PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
ASK WHERE {
  ?movie wdt:P57 wd:Q55400 ; wdt:P166 wd:Q1604012 .
}

[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 Oscars did all the movies directed by Hayao Miyazaki combined win?

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

[Tool]
Example 1:
Question:
Which movies did Kurosawa direct?

SPARQL:
SELECT DISTINCT * WHERE {
  ?uri wdt:P57 wd:Q8006 .
}

Using entities:
Akira Kurosawa, also known as Kurosawa Akira, Kurosawa (wd:Q8006): Japanese filmmaker (1910–1998), film producer, film director, screenwriter, film editor, producer, director, painter, writer

Using properties:
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

Example 2:
Question:
How many films did Leonardo DiCaprio star in?

SPARQL:
SELECT ( COUNT( DISTINCT ?uri ) AS ?c ) WHERE {
  ?uri wdt:P31 wd:Q11424 ; wdt:P161 wd:Q38111 .
}

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
Leonardo DiCaprio (wd:Q38111): American actor and film producer (born 1974), television actor, environmentalist, film producer, screenwriter, stage actor, film actor, 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
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 3:
Question:
Give me all movies directed by Francis Ford Coppola.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?uri wdt:P31 / wdt:P279 * wd:Q11424 ; wdt:P57 wd:Q56094 .
}

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
Francis Ford Coppola, also known as Francis Coppola (wd:Q56094): American filmmaker, executive producer, businessperson, film producer, film director, screenwriter, film editor, winegrower, film actor, producer, director, composer, writer, actor

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)
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 need to identify the movies directed by Hayao Miyazaki and then count the number of Oscars these movies won. Let's first find the entity for Hayao Miyazaki.

[Tool]
Top 10 entity alternatives:
1. Hayao Miyazaki, also known as Miyazaki Hayao, Tsutomu Teruki (wd:Q55400): Japanese animator, film director, and mangaka (born 1941), mechanical designer, character designer, animation director, environmentalist, film producer, film director, comics artist, screenwriter, film editor, illustrator, animator, director, lyricist, mangaka
2. Hayao Miyazaki (wd:Q11454632): Japanese baseball player, baseball player
3. Hayao Miyazaki bibliography (wd:Q130265400)
4. Never-Ending Man: Hayao Miyazaki (wd:Q42859983): 2016 film
5. Hayao Miyazaki's Daydream Data Notes, also known as Miyazaki Hayao no Zassō Nōto (wd:Q888819): collection of manga and illustrated writings by Hayao Miyazaki
6. Hayao Miyazaki and the Heron (wd:Q130287351): 2024 documentary film
7. Miyazaki Prefecture, also known as Miyazaki (wd:Q130300): prefecture of Japan
8. Miyazaki (wd:Q204308): city in Miyazaki prefecture, Japan
9. 6905 Miyazaki, also known as Miyazaki (wd:Q717728): asteroid
10. Hayao (wd:Q60786238): Japanese male given name (はやお)

[Assistant] The correct entity for Hayao Miyazaki is `wd:Q55400`. Next, let's find the movies he directed.

[Tool]
Top 10 entity alternatives:
1. Hayao Miyazaki, also known as Miyazaki Hayao, Tsutomu Teruki (wd:Q55400): Japanese animator, film director, and mangaka (born 1941), mechanical designer, character designer, animation director, environmentalist, film producer, film director, comics artist, screenwriter, film editor, illustrator, animator, director, lyricist, mangaka
2. Gorō Miyazaki, also known as Gorou Miyazaki, Goro Miyazaki (wd:Q459078): Japanese anime director, film director, screenwriter, architect
3. Hidetaka Miyazaki, also known as Miyazaki Hidetaka (wd:Q11454590): Japanese video game designer and executive (born 1974), representative director, video game designer, video game writer, creative director
4. Daisuke Miyazaki (wd:Q11454239): Japanese film director and screenwriter, film director, screenwriter
5. Hikari, also known as Mitsuyo Miyazaki (wd:Q110403014): Japanese film director, film producer, film director
6. Nagisa Miyazaki (wd:Q11454153): character designer, Japanese animator, film director, animator
7. Jun Miyazaki (wd:Q56490130): film director

No other items found

No literal items found

[Assistant]
It seems that the search did not return the specific movies directed by Hayao Miyazaki. Let's directly query for the movies he directed using his entity ID `wd:Q55400`.

