PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?dog ?dogLabel ( ( YEAR( ?death ) - YEAR( ?birth ) ) AS ?lifespan ) WHERE {
  ?dog wdt:P31 wd:Q144 .
  ?dog wdt:P569 ?birth .
  ?dog wdt:P570 ?death .
  OPTIONAL {
    ?dog rdfs:label ?dogLabel FILTER ( LANG( ?dogLabel ) = "en" )
  }
}
ORDER BY DESC ( ?lifespan )
LIMIT 1
OFFSET 1

The second oldest dog in the world is Bobi, who lived for 31 years.

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

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

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

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

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

[User] How many years did the second oldest dog in the world live?

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

[Tool]
Example 1:
Question:
What is the second highest mountain on Earth?

SPARQL:
SELECT ?res WHERE {
  ?res wdt:P31 / wdt:P279 * wd:Q8502 .
  ?res wdt:P2044 ?elevation .
  ?res wdt:P30 / wdt:P361 wd:Q2 .
}
ORDER BY DESC ( ?elevation )
LIMIT 1
OFFSET 1

Using entities:
Earth, also known as World, The Blue Planet, Planet Earth, Mother Earth (wd:Q2): third planet from the Sun in the Solar System
mountain, also known as mt., mtn., mountains, mount (wd:Q8502): large natural elevation of the Earth's surface

Using properties:
elevation above sea level, also known as MAMSL, MASL, height, elevation above mean sea level, elevation (wd:P2044 as wdt): height of the item (geographical object) as measured relative to sea level
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
continent (wd:P30 as wdt): continent of which the subject is a part, located in/on physical feature
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
part of, also known as of, within, system of, subsystem of, subgroup of (wd:P361 as wdt): object of which the subject is a part (if this subject is alread... of "has part" (P527, see also "has parts of the class" (P2670))

[Assistant]
The example found is about the second highest mountain on Earth, using ORDER BY DESC and OFFSET 1 to get the second highest. We can use a similar approach for the second oldest dog by ordering dogs by their lifespan and using OFFSET 1 to get the second oldest.

Next, I will search for the entity "dog" to find the relevant entity in Wikidata.

[Tool]
Top 10 entity alternatives:
1. dog, also known as Canis lupus familiaris, Canis familiaris, domestic dogs, domestic dog (wd:Q144): domestic animal
2. Dog (wd:Q755126): sign of Chinese zodiac
3. Dog (wd:Q104843787): 2022 film directed by Reid Carolin and Channing Tatum
4. Dongola Airport, also known as DOG, HSDN (wd:Q1431231): airport
5. Hurricane Dog, also known as Dog (wd:Q217669): Category 5 Atlantic hurricane in 1950
6. Wax, also known as Dog, WAX (wd:Q624269): South Korean singer, singer
7. Dog, also known as D0g (wd:Q1211818): fictional character in Half-Life
8. hound, also known as dog (wd:Q1637371): heraldic animal
9. dog, also known as shutter, shutter dog (wd:Q5288153): tool in engineering
10. Canis familiaris, also known as dog, domestic dog (wd:Q20717272): species of mammal

[Assistant] The most relevant entity for "dog" is wd:Q144 which represents the domestic dog (Canis lupus familiaris). Next, I will search for properties related to lifespan or age for this entity.

[Tool]
Top 10 property alternatives:
1. life expectancy, also known as life span, lifespan (wd:P2250 as p/wdt): average life expectancy for this group or species, duration
2. longest observed lifespan, also known as maximum age, oldest recorded individual, oldest observed, maximum life span, highest observed lifespan (wd:P4214 as p/wdt): age of the oldest specimen of a taxon for which the age can be verified
3. has characteristic, also known as has quality, inherent property, object has characteristic, parameter, quality (wd:P1552 as p/wdt): inherent or distinguishing quality or feature of the entity. Use a more specific property when possible
4. has use, also known as utility, used in, used for, used as, use (wd:P366 as p/wdt): main use of the subject (includes current and former usage)
5. sequenced genome URL, also known as genome, genome URL (wd:P6800 as p/wdt): sequenced and assembled genome for this taxon, URL
6. 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)
7. main food source, also known as diet, eats, ecology (Fossilworks field  name), food plant, food source (wd:P1034 as p/wdt): species, genus or family that an organism depends on for nutrition
8. uses, also known as uses trope, used, using, wielded, wields (wd:P2283 as p/wdt): item or concept used by the subject or in the operation (see also instrument [P1303] and armament [P520])
9. Guardian topic ID, also known as Guardian, The Guardian topic, The Guardian topic ID (wd:P3106 as p/wdt): identifier for a topic at the Guardian newspaper website
10. heart rate, also known as heart pulse (wd:P3395 as p/wdt): speed of the heartbeat measured by the number of contractions of the heart per minute (bpm)

No other items found

[Assistant] The property "longest observed lifespan" (wdt:P4214) seems to be the most relevant to find the age of the oldest dog. Now I will write a query to find the second oldest dog by ordering dogs by their longest observed lifespan and using OFFSET 1. I will also retrieve the lifespan value.

[Tool] Got no rows and 3 columns

[Assistant] The query returned no results, which means there might not be individual dogs with the property "longest observed lifespan" (wdt:P4214) directly stated. Instead, I will try to find notable dogs (instances of dog) and check if they have any lifespan or age-related properties. I will search for dogs with the property "instance of" dog (wd:Q144) and then look for properties related to age or lifespan for these dogs.

