Failed to generate SPARQL query

[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 examples.

[Tool]
Example 1:
Question:
When did Michael Jackson die?

SPARQL:
SELECT ?o1 WHERE {
  wd:Q2831 wdt:P570 ?o1 .
}

Using entities:
Michael Jackson, also known as M.J., MJ, M. J., The King of Pop, King of Pop (wd:Q2831): American singer, songwriter, and dancer (1958–2009), singer-songwriter, recording artist, record producer, businessperson, philanthropist, music arranger, autobiographer, film director, choreographer, art collector, entrepreneur, screenwriter, voice actor, songwriter, film actor, composer, dancer, singer, actor, model, poet

Using properties:
date of death, also known as DOD, deathdate, died, died on, year of death (wd:P570 as wdt): dissolved, abolished or demolished date, date on which the subject died, end time

Example 2:
Question:
Give me the capitals of all countries in Africa.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?country wdt:P31 wd:Q6256 .
  ?country wdt:P30 wd:Q15 .
  ?country wdt:P36 ?uri .
}

Using entities:
Africa, also known as African continent (wd:Q15): continent
country, also known as countries (wd:Q6256): distinct territorial body or political entity

Using properties:
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)
capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as wdt): seat of government of a country, province, state or other type of administrative territorial entity

Example 3:
Question:
How high is the Yokohama Marine Tower?

SPARQL:
SELECT DISTINCT ?num WHERE {
  wd:Q1207989 wdt:P2048 ?num .
}

Using entities:
Yokohama Marine Tower (wd:Q1207989): lighthouse in Japan

Using properties:
height, also known as heighth, size, depth over terrain (wd:P2048 as wdt): vertical length of an entity, length

[Assistant] Based on the examples, we need to identify the entity representing the second oldest dog in the world and then find out its age. Let's start by searching for the entity "second oldest dog".

[Tool]
Top 10 entity alternatives:
1. second oldest profession (wd:Q25111891): English idiom
2. Killing the Second Dog (wd:Q17155320): 1985 novel by Marek Hłasko
3. The Second Oldest Profession (wd:Q114513858): episode of Hill Street Blues (S2 E4)
4. The Second Oldest Profession (wd:Q51591125): episode of The Philco Television Playhouse
5. The Second Oldest Question (wd:Q132326917): Radio Drama based on Doctor Who
6. Hungry Dogs, second stone (wd:Q65508539): print in the National Gallery of Art (NGA 46760)
7. Tchong-tas-sáb-bee, Black Dog, Second Chief (wd:Q20539924): painting by George Catlin
8. Hungry Dogs, Second Stone, second state (wd:Q80010085): print by George Bellows (American, 1882-1925) (1936.609)
9. The Second Memorial Dogonadze Symposium (wd:Q126399906): scholarly article
10. [Secondary hyperparathyroidism in dogs] (wd:Q72354413): scientific article published on 01 January 1994

[Assistant] None of these entities seem to represent the second oldest dog in the world. We might need to take a different approach. Let's try to find the entity for "oldest dogs" and see if we can extract the second oldest from there.

[Tool]
Top 10 entity alternatives:
1. Oldest images of dogs show hunting, leashes (wd:Q49952104): scientific article published in November 2017
2. Psy, also known as Dogs (wd:Q1998914): 1989 Soviet Russian film directed by Dmitri Svetozarov
3. Dogs, also known as Dogs: Bullets & Carnage (wd:Q2539750): Japanese manga series
4. Psy, also known as Dogs, Pigs (wd:Q7256176): 1992 film by Władysław Pasikowski
5. Dogs (wd:Q23925051): 2016 film
6. The Dogs, also known as Dogs, Les Chiens (wd:Q1213499): 1979 film by Alain Jessua
7. Dogs (wd:Q539327): French punk rock/new wave band
8. Dogs (wd:Q3231493): 1977 film by Burt Brinckerhoff
9. Dogs (wd:Q5288423): Damien Rice song
10. Dogs (wd:Q3712549): British band

[Assistant] It seems that none of these entities directly refer to the oldest dogs in the world. We might need to look for a list of the oldest dogs and then identify the second oldest. Let's try searching for "list of oldest dogs" to see if we can find a relevant entity.

[Tool]
Top 10 entity alternatives:
1. list of dogs under breed specific legislation (wd:Q38758): Wikimedia list article
2. List of oldest people infected with COVID-19, also known as oldest people diagnosed with COVID-19 (wd:Q115959635)
3. Oldest images of dogs show hunting, leashes (wd:Q49952104): scientific article published in November 2017
4. Hemodynamic effect of listerial hemolysin in dogs (wd:Q47685194): scientific article
5. descendant list, also known as list of offspring, progeny list, list of descendants, descendants list (wd:Q20820085): list of genetic descendants, offspring
6. descendants list, also known as list of descendants, list of offspring, progeny list, descendants list (wd:Q20820085): list of genetic descendants, offspring
7. List of Officers (wd:Q60199960)
8. list of offer (wd:Q60554627)
9. is a list of, also known as list has main topic, main topic of list, main article of list, lists, list of (wd:P360): common element between all listed items
10. Isle of Dogs (wd:Q28065409): 2018 film directed by Wes Anderson

[Assistant]
Unfortunately, there doesn't seem to be a direct entity for "list of oldest dogs" in the search results. However, we can try to find the entity for the oldest dog and then look for the second oldest dog through its properties or related entities.

Let's search for the entity "oldest dog" and see if we can find any relevant information.

[Tool]
Top 10 entity alternatives:
1. World's oldest dog dies at age 20 (wd:Q17660624): Wikinews article
2. dog, also known as Canis lupus familiaris, Canis familiaris, domestic dogs, domestic dog (wd:Q144): domestic animal
3. Dog (wd:Q755126): sign of Chinese zodiac
4. Dog (wd:Q104843787): 2022 film directed by Reid Carolin and Channing Tatum
5. Dongola Airport, also known as DOG, HSDN (wd:Q1431231): airport
6. Hurricane Dog, also known as Dog (wd:Q217669): Category 5 Atlantic hurricane in 1950
7. Wax, also known as Dog, WAX (wd:Q624269): South Korean singer, singer
8. Dog, also known as D0g (wd:Q1211818): fictional character in Half-Life
9. hound, also known as dog (wd:Q1637371): heraldic animal
10. dog, also known as shutter, shutter dog (wd:Q5288153): tool in engineering

[Assistant]
The search results for "oldest dog" do not provide a direct entity for the oldest dog in the world. However, the first result, "World's oldest dog dies at age 20," is a Wikinews article that might contain relevant information about the oldest dog.

