PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?animal ?animalLabel WHERE {
  wd:Q599644 wdt:P156 ?animal .
  OPTIONAL {
    ?animal rdfs:label ?animalLabel FILTER ( lang( ?animalLabel ) = "en" )
  }
}

The Chinese zodiac animal that follows the ox is the tiger (wd:Q740762).

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

You have access to the following knowledge graphs:
wikidata at http://amur:7001

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

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

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

[User] What is the Chinese zodiac animal that follows the ox?

[Assistant]
Let's break down the question:

1. We need to identify the entity for "Chinese zodiac".
2. Then, we need to find the entity for "ox" within the context of the Chinese zodiac.
3. Next, we need to find the property that represents the ordering or sequence of animals in the Chinese zodiac.
4. Finally, we need to find which animal comes after the ox in this sequence.

First, I'll search for the entity "Chinese zodiac" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Chinese zodiac, also known as Celestial Branches, Earthly Branches (wd:Q1976204): lunar calendar classification, assigning a symbolic animal and i... year for a repeating cycle of twelve forming the Earthly Branch
2. Chinese Zodiac, also known as CZ12 (wd:Q391143): 2012 film directed by Jackie Chan
3. 12 Chinese Zodiac Signs (wd:Q108781655): 1995 animated series
4. Panel with Chinese Zodiac (wd:Q78712547): painting by anonymous painter
5. goat (Chinese zodiac animal) (wd:L1116276-S2)
6. horse (Chinese zodiac animal) (wd:L1116275-S2)
7. dragon (Chinese zodiac animal) (wd:L1116273-S2)
8. dog (Chinese zodiac animal) (wd:L293489-S2)
9. Dog (Chinese zodiac sign) (wd:L363339-S2)
10. rabbit (Chinese zodiac animal) (wd:L1116272-S2)

[Assistant]
The most relevant entity for "Chinese zodiac" is wd:Q1976204.

Next, I need to identify the entity for "ox" within the context of the Chinese zodiac. I'll search for "ox Chinese zodiac" to get the correct entity.

[Tool]
Top 10 entity alternatives:
1. ox (Chinese zodiac animal) (wd:L1116270-S2)
2. Chinese zodiac, also known as Celestial Branches, Earthly Branches (wd:Q1976204): lunar calendar classification, assigning a symbolic animal and i... year for a repeating cycle of twelve forming the Earthly Branch
3. Ox, also known as Ox (zodiac) (wd:Q599644): 2nd sign of Chinese zodiac
4. Chinese Zodiac, also known as CZ12 (wd:Q391143): 2012 film directed by Jackie Chan
5. 12 Chinese Zodiac Signs (wd:Q108781655): 1995 animated series
6. Ox in Chinese mythology (wd:Q16242069)
7. Panel with Chinese Zodiac (wd:Q78712547): painting by anonymous painter
8. Zodiac Aerospace (United Kingdom), also known as Zodiac Oxygen Systems, Icore International Ltd (wd:Q28971327): UK business
9. Zodiac Aerospace (United States), also known as Zodiac Oxygen Systems (wd:Q28971326)
10. goat (Chinese zodiac animal) (wd:L1116276-S2)

[Assistant]
The most relevant entity for "ox" in the Chinese zodiac is wd:Q599644.

Now, I need to find the property that represents the ordering or sequence of animals in the Chinese zodiac. I will search for properties related to "follows" or "next" to see if there is a property that links zodiac animals in sequence.

[Tool]
Top 10 property alternatives:
1. based on, also known as modelled after, inspired by, iteration of, modeled after, fork of (wd:P144 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): the work(s) or inputs used as the basis for subject item; for fictional analog use P1074, references work, tradition or theory, inspired by
2. follows, also known as prev, successor to, succeeds to, succeeds, split from (wd:P155 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): immediately prior item in a series of which the subject is a par... preceding item, e.g. political offices, use "replaces" (P1365)]
3. followed by, also known as continued as, then, successor, succeeded by, sequel is (wd:P156 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): immediately following item in a series of which the subject is a...een replaced, e.g. political offices, use "replaced by" (P1366)]
4. number of subscribers, also known as number of followers, subscriptions, subscription count, subscribers, subscriber number (wd:P3744 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): number of subscribers for subscription-based companies, e.g. tel...unication companies, newspapers, pay-TV channels, software, etc.
5. social media followers, also known as number of subs, number of subscribers, sub count, sub number, subscriber number (wd:P8687 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): number of subscribers on a particular social media website (use ... in time" and property for account. For Twitter, use numeric id.
6. perpetrator, also known as robber, perpetrators, perpetrated by, perp, offender (wd:P8031 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): person or organization who carried out this harmful, illegal, or immoral act, participant
7. follower of (wd:P1775 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): for unknown artists who work in the manner of the named artist, significant person
8. lifestyle, also known as diet, follows lifestyle, has lifestyle, life style (wd:P1576 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): typical way of life of an individual, group, or culture
9. has effect, also known as has symptom, implies, leads to, led to, outcome (wd:P1542 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): effect of this item, followed by
10. replaces, also known as supersedes, succeeds, replaced, previous job holder, preceded by (wd:P1365 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): person, state or item replaced. Use "structure replaces" (P1398)...item was not replaced or predecessor and successor are identical, follows

[Assistant]
The most relevant properties for sequence are:
- "follows" (wd:P155): immediately prior item in a series.
- "followed by" (wd:P156): immediately following item in a series.

Since we want to know which animal comes after the ox, we should use "followed by" (wd:P156) with the ox entity.

I will now check if the ox (wd:Q599644) has a "followed by" property and what entity it points to.

[Tool]
Got 1 row and 3 columns:
| subject         | property               | object             |
| --------------- | ---------------------- | ------------------ |
| Ox (wd:Q599644) | followed by (wdt:P156) | Tiger (wd:Q740762) |

[Tool]
Got 207 rows and 3 columns, showing the first 10 rows below:
| subject            | property                    | object                                                                            |
| ------------------ | --------------------------- | --------------------------------------------------------------------------------- |
| Tiger (wd:Q740762) | instance of (wdt:P31)       | animal from the Chinese zodiac (wd:Q79226802)                                     |
| Tiger (wd:Q740762) | Commons category (wdt:P373) | Tiger (zodiac)                                                                    |
| Tiger (wd:Q740762) | image (wdt:P18)             | <http://commons.wikimedia.org/wiki/Special:FilePath/OMBRE%20CHINOISE%20TIGRE.jpg> |
| Tiger (wd:Q740762) | part of (wdt:P361)          | Chinese zodiac (wd:Q1976204)                                                      |
| Tiger (wd:Q740762) | follows (wdt:P155)          | Ox (wd:Q599644)                                                                   |
| Tiger (wd:Q740762) | followed by (wdt:P156)      | Rabbit (wd:Q844723)                                                               |
| Tiger (wd:Q740762) | opposite of (wdt:P461)      | Monkey (wd:Q740674)                                                               |
| Tiger (wd:Q740762) | compatible with (wdt:P8956) | Dog (wd:Q755126)                                                                  |
| Tiger (wd:Q740762) | Freebase ID (wdt:P646)      | /m/01pg6f                                                                         |
| Tiger (wd:Q740762) | NL CR AUT ID (wdt:P691)     | ph118156                                                                          |
| ...                | ...                         | ...                                                                               |

[Tool]
Got 1 row and 1 column:
| animal             |
| ------------------ |
| Tiger (wd:Q740762) |

[Tool]
Got 1 row and 2 columns:
| animal             | animalLabel |
| ------------------ | ----------- |
| Tiger (wd:Q740762) | Tiger (en)  |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly uses the 'followed by' (wdt:P156) property on the Ox (zodiac) entity (wd:Q599644) to retrieve the next animal in the Chinese zodiac, which is the Tiger (wd:Q740762). The query also optionally retrieves the English label for the animal. The answer and the query are both correct and complete according to the user's question.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
SELECT ( COUNT( ?month ) AS ?count ) WHERE {
  ?statement ps:P2922 ?month ; pq:P3005 wd:Q39061 .
  wd:Q1311 p:P2922 ?statement .
}

Got 1 row and 1 column:
| count       |
| ----------- |
| 3 (xsd:int) |

Winter in Germany consists of 3 months.