[Tool]
Got 512 rows and 3 columns, showing the first 10 rows below:
| subject                      | property              | object        |
| ---------------------------- | --------------------- | ------------- |
| Laika (wd:Q53662)            | instance of (wdt:P31) | dog (wd:Q144) |
| Hachikō (wd:Q186486)         | instance of (wdt:P31) | dog (wd:Q144) |
| Blondi (wd:Q155695)          | instance of (wdt:P31) | dog (wd:Q144) |
| Balto (wd:Q805807)           | instance of (wdt:P31) | dog (wd:Q144) |
| Patron (wd:Q111671657)       | instance of (wdt:P31) | dog (wd:Q144) |
| Sergeant Stubby (wd:Q687727) | instance of (wdt:P31) | dog (wd:Q144) |
| Bobi (wd:Q116658361)         | instance of (wdt:P31) | dog (wd:Q144) |
| Koni (wd:Q1320354)           | instance of (wdt:P31) | dog (wd:Q144) |
| Fala (wd:Q1393864)           | instance of (wdt:P31) | dog (wd:Q144) |
| Loukanikos (wd:Q2501596)     | instance of (wdt:P31) | dog (wd:Q144) |
| ...                          | ...                   | ...           |

[Assistant] There are many individual dogs listed as instances of dog (wd:Q144). I will now check the properties of one of these dogs, for example, Bobi (wd:Q116658361), to see if there is any property related to lifespan or age.

[Tool]
Got 87 rows and 3 columns, showing the first 10 rows below:
| subject              | property                            | object                                                                         |
| -------------------- | ----------------------------------- | ------------------------------------------------------------------------------ |
| Bobi (wd:Q116658361) | instance of (wdt:P31)               | dog (wd:Q144)                                                                  |
| Bobi (wd:Q116658361) | sex or gender (wdt:P21)             | male organism (wd:Q44148)                                                      |
| Bobi (wd:Q116658361) | given name (wdt:P735)               | Bobi (wd:Q122232044)                                                           |
| Bobi (wd:Q116658361) | date of birth (wdt:P569)            | 1992-05-11T00:00:00Z (xsd:dateTime)                                            |
| Bobi (wd:Q116658361) | Commons category (wdt:P373)         | Bobi                                                                           |
| Bobi (wd:Q116658361) | image (wdt:P18)                     | <http://commons.wikimedia.org/wiki/Special:FilePath/Dog%20Bobi%20%2801%29.jpg> |
| Bobi (wd:Q116658361) | place of birth (wdt:P19)            | Conqueiros (wd:Q48856032)                                                      |
| Bobi (wd:Q116658361) | date of death (wdt:P570)            | 2023-10-21T00:00:00Z (xsd:dateTime)                                            |
| Bobi (wd:Q116658361) | place of death (wdt:P20)            | Conqueiros (wd:Q48856032)                                                      |
| Bobi (wd:Q116658361) | name in native language (wdt:P1559) | Bobi (pt)                                                                      |
| ...                  | ...                                 | ...                                                                            |

[Assistant] The dog Bobi (wd:Q116658361) has both date of birth (wdt:P569) and date of death (wdt:P570) properties. We can calculate the lifespan by subtracting the birth year from the death year. I will now write a query to find the second oldest dog by calculating the lifespan from date of birth and date of death, ordering by lifespan, and using OFFSET 1.

[Tool]
Got 1 row and 3 columns:
| dog                  | dogLabel  | lifespan     |
| -------------------- | --------- | ------------ |
| Bobi (wd:Q116658361) | Bobi (en) | 31 (xsd:int) |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ( COUNT( ?mountain ) AS ?count ) WHERE {
  ?mountain wdt:P31 wd:Q8502 ; wdt:P17 wd:Q183 .
}

There are 6830 mountains located in Germany according to Wikidata.

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

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

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

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

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

[User] How many mountains are located in Germany?

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

[Tool]
Example 1:
Question:
What is the highest mountain in Germany?

SPARQL:
SELECT ?uri WHERE {
  ?uri wdt:P31 wd:Q8502 ; wdt:P2044 ?elevation ; wdt:P17 wd:Q183 .
}
ORDER BY DESC ( ?elevation )
LIMIT 1

Using entities:
Germany, also known as BR Deutschland, Bundesrepublik Deutschland, Deutschland, Federal Republic of Germany (wd:Q183): country in Central Europe
mountain, also known as mt., mtn., mountains, mount (wd:Q8502): large natural elevation of the Earth's surface

Using properties:
country, also known as sovereign state, state, land, host country (wd:P17 as wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
elevation above sea level, also known as MAMSL, MASL, height, elevation above mean sea level, elevation (wd:P2044 as wdt): height of the item (geographical object) as measured relative to sea level
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 2:
Question:
What is the highest mountain in Saxony Germany?

SPARQL:
SELECT ?res WHERE {
  ?res wdt:P31 wd:Q8502 .
  ?res wdt:P131 + wd:Q1202 .
  ?res wdt:P2044 ?height .
}
ORDER BY DESC ( ?height )
LIMIT 1

Using entities:
Saxony, also known as DE-SN, Free State of Saxony, Swobodny stat Sakska, Freistaat Sachsen, Sachsen (wd:Q1202): state in Germany
mountain, also known as mt., mtn., mountains, mount (wd:Q8502): large natural elevation of the Earth's surface

Using properties:
located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
elevation above sea level, also known as MAMSL, MASL, height, elevation above mean sea level, elevation (wd:P2044 as wdt): height of the item (geographical object) as measured relative to sea level
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 3:
Question:
how much is the population densty rank of germany?

SPARQL:
SELECT ( COUNT( DISTINCT ?country ) as ?cnt ) {
  ?country wdt:P31 wd:Q6256 ; wdt:P1082 ?population ; wdt:P2046 ?area .
  wd:Q183 wdt:P1082 ?germanPopulation .
  wd:Q183 wdt:P2046 ?germanArea .
  BIND( ( ?population / ?area ) AS ?density ) BIND( ( ?germanPopulation / ?germanArea ) AS ?germanDensity ) FILTER ( ?density > ?germanDensity )
}

Using entities:
Germany, also known as BR Deutschland, Bundesrepublik Deutschland, Deutschland, Federal Republic of Germany (wd:Q183): country in Central Europe
country, also known as countries (wd:Q6256): distinct territorial body or political entity

Using properties:
population, also known as inhabitants, human population (wd:P1082 as wdt): number of people inhabiting the place; number of people of subject
area, also known as total area, surface area, surface, size, resolution (wd:P2046 as wdt): area occupied by an object
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

[Assistant]
From the examples, we see that mountains are identified as instances of wd:Q8502 (mountain) and their location is indicated by the property wdt:P17 (country). Germany is identified as wd:Q183.

