PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?founder WHERE {
  wd:Q848490 wdt:P112 ?founder
}

Ikutaro Kakehashi

[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 founded the Roland Corporation?

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

[Tool]
Example 1:
Question:
Who founded Intel?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q248 wdt:P112 ?uri .
}

Using entities:
Intel, also known as INTC, Integrated Electronics, Integrated Electronics Corporation, INTEL CORPORATION (Santa Clara, CA), N M Electronics (wd:Q248): American multinational technology corporation, American multinational technology company

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

Example 2:
Question:
Who developed Skype?

SPARQL:
SELECT ?uri WHERE {
  wd:Q40984 wdt:P178 ?uri .
}

Using entities:
Skype (wd:Q40984): telecommunications software service

Using properties:
developer, also known as written by, video game developer, video game dev, game developer, game dev (wd:P178 as wdt): organization or person that developed the item, creator

Example 3:
Question:
Which electronics companies were founded in Beijing?

SPARQL:
SELECT DISTINCT ?company WHERE {
  ?company wdt:P452 wd:Q581105 ; wdt:P740 wd:Q956 .
}

Using entities:
consumer electronics, also known as home electronics, household electronics (wd:Q581105): electronic equipment intended for everyday use, typically in private homes
Beijing, also known as Pei-ping, Peip'ing, Peiping, Pekin, Pe-king (wd:Q956): capital city of China

Using properties:
industry, also known as branch, economic branch, field of action, field of exercise, sector (wd:P452 as wdt): specific industry of company or organization, part of
location of formation, also known as place of incorporation, originates from, place of establishment, place of formation, place of foundation (wd:P740 as wdt): location where a group or organization was formed, location of creation

[Assistant] Based on the examples, we need to find the entity for Roland Corporation and then use the property 'founded by' (P112) to find the founder. Let's first search for the entity Roland Corporation.

[Tool]
Top 10 entity alternatives:
1. Roland Corporation, also known as Roland, Roland Corp. (wd:Q848490): Japanese audiovisual equipment company
2. Roland DG, also known as Roland DG Corporation (wd:Q2162714)
3. Roland Foods Corporation (wd:Q23461918): Food importer in New York
4. Roland DGA Corporation (wd:Q22812960): American arm of Roland DG Corporation
5. corporation, also known as corporated entity (wd:Q167037): legal entity incorporated through a legislative or registration process
6. Roland, also known as Rotholandus, Orlando, Hruodlandus, Hruodland (wd:Q207535): Frankish military leader under Charlemagne and main character of the Song of Roland, knight
7. Roland, also known as Roland, IA, Roland, Iowa (wd:Q1925777): city in Iowa
8. Roland, also known as Roland, USA, Roland, Oklahoma, Roland, OK (wd:Q2321457): town in Sequoyah County, Oklahoma, USA
9. Roland (wd:Q1068487): male given name
10. Roland, also known as Euromissile Roland, Roland SAM, MIM-115, Roland missile (wd:Q705254): 1960s surface-to-air missile system of Franco-German origin

[Assistant] The correct entity for Roland Corporation is the first one, wd:Q848490. Now let's use the property 'founded by' (P112) to find the founder of Roland Corporation.

[Tool]
Got 1 row and 1 column:
| founder                        |
| ------------------------------ |
| Ikutaro Kakehashi (wd:Q322845) |

[Assistant]
The founder of Roland Corporation is Ikutaro Kakehashi.

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

[Tool] Stopped generation process

[User]
Feedback (status=done):
The output is correct and complete. The SPARQL query correctly identifies Ikutaro Kakehashi as the founder of Roland Corporation using the appropriate Wikidata entity and property.


PREFIX p: <http://www.wikidata.org/prop/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?country ?countryLabel ?start ?end WHERE {
  wd:Q641 p:P17 ?statement .
  ?statement ps:P17 ?country .
  OPTIONAL {
    ?statement pq:P580 ?start .
  }
  OPTIONAL {
    ?statement pq:P582 ?end .
  }
  OPTIONAL {
    ?country rdfs:label ?countryLabel .
    FILTER ( LANG( ?countryLabel ) = "en" )
  }
  FILTER ( ?country = wd:Q131964 )
}

Yes, Venice belonged to the Austrian Empire during the periods from August 11, 1804, to December 26, 1805, and from June 9, 1815, to August 22, 1866.

[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 similar examples.

[Tool] No examples found

[Assistant] Since we couldn't find any similar examples, let's start by searching for the entities mentioned in the question: Venice and the 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

[Assistant]
From the search results, it seems that the correct entity for Venice is `wd:Q641`, which refers to the capital city of Veneto, Italy.

Next, let's search for 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 correct entity for the Austrian Empire is `wd:Q131964`.

Now, let's look for properties that might indicate whether Venice belonged to the Austrian Empire at any point in time. We can search for properties related to "belonging" or "part of" for the entity Venice.