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

You have access to the following knowledge graphs:
wikidata at http://amur:7001

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

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

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

[User] How many months does winter consist of in Germany?

[Assistant]
Let's break down the question:

1. The question asks about the number of months that winter consists of in Germany.
2. This involves identifying:
   - The entity for "winter" (the season).
   - The entity for "Germany".
   - The relationship between "winter" and its duration (number of months) as it applies to Germany.

First, I will search for the entity "winter" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. winter, also known as winter season, wintertime season, wintertime (wd:Q1311): one of the Earth's four temperate seasons, occurring between autumn and spring
2. Winter, also known as Village of Winter, Winter, WI (wd:Q2671552): village in Sawyer County, Wisconsin, United States
3. Winter, also known as Kim Min-jeong (wd:Q101161289): South Korean singer (born 2001), pop singer
4. Cornelis Bloemaert, also known as Cornelis, II Bloemaert, Cornelis II Bloemaert, corn. blomaert, Cornelis Bloemaert II, Cornelis Bloemaert (II) (wd:Q518767): Dutch painter and engraver (1603–1692), draftsperson, printmaker, painter
5. Katarina Waters, also known as Katarina Leigh Waters, Winter (wd:Q242899): German-born English professional wrestler and professional wrestling valet, professional wrestler, film director, manager, actor
6. Winter (wd:Q82356): dolphin at the Clearwater Marine Aquarium in Clearwater, Florida
7. Winter, also known as Winter Egg (wd:Q4191977): 1913 Imperial Fabergé egg
8. Winter (wd:Q1485942): family name
9. Fritz Winter, also known as fritz winter, winter (wd:Q578152): German painter (1905-1976), painter
10. Winter (wd:Q8026201): town in Sawyer County, Wisconsin

[Assistant]
The most relevant entity for "winter" as a season is wd:Q1311.

Next, I will search for the entity "Germany" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Germany, also known as BR Deutschland, Bundesrepublik Deutschland, Deutschland, Federal Republic of Germany (wd:Q183): country in Central Europe
2. Weimar Republic, also known as German Republic, Weimar Germany, Republic of Germany, Germany, German Reich (wd:Q41304): Germany in the years 1918/1919–1933
3. German Reich, also known as Deutsches Reich, German Empire, German Realm, Germany, Imperial Germany (wd:Q1206012): official name for the German nation state from 1871 to 1945, and name of Germany until 1949
4. Burg Drachenfels, also known as Germany (wd:Q1011486): castle
5. Germany (wd:Q5552078): European Parliament constituency
6. Geilenkirchen-Heinsberg, also known as Germany (wd:Q2268218)
7. Germany, also known as Germany, IN, Germany, Indiana (wd:Q18151573): unincorporated community in Clark County, Indiana
8. Germany (wd:Q19147844): poem by Vladimir Mayakovsky
9. Germany, also known as Ludwig, West (wd:Q3839160): Hetalia character
10. Germany, also known as Germany, Texas, Germany, TX (wd:Q15221573): unincorporated community in Houston County, Texas, United States

[Assistant]
The most relevant entity for "Germany" as a country is wd:Q183.

Now, I need to find out how to relate "winter" (wd:Q1311) and "Germany" (wd:Q183) to the number of months winter lasts in Germany. This likely involves properties related to duration, months, or seasonality in a specific country.

I will search for properties related to "duration" or "months" for the entity "winter".

[Tool]
Top 10 property alternatives:
1. event interval, also known as event frequency, frequency of event, interval, period (wd:P2257 as p/wdt): standard nominal interval between scheduled or regularly recurri...1/(event frequency). Time period of periodically occurring event
2. month of the year, also known as month of year, month (wd:P2922 as p/wdt): month of the year during which this item occurs, applies to or is valid in, part of
3. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as p/wdt): main Wikimedia category
4. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
5. Freebase ID, also known as Freebase, MID, Freebase identifier, FID (wd:P646 as p/wdt): identifier for a page in the Freebase database. Format: "/m/0" f...r IDs starting with "/g/", use Google Knowledge Graph ID (P2671)
6. followed by, also known as continued as, then, successor, succeeded by, sequel is (wd:P156 as p/wdt): immediately following item in a series of which the subject is a...een replaced, e.g. political offices, use "replaced by" (P1366)]
7. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as p/wdt): work where this item is described, attested in
8. follows, also known as prev, successor to, succeeds to, succeeds, split from (wd:P155 as p/wdt): immediately prior item in a series of which the subject is a par... preceding item, e.g. political offices, use "replaces" (P1365)]
9. depicted by, also known as acted by, shown in, seen in, portrayed by, played by (wd:P1299 as p/wdt): object depicting this subject (object being creative works such as books, films, paintings)
10. subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as p/wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain

No other items found

[Assistant]
The property "month of the year" (wd:P2922) is promising, as it relates to the months during which an item (like winter) occurs or is valid in, and it can be qualified by location.

Next, I will check how "month of the year" (wd:P2922) is used for "winter" (wd:Q1311), and whether it is qualified by country (Germany, wd:Q183).

[Tool]
Got 6 rows and 3 columns:
| subject           | property                      | object             |
| ----------------- | ----------------------------- | ------------------ |
| winter (wd:Q1311) | month of the year (wdt:P2922) | January (wd:Q108)  |
| winter (wd:Q1311) | month of the year (wdt:P2922) | June (wd:Q120)     |
| winter (wd:Q1311) | month of the year (wdt:P2922) | August (wd:Q122)   |
| winter (wd:Q1311) | month of the year (wdt:P2922) | February (wd:Q109) |
| winter (wd:Q1311) | month of the year (wdt:P2922) | December (wd:Q126) |
| winter (wd:Q1311) | month of the year (wdt:P2922) | July (wd:Q121)     |

[Assistant]
The property "month of the year" (wdt:P2922) for "winter" (wd:Q1311) is linked to several months: January, February, December, and also June, July, August. This is likely because winter occurs in different months in the northern and southern hemispheres.

To answer the question specifically for Germany, I need to check if there are qualifiers (such as "applies to part" or "country") that specify which months apply to Germany (northern hemisphere).

I will check if the "month of the year" statements for "winter" have qualifiers for country or location.