To answer the question "How many mountains are located in Germany?", we need to count the number of entities that are instances of mountain (wd:Q8502) and have Germany (wd:Q183) as their country (wdt:P17).

I will now write a SPARQL query to count the number of mountains located in Germany.

[Tool]
Got 1 row and 1 column:
| count          |
| -------------- |
| 6830 (xsd:int) |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?date WHERE {
  wd:Q1771942 wdt:P571 ?date .
}

The United Fruit Company was founded in the year 1899.

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

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

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

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

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

[User] When was United Fruit Company founded?

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

[Tool]
Example 1:
Question:
When was the De Beers company founded?

SPARQL:
SELECT ?date WHERE {
  wd:Q471891 wdt:P571 ?date .
}

Using entities:
De Beers, also known as De Beers Group, The De Beers Group of Companies (wd:Q471891): International corporation that specialises in diamond exploratio...retail, rough diamond sales and industrial diamond manufacturing

Using properties:
inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as wdt): time when an entity begins to exist; for date of official opening use P1619, start time

Example 2:
Question:
When were the Hells Angels founded?

SPARQL:
SELECT ?date WHERE {
  wd:Q622188 wdt:P571 ?date .
}

Using entities:
Hells Angels, also known as H. A., Red & White, Hells Angels Motorcycle Club, HAMC, H.A. (wd:Q622188): outlaw motorcycle club

Using properties:
inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as wdt): time when an entity begins to exist; for date of official opening use P1619, start time

[Assistant] From the examples, the property for the founding date or inception is wdt:P571. Now, I need to find the entity for "United Fruit Company" in Wikidata to use it in the query. I will search for the entity "United Fruit Company".

[Tool]
Top 10 entity alternatives:
1. United Fruit Company (wd:Q1771942): American corporation
2. United Fruit Company Building (wd:Q79310992): historic building in Wellington, New Zealand
3. United Fruit Company Infrastructure (wd:Q65591387): Tentative World Heritage Site in Colombia
4. Kossick v. United Fruit Company (wd:Q19089122): United States Supreme Court case
5. United Fruit Company Medal (obverse) (wd:Q122934149): bronze medal-sample by Paul Manship
6. United Fruit Company Medal (reverse) (wd:Q122934151): bronze medal-sample by Paul Manship
7. American Banana Company v. United Fruit Company (wd:Q19037455)
8. United Fruit Company strike of 1913 (wd:Q105962401)
9. United States v. Fruit Growers' Express Company (wd:Q19030798): United States Supreme Court case
10. United Surety Company v. American Fruit Product Company (wd:Q19041555)

[Assistant] The entity for "United Fruit Company" is wd:Q1771942. The property for the founding date or inception is wdt:P571. I will now construct a SPARQL query to get the founding date of the United Fruit Company.

[Tool]
Got 1 row and 1 column:
| date                                |
| ----------------------------------- |
| 1899-01-01T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?discipline ?disciplineLabelGerman WHERE {
  ?discipline wdt:P279 * wd:Q11862829 .
  ?discipline rdfs:label ?disciplineLabelGerman .
  FILTER ( CONTAINS( LCASE( ?disciplineLabelGerman ) , "linguistik" ) ) FILTER ( LANG( ?disciplineLabelGerman ) = "de" )
}

Got 34 rows and 2 columns, showing the first 5 and last 5 rows below:
| discipline                                 | disciplineLabelGerman                |
| ------------------------------------------ | ------------------------------------ |
| Saami linguistics in Sweden (wd:Q10660925) | Samische Linguistik in Schweden (de) |
| statistical linguistics (wd:Q112633055)    | statistische Linguistik (de)         |
| textology (wd:Q1206895)                    | Textlinguistik (de)                  |
| Saami linguistics (wd:Q12718141)           | Samische Linguistik (de)             |
| generative linguistics (wd:Q1369684)       | Generative Linguistik (de)           |
| ...                                        | ...                                  |
| ethnolinguistics (wd:Q853085)              | Ethnolinguistik (de)                 |
| interlinguistics (wd:Q856574)              | Interlinguistik (de)                 |
| corpus linguistics (wd:Q865083)            | Korpuslinguistik (de)                |
| forensic linguistics (wd:Q938318)          | forensische Linguistik (de)          |
| variational sociolinguistics (wd:Q999272)  | Varietätenlinguistik (de)            |

The German names of academic disciplines containing "linguistik" include: Samische Linguistik in Schweden, statistische Linguistik, Textlinguistik, Samische Linguistik, Generative Linguistik, Ethnolinguistik, Interlinguistik, Korpuslinguistik, forensische Linguistik, and Varietätenlinguistik.

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

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

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

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

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

[User] What are the German names of academic disciplines containing “linguistik”?

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

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

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

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

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

Example 2:
Question:
Which university did Angela Merkel attend?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  VALUES ?types {
    wd:Q3918 wd:Q875538
  }
  wd:Q567 wdt:P69 ?uri .
  ?uri wdt:P31 ?types .
}

Using entities:
university, also known as uni, universities (wd:Q3918): academic institution for further education
Angela Merkel, also known as Angela Dorothea Merkel, leader of the free world, Angela Kasner (wd:Q567): chancellor of Germany from 2005 to 2021, politician, physicist
public university (wd:Q875538): university predominantly funded by public means

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

[Assistant] The examples found are not directly related to academic disciplines or their German names. I will now search for entities related to "linguistik" to find academic disciplines containing this term. Then I will check their German names.