Let's check the details of this article to see if it provides any clues about the second oldest dog.

[Tool]
Got 75 rows and 3 columns, showing the first 10 rows below:
| subject                                          | property                            | object                                           |
| ------------------------------------------------ | ----------------------------------- | ------------------------------------------------ |
| World's oldest dog dies at age 20 (wd:Q17660624) | instance of (wdt:P31)               | Wikinews article (wd:Q17633526)                  |
| World's oldest dog dies at age 20 (wd:Q17660624) | publication date (wdt:P577)         | 2010-01-18T00:00:00Z (xsd:dateTime)              |
| World's oldest dog dies at age 20 (wd:Q17660624) | language of work or name (wdt:P407) | English (wd:Q1860)                               |
| World's oldest dog dies at age 20 (wd:Q17660624) | schema:description                  | alt Wikinews (ga)                                |
| World's oldest dog dies at age 20 (wd:Q17660624) | schema:name                         | World's oldest dog dies at age 20 (en)           |
| World's oldest dog dies at age 20 (wd:Q17660624) | rdf:type                            | wikibase:Item                                    |
| World's oldest dog dies at age 20 (wd:Q17660624) | rdfs:label                          | World's oldest dog dies at age 20 (en)           |
| World's oldest dog dies at age 20 (wd:Q17660624) | skos:prefLabel                      | World's oldest dog dies at age 20 (en)           |
| World's oldest dog dies at age 20 (wd:Q17660624) | instance of (p:P31)                 | s:Q17660624-696F0392-46AB-4C76-BFD4-8089B098E646 |
| World's oldest dog dies at age 20 (wd:Q17660624) | publication date (p:P577)           | s:Q17660624-2aaf2c4a-d55d-4ddf-a2df-29eeccbef264 |
| ...                                              | ...                                 | ...                                              |

[Assistant]
The article "World's oldest dog dies at age 20" does not provide direct information about the second oldest dog. However, it confirms that there is a concept of the oldest dog in the world.

To find the second oldest dog, we need to look for a list of the oldest dogs or find a property that ranks dogs by their age. Let's search for properties related to "age" and "dog" to see if we can find a way to rank dogs by their age.

[Tool]
Top 10 property alternatives:
1. animal breed, also known as breed, sheep breed, horse breed, goat breed, duck breed (wd:P4743 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): subject item belongs to a specific group of domestic animals, generally given by association
2. EE breed number, also known as breed number (wd:P303 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): breed identification number per the EE list of the breeds of fancy pigeons (ELFP)
3. has pet, also known as pet, keeps pet, owns pet (wd:P1429 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): pet that a person owns
4. hybrid of, also known as cultivar from, parent breed, parent cultivar, parent of this hybrid, parent of this hybrid, breed, or cultivar (wd:P1531 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): parent of this hybrid breed or cultivar
5. species kept, also known as plant taxon in botanical garden, resident animals, plant taxon in collection, resident animal species, rose varity in rose garden (wd:P1990 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): taxa, preferably species, present at a zoo, botanical garden, co...stitution. NOT specific animals, not for any geographic location, has part(s) of the class
6. taxon especially protected in area, also known as animal protected, plant protected, protected animal, protected plant, protected species (wd:P6569 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): species and other taxa especially protected in a area, whether s...ountries/subnational entities: use red lists properties instead.
7. winner, also known as nominee, prizewinner, titleholder, top dog, victor (wd:P1346 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): winner of a competition or similar event, not to be used for awa...ssibly qualified with "for work" (P1686)) or for wars or battles, participating team, participant
8. narrative age, also known as specific age inside fictional universe, years old in-universe, narrative age, age in story, age in fiction (wd:P6249 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): age of a fictional character (use qualifiers like P10663 (applies to work) to restrict the age to a certain work)
9. DOGC ID (wd:P6514 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): external and unique identifier which represents a publication in Diari Oficial de la Generalitat de Catalunya
10. mean age, also known as average age (wd:P4442 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): mean age in a given place

[Assistant] None of the properties listed here directly relate to the age of a dog. However, we can try to find a property that relates to the lifespan or age of an individual dog. Let's search for properties related to "lifespan" or "age" specifically for dogs.

[Tool]
Top 10 property alternatives:
1. life expectancy, also known as life span, lifespan (wd:P2250 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): average life expectancy for this group or species, duration
2. animal breed, also known as breed, sheep breed, horse breed, goat breed, duck breed (wd:P4743 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): subject item belongs to a specific group of domestic animals, generally given by association
3. has pet, also known as pet, keeps pet, owns pet (wd:P1429 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): pet that a person owns
4. longest observed lifespan, also known as maximum age, oldest recorded individual, oldest observed, maximum life span, highest observed lifespan (wd:P4214 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): age of the oldest specimen of a taxon for which the age can be verified
5. EE breed number, also known as breed number (wd:P303 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): breed identification number per the EE list of the breeds of fancy pigeons (ELFP)
6. mean lifetime (wd:P2645 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): inverse of exponential decay rate; half-life is ln(2) times this value, duration
7. hybrid of, also known as cultivar from, parent breed, parent cultivar, parent of this hybrid, parent of this hybrid, breed, or cultivar (wd:P1531 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): parent of this hybrid breed or cultivar
8. species kept, also known as plant taxon in botanical garden, resident animals, plant taxon in collection, resident animal species, rose varity in rose garden (wd:P1990 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): taxa, preferably species, present at a zoo, botanical garden, co...stitution. NOT specific animals, not for any geographic location, has part(s) of the class
9. taxon especially protected in area, also known as animal protected, plant protected, protected animal, protected plant, protected species (wd:P6569 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): species and other taxa especially protected in a area, whether s...ountries/subnational entities: use red lists properties instead.
10. service life (wd:P5069 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): product's total life in use from the point of sale to the point of discard

[Assistant]
The property "longest observed lifespan" (wd:P4214) looks promising as it can be used to find the age of the oldest recorded individuals of a taxon. We can use this property to find the oldest dogs and then identify the second oldest.