[Tool]
Got 6 rows and 3 columns:
| subject           | property                    | object                                       |
| ----------------- | --------------------------- | -------------------------------------------- |
| winter (wd:Q1311) | month of the year (p:P2922) | s:Q1311-123baf7f-421e-3059-1609-99f048f5ae87 |
| winter (wd:Q1311) | month of the year (p:P2922) | s:Q1311-3ca1d0d8-4c0d-e7ae-fca9-98ed0a851c73 |
| winter (wd:Q1311) | month of the year (p:P2922) | s:Q1311-4953942a-4cf1-11f2-877e-27630af39faf |
| winter (wd:Q1311) | month of the year (p:P2922) | s:Q1311-a15bcbcb-4ce6-38a9-3081-8164031b7b4e |
| winter (wd:Q1311) | month of the year (p:P2922) | s:Q1311-a35e8941-420e-1695-f174-603ff657b389 |
| winter (wd:Q1311) | month of the year (p:P2922) | s:Q1311-fd08819b-473b-9c34-4d41-effcb6272c06 |

[Tool]
Got 5 rows and 3 columns:
| subject                                      | property                     | object                          |
| -------------------------------------------- | ---------------------------- | ------------------------------- |
| s:Q1311-123baf7f-421e-3059-1609-99f048f5ae87 | month of the year (ps:P2922) | August (wd:Q122)                |
| s:Q1311-123baf7f-421e-3059-1609-99f048f5ae87 | valid in place (pq:P3005)    | Southern Hemisphere (wd:Q41228) |
| s:Q1311-123baf7f-421e-3059-1609-99f048f5ae87 | wikibase:rank                | wikibase:NormalRank             |
| s:Q1311-123baf7f-421e-3059-1609-99f048f5ae87 | rdf:type                     | wikibase:BestRank               |
| s:Q1311-123baf7f-421e-3059-1609-99f048f5ae87 | rdf:type                     | wikibase:Statement              |

[Tool]
Got 5 rows and 3 columns:
| subject                                      | property                     | object                          |
| -------------------------------------------- | ---------------------------- | ------------------------------- |
| s:Q1311-3ca1d0d8-4c0d-e7ae-fca9-98ed0a851c73 | month of the year (ps:P2922) | June (wd:Q120)                  |
| s:Q1311-3ca1d0d8-4c0d-e7ae-fca9-98ed0a851c73 | valid in place (pq:P3005)    | Southern Hemisphere (wd:Q41228) |
| s:Q1311-3ca1d0d8-4c0d-e7ae-fca9-98ed0a851c73 | wikibase:rank                | wikibase:NormalRank             |
| s:Q1311-3ca1d0d8-4c0d-e7ae-fca9-98ed0a851c73 | rdf:type                     | wikibase:BestRank               |
| s:Q1311-3ca1d0d8-4c0d-e7ae-fca9-98ed0a851c73 | rdf:type                     | wikibase:Statement              |

[Tool]
Got 5 rows and 3 columns:
| subject                                      | property                     | object                          |
| -------------------------------------------- | ---------------------------- | ------------------------------- |
| s:Q1311-4953942a-4cf1-11f2-877e-27630af39faf | month of the year (ps:P2922) | July (wd:Q121)                  |
| s:Q1311-4953942a-4cf1-11f2-877e-27630af39faf | valid in place (pq:P3005)    | Southern Hemisphere (wd:Q41228) |
| s:Q1311-4953942a-4cf1-11f2-877e-27630af39faf | wikibase:rank                | wikibase:NormalRank             |
| s:Q1311-4953942a-4cf1-11f2-877e-27630af39faf | rdf:type                     | wikibase:BestRank               |
| s:Q1311-4953942a-4cf1-11f2-877e-27630af39faf | rdf:type                     | wikibase:Statement              |

[Tool]
Got 5 rows and 3 columns:
| subject                                      | property                     | object                          |
| -------------------------------------------- | ---------------------------- | ------------------------------- |
| s:Q1311-a15bcbcb-4ce6-38a9-3081-8164031b7b4e | month of the year (ps:P2922) | January (wd:Q108)               |
| s:Q1311-a15bcbcb-4ce6-38a9-3081-8164031b7b4e | valid in place (pq:P3005)    | Northern Hemisphere (wd:Q39061) |
| s:Q1311-a15bcbcb-4ce6-38a9-3081-8164031b7b4e | wikibase:rank                | wikibase:NormalRank             |
| s:Q1311-a15bcbcb-4ce6-38a9-3081-8164031b7b4e | rdf:type                     | wikibase:BestRank               |
| s:Q1311-a15bcbcb-4ce6-38a9-3081-8164031b7b4e | rdf:type                     | wikibase:Statement              |

[Tool]
Got 5 rows and 3 columns:
| subject                                      | property                     | object                          |
| -------------------------------------------- | ---------------------------- | ------------------------------- |
| s:Q1311-a35e8941-420e-1695-f174-603ff657b389 | month of the year (ps:P2922) | February (wd:Q109)              |
| s:Q1311-a35e8941-420e-1695-f174-603ff657b389 | valid in place (pq:P3005)    | Northern Hemisphere (wd:Q39061) |
| s:Q1311-a35e8941-420e-1695-f174-603ff657b389 | wikibase:rank                | wikibase:NormalRank             |
| s:Q1311-a35e8941-420e-1695-f174-603ff657b389 | rdf:type                     | wikibase:BestRank               |
| s:Q1311-a35e8941-420e-1695-f174-603ff657b389 | rdf:type                     | wikibase:Statement              |

[Tool]
Got 5 rows and 3 columns:
| subject                                      | property                     | object                          |
| -------------------------------------------- | ---------------------------- | ------------------------------- |
| s:Q1311-fd08819b-473b-9c34-4d41-effcb6272c06 | month of the year (ps:P2922) | December (wd:Q126)              |
| s:Q1311-fd08819b-473b-9c34-4d41-effcb6272c06 | valid in place (pq:P3005)    | Northern Hemisphere (wd:Q39061) |
| s:Q1311-fd08819b-473b-9c34-4d41-effcb6272c06 | wikibase:rank                | wikibase:NormalRank             |
| s:Q1311-fd08819b-473b-9c34-4d41-effcb6272c06 | rdf:type                     | wikibase:BestRank               |
| s:Q1311-fd08819b-473b-9c34-4d41-effcb6272c06 | rdf:type                     | wikibase:Statement              |

[Assistant]
From the qualifiers, I see that:
- For the Northern Hemisphere (which includes Germany), winter consists of December, January, and February.

Now, I will write a SPARQL query to count the number of months for which "winter" (wd:Q1311) is valid in the Northern Hemisphere (wd:Q39061), which applies to Germany.

I will also include the IRIs of the months in the result, but the main answer will be the count.

[Tool]
Got 1 row and 2 columns:
| count       | months                                                              |
| ----------- | ------------------------------------------------------------------- |
| 3 (xsd:int) | http://www.wikidata.org/entity/Q...p://www.wikidata.org/entity/Q126 |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly counts the number of months that winter consists of in Germany by filtering for the months associated with 'winter' (wd:Q1311) and ensuring the statement is valid for the Northern Hemisphere (wd:Q39061), which includes Germany. The query returns the expected result, and all rules for SPARQL queries are followed. No further refinement is needed.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?river WHERE {
  wd:Q118841 wdt:P206 ?river
}

The river that flows through the Grand Canyon is the Colorado River (wd:Q1265).

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

You have access to the following knowledge graphs:
wikidata at http://amur:7001

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

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

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

[User] Which river flows through the Grand Canyon?

[Assistant]
Let's break down the question:

1. The main entity is "Grand Canyon".
2. The property of interest is "river that flows through" or "river passing through".
3. The answer should be the river entity that flows through the Grand Canyon.

First, I will search for the entity "Grand Canyon" in Wikidata to get its identifier.

[Tool]
Top 10 entity alternatives:
1. Grand Canyon, also known as Cañon of Colorado (wd:Q118841): steep-sided canyon carved by the Colorado River in Arizona, United States
2. Grand Canyon (wd:Q1542548): 1991 film directed by Lawrence Kasdan
3. Grand Canyon (wd:Q2062523): 1958 film by James Algar
4. Grand Canyon (wd:Q2901889): mall in Haifa, Israel
5. Snake River Canyon, also known as Grand Canyon (wd:Q7547072): canyon in Lincoln County, Wyoming, United States
6. Grand Canyon (wd:Q15701160): 1949 film by Paul Landres
7. Grand Canyon (wd:Q60752901): 2017 picture book by Jason Chin
8. Grand Canyon, also known as IMO 9614608 (wd:Q52514537): offshore supply ship built in 2012
9. Grand Canyon (wd:Q49805880): valley in Crook County, Wyoming, United States of America
10. Grand Canyon (wd:Q49805879)

[Assistant]
The most relevant entity for "Grand Canyon" as a geographic feature is wd:Q118841 ("steep-sided canyon carved by the Colorado River in Arizona, United States").