[Tool]
Top 10 property alternatives:
1. part of, also known as of, within, system of, subsystem of, subgroup of (wd:P361 as wdt/p): object of which the subject is a part (if this subject is alread... of "has part" (P527, see also "has parts of the class" (P2670))
2. member of, also known as band member of, membership, member of musical group, in musical group, be member of (wd:P463 as wdt/p): organization, club or musical group to which the subject belongs...ical position, such as a member of parliament (use P39 for that), part of
3. shares border with, also known as shares borders with, next to, bordered by, border, borders clockwise (wd:P47 as wdt/p): countries or administrative subdivisions, of equal level, that t...rders, either by land or water. A single common point is enough.
4. contains the administrative territorial entity, also known as has shires, has rural cities, has regions, has municipalities, has members (wd:P150 as wdt/p): (list of) direct subdivisions of an administrative territorial entity, has part(s)
5. 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
6. area, also known as total area, surface area, surface, size, resolution (wd:P2046 as wdt/p): area occupied by an object
7. category of associated people, also known as key people category, category of people associated with this place, category for people associated with this place (wd:P1792 as wdt/p): Wikimedia category for people associated with this place or organization, related category
8. depicted by, also known as acted by, shown in, seen in, portrayed by, played by (wd:P1299 as wdt/p): object depicting this subject (object being creative works such as books, films, paintings)
9. present in work, also known as is shown in, in work, in narrative, character in, from work (wd:P1441 as wdt/p): this (fictional or fictionalized) entity, place, or person appea...r works, P1343 for entities described in non-fictional accounts)
10. legislative body, also known as aboriginal council, Zila, Tehsil, rural council, representative body (wd:P194 as wdt/p): legislative body governing this entity; political institution wi...ted representatives, such as a parliament/legislature or council

No other items found

[Assistant]
The property `part of` (wd:P361) seems relevant for determining if Venice was part of the Austrian Empire at any point. Let's check if there are any statements indicating that Venice was part of the Austrian Empire.

We'll start with a simple query to see if there is a direct statement linking Venice to the Austrian Empire.

```sparql
SELECT ?empire
WHERE {
  wd:Q641 wdt:P361 ?empire .
  FILTER(?empire = wd:Q131964)
}
```

Let's execute this query.

[Tool] Got no rows and 1 columns

[Assistant]
The query did not return any results, which suggests that there is no direct statement indicating that Venice was part of the Austrian Empire. However, this does not necessarily mean that Venice never belonged to the Austrian Empire. It could be that the relationship is more complex or involves a different property.

Let's try another approach by looking at the historical context. We can search for properties related to "history" or "rule" for the entity 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 wdt/p): time when an entity begins to exist; for date of official opening use P1619, start time
2. significant event, also known as significant occurrence, significant incident, significant achievment, sign. event, outcome (wd:P793 as wdt/p): significant or notable events associated with the subject
3. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as wdt/p): award or recognition received by a person, organization or creative work
4. present in work, also known as is shown in, in work, in narrative, character in, from work (wd:P1441 as wdt/p): this (fictional or fictionalized) entity, place, or person appea...r works, P1343 for entities described in non-fictional accounts)
5. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as wdt/p): work where this item is described, attested in
6. different from, also known as not to be confused with, to be distinguished from, similar to, see also, rejected match (wd:P1889 as wdt/p): item that is different from another item, with which it may be confused
7. named after, also known as toponym, namesake, named in honor of, named for, etymology (wd:P138 as wdt/p): entity or event that inspired the subject's name, or namesake (i...fier "applies to name" (P5168) can be used to indicate which one
8. 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
9. official name, also known as long title, name, official title, registered name, full title (wd:P1448 as wdt/p): official name of the subject in its official language(s), name
10. Treccani's Dizionario di Storia ID, also known as Dizionario di Storia ID (wd:P6404 as wdt/p): identifier for Dizionario di Storia ("Dictionary of History") by Treccani

No other items found

[Assistant]
The property `significant event` (wd:P793) seems relevant for finding historical events related to Venice. Let's check if there are any significant events that indicate Venice's relationship with the Austrian Empire.

We'll start with a query to find significant events related to Venice:

```sparql
SELECT ?event ?eventLabel
WHERE {
  wd:Q641 wdt:P793 ?event .
  OPTIONAL { ?event rdfs:label ?eventLabel . FILTER(LANG(?eventLabel) = "en") }
}
LIMIT 10
```

Let's execute this query to see if we can find any relevant events.

[Tool]
Got 1 row and 2 columns:
| event                       | eventLabel           |
| --------------------------- | -------------------- |
| excommunication (wd:Q49822) | excommunication (en) |

[Assistant]
The query returned only one significant event, which is "excommunication." This event does not seem to be directly related to Venice's relationship with the Austrian Empire.

Given that the direct and indirect approaches have not yielded clear results, let's try a more specific query to check if there are any historical periods during which Venice was under the control of the Austrian Empire. We can look for properties related to "rule" or "control" and see if there are any statements indicating a period of Austrian rule over Venice.

Let's search for properties related to "rule" or "control" for the entity Venice.

[User]
Feedback (status=refine):
The current query focuses on significant events related to Venice, but it does not specifically address whether Venice belonged to the Austrian Empire. To better answer the question, we should look for periods of rule or control over Venice, particularly by the Austrian Empire. Let's refine the query to check for such relationships.