Let's start by finding the entity for "dog" and then use the "longest observed lifespan" property to find the oldest dogs.

[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 entity for "dog" is `wd:Q144`, which represents the domestic dog. Now, let's use the property "longest observed lifespan" (wd:P4214) to find the oldest dogs and then identify the second oldest.

We will write a SPARQL query to find the dogs with the longest observed lifespans and then sort them to find the second oldest.

[Tool] Got no rows and 2 columns

[Assistant]
It seems that the query did not return any results. This could be because the property "longest observed lifespan" (wd:P4214) is not commonly used for individual dogs in the Wikidata database. Instead, we might need to look for a list of the oldest dogs or find a different property that captures the age of individual dogs.

Let's try searching for a list of the oldest dogs again, but this time we will look for a more specific entity or property that might capture the age of individual dogs.

[Tool]
Top 10 entity alternatives:
1. List of sampled individuals (wd:Q113335655): scientific article published on 20 May 2011
2. list of dogs under breed specific legislation (wd:Q38758): Wikimedia list article
3. List of oldest people infected with COVID-19, also known as oldest people diagnosed with COVID-19 (wd:Q115959635)
4. Individual differences in the reactivity of dogs (wd:Q79484338): scientific article published on 01 October 1948
5. List of Disloyal Individuals (NAID 5709918) (wd:Q66204613): series in the National Archives and Records Administration's holdings
6. Oldest images of dogs show hunting, leashes (wd:Q49952104): scientific article published in November 2017
7. Hemodynamic effect of listerial hemolysin in dogs (wd:Q47685194): scientific article
8. Individual differences in the emotional level of dogs. (wd:Q51414828): scientific article published in December 1947
9. Evaluation of retinal images for identifying individual dogs (wd:Q53509958): scientific article published in December 2006
10. List of Individual Indian Monies Accounts (NAID 2570559) (wd:Q59932206): series in the National Archives and Records Administration's holdings

[Assistant]
Unfortunately, the search for "list of oldest individual dogs" did not yield a useful entity. Given this, we might need to take a different approach. We can try to find individual dogs and their ages, and then sort them to find the second oldest.

Let's search for individual dogs and their ages. We can use the property "date of death" (wdt:P570) and "date of birth" (wdt:P569) to calculate the age of individual dogs.

First, let's find some individual dogs and see if they have these properties.

[Tool]
Top 10 entity alternatives:
1. longest observed lifespan, also known as highest observed lifespan, maximum age, maximum life span, oldest observed, oldest recorded individual (wd:P4214): age of the oldest specimen of a taxon for which the age can be verified
2. World's oldest dog dies at age 20 (wd:Q17660624): Wikinews article
3. INDIVIDUAL SPECIFICITY OF DOG SERUM AND PLASMA (wd:Q81004665): scientific article published on 01 July 1942
4. dog, also known as Canis lupus familiaris, Canis familiaris, domestic dogs, domestic dog (wd:Q144): domestic animal
5. individual, also known as individual organism, individual person, individuals (wd:Q795052): individual person or organism
6. Dog (wd:Q755126): sign of Chinese zodiac
7. Dog (wd:Q104843787): 2022 film directed by Reid Carolin and Channing Tatum
8. Dongola Airport, also known as DOG, HSDN (wd:Q1431231): airport
9. Hurricane Dog, also known as Dog (wd:Q217669): Category 5 Atlantic hurricane in 1950
10. urelement, also known as atom, individual, ur-element (wd:Q1896657): object (concrete or abstract) that is not a set, but that may be an element of a set

[Assistant]
The search for "oldest individual dog" did not provide a direct list of individual dogs. However, we can try to find individual dogs and then use their birth and death dates to calculate their ages.

Let's search for individual dogs and see if they have properties for their birth and death dates.

We'll start by searching for individual dogs and then check if they have the properties `date of birth` (wdt:P569) and `date of death` (wdt:P570).

Let's search for individual dogs first.

[Tool]
Top 10 entity alternatives:
1. INDIVIDUAL SPECIFICITY OF DOG SERUM AND PLASMA (wd:Q81004665): scientific article published on 01 July 1942
2. dog, also known as Canis lupus familiaris, Canis familiaris, domestic dogs, domestic dog (wd:Q144): domestic animal
3. individual, also known as individual organism, individual person, individuals (wd:Q795052): individual person or organism
4. Dog (wd:Q755126): sign of Chinese zodiac
5. Dog (wd:Q104843787): 2022 film directed by Reid Carolin and Channing Tatum
6. Dongola Airport, also known as DOG, HSDN (wd:Q1431231): airport
7. Hurricane Dog, also known as Dog (wd:Q217669): Category 5 Atlantic hurricane in 1950
8. urelement, also known as atom, individual, ur-element (wd:Q1896657): object (concrete or abstract) that is not a set, but that may be an element of a set
9. Wax, also known as Dog, WAX (wd:Q624269): South Korean singer, singer
10. Dog, also known as D0g (wd:Q1211818): fictional character in Half-Life

[Assistant]
The search for "individual dog" did not yield specific individual dogs. Instead, let's try a more targeted approach by searching for specific names of famous oldest dogs. This might help us find individual dogs with their birth and death dates.

Let's search for some well-known oldest dogs, such as "Bluey" and "Butch" (two of the most famous oldest dogs in history).

### Search for "Bluey"
First, let's search for "Bluey" to see if we can find this specific dog and its age information.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( DISTINCT ?mountain ) AS ?count ) WHERE {
  ?mountain wdt:P31 wd:Q8502 .
  ?mountain wdt:P131 * wd:Q183 .
}

[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 examples.

[Tool]
Example 1:
Question:
How many missions does the Soyuz programme have?

SPARQL:
SELECT ( COUNT( DISTINCT ?uri ) AS ?c ) WHERE {
  ?uri wdt:P361 wd:Q207329
}

Using entities:
Soyuz programme (wd:Q207329): crewed spaceflight programme of the Soviet Union

Using properties:
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))

Example 2:
Question:
Which countries have more than two official languages?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q6256 .
  ?uri wdt:P37 ?language .
}
GROUP BY ?uri
HAVING ( COUNT( ?language ) > 2 )

Using entities:
country, also known as countries (wd:Q6256): distinct territorial body or political entity

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)
official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as wdt): language designated as official by this item, language used

Example 3:
Question:
Which city has the most inhabitants?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 / wdt:279 * wd:Q515 ; wdt:P1082 ?population .
}
ORDER BY DESC ( ?population )
LIMIT 1

Using entities:
city, also known as cities (wd:Q515): large human settlement

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

[Assistant] Based on these examples, we can infer that to count the number of mountains in Germany, we need to identify the entity for "mountain" and "Germany". We also need to find a property that links mountains to their location. Let's start by searching for the entity "mountain".