Next, I need to find the property that links a canyon or geographic feature to a river that flows through it. I will search for properties related to "river" for the Grand Canyon entity.

[Tool]
Top 10 property alternatives:
1. located in or next to body of water, also known as located on body of water, ocean, on bay, next to lake, on coast of (wd:P206 as p/wdt): body of water on or next to which a place is located, location
2. drainage basin, also known as watershed, water basin, river basin district, river basin, catchment area (wd:P4614 as p/wdt): area where precipitation collects and drains off into a common outlet, such as into a river, bay, or other body of water, located in/on physical feature
3. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
4. located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as p/wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
5. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as p/wdt): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
6. subreddit, also known as r/, reddit, Reddit community ID, Reddit forum, Reddit sub ID (wd:P3984 as p/wdt): name of the Reddit forum associated to this subject
7. vertical depth, also known as depth, oceandepth, lakedepth (wd:P4511 as p/wdt): vertical distance from a horizontal area to a point below. Compare with "horizontal depth" (P5524), length
8. length, also known as size, long, LOA, distance, dimension (wd:P2043 as p/wdt): measured dimension of an object
9. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as p/wdt): work where this item is described, attested in
10. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)

No other items found

[Assistant]
The most relevant property from the search is "located in or next to body of water" (wdt:P206). This property is often used to indicate which body of water (including rivers) a geographic feature is associated with.

I will now list the values of this property for the Grand Canyon (wd:Q118841) to see which river(s) are linked.

[Tool]
Got 1 row and 3 columns:
| subject                   | property                                       | object                    |
| ------------------------- | ---------------------------------------------- | ------------------------- |
| Grand Canyon (wd:Q118841) | located in or next to body of water (wdt:P206) | Colorado River (wd:Q1265) |

[Tool]
Got 1 row and 1 column:
| river                     |
| ------------------------- |
| Colorado River (wd:Q1265) |

[Tool]
Got 1 row and 2 columns:
| river                     | riverLabel          |
| ------------------------- | ------------------- |
| Colorado River (wd:Q1265) | Colorado River (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The answer is correct and complete. The SPARQL query directly asks for the body of water (river) that the Grand Canyon (wd:Q118841) is located on or next to, using the appropriate property (wdt:P206). The result, Colorado River (wd:Q1265), is accurate. The query returns the IRI as required. No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
ASK {
  wd:Q567 wdt:P26 ?spouse
}

Yes, the first female chancellor of Germany (Angela Merkel) was married.

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

You have access to the following knowledge graphs:
wikidata at http://amur:7001

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

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

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

[User] Was the first female chancellor in Germany ever married?

[Assistant]
Let's break down the question:

1. We need to identify the first female chancellor of Germany.
2. Then, we need to check if she was ever married.

Step 1: Identify the first female chancellor of Germany.
- Let's search for "first female chancellor Germany" in Wikidata to find the relevant entity.

Step 2: Once we have the entity, we need to check for a property related to marital status or spouse.

Let's start by searching for "first female chancellor Germany".

[Tool]
Top 10 entity alternatives:
1. Europe first, also known as Germany first (wd:Q557479): strategy focusing on Nazi Germany over Japan
2. Chancellor of Germany (wd:Q56022): offices held over time by the head of government of Germany
3. Federal Chancellor of Germany, also known as German Federal Chancellor, prime minister of Germany, German Chancellor, Federal Chancellor of the Federal Republic of Germany, Federal Chancellor (wd:Q4970706): head of government of the Federal Republic of Germany (1949–present)
4. First Over Germany (wd:Q28495986): 1988 video game
5. Chancellor candidate (Germany) (wd:Q1728256): German political term
6. female first cousin, also known as cousin sister (wd:Q12051531): female first degree cousin
7. Fitness First Germany, also known as Fitness First Berlin GmbH, Fitness First Germany GmbH (wd:Q124129522): Fitness companies based in Germany
8. First Sensor (Germany), also known as First Sensor AG (wd:Q30267525): company in Berlin, Germany
9. Vice-Chancellor of Germany, also known as Vice Chancellor of Germany, Deputy to the Federal Chancellor (wd:Q504272): position
10. first names in Germany (wd:Q15728719): Given first names in Germany

[Assistant] The search did not directly return an entity for the first female chancellor of Germany, but we know from general knowledge that Angela Merkel is widely recognized as the first female chancellor of Germany. To proceed systematically, I will search for "Angela Merkel" in Wikidata to confirm her entity and then check her marital status.

[Tool]
Top 10 entity alternatives:
1. Angela Merkel, also known as Angela Dorothea Merkel, leader of the free world, Angela Kasner (wd:Q567): chancellor of Germany from 2005 to 2021, politician, physicist
2. Angela Merkel (wd:Q94746073)
3. Angela Merkel (wd:Q41495976): Polish Biography of Angela Merkel
4. Angela Merkel (wd:Q41495489): German biography of Angela Merkel
5. Angela Merkel (wd:Q125701744)
6. family of Angela Merkel (wd:Q27973987): family of Angela Merkel, the Chancellor of Germany
7. Lentapedia / Angela Merkel (wd:Q17316816): encyclopedia article
8. Angela Merkel and Vladimir Putin (wd:Q127786484)
9. public image of Angela Merkel (wd:Q106041150)
10. Angela Merkel - The Unexpected (wd:Q28464539): 2016 documentary film by Torsten Körner and Matthias Schmidt

[Assistant] The entity for Angela Merkel, the chancellor of Germany from 2005 to 2021, is wd:Q567. Now, I will search for properties related to marital status or spouse for this entity to determine if she was ever married.

[Tool]
Top 10 property alternatives:
1. spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as p/wdt): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative
2. married name, also known as full name (married) (wd:P2562 as p/wdt): name or surname adopted by a person upon marriage, name
3. relative, also known as relatives, grandparent, relation, non-binary parent, niece (wd:P1038 as p/wdt): family member (qualify with "kinship to subject", P1039; for direct family member please use specific property), significant person
4. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as p/wdt): full name of a person at birth, if different from their current, generally used name, name
5. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as p/wdt): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)
6. child, also known as has son, kids, mother of, kid, issue (wd:P40 as p): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative
7. family, also known as royal house, noble family, member of family, house, dynasty (wd:P53 as p/wdt): family, including dynasty and nobility houses. Not family name (use P734 for family name)., member of
8. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as p/wdt): most specific known birth location of a person, animal or fictional character, location
9. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as p/wdt): date on which the subject was born, inception
10. ethnic group, also known as ethnic or cultural origin, tribal affiliation, race, people, ethnicity (wd:P172 as p/wdt): subject's ethnicity (consensus is that a VERY high standard of p...agreed on by scholars, or 3) is fictional and portrayed as such)

No other items found

[Tool]
Got 2 rows and 3 columns:
| subject                 | property         | object                       |
| ----------------------- | ---------------- | ---------------------------- |
| Angela Merkel (wd:Q567) | spouse (wdt:P26) | Joachim Sauer (wd:Q62085)    |
| Angela Merkel (wd:Q567) | spouse (wdt:P26) | Ulrich Merkel (wd:Q13415350) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is correct for the question. It uses an ASK query to check if Angela Merkel (the first female chancellor of Germany) has a value for the 'spouse' property (wdt:P26), which directly answers whether she was ever married. The answer and explanation are accurate and complete.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?schoolLevel WHERE {
  wd:Q11419997 wdt:P921 ?schoolLevel
}

The main subject of the manga 'Your Lie in April' is a middle school student.