[Assistant]
To refine our approach, let's look for properties that indicate periods of rule or control over Venice. Specifically, we can search for properties related to "ruled by" or "controlled by."

Let's search for these properties for the entity Venice.

[Tool]
Top 10 property alternatives:
1. 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]
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. shares border with, also known as shares borders with, next to, bordered by, border, borders clockwise (wd:P47 as wdt/p): countries or administrative subdivisions, of equal level, that t...rders, either by land or water. A single common point is enough.
4. depicted by, also known as acted by, shown in, seen in, portrayed by, played by (wd:P1299 as wdt/p): object depicting this subject (object being creative works such as books, films, paintings)
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. head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as wdt/p): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson
7. legislative body, also known as aboriginal council, Zila, Tehsil, rural council, representative body (wd:P194 as wdt/p): legislative body governing this entity; political institution wi...ted representatives, such as a parliament/legislature or council
8. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as wdt/p): label for the items in their official language  or their original language, name
9. official name, also known as long title, name, official title, registered name, full title (wd:P1448 as wdt/p): official name of the subject in its official language(s), name
10. part of, also known as of, within, system of, subsystem of, subgroup of (wd:P361 as wdt/p): object of which the subject is a part (if this subject is alread... of "has part" (P527, see also "has parts of the class" (P2670))

No other items found

[Assistant]
The property `country` (wd:P17) seems relevant for determining the sovereign state that Venice belonged to at different points in history. Let's check if there are any statements indicating that Venice was part of the Austrian Empire during a specific period.

We'll start with a query to find the country or sovereign state that Venice belonged to:

```sparql
SELECT ?country ?countryLabel ?start ?end
WHERE {
  wd:Q641 p:P17 ?statement .
  ?statement ps:P17 ?country .
  OPTIONAL { ?statement pq:P580 ?start . }
  OPTIONAL { ?statement pq:P582 ?end . }
  OPTIONAL { ?country rdfs:label ?countryLabel . FILTER(LANG(?countryLabel) = "en") }
  FILTER(?country = wd:Q131964)
}
```

This query will check if there is a statement indicating that Venice was part of the Austrian Empire and also retrieve the start and end dates of this period if available.

Let's execute this query.

[Tool]
Got 2 rows and 4 columns:
| country                      | countryLabel         | start                               | end                                 |
| ---------------------------- | -------------------- | ----------------------------------- | ----------------------------------- |
| Austrian Empire (wd:Q131964) | Austrian Empire (en) | 1804-08-11T00:00:00Z (xsd:dateTime) | 1805-12-26T00:00:00Z (xsd:dateTime) |
| Austrian Empire (wd:Q131964) | Austrian Empire (en) | 1815-06-09T00:00:00Z (xsd:dateTime) | 1866-08-22T00:00:00Z (xsd:dateTime) |

[Assistant]
The query results show that Venice was indeed part of the Austrian Empire during two distinct periods:

1. From August 11, 1804, to December 26, 1805.
2. From June 9, 1815, to August 22, 1866.

This confirms that Venice belonged to the Austrian Empire at certain points in history.

Here is the final SPARQL query and the answer to the question:

```sparql
SELECT ?country ?countryLabel ?start ?end
WHERE {
  wd:Q641 p:P17 ?statement .
  ?statement ps:P17 ?country .
  OPTIONAL { ?statement pq:P580 ?start . }
  OPTIONAL { ?statement pq:P582 ?end . }
  OPTIONAL { ?country rdfs:label ?countryLabel . FILTER(LANG(?countryLabel) = "en") }
  FILTER(?country = wd:Q131964)
}
```

Answer: Yes, Venice belonged to the Austrian Empire during the periods from August 11, 1804, to December 26, 1805, and from June 9, 1815, to August 22, 1866.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The output is correct and complete. The SPARQL query successfully retrieves the periods during which Venice belonged to the Austrian Empire, and the answer accurately reflects this information.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ( COUNT( ?work ) AS ?count ) WHERE {
  wd:Q1621261 wdt:P1441 ?work .
  ?work wdt:P144 wd:Q79037 .
}

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

[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 similar 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)

[Assistant] Based on the example, we need to identify the entities for Spider-Man and Venom, and the property that links them to the works they are part of. Let's start by searching for these entities.

[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] The first result, `wd:Q79037`, seems to be the most appropriate for the character Spider-Man. Now let's search for Venom.

[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

[Assistant]
The third result, `wd:Q1621261`, seems to be the most appropriate for the character Venom. Now let's look for the property that links characters to the works they are part of. We can search for properties related to "character" or "part of" for both Spider-Man and Venom to see if we can find a common property.

First, let's search for properties related to "character" for Spider-Man.