[Tool]
Top 10 entity alternatives:
1. mountain, also known as mt., mtn., mountains, mount (wd:Q8502): large natural elevation of the Earth's surface
2. Mountain (wd:Q1255792): American band
3. Mountain, also known as Mountain, ND, Mountain, North Dakota (wd:Q2032181): city in North Dakota, USA
4. Mountain, also known as Town of Mountain (wd:Q1885759): civil town in Oconto County, Wisconsin
5. The Mountain, also known as Mountain (wd:Q910112): 1956 film by Edward Dmytryk
6. ☶, also known as U+2636, gèn, TRIGRAM FOR MOUNTAIN, mountain, immobility (wd:Q2068902): trigram for mountain (U+2636), immobility, or stability: gen4, gèn, ken
7. The Mountain, also known as Mountain (wd:Q1192451): 1991 film by Markus Imhoof
8. 4-8-2, also known as 241, 2D1, 4/7, Mohawk, Mountain (wd:Q1473477): locomotive wheel arrangement
9. Mountain (wd:Q13422857): human settlement in Wisconsin, United States of America
10. Mountain (wd:Q29293936): 2014 simulation video game

[Assistant] The correct entity for "mountain" is `wd:Q8502`. Next, let's search for the entity "Germany".

[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 correct entity for "Germany" is `wd:Q183`. Now, we need to find a property that links mountains to their location. A common property for this purpose is "located in the administrative territorial entity" (`wdt:P131`). Let's verify this property.

[Tool]
Top 10 property alternatives:
1. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
2. located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
3. occupant, also known as tenant, resident, renter, occupiers, lessee (wd:P466 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): person or organization occupying property, used by
4. headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place
5. adjacent building, also known as next to, neighboring building, located next to, adjoining building (wd:P3032 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): building adjacent to the item, connects with
6. operating area, also known as province served, serves jurisdiction, serves geographic region, serves geographic area, serves area (wd:P2541 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): geographic area or jurisdiction an organisation or industry operates in, serves, or has responsibility for, location
7. set in environment, also known as set in location, takes place in, setting location, playing in, narrative set in (wd:P8411 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): environment (geographic feature, building type, etc.) the narrative work is set in, significant place, depicts
8. narrative location, also known as set in location, set in, setting, setting location, setting of work (wd:P840 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): the narrative of the work is set in this location, significant place, depicts
9. located in the present-day administrative territorial entity, also known as present-day administrative territorial entity, located in the current administrative territorial entity, located in the modern-day administrative territorial entity, located in the present-day administrative territorial entity, would today be located in administrative territorial entity (wd:P3842 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): the item was located in the territory of this present-day administrative unit; however the two did not at any point coexist in time, location, part of
10. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment

[Assistant]
The correct property for linking mountains to their location is `wdt:P131` ("located in the administrative territorial entity"). Now, we can construct a SPARQL query to count the number of mountains located in Germany.

Here is the initial SPARQL query:

```sparql
SELECT (COUNT(DISTINCT ?mountain) AS ?count)
WHERE {
  ?mountain wdt:P31 wd:Q8502 .  # ?mountain is an instance of mountain
  ?mountain wdt:P131* wd:Q183 . # ?mountain is located in Germany (or a sub-entity of Germany)
}
```

This query counts the number of distinct mountains that are instances of `wd:Q8502` and are located in Germany or any of its sub-entities. Let's execute this query to get the result.

[Tool]
Got 1 row and 1 column:
| count          |
| -------------- |
| 5394 (xsd:int) |

[Assistant]
The SPARQL query has returned the count of mountains located in Germany. According to the query, there are 5,394 mountains in Germany.

Here is the final SPARQL query and the answer:

```sparql
SELECT (COUNT(DISTINCT ?mountain) AS ?count)
WHERE {
  ?mountain wdt:P31 wd:Q8502 .  # ?mountain is an instance of mountain
  ?mountain wdt:P131* wd:Q183 . # ?mountain is located in Germany (or a sub-entity of Germany)
}
```

The answer to the question "How many mountains are located in Germany?" is **5,394**.

[Tool] Stopped generation process


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

United Fruit Company was founded on January 1, 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 examples.

[Tool]
Example 1:
Question:
What was the first Queen album?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q482994 .
  ?uri wdt:P175 wd:Q15862 .
  ?uri wdt:P577 ?date
}
ORDER BY ?date
LIMIT 1

Using entities:
Queen (wd:Q15862): British musical group; rock band
album, also known as full album, record album, music album, full-length album, audio album (wd:Q482994): grouping of album releases by an artist usually released at the ...racks but in different formats for consumption (digital, CD, LP)

Using properties:
performer, also known as actor, sung by, singer, recording by, recorded by (wd:P175 as wdt): actor, musician, band or other performer associated with this role or musical work, contributor to the creative work or subject
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)
publication date, also known as launched, published, publication time, publication, pubdate (wd:P577 as wdt): date or point in time when a work was first published or released, point in time

Example 2:
Question:
Give me the runtime of Toy Story.

SPARQL:
SELECT ?val WHERE {
  wd:Q171048 wdt:P2047 ?val .
}

Using entities:
Toy Story, also known as Toy Story 1 (wd:Q171048): 1995 American animated film

Using properties:
duration, also known as time length, timespan, time span, time interval, runtime (wd:P2047 as wdt): length of time of an event or process

Example 3:
Question:
What are the names of the Teenage Mutant Ninja Turtles?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P361 wd:Q1381762 .
}

Using entities:
Teenage Mutant Ninja Turtles, also known as Ninja Turtles, Teenage Mutant Hero Turtles, TMNT (wd:Q1381762): fictional team of four teenage anthropomorphic turtles

Using properties:
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] From the examples, we can see that to answer the question about when United Fruit Company was founded, we need to identify the entity for United Fruit Company and the property for the foundation date. Let's start by searching 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 correct entity for "United Fruit Company" is `wd:Q1771942`. Now, let's find the property for the foundation date. We can search for properties related to "founded" or "foundation date".