We will use the property `wdt:P57` to find the movies directed by Hayao Miyazaki.

[Tool]
Got 34 rows and 1 column, showing the first 5 and last 5 rows below:
| movie                                            |
| ------------------------------------------------ |
| Kujiratori (wd:Q1083425)                         |
| Koro no Daisanpo (wd:Q1083462)                   |
| Sherlock Hound (wd:Q1150791)                     |
| Piyopiyo Baba (wd:Q122390248)                    |
| Tacolator (wd:Q122390707)                        |
| ...                                              |
| Sora Iro no Tane (wd:Q67176601)                  |
| Future Boy Conan (wd:Q697616)                    |
| Mizugumo Monmon (wd:Q735713)                     |
| The Wind Rises (wd:Q888131)                      |
| Nausicaä of the Valley of the Wind (wd:Q8885676) |

[Assistant]
We have successfully retrieved the movies directed by Hayao Miyazaki. Now, we need to find out how many Oscars these movies have won. We will use the property `wdt:P166` to find the awards received by these movies and filter for the Oscar award.

First, let's find the entity for the Oscar award.

[Tool]
Top 10 entity alternatives:
1. Ophir Award, also known as Ofir Award, Israeli Oscar award, Ophir Prize, Ofir Prize (wd:Q1604012): Israeli film award
2. Oscar Mathisen Award, also known as Oscar Mathisen Memorial Award, Oscar Mathisen Memorial Trophy, Skating Oscar (wd:Q573079): sports award
3. Oscar Hammerstein Award (wd:Q7106027): American arts award
4. Oscar-Gans Award, also known as Oscar-Gans-Award (wd:Q128213997): award
5. The JGHE Oscar awards (wd:Q126248623): scholarly article
6. OSCAR AWARDS 1969 (NAID 132063) (wd:Q67651068): item in the National Archives and Records Administration's holdings
7. Oscar S. Causey Award: James V. Hoffman (wd:Q126825631): scholarly article
8. SIDNEY POITIER OSCAR AWARDS (NAID 130788) (wd:Q67644879): item in the National Archives and Records Administration's holdings
9. O, also known as letter 15, o, O, Oscar (wd:Q9941): letter of the Latin alphabet
10. Oscar, also known as Oscar dos Santos Emboaba Junior, Oscar dos Santos Emboaba Júnior (wd:Q19497): Brazilian association football player (born 1991), association football player

[Assistant]
The correct entity for the Oscar award is `wd:Q1604012`. Now, let's query the movies directed by Hayao Miyazaki and check if they have won the Oscar award.

We will use the property `wdt:P166` to find the awards received by these movies and filter for the Oscar award.

[Tool] Got no rows and 2 columns

[Assistant]
It appears that none of the movies directed by Hayao Miyazaki have won the Oscar award according to the data in Wikidata. To confirm this, we can use an ASK query to check if any of the movies directed by Hayao Miyazaki have won the Oscar award.

Let's construct and execute the ASK query.

[Tool] False

[Assistant]
The ASK query confirms that none of the movies directed by Hayao Miyazaki have won the Oscar award.

Therefore, the answer to the question "How many Oscars did all the movies directed by Hayao Miyazaki combined win?" is 0.

Here is the final SPARQL query and answer:

```sparql
ASK WHERE { ?movie wdt:P57 wd:Q55400 ; wdt:P166 wd:Q1604012 . }
```

Answer: False (which means 0 Oscars).

[Tool] Stopped generation process


SELECT ( YEAR( NOW () ) - 1928 AS ?minAge ) ( YEAR( NOW () ) - 1945 AS ?maxAge ) WHERE {
}

People belonging to the Silent Generation are currently between 80 and 97 years old.

[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] People of what age belong to the Silent Generation ?