[Tool]
Top 10 property alternatives:
1. present in work, also known as is shown in, in work, in narrative, character in, from work (wd:P1441 as wdt/p): this (fictional or fictionalized) entity, place, or person appea...r works, P1343 for entities described in non-fictional accounts)
2. performer, also known as actor, sung by, singer, recording by, recorded by (wd:P175 as wdt/p): actor, musician, band or other performer associated with this role or musical work, contributor to the creative work or subject
3. Personality Database profile ID, also known as Personality DB ID, www.personality-database.com/profile/, Personality DB profile ID, Personality DB profile, Personality DB identifier (wd:P10757 as wdt/p): identifier of a human, fictional character, or other entity on the Personality Database website
4. 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)
5. superhuman feature or ability, also known as has superpower, magic, magic ability, magical ability, supernatural abilities (wd:P2563 as wdt/p): superhuman, supernatural, or paranormal abilities that the fictional subject exhibits, uses
6. from narrative universe, also known as from narrative, in continuity, from universe, in cycle, in world of (wd:P1080 as wdt/p): subject's fictional entity is in the object narrative. See also P1441 (present in work) and P1445 (fictional universe described in), part of
7. 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)
8. occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt/p): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
9. given name, also known as name, proper name, personal name, middle name, forename (wd:P735 as wdt/p): first name or another given name of this person; values used with the property should not link disambiguations nor family names, name
10. Behind The Voice Actors character ID, also known as Behind The Voice Actors character identifier, BTVA character ID, BTVA character identifier (wd:P5107 as wdt/p): identifier of a character from the Behind The Voice Actors website

No other items found

[Assistant] The property `wdt:P1441` (present in work) seems to be the most relevant for linking characters to the works they are part of. Let's verify this property for Venom as well.

[Tool]
Top 10 property alternatives:
1. present in work, also known as is shown in, in work, in narrative, character in, from work (wd:P1441 as wdt/p): this (fictional or fictionalized) entity, place, or person appea...r works, P1343 for entities described in non-fictional accounts)
2. character type, also known as -dere, stock character, stereotype, dere, character stereotype (wd:P9071 as wdt/p): generic character type that this fictional character represents, manifestation of
3. performer, also known as actor, sung by, singer, recording by, recorded by (wd:P175 as wdt/p): actor, musician, band or other performer associated with this role or musical work, contributor to the creative work or subject
4. Personality Database profile ID, also known as Personality DB ID, www.personality-database.com/profile/, Personality DB profile ID, Personality DB profile, Personality DB identifier (wd:P10757 as wdt/p): identifier of a human, fictional character, or other entity on the Personality Database website
5. 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)
6. from narrative universe, also known as from narrative, in continuity, from universe, in cycle, in world of (wd:P1080 as wdt/p): subject's fictional entity is in the object narrative. See also P1441 (present in work) and P1445 (fictional universe described in), part of
7. 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)
8. Behind The Voice Actors character ID, also known as Behind The Voice Actors character identifier, BTVA character ID, BTVA character identifier (wd:P5107 as wdt/p): identifier of a character from the Behind The Voice Actors website
9. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as wdt/p): language(s) that a person or a people speaks, writes or signs, including the native language(s)
10. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as wdt/p): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)

No other items found

[Assistant]
The property `wdt:P1441` (present in work) is also relevant for Venom. Now, let's construct a SPARQL query to count the number of works that are based on Spider-Man and in which Venom has appeared.

We will use the following entities and properties:
- Spider-Man: `wd:Q79037`
- Venom: `wd:Q1621261`
- Present in work: `wdt:P1441`

Let's write the initial SPARQL query to count the works.

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

[Assistant]
It seems that the initial query did not return any results, indicating that there might be no works where Venom appears and are also based on Spider-Man. However, let's refine the query to ensure we are not missing any works by checking if there are any works where Venom appears and then separately check if those works are based on Spider-Man.

We will first list the works where Venom appears and then check if those works are based on Spider-Man.

[Tool]
Got 6 rows and 1 column:
| work                                                   |
| ------------------------------------------------------ |
| Spider-Man 3 (wd:Q182212)                              |
| Spider-Man 3 (wd:Q2337769)                             |
| Marvel vs. Capcom: Clash of Super Heroes (wd:Q2415823) |
| Marvel vs. Capcom: Infinite (wd:Q27971937)             |
| Spider-Man (wd:Q288296)                                |
| Marvel vs. Capcom 2: New Age of Heroes (wd:Q383700)    |

[Assistant]
We have identified several works where Venom appears. Now, let's check if any of these works are based on Spider-Man. We will use the property `wdt:P144` (based on) to check if these works are based on Spider-Man.

Let's write the SPARQL query to check this.

[Tool] Got no rows and 1 columns

[Assistant]
The query did not return any results, indicating that none of the works where Venom appears are directly based on Spider-Man. However, it's possible that some of these works are part of a larger series or franchise that is based on Spider-Man. Let's check if any of these works are part of a series or franchise that includes Spider-Man.

We will use the property `wdt:P179` (part of the series) to check if any of the works are part of a series that includes Spider-Man.

[Tool] Got no rows and 2 columns

[Assistant]
The query did not return any results, indicating that none of the works where Venom appears are part of a series that is based on Spider-Man.

Given the results, it seems that there are no works where Venom appears that are directly based on Spider-Man or part of a series based on Spider-Man. Therefore, the answer to the question is that there are 0 such works.

Let's finalize the answer with an ASK query to confirm this conclusion.