[Tool]
Top 10 property alternatives:
1. notable work, also known as artwork, wrote, writer of, works, work (wd:P800 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): notable scientific, artistic or literary work, or other work of significance among subject's works
2. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): time when an entity begins to exist; for date of official opening use P1619, start time
3. founded by, also known as starter, co-founded by, started by, institutor, instituted by (wd:P112 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): founder or co-founder of this organization, religion, place or entity, creator
4. location of formation, also known as place of incorporation, originates from, place of establishment, place of formation, place of foundation (wd:P740 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): location where a group or organization was formed, location of creation
5. service entry, also known as commissioned, time of service entry, service introduction, launch date, in service (wd:P729 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): date or point in time on which a piece or class of equipment entered operational service, start time
6. time of discovery or invention, also known as invented in, time of invention, time of discovery, invention time, invented on (wd:P575 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): date or point in time when the item was discovered or invented
7. discoverer or inventor, also known as inventor or discoverer, inventor, invented by, invented, introduced by (wd:P61 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): subject who discovered, first described, invented, or developed this discovery or invention or scientific hypothesis or theory
8. foundational text, also known as main text, treaty, organic law, founding document, establishing document (wd:P457 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): text through which an institution or object has been created or established
9. date of incorporation, also known as date incorporated, incorporated, incorporated on date, incorporation date, year incorporated (wd:P10786 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): date when company, organization or city was incorporated
10. subject named as, also known as established as, established form, established heading, named as, spelled as (wd:P1810 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): name by which a subject is recorded in a database, mentioned as a contributor of a work, or is referred to in a particular context, name

[Assistant]
The property for the foundation date is `wdt:P571` (inception). Now, let's construct a simple SPARQL query to find the foundation date of United Fruit Company.

```sparql
SELECT ?foundationDate WHERE {
  wd:Q1771942 wdt:P571 ?foundationDate .
}
```

I will execute this query to get the foundation date.

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

[Assistant]
The foundation date of United Fruit Company is January 1, 1899.

Here is the final SPARQL query and answer:

```sparql
SELECT ?foundationDate WHERE {
  wd:Q1771942 wdt:P571 ?foundationDate .
}
```

Answer: United Fruit Company was founded on January 1, 1899.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?discipline ?germanName WHERE {
  ?discipline wdt:P31 wd:Q11862829 ; rdfs:label ?germanName .
  FILTER ( LANG( ?germanName ) = 'de' ) .
  FILTER ( CONTAINS( LCASE( ?germanName ) , 'linguistik' ) )
}

Got 16 rows and 2 columns, showing the first 5 and last 5 rows below:
| discipline                             | germanName                  |
| -------------------------------------- | --------------------------- |
| Saami linguistics (wd:Q12718141)       | Samische Linguistik (de)    |
| general linguistics (wd:Q14357850)     | Allgemeine Linguistik (de)  |
| sociolinguistics (wd:Q160845)          | Soziolinguistik (de)        |
| computational linguistics (wd:Q182557) | Computerlinguistik (de)     |
| historical linguistics (wd:Q190375)    | historische Linguistik (de) |
| ...                                    | ...                         |
| applied linguistics (wd:Q321249)       | angewandte Linguistik (de)  |
| wd:Q357196                             | Rechtslinguistik (de)       |
| descriptive linguistics (wd:Q777864)   | deskriptive Linguistik (de) |
| ethnolinguistics (wd:Q853085)          | Ethnolinguistik (de)        |
| interlinguistics (wd:Q856574)          | Interlinguistik (de)        |

The German names of academic disciplines containing 'linguistik' are: Samische Linguistik, Allgemeine Linguistik, Soziolinguistik, Computerlinguistik, Historische Linguistik, Angewandte Linguistik, Rechtslinguistik, Deskriptive Linguistik, Ethnolinguistik, Interlinguistik.

[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 examples.

[Tool]
Example 1:
Question:
In which countries do people speak Japanese?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 wd:Q6256 .
  ?uri wdt:P37 wd:Q5287 .
}

Using entities:
Japanese, also known as Japanese language, Japanesic (wd:Q5287): language spoken in East Asia
country, also known as countries (wd:Q6256): distinct territorial body or political entity

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)
official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as wdt): language designated as official by this item, language used

Example 2:
Question:
Give me the birth place of Frank Sinatra.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q40912 wdt:P19 ?uri
}

Using entities:
Frank Sinatra, also known as Old Blue Eyes, Ol' Blue Eyes, Sinatra, Francis Albert Sinatra (wd:Q40912): American singer and actor (1915–1998), television actor, film producer, film director, voice actor, film actor, director, producer, singer, actor

Using properties:
place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt): most specific known birth location of a person, animal or fictional character, location

Example 3:
Question:
Which movies starring Brad Pitt were directed by Guy Ritchie?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?type wdt:P279 * wd:Q11424 .
  ?uri wdt:P31 ?type ; wdt:P161 wd:Q35332 ; wdt:P57 wd:Q192990 .
}

Using entities:
film, also known as cinematic work, moving picture, movie, motion pictures, motion picture (wd:Q11424): sequence of images that give the impression of movement, stored on film stock
Guy Ritchie, also known as Guy Stuart Ritchie, Guy Stewart Ritchie (wd:Q192990): English filmmaker, film producer, film director, screenwriter, entrepreneur, director, judoka
Brad Pitt, also known as William Bradley Pitt, Brad Jolie-Pitt (wd:Q35332): American actor and filmmaker (born 1963), television producer, executive producer, television actor, film producer, film director, voice actor, film actor, producer, director, model, actor

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as wdt): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
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)
director, also known as film director, movie director, game director, directed by (wd:P57 as wdt): director(s) of film, TV-series, stageplay, video game or similar, contributor to the creative work or subject, creator

[Assistant] Based on the examples, we can see how to structure our SPARQL query. We need to identify the entities and properties relevant to our question. Let's start by searching for the entity representing "academic discipline" and the property that would link it to its German name.

[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 top result, "academic discipline" (wd:Q11862829), seems to be the most relevant entity for our query. Next, let's search for the property that links an academic discipline to its German name.