[Tool]
Top 10 entity alternatives:
1. Kajian Linguistik (wd:Q96720765): Indonesian scientific journal
2. Kamus Linguistik (wd:Q67393496)
3. Linguistik Online, also known as LO (wd:Q15753135): journal
4. Linguistik Indonesia (wd:Q96725533)
5. TAFSIR LINGUISTIK (wd:Q127574326): scholarly article
6. Linguistik der Wissenschaftssprache (wd:Q110686461): book published in 1995
7. Gesellschaft für Angewandte Linguistik, also known as GAL (wd:Q1341180): German association for applied linguistics
8. Lexikon der Romanistischen Linguistik (wd:Q1680675)
9. Journal of Arabic Linguistics, also known as Zeitschrift fuer Arabische Linguistik, Zeitschrift für Arabische Linguistik (wd:Q15764028): journal
10. Kajian Linguistik dan Sastra, also known as KLS (wd:Q50817999): Academic journal published by Muhammadiyah University Press , co...g the subjects:  Language and Literature: Philology. Linguistics

[Assistant] I found several entities related to "linguistik," but most are journals or books. I need to find academic disciplines containing "linguistik" in their German names. I will search for academic disciplines and filter those whose German labels contain "linguistik." To do this, I first need to find the Wikidata entity for "academic discipline."

[Tool]
Top 10 entity alternatives:
1. academic discipline, also known as research field, sub-discipline, field of study, field of research, discipline (wd:Q11862829): academic field of study or profession
2. academic discipline (wd:L24102-S1)
3. field of work, also known as purpose, specialty, research, research field, research fields (wd:P101): specialization of a person or organization; see P106 for the occupation
4. English studies, also known as English philology, English major, English language and literature, English (academic discipline), English language (wd:Q27968): discipline that studies the English language and literature
5. French language studies, also known as French (academic discipline), French philology, French major, French language, French language and literature (wd:Q11333703): discipline that studies the French language and literature
6. fictional academic discipline (wd:Q126090312)
7. legal management (academic discipline), also known as LegMa (wd:Q6517540): academic and professional discipline that is a hybrid between the study of law and management
8. Academic freedom and academic discipline (wd:Q72399041): scientific article published on 01 April 1969
9. academic discipline and profession (wd:L454629-S1)
10. postcolonialism, - academic discipline (wd:L1319105-S1)

[Assistant] The entity for academic discipline is wd:Q11862829. I will now query for instances or subclasses of this entity and filter those whose German labels contain "linguistik".

[Tool]
Got 34 rows and 2 columns, showing the first 5 and last 5 rows below:
| discipline                                 | disciplineLabelGerman                |
| ------------------------------------------ | ------------------------------------ |
| Saami linguistics in Sweden (wd:Q10660925) | Samische Linguistik in Schweden (de) |
| statistical linguistics (wd:Q112633055)    | statistische Linguistik (de)         |
| textology (wd:Q1206895)                    | Textlinguistik (de)                  |
| Saami linguistics (wd:Q12718141)           | Samische Linguistik (de)             |
| generative linguistics (wd:Q1369684)       | Generative Linguistik (de)           |
| ...                                        | ...                                  |
| ethnolinguistics (wd:Q853085)              | Ethnolinguistik (de)                 |
| interlinguistics (wd:Q856574)              | Interlinguistik (de)                 |
| corpus linguistics (wd:Q865083)            | Korpuslinguistik (de)                |
| forensic linguistics (wd:Q938318)          | forensische Linguistik (de)          |
| variational sociolinguistics (wd:Q999272)  | Varietätenlinguistik (de)            |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?birthDate WHERE {
  wd:Q27449519 wdt:P569 ?birthDate .
}

The author of "The Vanishing Half", Brit Bennett, was born in the year 1990.

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

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

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

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

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

[User] In which year was the author of “The Vanishing Half” born?

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

[Tool]
Example 1:
Question:
Who is the novelist of the work a song of ice and fire?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q45875 ?p ?uri .
  ?uri wdt:P106 wd:Q6625963 .
}

Using entities:
A Song of Ice and Fire, also known as A Song of Ice and Fire Series, Game of Thrones, Song of Ice and Fire, ASOIAF (wd:Q45875): series of epic fantasy novels by George R. R. Martin
novelist, also known as novel author, novel writer (wd:Q6625963): writer of novels

Using properties:
occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)

Example 2:
Question:
Who wrote the book The Pillars of the Earth?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q1163227 wdt:P50 ?uri .
}

Using entities:
The Pillars of the Earth, also known as The Pillars of the Earth (Kingsbridge, #1) (wd:Q1163227): 1989 novel by Ken Follett

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

Example 3:
Question:
Who wrote the book The pillars of the Earth?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q1163227 wdt:P50 ?uri .
}

Using entities:
The Pillars of the Earth, also known as The Pillars of the Earth (Kingsbridge, #1) (wd:Q1163227): 1989 novel by Ken Follett

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

[Assistant] From the examples, we see that the property for the author of a book is wdt:P50. First, I will search for the entity "The Vanishing Half" to get its Wikidata ID. Then I will query the author of this book and finally get the birth year of that author.

[Tool]
Top 10 entity alternatives:
1. The Vanishing Half (wd:Q98476957): 2020 novel by Brit Bennett
2. The Vanishing, also known as Vanishing (wd:Q616301): 1993 film directed by George Sluizer
3. The Vanishing, also known as L'Homme qui voulait savoir, Vanishing (wd:Q1895379): 1988 film by George Sluizer
4. The Vanishing, also known as Keepers, The Devil to Pay (wd:Q29514859): 2018 film directed by Kristoffer Nyholm
5. The Half (wd:Q63109025)
6. The Vanishing (wd:Q129416681): 2024 film by Karim Moussaoui
7. The Vanishing, also known as Far Cry: The Vanishing, Far Cry 6: The Vanishing (wd:Q114877764): 2022 Far Cry 6 mission that is a crossover with Stranger Things
8. The Vanishing (wd:Q114523535): episode of Scream (S2 E10)
9. The Vanishing (wd:Q114539612): episode of Z Nation (S4 E3)
10. The Vanishing (wd:Q123307638): 1993 film by George Sluizer

[Assistant] The Vanishing Half is identified as wd:Q98476957. Now I will query the author (wdt:P50) of this book.

[Tool]
Got 1 row and 1 column:
| author                      |
| --------------------------- |
| Brit Bennett (wd:Q27449519) |

[Assistant] The author of "The Vanishing Half" is Brit Bennett (wd:Q27449519). Now I will query the birth year (wdt:P569) of Brit Bennett.