[Tool] Stopped generation process

[User]
Feedback (status=retry):
The SPARQL query is using an ASK query which will only return a boolean value. However, the question asks for a count of works, not a boolean. The query should be changed to a SELECT query that counts the number of works where Venom is present and the work is based on Spider-Man.

[Assistant]
Thank you for the feedback. I understand that the question asks for a count of works, not a boolean value. Let's correct the SPARQL query to count the number of works where Venom appears and the work is based on Spider-Man.

Here is the corrected SPARQL query:

```sparql
SELECT (COUNT(?work) AS ?count) WHERE {
  wd:Q1621261 wdt:P1441 ?work .
  ?work wdt:P144 wd:Q79037 .
}
```

Let's execute this query to get the count of works.

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

[Assistant]
The query confirms that there are 0 works where Venom appears and the work is based on Spider-Man.

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

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is correctly formulated and returns the accurate count of works where Venom has been a part of that are based on Spider-Man. The answer is 0, which means there are no such works according to the data in Wikidata.


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

The Ayutthaya Kingdom (wd:Q841364) preceded the Thonburi 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 similar examples.

[Tool] No examples found

[Assistant] Since no similar examples were found, let's proceed by searching for the entity "Thonburi Kingdom" in the knowledge graph.

[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 first result, "Thonburi Kingdom" (wd:Q1115291), seems to be the correct entity we are looking for. Now, let's search for properties related to "preceding" or "predecessor" for this entity.

[Tool]
Top 10 property alternatives:
1. followed by, also known as continued as, then, successor, succeeded by, sequel is (wd:P156 as wdt/p): immediately following item in a series of which the subject is a...een replaced, e.g. political offices, use "replaced by" (P1366)]
2. replaces, also known as supersedes, succeeds, replaced, previous job holder, preceded by (wd:P1365 as wdt/p): person, state or item replaced. Use "structure replaces" (P1398)...item was not replaced or predecessor and successor are identical, follows
3. 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
4. Freebase ID, also known as Freebase, MID, Freebase identifier, FID (wd:P646 as wdt/p): identifier for a page in the Freebase database. Format: "/m/0" f...r IDs starting with "/g/", use Google Knowledge Graph ID (P2671)
5. 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)
6. dissolved, abolished or demolished date, also known as ended, publication end date, final issue, date repealed, final year (wd:P576 as wdt/p): point in time at which the subject (organisation, building) ceas...g equipment,  "discontinued date" (P2669) for stopping a product, end time
7. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as wdt/p): main Wikimedia category

No other items found

[Assistant]
The property "replaces" (wd:P1365) seems to be the most relevant for finding the kingdom that preceded the Thonburi Kingdom. Let's construct a simple SPARQL query to find the value of this property for the Thonburi Kingdom.

Here is the initial SPARQL query:

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

Let's execute this query to see if it returns the expected result.

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

[Assistant]
The query returned the expected result: the Ayutthaya Kingdom (wd:Q841364) is the kingdom that preceded the Thonburi Kingdom.

Here is the final SPARQL query and the answer:

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

Answer: The Ayutthaya Kingdom (wd:Q841364) preceded the Thonburi Kingdom.

Now, let's provide the final answer using the `answer` function.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The output is correct and complete. The SPARQL query correctly identifies the predecessor of the Thonburi Kingdom using the 'preceded by' property (P1365). The result matches the expected answer, and no further refinement is needed.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
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 similar examples.

[Tool]
Example 1:
Question:
Which city has the oldest running metro?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?metro wdt:P31 wd:Q5503 ; wdt:P571 ?inception ; wdt:P131 ?uri .
}
ORDER BY ?inception
LIMIT 1

Using entities:
rapid transit, also known as rail rapid transit, underground, subway, metro (wd:Q5503): high-capacity public transport generally used in urban areas

Using properties:
located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
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)
inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as wdt): time when an entity begins to exist; for date of official opening use P1619, start time

[Assistant] From the example, we see that the property for the inception or start date is used, but for the official opening date, we should look for a different property. Let's search for the entity "Hamburg S-Bahn" first.

[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 correct entity for the Hamburg S-Bahn is `wd:Q693956`. Now let's search for the property related to the 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 pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): 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 pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): 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 pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): 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 pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): 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 pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): 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 pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): 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 pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): 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 pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): 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 pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): 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 pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): date of spacecraft launch in UTC

[Assistant]
The property for the official opening date is `wd:P1619`. Now we can construct a simple SPARQL query to find the official opening date of the Hamburg S-Bahn.

Let's execute the query:

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

[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.

Now, I will provide the final answer using the `answer` function.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The provided SPARQL query correctly retrieves the official opening date of the Hamburg S-Bahn from Wikidata. The answer is accurate and matches the expected result. No further refinements are necessary.


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

No, the production company of Samurai Champloo is not still existing.

[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 similar examples.

[Tool] No examples found

[Assistant] Since we couldn't find any similar examples, let's start by finding 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] From the search results, it seems that the first option, "Samurai Champloo (wd:Q143276)", is the correct entity for the anime series. Now, let's find out the production company of Samurai Champloo.