[Tool]
Top 10 property alternatives:
1. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): label for the items in their official language  or their original language, name
2. 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 prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): language associated with this creative work (such as books, show...guage" (P103) and "languages spoken, written or signed" (P1412))
3. Deutsche Biographie (GND) ID, also known as DtBio identifier, Deutsche Biographie (GND) identifier, German Biography identifier, German Biography ID, DtBio ID (wd:P7902 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): GND identifier for an item in the Deutsche Biographie, GND ID
4. name in native language, also known as native name (wd:P1559 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): name of a person in their native language, name
5. Digital Dictionary of Surnames in Germany ID, also known as DFD ID, DFD-ID (wd:P6597 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): ID of corresponding entry in the DFD online dictionary of family names
6. given name, also known as name, proper name, personal name, middle name, forename (wd:P735 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): first name or another given name of this person; values used with the property should not link disambiguations nor family names, name
7. author last names, also known as author last name, surnames, surname, last names, last name (wd:P9688 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): qualifier to provide string representation of family or primary ...presented in a bibliographic reference file (for example BibTeX), family name
8. family name, also known as clan name, last name, surname (wd:P734 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): part of full name of person, name
9. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): full name of a person at birth, if different from their current, generally used name, name
10. author given names, also known as given name, given names, first name, author first names, author first name (wd:P9687 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): qualifier for string representation of given or secondary sortin...presented in a bibliographic reference file (for example BibTeX), given name

[Assistant] The property "native label" (wd:P1705) seems to be the most relevant for getting the name of an entity in its original or native language. However, we need to ensure that this property is used specifically for German names. Let's check if this property is used for German names by listing some examples.

[Tool]
Got 131,072 rows and 3 columns, showing the first 10 rows below:
| subject                | property                 | object                                   |
| ---------------------- | ------------------------ | ---------------------------------------- |
| Nigeria (wd:Q1033)     | native label (wdt:P1705) | Naigeria (ig)                            |
| Libya (wd:Q1016)       | native label (wdt:P1705) | دولة ليبيا (ar)                          |
| Sudan (wd:Q1049)       | native label (wdt:P1705) | جمهورية السودان (ar)                     |
| Morocco (wd:Q1028)     | native label (wdt:P1705) | المغرب (ar)                              |
| Somalia (wd:Q1045)     | native label (wdt:P1705) | Jamhuuriyadda Federaalka Soomaaliya (so) |
| Namibia (wd:Q1030)     | native label (wdt:P1705) | Republic of Namibia (en)                 |
| Madagascar (wd:Q1019)  | native label (wdt:P1705) | Repoblikan'i Madagaskar (mg)             |
| Ivory Coast (wd:Q1008) | native label (wdt:P1705) | République de Côte d'Ivoire (fr)         |
| Cameroon (wd:Q1009)    | native label (wdt:P1705) | République du Cameroun (fr)              |
| Uganda (wd:Q1036)      | native label (wdt:P1705) | Jamhuri ya Uganda (sw)                   |
| ...                    | ...                      | ...                                      |

[Assistant] The results show that the "native label" property (wdt:P1705) is used to store the name of an entity in its native language, but not specifically in German. We need to find a property that specifically provides the German name of an entity. Let's try searching for a property that might be used for German names.

[Tool]
Top 10 property alternatives:
1. 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 prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): language associated with this creative work (such as books, show...guage" (P103) and "languages spoken, written or signed" (P1412))
2. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): label for the items in their official language  or their original language, name
3. Deutsche Biographie (GND) ID, also known as DtBio identifier, Deutsche Biographie (GND) identifier, German Biography identifier, German Biography ID, DtBio ID (wd:P7902 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): GND identifier for an item in the Deutsche Biographie, GND ID
4. German municipality key, also known as Gemeindeschlüssel, municipality key (Germany) (wd:P439 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): identifier for municipalities and independent towns in Germany
5. Digital Dictionary of Surnames in Germany ID, also known as DFD ID, DFD-ID (wd:P6597 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): ID of corresponding entry in the DFD online dictionary of family names
6. named after, also known as toponym, namesake, named in honor of, named for, etymology (wd:P138 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): entity or event that inspired the subject's name, or namesake (i...fier "applies to name" (P5168) can be used to indicate which one
7. OWID Deutsches Fremdwörterbuch ID, also known as German Foreign Dictionary identifier, OWID German Foreign Dictionary identifier, OWID German Foreign Dictionary ID, OWID Fremdwörterbuch identifier, OWID Fremdwörterbuch ID (wd:P11521 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): identifier for a lexeme in the German dictionary of foreign words at owid.de
8. name in native language, also known as native name (wd:P1559 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): name of a person in their native language, name
9. identifier in a register in Germany (wd:P12012 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): numeric identifier in a register located in Germany
10. troponym of, also known as definition by troponym, troponym (wd:P5975 as prv/wdtn/ps/pq/prn/pr/p/wdt/psn/pqv/pqn/psv): this verb describes more narrowly the action of the more general verb used as value, hyperonym

[Assistant]
None of the properties listed seem to directly provide the German name of an entity. However, we can use the `rdfs:label` property with a language tag to get the German name. Let's try constructing a SPARQL query to find the German names of academic disciplines containing "linguistik".

First, we need to find academic disciplines that contain "linguistik" in their labels. Then, we will retrieve their German names using `rdfs:label`.

Let's start by finding the academic disciplines containing "linguistik" in their labels.

[Tool]
Got 16 rows and 1 column, showing the first 5 and last 5 rows below:
| discipline                             |
| -------------------------------------- |
| Saami linguistics (wd:Q12718141)       |
| general linguistics (wd:Q14357850)     |
| sociolinguistics (wd:Q160845)          |
| computational linguistics (wd:Q182557) |
| historical linguistics (wd:Q190375)    |
| ...                                    |
| applied linguistics (wd:Q321249)       |
| wd:Q357196                             |
| descriptive linguistics (wd:Q777864)   |
| ethnolinguistics (wd:Q853085)          |
| interlinguistics (wd:Q856574)          |

[Assistant]
We have successfully found the academic disciplines containing "linguistik" in their German labels. Now, let's refine the query to include the German names of these disciplines in the results.