[Tool]
Got 1 row and 1 column:
| birthDate                           |
| ----------------------------------- |
| 1990-01-01T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?country ?countryLabel WHERE {
  wd:Q327818 wdt:P17 ?country .
  ?country rdfs:label ?countryLabel
  FILTER ( LANG( ?countryLabel ) = "en" )
}

Got 1 row and 2 columns:
| country           | countryLabel |
| ----------------- | ------------ |
| Germany (wd:Q183) | Germany (en) |

The Kandahar-downhill (Kandahar Downhill Piste) is located in the country Germany.

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

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

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

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

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

[User] In what country is the Kandahar-downhill?

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

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

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

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

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

Example 2:
Question:
To which countries does the Himalayan mountain system extend?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q5451 wdt:P17 ?uri .
}

Using entities:
Himalayas, also known as Himalaya, Himálaya, Himalaya Mountains, Himálaya Mountains, Himalayan Mountains (wd:Q5451): mountain range in Asia

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

Example 3:
Question:
What is the highest place of Karakoram?

SPARQL:
SELECT ?uri WHERE {
  wd:Q5469 wdt:P610 ?uri
}

Using entities:
Karakoram, also known as Karakoram Mountains, Karakoram Range, Karakoroum, Karakoroum Mountains, Karakorum (wd:Q5469): major mountain range spanning the borders between India, Pakistan, and China

Using properties:
highest point, also known as tallest point, zenith, summit, pinnacle, highest peak (wd:P610 as wdt): point with highest elevation in a region or path, has part(s)

[Assistant] From the examples, it is clear that the property "country" (wdt:P17) is used to find the country in which a geographical entity is located. Next, I will search for the entity "Kandahar-downhill" in Wikidata to find its identifier.

[Tool] No entity items found

[Assistant] I could not find an entity named "Kandahar-downhill" in Wikidata. It is possible that the entity is named differently or is part of a larger entity. I will try searching for "Kandahar" to see if there is a related entity that might include the "Kandahar-downhill."

[Tool]
Top 10 entity alternatives:
1. Kandahar, also known as Candahar, Qandahar (wd:Q45604): city in Kandahar Province, Afghanistan
2. Kandahar, also known as Safar-e Ghandehar, The Sun Behind the Moon (wd:Q785496): 2001 film directed by Mohsen Makhmalbaf
3. Kandahar, also known as with Albert and sonichoc (wd:Q111940088): 2023 film by Ric Roman Waugh
4. Kandahar (wd:Q6361199): 2010 Malayalam film directed by Major Ravi
5. Kandahar, also known as Kandahar, Saskatchewan (wd:Q14874966): organized hamlet in Saskatchewan, Canada
6. Kandahar (wd:Q55956959): episode of The Punisher (S1 E3)
7. Kandahar (wd:Q50902249): painting by Victor Vasarely
8. Kandahar Province, also known as Ghandahar Province, Qandahar Province (wd:Q173808): province of Afghanistan
9. Kandahar International Airport, also known as OAKN, Kandahar Airfield, KDH, KAF, Kandahar Airport (wd:Q33156): international airport serving Kandahar, Afghanistan
10. Kandahar District, also known as Dand District (wd:Q2673970): district in Kandahar Province, Afghanistan

[Assistant]
I found several entities related to "Kandahar," but none explicitly mention "Kandahar-downhill." The most relevant geographic entities are Kandahar city (wd:Q45604) and Kandahar Province (wd:Q173808) in Afghanistan.

Since "Kandahar-downhill" might be a ski or sports-related location, I will try searching for properties related to "downhill" to see if there is a property or related entity that can help identify the location or country of "Kandahar-downhill."

[Tool]
Top 10 property alternatives:
1. slope, also known as angle (wd:P4184 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): angle the surface of an item makes with the horizontal
2. slope rating (wd:P3840 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): the slope rating of a golf course is a measure of its difficulty for bogey golfers
3. average gradient, also known as gradient (wd:P2198 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): gradient expressed as a percentage (between 0 and 1)
4. maximum gradient, also known as maximum incline, ruling grade, max slop, maximum slope, max gradient (wd:P2595 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): maximum gradient on a route, expressed as a percentage
5. DoBIH Number, also known as Database of British and Irish Hills number, Hillbagging number, Hill Bagging number (wd:P6515 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): stable identifying number for hills in the Database of British and Irish Hills
6. mountain range, also known as system of mountains, hill range, range, parent range, mountain system (wd:P4552 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): range or subrange to which the geographical item belongs, geomorphological unit
7. next lower rank, also known as lower level, lower rank, next (lower), next lower level (wd:P3729 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): lower rank or level in a ranked hierarchy like sport league, mil...fiers. For sports leagues/taxa, use specific properties instead., follows
8. elevation above sea level, also known as MAMSL, MASL, height, elevation above mean sea level, elevation (wd:P2044 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): height of the item (geographical object) as measured relative to sea level
9. descending scale, also known as raga theme, avarohana (wd:P7599 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): sequence of notes starting from a tonic in one octave and ending with the tonic one octave below
10. relegated, also known as team relegated, relegation, player relegated, competitor relegated (wd:P2882 as prv/wdtn/prn/psv/pq/pqn/p/ps/psn/pqv/pr/wdt): competitor or team relegated during competition

[Assistant] There is no direct property related to "downhill" as a location or event. Since "Kandahar-downhill" might be a specific ski run or sports venue, I will try searching for "Kandahar" combined with "downhill" to see if there is an entity or related information.