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

You have access to the following knowledge graphs:
wikidata at http://amur:7001

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

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

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

[User] what is the main subject of the manga "your lie in april": primary school, middle school or high school student?

[Assistant]
Let's break down the question:

1. The user wants to know the main subject (i.e., the main character's school level) of the manga "Your Lie in April".
2. The possible answers are: primary school, middle school, or high school student.

Step 1: Identify the entity for "Your Lie in April" in Wikidata.
Step 2: Find the property that links a manga to its main subject or main character.
Step 3: For the main character(s), determine their school level (primary, middle, or high school student).

Let's start by searching for the entity "Your Lie in April" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Your Lie in April, also known as Kimiuso, Shigatsu wa Kimi no Uso (wd:Q11419997): Japanese manga series
2. Your Lie in April (wd:Q26810037): 2016 film by Takehiko Shinjō
3. Your Lie in April (wd:Q123944284): your Lie in April stage musical
4. Your Lie in April, also known as Kimiuso, Shigatsu wa Kimi no Uso (wd:Q91333870): Japanese anime television series
5. Your Lie in April: A Six Person Etude, also known as Shigatsu wa Kimi no Uso: 6-nin no Études (wd:Q91334211): Japanese light novel
6. Lies in Your Eyes (wd:Q6544290): extended play by Dive
7. Your Lies in Check (wd:Q4023078): album by Cripple Bastards
8. Lier in Your Eyes (wd:Q29424453): X-Ray song
9. The Lies in Your Eyes (wd:Q5409466): single
10. [It lies in your hand!] (wd:Q87357297): scientific article published on 01 February 2014

[Assistant]
The most relevant entity for the manga "Your Lie in April" is wd:Q11419997 (Japanese manga series).

Next, I need to find the property that links a manga to its main subject or main character. The main character's school level will help answer the question.

I'll search for properties related to "main character" or "subject" for manga in Wikidata.

[Tool]
Top 10 property alternatives:
1. main subject, also known as primary topic, primary subject, primary keyword, plot keyword, of (wd:P921 as p/wdt): primary topic of a work (see also P180: depicts), depicts
2. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
3. author, also known as writer, written by, poet, playwright, maker (wd:P50 as p/wdt): main creator(s) of a written work (use on works, not humans); us...hor name string) when Wikidata item is unknown or does not exist, creator
4. title, also known as name, titled, page name, original title, known as (wd:P1476 as p/wdt): published name of a work, such as a newspaper article, a literary work, piece of music, a website, or a performance work, name
5. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as p/wdt): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
6. language of work or name, also known as language of the reference, language of URL, language of website, language of work, named in language (wd:P407 as p/wdt): language associated with this creative work (such as books, show...guage" (P103) and "languages spoken, written or signed" (P1412))
7. MyAnimeList manga ID, also known as Manga ID MAL, MAL manga ID (wd:P4087 as p/wdt): identifier for a manga or novel on MyAnimeList
8. start time, also known as start date, since, valid, join time, joined (wd:P580 as p/wdt): time an entity begins to exist or a statement starts being valid, point in time
9. country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as p/wdt): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country
10. end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as p/wdt): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time

No other items found

[Assistant]
The property "main subject" (wd:P921) is relevant here, as it links a work to its primary topic. However, to determine the school level of the main character, it may be more direct to look for the "main character" property, but it did not appear in the top results.

I'll check if the "main subject" property for "Your Lie in April" points to a school level or a character, and then proceed accordingly.

[Tool]
Got 1 row and 3 columns:
| subject                          | property                | object                               |
| -------------------------------- | ----------------------- | ------------------------------------ |
| Your Lie in April (wd:Q11419997) | main subject (wdt:P921) | middle school student (wd:Q16003532) |

[Tool]
Got 1 row and 1 column:
| schoolLevel                          |
| ------------------------------------ |
| middle school student (wd:Q16003532) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The answer is correct and the SPARQL query is well-formed. It directly queries the main subject (wdt:P921) of the manga 'Your Lie in April' (wd:Q11419997) and retrieves the relevant Wikidata entity, which is 'middle school student'. The result matches the user's question and follows all the required rules for SPARQL queries. No further refinement is needed.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?country WHERE {
  {
    ?store wdt:P31 wd:Q50399787 ; wdt:P17 ?country .
  } UNION {
    ?entity wdt:P127 wd:Q54078 ; wdt:P17 ?country .
  }
}

Got 8 rows and 1 column:
| country                              |
| ------------------------------------ |
| United Kingdom (wd:Q145)             |
| People's Republic of China (wd:Q148) |
| Japan (wd:Q17)                       |
| Germany (wd:Q183)                    |
| Czech Republic (wd:Q213)             |
| Sweden (wd:Q34)                      |
| Poland (wd:Q36)                      |
| Turkey (wd:Q43)                      |

According to Wikidata, IKEA has been established in the following 8 countries (based on available data for IKEA stores and entities owned by IKEA): United Kingdom, People's Republic of China, Japan, Germany, Czech Republic, Sweden, Poland, and Turkey.

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

You have access to the following knowledge graphs:
wikidata at http://amur:7001

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

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

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

[User] In how many countries has IKEA been established?

[Assistant]
Let's break down the question:

1. We need to identify the entity for IKEA.
2. We need to find the property that links IKEA to the countries where it has been established (likely something like "country of operation" or "located in").
3. We need to count the number of unique countries associated with IKEA.

First, I'll search for the entity "IKEA" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. IKEA, also known as Ikea, Ingvar Kamprad Elmtaryd Agunnaryd (wd:Q54078): international furniture store chain
2. Ikea (wd:Q18587732): genus of insects
3. Ikea effect (wd:Q1653973): cognitive bias in which consumers place a disproportionately high value on products they partially created
4. Swedish meatballs, also known as IKEA meatballs, Köttbullar (wd:Q1501015): Swedish dish made from ground meat
5. Blåhaj, also known as BLÅHAJ, funny meme shark, IKEA shark, Klappar Haj, Smolhaj (wd:Q107133815): stuffed toy shark sold at IKEA
6. IKEA Catalogue (wd:Q2941621): catalogue published annually by the Swedish home furnishing retailer IKEA
7. IKEA pencil (wd:Q18350690): small pencils provided for free in IKEA stores worldwide
8. IKEA Museum (wd:Q25063953): museum in Älmhult, Sweden
9. IKEA Heights (wd:Q15995166): Comedy web series
10. IKEA Sendai (wd:Q17988690)

[Assistant]
The correct entity for IKEA, the international furniture store chain, is wd:Q54078.

Next, I need to find the property that links IKEA to the countries where it operates or has been established. I'll search for properties related to "country" for the IKEA entity.

[Tool]
Top 10 property alternatives:
1. location of formation, also known as place of incorporation, originates from, place of establishment, place of formation, place of foundation (wd:P740 as p/wdt): location where a group or organization was formed, location of creation
2. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
3. typically sells, also known as product, sells, sold products, usually sells (wd:P7163 as p/wdt): type of goods particular type of shops typically sell
4. product, material, or service produced or provided, also known as products, product or service provided, product, material, or service produced or provided, product, output (wd:P1056 as p/wdt): material or product produced or sold by an organization, industry, facility, or process, material or product produced by an organization, industry, facility, or process, immediate cause of
5. used by, also known as armiger, user, played by, of (wd:P1535 as p/wdt): item or concept that makes use of the subject (use sub-properties when appropriate)
6. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as p/wdt): main Wikimedia category
7. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
8. industry, also known as branch, economic branch, field of action, field of exercise, sector (wd:P452 as p/wdt): specific industry of company or organization, part of
9. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as p/wdt): time when an entity begins to exist; for date of official opening use P1619, start time
10. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as p/wdt): label for the items in their official language  or their original language, name

No other items found

[Assistant]
None of the top returned properties directly indicate "countries of operation" or "countries where established." The closest is "location of formation" (wd:P740), but that refers to where the company was founded, not where it operates.