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

[Tool]
Example 1:
Question:
List the children of Margaret Thatcher.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q7416 wdt:P40 ?uri .
}

Using entities:
Margaret Thatcher, also known as Margaret Hilda Thatcher, Margaret Roberts, Margaret Hilda Roberts, Mrs. T, Mrs. Thatcher (wd:Q7416): British stateswoman and prime minister (1925–2013), research scientist, business executive, autobiographer, statesperson, politician, barrister, chemist

Using properties:
child, also known as has son, kids, mother of, kid, issue (wd:P40 as wdt): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative

[Assistant]
None of the examples provided seem to directly relate to the concept of the Silent Generation or age groups. However, we can infer that we need to look for the definition of the Silent Generation and possibly the typical age range associated with it.

I will first search for the entity "Silent Generation" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Silent Generation, also known as Lucky Few Generation (wd:Q3044693): cohort succeeding the Greatest Generation, born from 1928 to 1945
2. The Silent Generation (wd:Q7764217): album by The Dimes
3. The Silent Generation (wd:Q112669391): 2020 film
4. Silent zone generation (wd:Q124647370): US patent 11495205
5. Winter’s Children - The Silent Generation (wd:Q85671231): 2005 documentary film by Jens Schanze
6. China Witness, also known as China Witness: Voices from a Silent Generation. (wd:Q113681807): History of China in the 20th century
7. Comparison of Silent Navigator Waveform Generation Methods (wd:Q92381831): scientific article published on 30 May 2019
8. AI-assisted sound effect generation for silent video (wd:Q122763863): US patent 11381888
9. From the silent generation to the involved generation (wd:Q40372593): scientific article published on April 1, 1978
10. Retirement income decisions: the silent generation speaks. (wd:Q40344803): scientific article published on January 2005

[Assistant]
The top result, `wd:Q3044693`, seems to be the correct entity for the Silent Generation. Now, let's check the properties associated with this entity to see if there is any information about the age range of people belonging to this generation.

I will list the triples for this entity to gather more information.

[Tool]
Got 113 rows and 3 columns, showing the first 10 rows below:
| subject                         | property                                              | object                                                                                |
| ------------------------------- | ----------------------------------------------------- | -------------------------------------------------------------------------------------- |
| Silent Generation (wd:Q3044693) | instance of (wdt:P31)                                 | cultural generation of western society (wd:Q15925549)                                  |
| Silent Generation (wd:Q3044693) | image (wdt:P18)                                       | <http://commons.wikimedia.org/wiki/Special:FilePath/Girl%20listening%20to%20radio.gif> |
| Silent Generation (wd:Q3044693) | subclass of (wdt:P279)                                | Great Power Saeculum (wd:Q113207359)                                                   |
| Silent Generation (wd:Q3044693) | location (wdt:P276)                                   | worldwide (wd:Q13780930)                                                               |
| Silent Generation (wd:Q3044693) | follows (wdt:P155)                                    | Greatest Generation (wd:Q27995878)                                                     |
| Silent Generation (wd:Q3044693) | followed by (wdt:P156)                                | Baby Boomers (wd:Q797819)                                                              |
| Silent Generation (wd:Q3044693) | Freebase ID (wdt:P646)                                | /m/02zksw                                                                              |
| Silent Generation (wd:Q3044693) | Quora topic ID (wdt:P3417)                            | Silent-Generation                                                                      |
| Silent Generation (wd:Q3044693) | Encyclopædia Britannica Online ID (wdt:P1417)         | topic/Silent-Generation                                                                |
| Silent Generation (wd:Q3044693) | Encyclopedia of China (Third Edition) ID (wdt:P10565) | 125938                                                                                |
| ...                             | ...                                                   | ...                                                                                |

[Assistant]
From the triples, we can see that the Silent Generation is a cultural generation of Western society, and it follows the Greatest Generation and is followed by the Baby Boomers. However, the specific age range is not directly provided in these triples.

To find the age range, we can search for properties related to the birth years or age range of the Silent Generation. Let's search for properties of the Silent Generation that might provide this information.

I will search for properties related to "age" or "birth year" for the Silent Generation.