[Tool]
Top 10 entity alternatives:
1. Kandahar Downhill Piste (wd:Q327818): ski course in Bavaria, Germany
2. Kandahar, also known as Candahar, Qandahar (wd:Q45604): city in Kandahar Province, Afghanistan
3. downhill, also known as downhill skiing (wd:Q319899): alpine skiing discipline
4. Kandahar, also known as Safar-e Ghandehar, The Sun Behind the Moon (wd:Q785496): 2001 film directed by Mohsen Makhmalbaf
5. Downhill (wd:Q495820): 1927 film by Alfred Hitchcock
6. Kandahar, also known as with Albert and sonichoc (wd:Q111940088): 2023 film by Ric Roman Waugh
7. Downhill (wd:Q60737609): 2020 film directed by Nat Faxon and Jim Rash
8. Downhill, also known as Downhill, County Londonderry (wd:Q702677): village in County Londonderry, Northern Ireland, UK
9. Kandahar (wd:Q6361199): 2010 Malayalam film directed by Major Ravi
10. Downhill (wd:Q17426163): 2014 film by James Rouse

[Assistant] I found the entity "Kandahar Downhill Piste" (wd:Q327818), which is a ski course in Bavaria, Germany. This seems to be the correct entity for "Kandahar-downhill." Now, I will query the country in which this ski course is located.

[Tool]
Got 1 row and 2 columns:
| country           | countryLabel |
| ----------------- | ------------ |
| Germany (wd:Q183) | Germany (en) |

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?game ?gameLabel WHERE {
  ?game wdt:P178 wd:Q677273 .
  ?game wdt:P577 ?releaseDate .
  OPTIONAL {
    ?game rdfs:label ?gameLabel FILTER ( LANG( ?gameLabel ) = "en" )
  }
}
ORDER BY ?releaseDate
OFFSET 1
LIMIT 1

The second game developed by Piranha Bytes is Gothic II.

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

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

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

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

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

[User] What is the second game developed by Piranha Bytes?

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

[Tool]
Example 1:
Question:
Who developed Minecraft?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q49740 wdt:P178 ?uri .
}

Using entities:
Minecraft, also known as MC, Mine Craft, MineCraft (wd:Q49740): 2011 video game

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

[Assistant]
The example shows that the property "developer" (wdt:P178) is used to find the developer of a video game. In our case, we want to find the games developed by "Piranha Bytes" and then determine the second game they developed.

Step 1: Identify the entity for "Piranha Bytes."
Step 2: Find the games developed by "Piranha Bytes."
Step 3: Order the games by their release date to determine the second game.

I will start by searching for the entity "Piranha Bytes."

[Tool]
Top 10 entity alternatives:
1. Piranha Bytes (wd:Q677273): German video game development company
2. piranha, also known as piraña, Serrasalmus nattereri (wd:Q185215): group of fish
3. Piranha 3D, also known as Piranha (wd:Q733995): 2010 film directed by Alexandre Aja
4. Piranha, also known as Mowag Piranha (wd:Q687702): armored fighting vehicle family by MOWAG
5. Piranha (wd:Q1140216): 1978 film by Joe Dante
6. Piranha (wd:Q1215873): 1995 television film
7. Piranha (wd:Q1551737): 2006 film by Andrey Kavun
8. Bytes (wd:Q5004626): 1993 debut studio album by Black Dog Productions
9. Piranha (wd:Q4394050): single by The Grace
10. Piranha (wd:Q3389104): fictional comic book character

[Assistant] The entity "Piranha Bytes" corresponds to wd:Q677273, which is a German video game development company. Next, I will find the games developed by Piranha Bytes using the developer property (wdt:P178).

[Tool]
SPARQL execution failed:
Error while executing a SERVICE request to <http://wikiba.se:80/ontology#label>: SERVICE responded with HTTP status code: 301, Moved Permanently. First 100 bytes of the response: '<html>
<head><title>301 Moved Permanently</title></head>
<body>
<center><h1>301 Moved Permanently'

[Assistant] The query failed because the SERVICE wikibase:label is not supported by the QLever SPARQL endpoint. I will rewrite the query without using SERVICE wikibase:label and instead use optional rdfs:label to get the game labels.

[Tool]
Got 22 rows and 3 columns, showing the first 5 and last 5 rows below:
| game                                         | gameLabel                         | releaseDate                         |
| -------------------------------------------- | --------------------------------- | ----------------------------------- |
| Gothic (wd:Q1088631)                         | Gothic (en)                       |                                     |
| ZenGin (wd:Q71850046)                        | ZenGin (en)                       |                                     |
| Genome (wd:Q71848663)                        | Genome (en)                       |                                     |
| Risen (wd:Q3433133)                          | Risen (en)                        |                                     |
| wd:Q767456                                   |                                   | 2001-03-15T00:00:00Z (xsd:dateTime) |
| ...                                          | ...                               | ...                                 |
| Risen 3: Titan Lords (wd:Q15918760)          | Risen 3: Titan Lords (en)         | 2014-08-15T00:00:00Z (xsd:dateTime) |
| Elex (wd:Q25345979)                          | Elex (en)                         | 2017-10-17T00:00:00Z (xsd:dateTime) |
| Elex II (wd:Q107248040)                      | Elex II (en)                      | 2022-03-01T00:00:00Z (xsd:dateTime) |
| Risen (wd:Q1513013)                          | Risen (en)                        | 2023-01-24T00:00:00Z (xsd:dateTime) |
| Gothic Classic Khorinis Saga (wd:Q125849513) | Gothic Classic Khorinis Saga (en) | 2024-06-27T00:00:00Z (xsd:dateTime) |

[Assistant] I found 22 games developed by Piranha Bytes. Some have release dates, and some do not. To find the second game developed, I should consider only those with release dates and order them by release date ascending. I will refine the query to filter out games without release dates and order by release date ascending, then limit the results to the second game.

[Tool]
Got 2 rows and 3 columns:
| game                    | gameLabel      | releaseDate                         |
| ----------------------- | -------------- | ----------------------------------- |
| wd:Q767456              |                | 2001-03-15T00:00:00Z (xsd:dateTime) |
| Gothic II (wd:Q1456987) | Gothic II (en) | 2002-11-29T00:00:00Z (xsd:dateTime) |

[Assistant]
The query returned two games developed by Piranha Bytes ordered by release date. The first game has no label but was released on 2001-03-15. The second game is "Gothic II" released on 2002-11-29. Since the question asks for the second game developed by Piranha Bytes, the answer is "Gothic II."