To find the correct property, I'll search for properties related to "country of operation" or "operates in country."

[Tool]
Top 10 property alternatives:
1. operating area, also known as province served, serves jurisdiction, serves geographic region, serves geographic area, serves area (wd:P2541 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): geographic area or jurisdiction an organisation or industry operates in, serves, or has responsibility for, location
2. applies to jurisdiction, also known as belongs to jurisdiction, applies to territorial jurisdiction, applies to region, applies to place, applies to geographic place (wd:P1001 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): the item (institution, law, public office, public register...) o...a territorial jurisdiction: a country, state, municipality, ...), significant place, characteristic of, operating area
3. headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place
4. location of creation, also known as manufactured in, manufacturing location, mint, minted at, photographed at (wd:P1071 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): place where the item was conceived or made; where applicable, location of final assembly, significant place
5. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
6. work location, also known as work place, working from, working at, worked from, worked at (wd:P937 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): location where persons or organisations were actively participating in employment, business or other work, significant place, location
7. 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 pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
8. country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country
9. valid in place, also known as applies to country, applies to location, applies to place, country, true in (wd:P3005 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): place where a statement is valid, applies to part
10. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): the object is a country that recognizes the subject as its citizen, country

[Assistant]
The property "operating area" (wd:P2541) is described as the geographic area or jurisdiction an organisation operates in. This seems to be the most relevant property for finding the countries where IKEA has been established.

Next, I'll check if IKEA (wd:Q54078) has values for the "operating area" (wd:P2541) property.

[Tool] Got no rows and 3 columns

[Assistant]
It appears that there are no direct triples linking IKEA (wd:Q54078) to countries using the "operating area" (wdt:P2541) property in the direct property namespace.

Since this direct property is not populated, I'll try a broader approach by checking if there are any other properties linking IKEA to countries, such as "located in the administrative territorial entity" (wdt:P131), "location" (wdt:P276), or similar. I'll list all direct properties for IKEA to see what geographic or country-related information is available.

[Tool]
Got 720 rows and 3 columns, showing the first 10 rows below:
| subject          | property                                       | object                                                                  |
| ---------------- | ---------------------------------------------- | ----------------------------------------------------------------------- |
| IKEA (wd:Q54078) | instance of (wdt:P31)                          | brand (wd:Q431289)                                                      |
| IKEA (wd:Q54078) | Commons category (wdt:P373)                    | IKEA                                                                    |
| IKEA (wd:Q54078) | image (wdt:P18)                                | <http://commons.wikimedia.org/wiki/Special:FilePath/Ikea%20almhult.jpg> |
| IKEA (wd:Q54078) | inception (wdt:P571)                           | 1943-01-01T00:00:00Z (xsd:dateTime)                                     |
| IKEA (wd:Q54078) | official website (wdt:P856)                    | <https://www.ikea.com>                                                  |
| IKEA (wd:Q54078) | on focus list of Wikimedia project (wdt:P5008) | NADD Wikidata project (wd:Q123694075)                                   |
| IKEA (wd:Q54078) | native label (wdt:P1705)                       | IKEA (sv)                                                               |
| IKEA (wd:Q54078) | different from (wdt:P1889)                     | INGKA Group (wd:Q47508300)                                              |
| IKEA (wd:Q54078) | topic's main category (wdt:P910)               | wd:Q8530102                                                             |
| IKEA (wd:Q54078) | social media followers (wdt:P8687)             | 116219 (xsd:decimal)                                                    |
| ...              | ...                                            | ...                                                                     |

[Assistant]
The direct properties for IKEA do not include any obvious links to countries of operation or establishment. Since IKEA is a chain with many stores, perhaps the information about countries is stored at the level of individual IKEA stores or subsidiaries.

A possible approach is to:
1. Find all entities that are instances of "IKEA store" or similar and are linked to IKEA.
2. For each store, find the country it is located in.
3. Count the number of unique countries.

First, I'll search for the entity "IKEA store" to see if such a class exists.

[Tool]
Top 10 entity alternatives:
1. IKEA store (wd:Q50399787): store operated by the IKEA company
2. IKEA Hangzhou Store (wd:Q22101403)
3. IKEA Kartal, also known as IKEA Kartal Store (wd:Q130014870): IKEA store in Istanbul, Turkey
4. IKEA İzmir, also known as IKEA İzmir Store (wd:Q130009564): IKEA store in İzmir, Turkey
5. IKEA Bursa, also known as IKEA Bursa Store (wd:Q130014865): IKEA store in Bursa, Turkey
6. IKEA Bayrampaşa, also known as IKEA Bayrampaşa Store (wd:Q130014861): IKEA store in Istanbul, Turkey
7. IKEA Ümraniye, also known as IKEA Ümraniye Store (wd:Q130013093): IKEA store in Istanbul, Turkey
8. IKEA Antalya, also known as IKEA Antalya Store (wd:Q130014874): IKEA store in Antalya, Turkey
9. IKEA Ankara, also known as IKEA Ankara Store (wd:Q130014867): IKEA store in Ankara, Turkey
10. IKEA, also known as Ikea, Ingvar Kamprad Elmtaryd Agunnaryd (wd:Q54078): international furniture store chain

[Assistant]
There is an entity "IKEA store" (wd:Q50399787), which represents stores operated by the IKEA company.

The next step is to find all entities that are instances of "IKEA store" (wd:Q50399787), and for each, retrieve the country they are located in. Then, count the number of unique countries.

First, I'll check which property is used to indicate the country for an "IKEA store". I'll search for properties related to "country" for the entity "IKEA store".

[Tool]
Top 10 property alternatives:
1. operator, also known as offered by, operated by, provided by, run by, service operator (wd:P137 as p/wdt): person, profession, organization or entity that operates the equipment, facility, or service, used by
2. subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as p/wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
3. Commons category, also known as category on Wikimedia Commons, Wikimedia Commons category, Wikimedia Commons cat, Commons cat, commonscat (wd:P373 as p/wdt): name of the Wikimedia Commons category containing files related to this item (without the prefix "Category:")

No other items found

[Assistant]
The search did not return a direct "country" property for "IKEA store". However, it's common in Wikidata for locations to use the property "country" (wdt:P17) to indicate the country an entity is located in.

I'll check if any instances of "IKEA store" (wd:Q50399787) have the property "country" (wdt:P17) set. I'll write a query to find all instances of "IKEA store" and their countries.