[Tool]
Top 10 property alternatives:
1. production company, also known as broadcasting company, theatrical troupe, theatre company, theater company, studio (wd:P272 as wdt/p): 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 wdt/p): 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 wdt/p): 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 wdt/p): 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 wdt/p): 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 wdt/p): 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 wdt/p): 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 wdt/p): identifier for a film on the Kinobox.cz website
9. distributed by, also known as distributor (wd:P750 as wdt/p): 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 wdt/p): 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 correct one to find the production company of Samurai Champloo. Let's execute a SPARQL query to get 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 (wd:Q645476). Now, let's check if Manglobe still exists.

To do this, we need to find a property that indicates whether a company is active or defunct. Let's search for such a property.

[Tool]
Top 10 property alternatives:
1. floruit, also known as work period, living, known alive in, flourished, fl. (wd:P1317 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): date when the person was known to be active or alive, when birth or death not documented
2. work location, also known as work place, working from, working at, worked from, worked at (wd:P937 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): location where persons or organisations were actively participating in employment, business or other work, significant place, location
3. work period (end), also known as floruit end, floruit (end of work), flourished (end), retirement, work ends (wd:P2032 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): end of period during which a person or group flourished (fl. = "floruit") in their professional activity, end time, floruit
4. work period (start), also known as start working, flourished (start), start time for work, start date of activity, fl. (start) (wd:P2031 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): start of period during which a person or group flourished (fl. = "floruit") in their professional activity, start time, floruit
5. state of use, also known as use status (wd:P5817 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): to indicate state of use of a building, monument, etc. It is not...t state of use. Ex.: abandoned, in use, temporarily closed, etc.
6. service status information URL, also known as status URL, system status URL, status URI, status page, status information URL (wd:P9138 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): URI with information about the status of the service, URL
7. online access status, also known as status of website, status of webpage, state of online access, publication access status, collection access status (wd:P6954 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): property or qualifier for an ID property indicating whether linked content is directly readable online, access restriction status, has characteristic
8. field of work, also known as scientific discipline, scientific area, responsible for, research on, research fields (wd:P101 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): specialization of a person or organization; see P106 for the occupation, interested in
9. heritage designation, also known as legal protection, protection, protected status, listing, listed status (wd:P1435 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): heritage designation of a cultural or natural site, has part(s), instance of
10. nature of statement, also known as validity of statement, status of statement, refine statement, precisely, modality of statement (wd:P5102 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): (qualifier only) the underlying circumstances of this statement

[Assistant]
None of these properties directly indicate whether a company is active or defunct. However, we can try to infer the status by checking if there are any recent activities or events associated with the company. One way to do this is to look for properties like "dissolved date" or "end date".

Let's search for properties related to "dissolved" or "end date" for the entity Manglobe.

[Tool]
Top 10 property alternatives:
1. dissolved, abolished or demolished date, also known as ended, publication end date, final issue, date repealed, final year (wd:P576 as wdt/p): point in time at which the subject (organisation, building) ceas...g equipment,  "discontinued date" (P2669) for stopping a product, end time
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

No other items found

[Assistant] The property "dissolved, abolished or demolished date" (wd:P576) is the one we need to check if Manglobe has been dissolved. Let's execute a SPARQL query to find out if Manglobe has a dissolved date.

[Tool] True

[Assistant]
The SPARQL query returned `True`, which means that Manglobe does have a dissolved date. Therefore, the production company of Samurai Champloo is no longer existing.

Here is the final SPARQL query and answer:

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

Answer: No, the production company of Samurai Champloo is not still existing.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is correctly formulated as an ASK query and it checks whether the production company of Samurai Champloo (Manglobe) has a dissolved date. Since the result is True, it means that Manglobe has indeed been dissolved, and thus the answer 'No, the production company of Samurai Champloo is not still existing' is correct.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ( COUNT( ?event ) AS ?invasionCount ) WHERE {
  ?event wdt:P361 wd:Q208156 .
  ?event wdt:P31 wd:Q178561 .
}

Got 1 row and 1 column:
| invasionCount |
| ------------- |
| 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 similar examples.

[Tool]
Example 1:
Question:
Give me all islands that belong to Japan.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q23442 ; wdt:P17 wd:Q17 .
}

Using entities:
Japan, also known as State of Japan, Nippon-koku, Nippon, Nihon-koku, Nihon (wd:Q17): island country in East Asia
island, also known as islands, isle (wd:Q23442): piece of sub-continental land completely surrounded by water

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
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] None of the examples directly relate to military invasions, but we can use them as a starting point. We need to identify the entities for Mongolia and Japan, and then look for properties related to military conflicts or invasions.

[Tool]
Top 10 entity alternatives:
1. Mongolia, also known as Mongol State, State of Mongolia (wd:Q711): country in East Asia
2. Mongolia (wd:Q5651926): Spanish satirical magazine
3. Mongolia, also known as IMO 9041069 (wd:Q83628274): ship built in 1996
4. Mongolia, also known as Mongolia, Ontario (wd:Q6899577): dispersed rural community in Markham, Ontario
5. Mongolia (wd:Q58155321)
6. Mongolia (wd:Q59107775)
7. Mongolia. (wd:Q39542880): scientific article published on May 1987
8. Mongólia (wd:Q130643499): novel by Brazilian writer Bernardo Carvalho
9. Mongolia (wd:Q125270233): Ship from Verne's novel "Around the world in 80 days"
10. Mongolia (wd:Q103958675): encyclopedia article

[Assistant] The correct entity for Mongolia is `wd:Q711`. Now let's find the entity for Japan.

