mongol invasions of Japan (wd:Q208156) | located in the administrative territorial entity (wdt:P131) | Saikaidō (wd:Q1334003)                                                                                |
| Mongol invasions of Japan (wd:Q208156) | Commons category (wdt:P373)                                 | Mongol invasions of Japan                                                                                |
| Mongol invasions of Japan (wd:Q208156) | image (wdt:P18)                                             | <http://commons.wikimedia.org/wiki/Special:FilePath/Japan%20in%20Marco%20Polo%27s%20travel%20record%20%282%29.JPG> |
| Mongol invasions of Japan (wd:Q208156) | part of (wdt:P361)                                          | Mongol invasions and conquests (wd:Q2092093)                                                                       |
| Mongol invasions of Japan (wd:Q208156) | location (wdt:P276)                                         | Northern Kyushu (wd:Q397703)                                                                                |
| Mongol invasions of Japan (wd:Q208156) | has part(s) (wdt:P527)                                      | Battle of Kōan (wd:Q2237622)                                                                                |
| Mongol invasions of Japan (wd:Q208156) | point in time (wdt:P585)                                    | 1274-01-01T00:00:00Z (xsd:dateTime)                                                                                |
| Mongol invasions of Japan (wd:Q208156) | participant (wdt:P710)                                      | Yuan dynasty (wd:Q7313)                                                                                |
| ...                                    | ...                                                         | ...                                                                                |

[Assistant] From the triples, we can see that the Mongol invasions of Japan (wd:Q208156) has parts, specifically the Battle of Kōan (wd:Q2237622). To determine the number of invasions, we can count the number of battles or events that are part of the Mongol invasions of Japan. Let's write a SPARQL query to count these parts.

[Tool]
Got 1 row and 1 column:
| count       |
| ----------- |
| 2 (xsd:int) |

[Assistant]
The SPARQL query returned a count of 2, indicating that there were two major invasions or battles during the Mongol invasions of Japan.

Therefore, the answer to the question "How often did the Mongols try to invade Japan?" is:

The Mongols tried to invade Japan 2 times.

Let's finalize this with the answer function.

[Tool] Stopped generation process