[Tool]
Got 26 rows and 2 columns, showing the first 5 and last 5 rows below:
| store                                   | country                              |
| --------------------------------------- | ------------------------------------ |
| IKEA Sindelfingen (wd:Q104698108)       | Germany (wd:Q183)                    |
| IKEA Hannover (wd:Q111691377)           | Germany (wd:Q183)                    |
| IKEA Southampton (wd:Q126165259)        | United Kingdom (wd:Q145)             |
| IKEA Reading (wd:Q126165371)            | United Kingdom (wd:Q145)             |
| IKEA İzmir (wd:Q130009564)              | Turkey (wd:Q43)                      |
| ...                                     | ...                                  |
| IKEA Tachikawa (wd:Q50400102)           | Japan (wd:Q17)                       |
| IKEA Touchpoint Kumamoto (wd:Q50400149) | Japan (wd:Q17)                       |
| IKEA Nagakute (wd:Q50400203)            | Japan (wd:Q17)                       |
| IKEA Town Rokko (wd:Q50400240)          | Japan (wd:Q17)                       |
| IKEA Shenzhen (wd:Q98222106)            | People's Republic of China (wd:Q148) |

[Assistant]
The query successfully retrieved IKEA stores and their countries, but only a limited number (26 rows). This suggests that not all IKEA stores are represented in Wikidata, or not all have the "country" property set.

To answer the question as accurately as possible with the available data, I will count the number of unique countries among all instances of "IKEA store" (wd:Q50399787) that have a "country" (wdt:P17) property. I'll write a query to count the distinct countries.

[Tool]
Got 1 row and 1 column:
| countryCount |
| ------------ |
| 6 (xsd:int)  |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The query counts the number of distinct countries where IKEA stores (instances of wd:Q50399787) exist. However, this approach only counts countries where individual IKEA stores are listed in Wikidata with a country property, which may undercount the actual number of countries where IKEA as a company is established. A more robust approach would be to check the countries where IKEA (the company, wd:Q45981) operates or is present, possibly using properties like 'country of origin' (P495), 'located in the administrative territorial entity' (P131), or 'has part' (P527) if available. Please consider refining the query to ensure it reflects all countries where IKEA is established as a company, not just where stores are individually listed.

[Assistant]
Thank you for the feedback. You are correct: counting only the countries where individual IKEA stores are listed in Wikidata may undercount the actual number of countries where IKEA is established as a company. A more robust approach is to look for properties on the IKEA company entity (wd:Q54078) that indicate its presence or operation in various countries.

Step-by-step, I will:
1. Check for properties on IKEA (wd:Q54078) that might link it to countries, such as "country of origin" (P495), "located in the administrative territorial entity" (P131), "has part" (P527), or similar.
2. If such properties are found, I will count the number of unique countries associated with IKEA as a company.

First, I'll search for properties related to "location", "presence", or "operation" for IKEA (wd:Q54078).

[Tool]
Top 10 property alternatives:
1. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as p/wdt): URL of the official page of an item (current or former). Usage: ...but see the "Hijacked or dead websites" section of the Talk page, URL
2. location of formation, also known as place of incorporation, originates from, place of establishment, place of formation, place of foundation (wd:P740 as p/wdt): location where a group or organization was formed, location of creation
3. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
4. product, material, or service produced or provided, also known as products, product or service provided, product, material, or service produced or provided, product, output (wd:P1056 as p/wdt): material or product produced or sold by an organization, industry, facility, or process, material or product produced by an organization, industry, facility, or process, immediate cause of
5. typically sells, also known as product, sells, sold products, usually sells (wd:P7163 as p/wdt): type of goods particular type of shops typically sell
6. subreddit, also known as r/, reddit, Reddit community ID, Reddit forum, Reddit sub ID (wd:P3984 as p/wdt): name of the Reddit forum associated to this subject
7. sitemap URL, also known as sitemap xml, site map URL, sitemap (wd:P11212 as p/wdt): URL to the sitemap of the subject's official website, URL
8. logo image, also known as masthead, wordmark, trademark, trade mark, sign (wd:P154 as p/wdt): graphic mark or emblem commonly used by commercial enterprises, organizations and products, icon
9. Commons gallery, also known as gallery (wd:P935 as p/wdt): name of the Wikimedia Commons gallery page(s) related to this item (is suitable to allow multiple links to more gallery pages)
10. YouTube channel ID, also known as YouTube account, YouTube channel, YouTube channel identifier, official YouTube channel, youtube.com/channel/ (wd:P2397 as p/wdt): ID of the YouTube channel of a person or organisation (not to be...f the channel) The ID can also be used for music.youtube.com IDs, website username or ID

No other items found

[Assistant]
The search for "location" properties on IKEA (wd:Q54078) did not yield any direct links to countries of operation or presence.

Next, I'll try searching for the property "has part" (P527), which could indicate subsidiaries or regional branches, and see if these are linked to countries.

[Tool] Got no rows and 3 columns

[Assistant]
There are no "has part" (P527) links from IKEA (wd:Q54078) to other entities, so this property does not help.

Next, I'll check for "country of origin" (P495) and "located in the administrative territorial entity" (P131) to see if either is used to indicate countries where IKEA is established.

[Tool] Got no rows and 3 columns

[Tool] Got no rows and 3 columns

[Assistant]
Neither "country of origin" (P495) nor "located in the administrative territorial entity" (P131) are used on the main IKEA entity (wd:Q54078) to indicate countries of operation or establishment.

Given that the main entity does not directly list countries, and the store-level approach is incomplete, I'll try a broader approach:
- Search for all organizations or companies that are subsidiaries or branches of IKEA, and see if these are linked to countries.
- Alternatively, see if there is a property like "country served" or "applies to jurisdiction" (P1001) that might be used.

I'll search for properties related to "jurisdiction" or "country served" for IKEA.

[Tool]
Top 10 property alternatives:
1. location of formation, also known as place of incorporation, originates from, place of establishment, place of formation, place of foundation (wd:P740 as p/wdt): location where a group or organization was formed, location of creation
2. Library of Congress authority ID, also known as LCSH Authority File ID, LC Name Authority ID, LCSH ID, LCSH LCCN, LC Subject Heading ID (wd:P244 as wdt/p/wdtn): Library of Congress name authority (persons, families, corporate...lowed by 8-10 digits (see regex). For manifestations, use P1144]
3. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as p/wdt): label for the items in their official language  or their original language, name
4. founded by, also known as starter, co-founded by, started by, institutor, instituted by (wd:P112 as p/wdt): founder or co-founder of this organization, religion, place or entity, creator
5. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as p/wdt): main Wikimedia category
6. logo image, also known as masthead, wordmark, trademark, trade mark, sign (wd:P154 as p/wdt): graphic mark or emblem commonly used by commercial enterprises, organizations and products, icon
7. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
8. used by, also known as armiger, user, played by, of (wd:P1535 as p/wdt): item or concept that makes use of the subject (use sub-properties when appropriate)
9. industry, also known as branch, economic branch, field of action, field of exercise, sector (wd:P452 as p/wdt): specific industry of company or organization, part of
10. product, material, or service produced or provided, also known as products, product or service provided, product, material, or service produced or provided, product, output (wd:P1056 as p/wdt): material or product produced or sold by an organization, industry, facility, or process, material or product produced by an organization, industry, facility, or process, immediate cause of

No other items found

[Assistant]
There are no properties like "applies to jurisdiction" or "country served" directly used on the IKEA entity.

Given all the above, the most robust approach available in Wikidata is still to aggregate the countries from the store-level data, as there is no company-level property listing all countries of operation. However, to maximize coverage, I can also check if there are any subsidiaries or branches of IKEA (using "subsidiary" P355 or "owned by" P127) that are linked to countries.

I'll search for subsidiaries of IKEA (wd:Q54078) and see if any of them are linked to countries.