[Tool]
Top 10 property alternatives:
1. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
2. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
3. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as p/wdt): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
4. Freebase ID, also known as Freebase, MID, Freebase identifier, FID (wd:P646 as p/wdt): identifier for a page in the Freebase database. Format: "/m/0" f...r IDs starting with "/g/", use Google Knowledge Graph ID (P2671)
5. followed by, also known as continued as, then, successor, succeeded by, sequel is (wd:P156 as p/wdt): immediately following item in a series of which the subject is a...een replaced, e.g. political offices, use "replaced by" (P1366)]
6. subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as p/wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
7. follows, also known as prev, successor to, succeeds to, succeeds, split from (wd:P155 as p/wdt): immediately prior item in a series of which the subject is a par... preceding item, e.g. political offices, use "replaces" (P1365)]
8. Encyclopædia Britannica Online ID, also known as Encyclopaedia Britannica Online ID, Encyclopedia Britannica Online ID, EBID, EB ID, Britannica online ID (wd:P1417 as p/wdt): identifier for an article in the online version of Encyclopædia Britannica

No other items found

[Assistant]
The search for properties related to "age" did not yield any useful results. Let's try searching for properties related to "birth year" instead.

I will search for properties related to "birth year" for the Silent Generation.

[Tool]
Top 10 property alternatives:
1. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
2. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
3. follows, also known as prev, successor to, succeeds to, succeeds, split from (wd:P155 as p/wdt): immediately prior item in a series of which the subject is a par... preceding item, e.g. political offices, use "replaces" (P1365)]
4. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as p/wdt): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
5. followed by, also known as continued as, then, successor, succeeded by, sequel is (wd:P156 as p/wdt): immediately following item in a series of which the subject is a...een replaced, e.g. political offices, use "replaced by" (P1366)]
6. Encyclopædia Britannica Online ID, also known as Encyclopaedia Britannica Online ID, Encyclopedia Britannica Online ID, EBID, EB ID, Britannica online ID (wd:P1417 as p/wdt): identifier for an article in the online version of Encyclopædia Britannica
7. Freebase ID, also known as Freebase, MID, Freebase identifier, FID (wd:P646 as p/wdt): identifier for a page in the Freebase database. Format: "/m/0" f...r IDs starting with "/g/", use Google Knowledge Graph ID (P2671)
8. subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as p/wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain

No other items found

[Assistant]
The search for properties related to "birth year" also did not yield any useful results. However, we can infer the age range from the description of the Silent Generation, which states that it includes people born from 1928 to 1945.

To confirm this, we can construct a simple SPARQL query to retrieve the birth years associated with the Silent Generation.

Let's execute a SPARQL query to confirm the birth years of the Silent Generation.

[Tool] Got no rows and 1 columns

[Assistant]
It appears that the Silent Generation entity does not have a direct property for birth years. However, based on the description, we know that the Silent Generation includes people born from 1928 to 1945.

To answer the question "People of what age belong to the Silent Generation?", we can calculate the current age range of people born in this period. We can use the current year to determine the age range.

Let's construct a SPARQL query to calculate the current age range of people born from 1928 to 1945.

[Tool]
Failed to call function execute:
failed to parse input: parse error at position 70 for token EOF with content '' (the input most likely does not follow the grammar)

[Assistant]
It looks like the SPARQL query syntax was incorrect. Let's correct the query to properly calculate the current age range of people born from 1928 to 1945.

We will use the `YEAR` function to get the current year and then subtract the birth years to get the age range.

Let's try the corrected SPARQL query.

[Tool]
Got 1 row and 2 columns:
| minAge       | maxAge       |
| ------------ | ------------ |
| 97 (xsd:int) | 80 (xsd:int) |

[Assistant]
The SPARQL query successfully calculated the current age range of people belonging to the Silent Generation. According to the results, people born from 1928 to 1945 are currently between 80 and 97 years old.

Therefore, the answer to the question "People of what age belong to the Silent Generation?" is:

People belonging to the Silent Generation are currently between 80 and 97 years old.

Let's finalize this with the answer function.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?founder WHERE {
  wd:Q479361 wdt:P112 ?founder .
}

Got 3 rows and 1 column:
| founder                      |
| ---------------------------- |
| Fritz Mackensen (wd:Q448400) |
| Hans am Ende (wd:Q561091)    |
| Otto Modersohn (wd:Q71425)   |

The Worpswede artist colony was founded by Fritz Mackensen, Hans am Ende, and Otto Modersohn.