[Tool]
Top 10 entity alternatives:
1. Japan, also known as State of Japan, Nippon-koku, Nippon, Nihon-koku, Nihon (wd:Q17): island country in East Asia
2. Honshu, also known as Nippon, Nipon, Niphon, Meako, Meaco (wd:Q13989): largest island of Japan
3. Empire of Japan, also known as Great Japanese Empire, Great Empire of Japan, Japanese Empire, Imperial Japan, Japan (wd:Q188712): Empire in the Asia-Pacific region from 1868 to 1947
4. Tokugawa shogunate, also known as Edo Japan, Japan, Shogunate of Japan, Tokugawa Shogunate (wd:Q205662): 1603–1868 Japanese military government
5. Japan (wd:Q174933): English new wave band
6. 🗾, also known as Japan emoji, map of Japan emoji, SILHOUETTE OF JAPAN, U+1F5FE (wd:Q87581504): Unicode character
7. Japón, also known as Japan, Japon (wd:Q1072282): 2002 film by Carlos Reygadas
8. Japan (wd:Q122802935): 2023 Tamil film directed by Raju Murugan
9. Japan (wd:Q1407064): manga by Buronson
10. Japan, also known as Desa Japan (wd:Q11014269): village in Kudus Regency, Central Java, Indonesia

[Assistant] The correct entity for Japan is `wd:Q17`. Now we need to find properties related to military conflicts or invasions. Let's search for properties related to "invasion" or "military conflict".

[Tool]
Top 10 property alternatives:
1. invasive to, also known as alien to, introduced to (wd:P5588 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): region which a taxon is not endemic to where the taxon has a ten...o cause damage to the environment, human economy or human health
2. perpetrator, also known as robber, perpetrators, perpetrated by, perp, offender (wd:P8031 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): person or organization who carried out this harmful, illegal, or immoral act, participant
3. enemy, also known as opponent, rival, archvillain, archrival, archnemesis (wd:P7047 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): opponent character or group of this fictive character or group, significant person
4. conflict, also known as war, theatre (military), theater (military), participated in conflict, military conflict (wd:P607 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): battles, wars or other military engagements in which the person or item participated, participant in
5. territory overlaps, also known as partially overlaps, partially coincident with, partly coincident with, partly located in territorial entity, partly overlaps (wd:P3179 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): part or all of the area associated with (this) entity overlaps part or all of the area associated with that entity, partially coincident with
6. merged into, also known as absorbed in, acquired by, annexed to, bought by, dissolved into (wd:P7888 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): the subject was dissolved and merged into the object, that existed previously
7. gained territory from, also known as receives territory from, territory from (wd:P7903 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): (qualifier) territorial entity from which the subject item gained territory as a result of the event in the statement
8. has boundary, also known as has border, has 2D boundary, frontier, delimited by, boundary (wd:P4777 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): element that's on the two dimensional border that surrounds the subject; the limit of an entity
9. shares border with, also known as shares borders with, next to, bordered by, border, borders clockwise (wd:P47 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): countries or administrative subdivisions, of equal level, that t...rders, either by land or water. A single common point is enough.
10. occupant, also known as tenant, resident, renter, occupiers, lessee (wd:P466 as pr/wdtn/p/pq/pqv/wdt/psn/prv/ps/psv/prn/pqn): person or organization occupying property, used by

[Assistant] The property `wd:P607` (conflict, also known as war, theatre (military), theater (military), participated in conflict, military conflict) seems relevant. Let's check if there are any specific invasions involving Mongolia and 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. Operation Downfall, also known as invasion of Japan, Allied invasion of Japan (wd:Q300879): codename for the Allied plan for the invasion of Japan near the end of World War II
3. Mongol invasion of Poland (wd:Q2667645): Military campaign, 1240 to 1241
4. Mongol invasion of Kievan Rus' (wd:Q1134220): 1223 Mongol military campaign in Europe
5. Japanese invasion of Manchuria, also known as Japanese occupation of Manchuria (wd:Q1551794): 1931 part of the Second Sino-Japanese War
6. Japanese invasion of Taiwan, also known as Japanese expedition to Taiwan (1874), 牡丹社事件, Mudan Incident, Taiwan Expedition (wd:Q703942): Punitive expedition to Formosa (Taiwan), first foreign military campaign after the Meiji Ishin (Meiji Restoration)
7. Japanese invasion of Taiwan (wd:Q717373): 1895 invasion of Taiwan by Imperial Japan
8. Mongol invasions of Vietnam (wd:Q2448644): 13th-century military campaigns of the Mongol Empire and Yuan-dynasty China in Vietnam
9. First Mongol invasion of Burma (wd:Q531916): 1277 historical conquest
10. invasion of Ryukyu, also known as Japanese invasion of Ryukyu (wd:Q1140134): invasion of the Ryukyu Kingdom by the Satsuma Domain, resulting in the former’s being reduced to a vassal state of the latter

No other items found

No literal items found

[Assistant]
The entity `wd:Q208156` represents the Mongol invasions of Japan. Now, let's check if there are any specific instances or details about these invasions, such as the number of times they occurred.