[Tool] Got no rows and 3 columns

[Tool]
Got 3 rows and 3 columns:
| subject                            | property            | object           |
| ---------------------------------- | ------------------- | ---------------- |
| Avion Shopping Park (wd:Q10859379) | owned by (wdt:P127) | IKEA (wd:Q54078) |
| wd:Q117222112                      | owned by (wdt:P127) | IKEA (wd:Q54078) |
| wd:Q124088712                      | owned by (wdt:P127) | IKEA (wd:Q54078) |

[Tool]
Got 28 rows and 3 columns, showing the first 10 rows below:
| subject                            | property                               | object                                                                           |
| ---------------------------------- | -------------------------------------- | -------------------------------------------------------------------------------- |
| Avion Shopping Park (wd:Q10859379) | instance of (wdt:P31)                  | brand (wd:Q431289)                                                               |
| Avion Shopping Park (wd:Q10859379) | country (wdt:P17)                      | Czech Republic (wd:Q213)                                                         |
| Avion Shopping Park (wd:Q10859379) | Commons category (wdt:P373)            | Avion Shopping Parks                                                             |
| Avion Shopping Park (wd:Q10859379) | image (wdt:P18)                        | <http://commons.wikimedia.org/wiki/Special:FilePath/Avion%20shopping%20park.jpg> |
| Avion Shopping Park (wd:Q10859379) | owned by (wdt:P127)                    | IKEA (wd:Q54078)                                                                 |
| Avion Shopping Park (wd:Q10859379) | Google Knowledge Graph ID (wdtn:P2671) | <http://g.co/kg/g/122q9fl8>                                                      |
| Avion Shopping Park (wd:Q10859379) | Quora topic ID (wdt:P3417)             | Avion-Shopping-Park                                                              |
| Avion Shopping Park (wd:Q10859379) | wdt:P31279                             | brand (wd:Q431289)                                                               |
| Avion Shopping Park (wd:Q10859379) | schema:description                     | Czech company of IKEA shopping centers in the Czech Republic (en)                |
| Avion Shopping Park (wd:Q10859379) | schema:name                            | Avion Shopping Park (cs)                                                         |
| ...                                | ...                                    | ...                                                                              |

[Tool]
Got 38 rows and 3 columns, showing the first 10 rows below:
| subject       | property                                                    | object                                                                              |
| ------------- | ----------------------------------------------------------- | ----------------------------------------------------------------------------------- |
| wd:Q117222112 | instance of (wdt:P31)                                       | shop (wd:Q213441)                                                                   |
| wd:Q117222112 | country (wdt:P17)                                           | Poland (wd:Q36)                                                                     |
| wd:Q117222112 | located in the administrative territorial entity (wdt:P131) | Wola (wd:Q1020136)                                                                  |
| wd:Q117222112 | coordinate location (wdt:P625)                              | POINT(20.996680 52.227010) (geo:wktLiteral)                                         |
| wd:Q117222112 | Commons category (wdt:P373)                                 | Swede Center                                                                        |
| wd:Q117222112 | image (wdt:P18)                                             | <http://commons.wikimedia.org/wiki/Special:FilePath/Swede%20center%20i%20varso.jpg> |
| wd:Q117222112 | inception (wdt:P571)                                        | 1994-01-01T00:00:00Z (xsd:dateTime)                                                 |
| wd:Q117222112 | street address (wdt:P6375)                                  | Al. Jerozolimskie 56c, 00-802 Warszawa (pl)                                         |
| wd:Q117222112 | significant event (wdt:P793)                                | reconstruction (wd:Q2478058)                                                        |
| wd:Q117222112 | owned by (wdt:P127)                                         | IKEA (wd:Q54078)                                                                    |
| ...           | ...                                                         | ...                                                                                |

[Tool]
Got 28 rows and 3 columns, showing the first 10 rows below:
| subject       | property                                                    | object                                                                                |
| ------------- | ----------------------------------------------------------- | -------------------------------------------------------------------------------------------------- |
| wd:Q124088712 | instance of (wdt:P31)                                       | shop (wd:Q213441)                                                                                |
| wd:Q124088712 | country (wdt:P17)                                           | Poland (wd:Q36)                                                                                |
| wd:Q124088712 | located in the administrative territorial entity (wdt:P131) | Targówek (wd:Q1247360)                                                                             |
| wd:Q124088712 | coordinate location (wdt:P625)                              | POINT(21.083150 52.305740) (geo:wktLiteral)                                                        |
| wd:Q124088712 | Commons category (wdt:P373)                                 | IKEA Targówek                                                                                |
| wd:Q124088712 | image (wdt:P18)                                             | <http://commons.wikimedia.org/wiki/Special:FilePath/Trasa%20Toru%C5%84ska%20Targ%C3%B3wek%202.JPG> |
| wd:Q124088712 | street address (wdt:P6375)                                  | ul. Malborska 51, 03-286 Warszawa (pl)                                                             |
| wd:Q124088712 | owned by (wdt:P127)                                         | IKEA (wd:Q54078)                                                                                |
| wd:Q124088712 | named after (wdt:P138)                                      | Targówek (wd:Q1247360)                                                                             |
| wd:Q124088712 | located on street (wdt:P669)                                | Toruńska Thoroughfare (wd:Q9361324)                                                                |
| ...           | ...                                                         | ...                                                                                |

[Assistant]
From the subsidiaries and owned entities, I found:
- Avion Shopping Park (Czech Republic)
- Two shops in Poland

This adds two more countries (Czech Republic and Poland) to the list of countries where IKEA is established, in addition to those found via the store-level approach.

To ensure completeness, I will now combine all unique countries found via:
1. Instances of "IKEA store" (wd:Q50399787) with a country property (wdt:P17)
2. Entities owned by IKEA (wd:Q54078) with a country property (wdt:P17)

I'll write a SPARQL query that unifies these two approaches and counts the number of unique countries.

[Tool]
Got 1 row and 1 column:
| countryCount |
| ------------ |
| 8 (xsd:int)  |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The query attempts to count the number of countries where IKEA has been established by looking at two things: (1) countries with an IKEA store (instance of IKEA store) and (2) countries with an entity owned by IKEA. This is a reasonable approach, but there are some issues:

1. The query may double-count countries if both a store and an entity owned by IKEA exist in the same country, since the UNION does not deduplicate countries across the two patterns before counting.
2. The query does not return the actual country IRIs, only the count. According to the guidelines, the query should return the IRIs (and optionally the count).

Suggested improvements:
- Instead of counting directly, first select DISTINCT ?country from both patterns (using UNION), then count the distinct countries. Also, return the IRIs of the countries in the result (even if only for inspection).

Example refinement:
SELECT DISTINCT ?country WHERE { ... } UNION ...
Then, count the number of distinct ?country IRIs.

Therefore, the output is sensible but needs refinement to ensure correctness and compliance with the guidelines.

[Assistant]
Thank you for the detailed feedback. To address your points:

1. I will ensure that countries are not double-counted by first selecting all distinct country IRIs from both patterns using UNION, then counting the unique IRIs.
2. I will return the actual country IRIs (and optionally their labels) in the result, as per the guidelines.

Here’s my plan:
- Write a query that selects all distinct ?country IRIs from both patterns (IKEA stores and entities owned by IKEA).
- Return the list of country IRIs (and optionally labels).
- Also return the total count of distinct countries.

Let’s construct and execute this refined query.

[Tool]
Got 8 rows and 2 columns:
| country                              | storeOrEntityCount |
| ------------------------------------ | ------------------ |
| United Kingdom (wd:Q145)             | 2 (xsd:int)        |
| People's Republic of China (wd:Q148) | 2 (xsd:int)        |
| Japan (wd:Q17)                       | 11 (xsd:int)       |
| Germany (wd:Q183)                    | 3 (xsd:int)        |
| Czech Republic (wd:Q213)             | 1 (xsd:int)        |
| Sweden (wd:Q34)                      | 1 (xsd:int)        |
| Poland (wd:Q36)                      | 2 (xsd:int)        |
| Turkey (wd:Q43)                      | 7 (xsd:int)        |

[Tool] Stopped generation process