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

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ( COUNT( ?album ) AS ?count ) WHERE {
  wd:Q16986149 wdt:P527 ?album .
  ?album wdt:P31 wd:Q482994 .
}

Got 1 row and 1 column:
| count        |
| ------------ |
| 22 (xsd:int) |

Mariah Carey performs on 22 albums according to her Wikimedia albums discography.

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

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

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

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

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

[User] On how many albums does Mariah Carey perform?

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

[Tool] No examples found

[Assistant] There are no similar examples available. Next, I will search for the entity "Mariah Carey" in Wikidata to identify her entity ID. This will help us find the albums on which she performs.

[Tool]
Top 10 entity alternatives:
1. Mariah Carey, also known as Queen of Christmas, Mirage, Songbird Supreme, Reina de la navidad, Carey (wd:Q41076): American singer and songwriter (born 1969), music video director, singer-songwriter, recording artist, philanthropist, businessperson, film director, film producer, DJ producer, voice actor, entertainer, composer, singer, model, actor
2. Mariah Carey (wd:Q732845): 1990 debut studio album by Mariah Carey
3. WikiProject Mariah Carey (wd:Q21830328): Wikimedia subject-area collaboration
4. Here Is Mariah Carey (wd:Q836551): VHS and DVD by Mariah Carey
5. The Essential Mariah Carey (wd:Q3235035): 2011 compilation album by Mariah Carey
6. M, also known as M By Mariah Carey (wd:Q690434): women's fragrance from Elizabeth Arden
7. Mariah Carey: DVD Collection (wd:Q3282698): album by Mariah Carey
8. Mariah Carey: Her Story (wd:Q131320674): book by the British writer Chris Nickson
9. Mariah Carey Collector's Set (wd:Q18277464): album by Mariah Carey
10. Why Mariah Carey Matters (wd:Q131160633): book written by Andrew Chan

[Assistant] The entity for Mariah Carey as an American singer and songwriter is wd:Q41076. Now, I will search for properties related to albums or performances for this entity to find how to query the albums on which Mariah Carey performs.

[Tool]
Top 10 property alternatives:
1. AllMusic artist ID, also known as AllMusic, AllMusic ID, amg artist (wd:P1728 as p/wdt): identifier for an artist, musical group, or record label in the AllMusic database (record labels are listed as "artists")
2. 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
3. discography, also known as discography link, recording catalog (wd:P358 as p/wdt): item for list pages with discography of artist or band, list of works
4. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
5. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as p/wdt): the object is a country that recognizes the subject as its citizen, country
6. record label, also known as label, labels (wd:P264 as p/wdt): brand and trademark associated with the marketing of subject music recordings and music videos
7. Apple Music artist ID (U.S. version), also known as iTunes author ID, music.apple.com/artist/, iTunes artist ID (American version), https://music.apple.com/artist/, Apple Music artist ID (American version) (wd:P2850 as p/wdt): identifier for a musical artist or author in the U.S. version of Apple Music
8. work period (start), also known as start working, flourished (start), start time for work, start date of activity, fl. (start) (wd:P2031 as p/wdt): start of period during which a person or group flourished (fl. = "floruit") in their professional activity, start time, floruit
9. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as p/wdt): award or recognition received by a person, organization or creative work
10. Official Charts artist ID, also known as Official Charts ID (wd:P6559 as p/wdt): identifier for musical acts at Official Charts Company's website

No other items found

[Assistant] The property "discography" (wdt:P358) is related to a list of works of the artist. This might help us find the albums Mariah Carey performs on. I will now check what kind of items are linked to Mariah Carey via the discography property.

[Tool]
Got 1 row and 3 columns:
| subject                  | property               | object     |
| ------------------------ | ---------------------- | ---------- |
| Mariah Carey (wd:Q41076) | discography (wdt:P358) | wd:Q263476 |

[Assistant] Mariah Carey's discography is linked to the entity wd:Q263476. I will now check what this entity represents and if it contains albums.

[Tool]
Got 104 rows and 3 columns, showing the first 10 rows below:
| subject    | property                | object                                                             |
| ---------- | ----------------------- | ------------------------------------------------------------------ |
| wd:Q263476 | instance of (wdt:P31)   | Wikimedia artist discography (wd:Q104635718)                       |
| wd:Q263476 | main subject (wdt:P921) | Mariah Carey (wd:Q41076)                                           |
| wd:Q263476 | has list (wdt:P2354)    | wd:Q1165154                                                        |
| wd:Q263476 | wdt:P31279              | discography (wd:Q273057)                                           |
| wd:Q263476 | schema:description      | artistdiskografi (sv)                                              |
| wd:Q263476 | schema:name             | Album của Mariah Carey (vi)                                        |
| wd:Q263476 | rdf:type                | wikibase:Item                                                      |
| wd:Q263476 | rdfs:label              | Album của Mariah Carey (vi)                                        |
| wd:Q263476 | skos:altLabel           | discografia completa della cantante statunitense Mariah Carey (it) |
| wd:Q263476 | skos:prefLabel          | Album của Mariah Carey (vi)                                        |
| ...        | ...                     | ...                                                                |

[Assistant] The entity wd:Q263476 is an artist discography for Mariah Carey. It has a property "has list" (wdt:P2354) pointing to wd:Q1165154. This might be the list of albums. I will check what wd:Q1165154 contains.

[Tool]
Got 64 rows and 3 columns, showing the first 10 rows below:
| subject     | property                | object                                                  |
| ----------- | ----------------------- | ------------------------------------------------------- |
| wd:Q1165154 | instance of (wdt:P31)   | videography (wd:Q17438413)                              |
| wd:Q1165154 | part of (wdt:P361)      | wd:Q263476                                              |
| wd:Q1165154 | has part(s) (wdt:P527)  | O Come All Ye Faithful/Hallelujah Chorus (wd:Q60517300) |
| wd:Q1165154 | is a list of (wdt:P360) | music video (wd:Q193977)                                |
| wd:Q1165154 | Freebase ID (wdt:P646)  | /m/01193dv0                                             |
| wd:Q1165154 | schema:description      | Mariah Carey videóklipjei (hu)                          |
| wd:Q1165154 | schema:name             | Anexo:Videografía de Mariah Carey (es)                  |
| wd:Q1165154 | rdf:type                | wikibase:Item                                           |
| wd:Q1165154 | rdfs:label              | Anexo:Videografía de Mariah Carey (es)                  |
| wd:Q1165154 | skos:altLabel           | videography from Mariah Carey (en)                      |
| ...         | ...                     | ...                                                     |

[Assistant] The entity wd:Q1165154 is a videography list, not an album list. I will check other "has list" (wdt:P2354) properties of wd:Q263476 to find the album list.