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

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

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

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

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

[User] Who founded the Worpswede artist colony ?

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

[Tool]
Example 1:
Question:
Where is the birthplace of Goethe?

SPARQL:
SELECT ?res WHERE {
  wd:Q5879 wdt:P19 ?res .
}

Using entities:
Johann Wolfgang von Goethe, also known as Johann Wolfgang Von Goethe, Goethe (wd:Q5879): German writer, artist, natural scientist and politician (1749–1832), theatre manager, autobiographer, art historian, travel writer, visual artist, statesperson, mineralogist, art theorist, music critic, philosopher, playwright, theologian, art critic, politician, librettist, librarian, physicist, zoologist, diplomat, aphorist, polymath, botanist, composer, novelist, literary, diarist, painter, writer, jurist, lawyer, poet

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 2:
Question:
To which artistic movement did the painter of The Three Dancers belong?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q3235867 wdt:P170 ?painter .
  ?painter wdt:P135 ?uri .
}

Using entities:
The Three Dancers (wd:Q3235867): painting by Pablo Picasso

Using properties:
movement, also known as subculture, trend, scientific movement, school, philosophical movement (wd:P135 as wdt): literary, artistic, scientific or philosophical movement or scen...ed with this person or work. For political ideologies use P1142.
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:
Who was Vincent van Gogh inspired by?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q5582 wdt:P737 ?uri .
}

Using entities:
Vincent van Gogh (wd:Q5582): Dutch painter (1853–1890), draftsperson, printmaker, painter

Using properties:
influenced by, also known as favorite player, has influence, informed by, role model (wd:P737 as wdt): this person, idea, etc. is informed by that other person, idea, etc., e.g. “Heidegger was influenced by Aristotle”

[Assistant] Based on these examples, we need to identify the entity representing the Worpswede artist colony and then look for a property that indicates its founder or founding members. Let's start by searching for the entity "Worpswede artist colony".

[Tool]
Top 10 entity alternatives:
1. Worpswede artist colony, also known as Worpswede circle (wd:Q479361): Artist's colony founded in Worpswede in 1889
2. art colony, also known as artist colony, artists' colony (wd:Q1558054): place where artists live and interact with each other
3. Worpswede colony (wd:Q103974815): encyclopedia article
4. Nagybánya art colony, also known as Nagybanya art colony, Nagybánya artists' colony, Nagybanya School, Nagybánya School (wd:Q591229)
5. Önningeby artists colony, also known as Önningebykolonin (wd:Q2687905): Finnish artists colony
6. Ekensund Artists' Colony (wd:Q1669854)
7. Ein Hod artist colony, also known as Artists Village of Ein Hod, Ein Hod artists village (wd:Q124390656)
8. Nishimui Art Village, also known as Nishimui Art Colony, Nishimui Artists' Colony (wd:Q38277516)
9. New Rochelle artist colony (wd:Q19877130)
10. Kirkcudbright Artists' Colony (wd:Q20713695): artists' community

[Assistant] The correct entity for the Worpswede artist colony is `wd:Q479361`. Now, let's find out who founded it. We need to look for a property that indicates the founder or founding members. A common property for this purpose might be "founded by" or "founder". Let's search for such a property.

[Tool]
Top 10 property alternatives:
1. founded by, also known as starter, co-founded by, started by, institutor, instituted by (wd:P112 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): founder or co-founder of this organization, religion, place or entity, creator
2. notable work, also known as artwork, wrote, writer of, works, work (wd:P800 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): notable scientific, artistic or literary work, or other work of significance among subject's works
3. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): time when an entity begins to exist; for date of official opening use P1619, start time
4. location of formation, also known as place of incorporation, originates from, place of establishment, place of formation, place of foundation (wd:P740 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): location where a group or organization was formed, location of creation
5. foundational text, also known as main text, treaty, organic law, founding document, establishing document (wd:P457 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): text through which an institution or object has been created or established
6. developer, also known as written by, video game developer, video game dev, game developer, game dev (wd:P178 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): organization or person that developed the item, creator
7. fabrication method, also known as process used, method of cooking, preparation method, obtained by, method used (wd:P2079 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): method, process or technique used to grow, cook, weave, build, assemble, manufacture the item, uses
8. creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): maker of this creative work or other object (where no more specific property exists)
9. discoverer or inventor, also known as inventor or discoverer, inventor, invented by, invented, introduced by (wd:P61 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): subject who discovered, first described, invented, or developed this discovery or invention or scientific hypothesis or theory
10. owned by, also known as belongs to, stockholders, stockholder, shareholders, shareholder (wd:P127 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): owner of the subject