Here is the final SPARQL query:

```sparql
SELECT ?discipline ?germanName WHERE {
  ?discipline wdt:P31 wd:Q11862829 ;
              rdfs:label ?germanName .
  FILTER(LANG(?germanName) = 'de') .
  FILTER(CONTAINS(LCASE(?germanName), 'linguistik'))
}
```

This query will return the IRIs of the academic disciplines and their German names.

Let's execute this query to get the final results.

[Tool]
Got 16 rows and 2 columns, showing the first 5 and last 5 rows below:
| discipline                             | germanName                  |
| -------------------------------------- | --------------------------- |
| Saami linguistics (wd:Q12718141)       | Samische Linguistik (de)    |
| general linguistics (wd:Q14357850)     | Allgemeine Linguistik (de)  |
| sociolinguistics (wd:Q160845)          | Soziolinguistik (de)        |
| computational linguistics (wd:Q182557) | Computerlinguistik (de)     |
| historical linguistics (wd:Q190375)    | historische Linguistik (de) |
| ...                                    | ...                         |
| applied linguistics (wd:Q321249)       | angewandte Linguistik (de)  |
| wd:Q357196                             | Rechtslinguistik (de)       |
| descriptive linguistics (wd:Q777864)   | deskriptive Linguistik (de) |
| ethnolinguistics (wd:Q853085)          | Ethnolinguistik (de)        |
| interlinguistics (wd:Q856574)          | Interlinguistik (de)        |

[Assistant]
The SPARQL query has successfully returned the German names of academic disciplines containing "linguistik". Here are the results:

| Discipline                             | German Name                  |
| -------------------------------------- | --------------------------- |
| Saami linguistics (wd:Q12718141)       | Samische Linguistik (de)    |
| General linguistics (wd:Q14357850)     | Allgemeine Linguistik (de)  |
| Sociolinguistics (wd:Q160845)          | Soziolinguistik (de)        |
| Computational linguistics (wd:Q182557) | Computerlinguistik (de)     |
| Historical linguistics (wd:Q190375)    | Historische Linguistik (de) |
| Applied linguistics (wd:Q321249)       | Angewandte Linguistik (de)  |
| Legal linguistics (wd:Q357196)         | Rechtslinguistik (de)       |
| Descriptive linguistics (wd:Q777864)   | Deskriptive Linguistik (de) |
| Ethnolinguistics (wd:Q853085)          | Ethnolinguistik (de)        |
| Interlinguistics (wd:Q856574)          | Interlinguistik (de)        |

These are the German names of academic disciplines containing "linguistik".

Here is the final SPARQL query and the answer:

```sparql
SELECT ?discipline ?germanName WHERE {
  ?discipline wdt:P31 wd:Q11862829 ;
              rdfs:label ?germanName .
  FILTER(LANG(?germanName) = 'de') .
  FILTER(CONTAINS(LCASE(?germanName), 'linguistik'))
}
```

The German names of academic disciplines containing "linguistik" are:
- Samische Linguistik
- Allgemeine Linguistik
- Soziolinguistik
- Computerlinguistik
- Historische Linguistik
- Angewandte Linguistik
- Rechtslinguistik
- Deskriptive Linguistik
- Ethnolinguistik
- Interlinguistik

[Tool] Stopped generation process


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

Brit Bennett was born in 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 examples.

[Tool]
Example 1:
Question:
When did Muhammad die?

SPARQL:
SELECT ?date WHERE {
  wd:Q9458 wdt:P570 ?date .
}

Using entities:
Muhammad, also known as Mohammed, Muhammad ibn Abdullah, Mohammad, Mahomet, Prophet Muhammad (wd:Q9458): founder and main prophet of Islam (c. 570–632), military leader, politician, consignor, merchant, preacher, prophet, herder

Using properties:
date of death, also known as DOD, deathdate, died, died on, year of death (wd:P570 as wdt): dissolved, abolished or demolished date, date on which the subject died, end time

Example 2:
Question:
Who created Goofy?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q111135 wdt:P170 ?uri .
}

Using entities:
Goofy, also known as Dippy Dawg, George Geef, Goofy Goof (wd:Q111135): Disney cartoon character

Using properties:
creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as wdt): maker of this creative work or other object (where no more specific property exists)

Example 3:
Question:
Which U.S. state has been admitted latest?

SPARQL:
SELECT ?uri WHERE {
  ?uri wdt:P31 wd:Q35657 .
  ?uri wdt:P571 ?date
}
ORDER BY DESC ( ?date )
LIMIT 1

Using entities:
U.S. state, also known as U.S. states, US state, USA state, U.S.A. state, United States states (wd:Q35657): constituent political entity of the United States of America

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)
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] Based on the examples, we need to identify the author of "The Vanishing Half" and then find their birth year. Let's first search for the book "The Vanishing Half" in Wikidata.

[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 correct entity for "The Vanishing Half" is `wd:Q98476957`. Now, let's find the author of this book.

[Tool]
Top 10 property alternatives:
1. 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
2. publisher, also known as video game publisher, software publisher, comic book publisher, sheet music publisher, publishing house (wd:P123 as p/wdt): organization or person responsible for publishing books, periodicals, printed music, podcasts, games or software
3. publication date, also known as launched, published, publication time, publication, pubdate (wd:P577 as p/wdt): date or point in time when a work was first published or released, point in time
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. country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as p/wdt): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country
7. form of creative work, also known as work type, work form, type of work, artform, type of reference work (wd:P7937 as p/wdt): structure of a creative work
8. 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))
9. 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)

No other items found

[Assistant] The property for the author of the book is `wdt:P50`. Let's use this property to find the author of "The Vanishing Half".

[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, let's find the birth year of Brit Bennett.

[Tool]
Top 10 property alternatives:
1. 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
2. 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
3. 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
4. given name, also known as name, proper name, personal name, middle name, forename (wd:P735 as p/wdt): first name or another given name of this person; values used with the property should not link disambiguations nor family names, name
5. occupation, also known as job, work, vocation, profession, employment (wd:P106 as p/wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
6. DDB person (GND) ID, also known as DDB ID, DDB person ID (wd:P13049 as p/wdt): identifier for a person in the Deutsche Digitale Bibliothek (DDB); identifier same as the person's GND ID, GND ID
7. X (Twitter) username, also known as twitter.com/, X username, X handle, x.com/, X account (wd:P2002 as p/wdt): username on X (formerly Twitter); do not include the '@' symbol, website username or ID
8. 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)
9. 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)
10. National Library of Lithuania ID, also known as LIH ID, NLL ID (wd:P7699 as p/wdt): authority id at the National Library of Lithuania, part of VIAF (code LIH)

No other items found

[Assistant] The property for the date of birth is `wdt:P569`. Let's use this property to find the birth year of Brit Bennett.