We can start by querying for the instances of the Mongol invasions of Japan and see if there are any specific events or dates associated with them.

[Tool] Got no rows and 2 columns

[Assistant]
It seems that the Mongol invasions of Japan (`wd:Q208156`) do not have direct instances listed under the `wdt:P607` property. Let's try a different approach by looking for specific events or battles that are part of the Mongol invasions of Japan.

We can search for events or battles that are specifically labeled as part of the Mongol invasions of Japan.

[Tool]
Falling back to an unconstrained search on the full precomputed search indices:
Got more than the maximum supported number of object candidates (65,536)

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. Ghenkō: The Mongol invasion of Japan (wd:Q131292625): book published in 1916
3. Mōko Shūrai Ekotoba, also known as Illustrated Account of the Mongol invasion of Japan, The Mongol Scroll, Mongol Scroll, Illustrated Scrolls of the Mongol Invasions (wd:Q3087790): Illustrated Account of the Mongol Invasion
4. Operation Downfall, also known as invasion of Japan, Allied invasion of Japan (wd:Q300879): codename for the Allied plan for the invasion of Japan near the end of World War II
5. Mongol invasion of Europe (wd:Q852171): 13th century conquests by the Mongol Empire
6. Mongol invasion of Java (wd:Q2672432): 13th-century military campaign
7. Mongol invasion of Poland (wd:Q2667645): Military campaign, 1240 to 1241
8. Mongol invasion of China (wd:Q4301657): 13th century conquest
9. Mongol conquest of Tibet, also known as Mongol invasion of Tibet (wd:Q6899566): (1206 — 1723 )
10. Mongol invasion of India (wd:Q19562959): 1297–1298 Mongol military expedition in India

No other items found

No literal items found

[Assistant]
The search for events or battles that are part of the Mongol invasions of Japan did not yield specific instances. However, we can try a different approach by looking for specific battles or events that are directly related to the Mongol invasions of Japan.

Let's search for specific battles or events that are part of the Mongol invasions of Japan using the `wdt:P31` property, which indicates the type or class of an entity.

[Tool] Got no rows and 2 columns

[Assistant]
It seems that there are no specific events or battles directly linked to the Mongol invasions of Japan (`wd:Q208156`) using the `wdt:P31` property. Let's try another approach by looking for specific battles or events that are part of the Mongol invasions of Japan using the `wdt:P17` property, which indicates the country involved.

We can also try searching for specific battles or events that are part of the Mongol invasions of Japan using the `wdt:P361` property, which indicates that something is a part of something else.

[Tool]
Got 4 rows and 2 columns:
| event                                           | eventLabel                            |
| ----------------------------------------------- | ------------------------------------- |
| kamikaze (wd:Q1565008)                          | kamikaze (en)                         |
| Battle of Bun'ei (wd:Q2237386)                  | Battle of Bun'ei (en)                 |
| Battle of Kōan (wd:Q2237622)                    | Battle of Kōan (en)                   |
| 1266 Kublai Khan letter to Japan (wd:Q36295019) | 1266 Kublai Khan letter to Japan (en) |

[Assistant]
The query results show that there were two specific battles during the Mongol invasions of Japan:

1. **Battle of Bun'ei** (`wd:Q2237386`)
2. **Battle of Kōan** (`wd:Q2237622`)

These battles indicate that the Mongols attempted to invade Japan at least twice. To confirm the number of invasions, we can count these specific events.

Let's finalize the SPARQL query to count the number of invasions.

[Tool] Stopped generation process

[User]
Feedback (status=retry):
The SPARQL query returned a count of 4, which does not match the human-readable answer of 2. This discrepancy suggests that the query might be counting more events than just the two major Mongol invasions of Japan. We need to refine the query to ensure it only counts the specific invasions. Consider using more specific properties or filters to narrow down the results.

[Assistant]
Thank you for the feedback. Let's refine the query to ensure it only counts the specific invasions. We need to filter out events that are not battles or invasions.

We can use the `wdt:P31` property to filter for events that are instances of battles or invasions. Let's try this approach.

[Tool]
Got 2 rows and 2 columns:
| event                          | eventLabel            |
| ------------------------------ | --------------------- |
| Battle of Bun'ei (wd:Q2237386) | Battle of Bun'ei (en) |
| Battle of Kōan (wd:Q2237622)   | Battle of Kōan (en)   |

[Assistant]
The refined query correctly identifies the two specific battles that were part of the Mongol invasions of Japan:

1. **Battle of Bun'ei** (`wd:Q2237386`)
2. **Battle of Kōan** (`wd:Q2237622`)

Now, let's count these specific battles to confirm the number of invasions.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is correct and returns the expected result. The answer provided is accurate based on the information from the knowledge graph.