[Assistant]
The property "founded by" (`wd:P112`) seems to be the most appropriate for our query. Let's use this property to find out who founded the Worpswede artist colony.

Here is the SPARQL query:

```sparql
SELECT ?founder WHERE {
  wd:Q479361 wdt:P112 ?founder .
}
```

Let's execute this query to get the result.

[Tool]
Got 3 rows and 1 column:
| founder                      |
| ---------------------------- |
| Fritz Mackensen (wd:Q448400) |
| Hans am Ende (wd:Q561091)    |
| Otto Modersohn (wd:Q71425)   |

[Assistant]
The founders of the Worpswede artist colony are Fritz Mackensen, Hans am Ende, and Otto Modersohn.

Here is the final SPARQL query and answer:

```sparql
SELECT ?founder WHERE {
  wd:Q479361 wdt:P112 ?founder .
}
```

Answer: The Worpswede artist colony was founded by Fritz Mackensen, Hans am Ende, and Otto Modersohn.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
ASK WHERE {
  {
    SELECT ?university ( COUNT( DISTINCT ?founder ) AS ?count ) WHERE {
      ?founder wdt:P69 ?university .
      VALUES ?founder {
        wd:Q15934341 wd:Q1739008 wd:Q18653685 wd:Q18659347 wd:Q20689208
      }
    }
    GROUP BY ?university
    HAVING ( ?count >= 2 )
  }
}

True

[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] Were at least two of the founders of tencent educated at the same university?

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

[Tool]
Example 1:
Question:
Which electronics companies were founded in Beijing?

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

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

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

[Assistant]
The example provided does not directly relate to our question about the education of Tencent's founders. However, it gives us an idea of how to structure a query involving organizations and their associated people. We need to identify the entity for Tencent and then look for its founders and their educational backgrounds.

First, let's find the entity for Tencent.

[Tool]
Top 10 entity alternatives:
1. Tencent, also known as Téngxùn Kònggǔ Yǒuxiàn Gōngsī, Teng xun (firma), Tencent Group, Téngxùn, Tengxun (wd:Q860580): Chinese multinational investment holding conglomerate
2. Tencent QQ, also known as QQ, Qq, QICQ, OPEN-ICQ, OpenICQ (wd:Q857640): instant messaging software service
3. Tencent Video, also known as v.qq.com, TencentVideo, WeTV (wd:Q28136991): video streaming service from China
4. Tencent Pictures (wd:Q22080095): Chinese film production company
5. Tencent Games, also known as Tencent Game (wd:Q39057776): division of Tencent Holdings
6. Tencent Music, also known as tencentmusic.com, Tencent Music Entertainment, Tencent Music Entertainment Group, TME (wd:Q56011958): Chinese music distribution company
7. Tencent Weibo (wd:Q3983400): Chinese microblogging website launched by Tencent in April 2010
8. WeGame, also known as Tencent Game Platform, Tencent Games Platform, Tencent Gaming Platform, Tencent WeGame, TGP (wd:Q10852223): video gaming platform of Tencent
9. QQ browser, also known as tbs, TBS, Tencent Browsing Service, Tencent Explorer, Tencent Traveler (wd:Q6862273): web browser
10. Tencent Comic (wd:Q22101513): Chinese animation and comics network

[Assistant] The correct entity for Tencent is `wd:Q860580`. Next, we need to find the property that links the founders of a company to the company itself. Let's search for the property "founder" or "co-founder".