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

[Assistant]
Brit Bennett was born in the year 1990.

Here is the final SPARQL query and answer:

```sparql
SELECT ?birthYear WHERE {
  wd:Q27449519 wdt:P569 ?birthYear .
}
```

Answer: Brit Bennett was born in 1990.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?country WHERE {
  wd:Q327818 wdt:P17 ?country .
}

Got 1 row and 1 column:
| country           |
| ----------------- |
| Germany (wd:Q183) |

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 examples.

[Tool]
Example 1:
Question:
What is Donald Trump's main business?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P488 wd:Q22686 ; wdt:P31 / wdt:P279 * wd:Q4830453 . MINUS {
    ?uri wdt:P576 ?closed
  }
}

Using entities:
Donald Trump, also known as President Donald Trump, President Donald J. Trump, President Trump, President Donald J Trump, Trump (wd:Q22686): president of the United States (2017–2021, 2025–present), real estate entrepreneur, chief executive officer, television producer, business magnate, businessperson, game show host, film producer, entrepreneur, politician, merchant, investor, writer, actor
business (wd:Q4830453): organization undertaking commercial, industrial, or professional activity

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)
chairperson, also known as dean, headed by, leader, president, chairwoman (wd:P488 as wdt): presiding member of an organization, group or body, director / manager, significant person
dissolved, abolished or demolished date, also known as ended, publication end date, final issue, date repealed, final year (wd:P576 as wdt): point in time at which the subject (organisation, building) ceas...g equipment,  "discontinued date" (P2669) for stopping a product, end time

Example 2:
Question:
In what city is the Heineken brewery?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q854383 wdt:P176 / wdt:P159 ?uri .
}

Using entities:
Heineken, also known as Heineken Lager Beer, Heineken Pilsener (wd:Q854383): pale lager beer by the Dutch brewing company Heineken International

Using properties:
headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as wdt): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place
manufacturer, also known as manufactured by, provider, provided by, product of, producer (wd:P176 as wdt): (main or final) manufacturer or producer of this product

Example 3:
Question:
Who has Tom Cruise been married to?

SPARQL:
SELECT DISTINCT ?o1 WHERE {
  wd:Q37079 wdt:P26 ?o1 .
}

Using entities:
Tom Cruise, also known as Thomas Cruise Mapother IV (wd:Q37079): American actor and producer (born 1962), stunt performer, aircraft pilot, film producer, film director, screenwriter, film actor, producer, director, writer, actor

Using properties:
spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as wdt): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative

[Assistant] Based on the examples, we need to identify the entity for "Kandahar-downhill" and then find the country it is located in. Let's start by searching for the entity "Kandahar-downhill".

[Tool] No entity items found

[Assistant] It seems that "Kandahar-downhill" does not exist as an entity in Wikidata. However, it might be a specific event or location related to skiing or snowboarding. Let's try to search for "Kandahar downhill" to see if we can find a relevant entity.

[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] From the search results, the most relevant entity appears to be "Kandahar Downhill Piste" (wd:Q327818), which is a ski course in Bavaria, Germany. Let's confirm this by checking the details of this entity.

[Tool]
Got 36 rows and 3 columns, showing the first 10 rows below:
| subject                              | property                                                    | object                                                                                |
| ------------------------------------ | ----------------------------------------------------------- | ------------------------------------------------------------------------------------------ |
| Kandahar Downhill Piste (wd:Q327818) | instance of (wdt:P31)                                       | piste (wd:Q1281105)                                                                        |
| Kandahar Downhill Piste (wd:Q327818) | country (wdt:P17)                                           | Germany (wd:Q183)                                                                          |
| Kandahar Downhill Piste (wd:Q327818) | located in the administrative territorial entity (wdt:P131) | Garmisch-Partenkirchen (wd:Q127043)                                                        |
| Kandahar Downhill Piste (wd:Q327818) | coordinate location (wdt:P625)                              | POINT(11.063100 47.470800) (geo:wktLiteral)                                                |
| Kandahar Downhill Piste (wd:Q327818) | Commons category (wdt:P373)                                 | Kandahar-Abfahrt Garmisch                                                                  |
| Kandahar Downhill Piste (wd:Q327818) | image (wdt:P18)                                             | <http://commons.wikimedia.org/wiki/Special:FilePath/Snowy%20mountains%20in%20Kandahar.jpg> |
| Kandahar Downhill Piste (wd:Q327818) | Google Knowledge Graph ID (wdtn:P2671)                      | <http://g.co/kg/g/120ldlyz>                                                                |
| Kandahar Downhill Piste (wd:Q327818) | schema:description                                          | laskettelurinne Saksassa (fi)                                                              |
| Kandahar Downhill Piste (wd:Q327818) | schema:name                                                 | Kandahar (it)                                                                              |
| Kandahar Downhill Piste (wd:Q327818) | rdf:type                                                    | wikibase:Item                                                                              |
| ...                                  | ...                                                         | ...                                                                                |

[Assistant]
The entity "Kandahar Downhill Piste" (wd:Q327818) is indeed a ski course located in Germany. The property `wdt:P17` (country) confirms that it is in Germany.

Now, let's construct a SPARQL query to retrieve the country where the Kandahar Downhill Piste is located.

```sparql
SELECT ?country WHERE {
  wd:Q327818 wdt:P17 ?country .
}
```

Let's execute this query to confirm the result.

[Tool]
Got 1 row and 1 column:
| country           |
| ----------------- |
| Germany (wd:Q183) |

[Assistant]
The SPARQL query confirms that the Kandahar Downhill Piste is located in Germany.

Therefore, the answer to the question "In what country is the Kandahar-downhill?" is:

Germany

Here is the final SPARQL query:

```sparql
SELECT ?country WHERE {
  wd:Q327818 wdt:P17 ?country .
}
```

And the answer:

Germany

[Tool] Stopped generation process