[Tool]
Got 10 rows and 3 columns:
| subject    | property             | object       |
| ---------- | -------------------- | ------------ |
| wd:Q263476 | has list (wdt:P2354) | wd:Q1165154  |
| wd:Q263476 | has list (wdt:P2354) | wd:Q1165157  |
| wd:Q263476 | has list (wdt:P2354) | wd:Q13424630 |
| wd:Q263476 | has list (wdt:P2354) | wd:Q16986149 |
| wd:Q263476 | has list (wdt:P2354) | wd:Q1845975  |
| wd:Q263476 | has list (wdt:P2354) | wd:Q19295779 |
| wd:Q263476 | has list (wdt:P2354) | wd:Q60501263 |
| wd:Q263476 | has list (wdt:P2354) | wd:Q60501735 |
| wd:Q263476 | has list (wdt:P2354) | wd:Q60501744 |
| wd:Q263476 | has list (wdt:P2354) | wd:Q61566854 |

[Assistant] There are multiple "has list" properties for wd:Q263476. I will check the labels and instance types of these lists to find which one corresponds to albums. I will start with wd:Q1165157.

[Tool]
Got 99 rows and 3 columns, showing the first 10 rows below:
| subject     | property                | object                                                 |
| ----------- | ----------------------- | ------------------------------------------------------ |
| wd:Q1165157 | instance of (wdt:P31)   | Wikimedia list of songs by performer (wd:Q83790536)    |
| wd:Q1165157 | part of (wdt:P361)      | wd:Q1845975                                            |
| wd:Q1165157 | is a list of (wdt:P360) | wd:Q57248574                                           |
| wd:Q1165157 | schema:description      | article de llista de Wikimedia (ca)                    |
| wd:Q1165157 | schema:name             | list of unreleased songs recorded by Mariah Carey (en) |
| wd:Q1165157 | rdf:type                | wikibase:Item                                          |
| wd:Q1165157 | rdfs:label              | list of unreleased songs recorded by Mariah Carey (en) |
| wd:Q1165157 | skos:prefLabel          | list of unreleased songs recorded by Mariah Carey (en) |
| wd:Q1165157 | wdt:P31279              | Wikimedia list of songs (wd:Q17099416)                 |
| wd:Q1165157 | instance of (p:P31)     | s:Q1165157-7C49454D-7D50-45B3-931D-594C1889AB31        |
| ...         | ...                     | ...                                                    |

[Assistant] The entity wd:Q1165157 is a list of unreleased songs recorded by Mariah Carey, not albums. I will check the next list wd:Q13424630.

[Tool]
Got 84 rows and 3 columns, showing the first 10 rows below:
| subject      | property                             | object                                       |
| ------------ | ------------------------------------ | -------------------------------------------- |
| wd:Q13424630 | instance of (wdt:P31)                | Wikimedia singles discography (wd:Q59248059) |
| wd:Q13424630 | part of (wdt:P361)                   | wd:Q263476                                   |
| wd:Q13424630 | has part(s) (wdt:P527)               | I Want to Know What Love Is (wd:Q1060955)    |
| wd:Q13424630 | is a list of (wdt:P360)              | single (wd:Q134556)                          |
| wd:Q13424630 | category related to list (wdt:P1754) | wd:Q9266769                                  |
| wd:Q13424630 | wdt:P31279                           | discography (wd:Q273057)                     |
| wd:Q13424630 | schema:description                   | discografie van Mariah Carey (nl)            |
| wd:Q13424630 | schema:name                          | Anexo:Sencillos de Mariah Carey (es)         |
| wd:Q13424630 | rdf:type                             | wikibase:Item                                |
| wd:Q13424630 | rdfs:label                           | Anexo:Sencillos de Mariah Carey (es)         |
| ...          | ...                                  | ...                                          |

[Assistant] The entity wd:Q13424630 is a singles discography, not albums. I will check the next list wd:Q16986149.

[Tool]
Got 123 rows and 3 columns, showing the first 10 rows below:
| subject      | property                             | object                                                 |
| ------------ | ------------------------------------ | ------------------------------------------------------ |
| wd:Q16986149 | instance of (wdt:P31)                | Wikimedia albums discography (wd:Q59191021)            |
| wd:Q16986149 | part of (wdt:P361)                   | wd:Q263476                                             |
| wd:Q16986149 | has part(s) (wdt:P527)               | Mariah Carey (wd:Q732845)                              |
| wd:Q16986149 | is a list of (wdt:P360)              | album (wd:Q482994)                                     |
| wd:Q16986149 | category related to list (wdt:P1754) | wd:Q6844055                                            |
| wd:Q16986149 | BabelNet ID (wdtn:P2581)             | <http://babelnet.org/rdf/s01760915n>                   |
| wd:Q16986149 | wdt:P31279                           | discography (wd:Q273057)                               |
| wd:Q16986149 | schema:description                   | albumdiskografi (sv)                                   |
| wd:Q16986149 | schema:name                          | albaim de chuid Mariah Carey in ord croineolaíoch (ga) |
| wd:Q16986149 | rdf:type                             | wikibase:Item                                          |
| ...          | ...                                  | ...                                                    |

[Assistant] The entity wd:Q16986149 is a Wikimedia albums discography and is a list of albums. It has parts which are albums. I will now count the number of albums in this list using the "has part(s)" (wdt:P527) property.

[Tool]
Got 1 row and 1 column:
| count        |
| ------------ |
| 22 (xsd:int) |

[Tool] Stopped generation process