[Tool]
Top 10 property alternatives:
1. founded by, also known as starter, co-founded by, started by, institutor, instituted by (wd:P112 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): founder or co-founder of this organization, religion, place or entity, creator
2. notable work, also known as artwork, wrote, writer of, works, work (wd:P800 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): notable scientific, artistic or literary work, or other work of significance among subject's works
3. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): time when an entity begins to exist; for date of official opening use P1619, start time
4. collection creator, also known as creator, archive creator, collector, archives of, archive of (wd:P6241 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): entity (person, organization, etc.) that caused a record or collection to be produced or gathered
5. creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): maker of this creative work or other object (where no more specific property exists)
6. author, also known as writer, written by, poet, playwright, maker (wd:P50 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): 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
7. location of formation, also known as place of incorporation, originates from, place of establishment, place of formation, place of foundation (wd:P740 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): location where a group or organization was formed, location of creation
8. discoverer or inventor, also known as inventor or discoverer, inventor, invented by, invented, introduced by (wd:P61 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): subject who discovered, first described, invented, or developed this discovery or invention or scientific hypothesis or theory
9. author name string, also known as short author name, writer named as, writer name, writer indicated as, songwriting credits string (wd:P2093 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): stores unspecified author or editor name for publications; use i...or editor (P98) does not exist or is not known. Do not use both.
10. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): most specific known birth location of a person, animal or fictional character, location

[Assistant]
The property "founded by" (`wd:P112`) seems to be the appropriate one to link the founders to the company. Now, let's find the founders of Tencent using this property.

We will execute a SPARQL query to get the founders of Tencent.

[Tool]
Got 5 rows and 1 column:
| founder                      |
| ---------------------------- |
| Zhang Zhidong (wd:Q15934341) |
| Ma Huateng (wd:Q1739008)     |
| Zeng Liqing (wd:Q18653685)   |
| Daniel Xu (wd:Q18659347)     |
| Chen Yidan (wd:Q20689208)    |

[Assistant]
We have identified the founders of Tencent. Now, we need to find out where these founders were educated. We will search for the property "educated at" to link the founders to their universities.

Let's search for the property "educated at".

[Tool]
Top 10 property alternatives:
1. educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): educational institution attended by subject, affiliation
2. conferred by, also known as presented by, officiated by, issued by, granted by, given by (wd:P1027 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): person or organization who grants an award, certification, grant, or role
3. student of, also known as professor, studied under, pupil of, tutor, mentor (wd:P1066 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): person who has taught this person, significant person
4. student, also known as teacher to, teacher of, had student, students, pupils (wd:P802 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): notable student(s) of the subject individual, significant person
5. studied in, also known as is studied by, studied by, science, that studies, researched in, researched by (wd:P2579 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): subject is studied by this science or domain, field of work
6. gender educated (wd:P7419 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): genders educated at this educational institution
7. academic major, also known as academic subject, college major, field of study, major, studied (wd:P812 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): major someone studied at college/university
8. has role in modeling, also known as has role in modelling, used for investigating, used for researching, used for studying, used to investigate (wd:P6530 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): relation between a research artefact and an entity that is used ... its replicating or approximating features of the studied entity
9. academic degree, also known as academic diploma, degree, diploma (wd:P512 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): academic degree that the person holds
10. influenced by, also known as favorite player, has influence, informed by, role model (wd:P737 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): this person, idea, etc. is informed by that other person, idea, etc., e.g. “Heidegger was influenced by Aristotle”

[Assistant]
The property "educated at" (`wd:P69`) is the correct one to link the founders to their universities. Now, let's find out where each founder was educated by executing a SPARQL query.

We will query the universities for each founder.

[Tool]
Got 9 rows and 2 columns:
| founder                      | university                                        |
| ---------------------------- | ------------------------------------------------- |
| Zhang Zhidong (wd:Q15934341) | Shenzhen University (wd:Q1945756)                 |
| Zhang Zhidong (wd:Q15934341) | South China University of Technology (wd:Q835366) |
| Ma Huateng (wd:Q1739008)     | Shenzhen University (wd:Q1945756)                 |
| Ma Huateng (wd:Q1739008)     | Shenzhen Middle School (wd:Q7494378)              |
| Zeng Liqing (wd:Q18653685)   | Xidian University (wd:Q649906)                    |
| Daniel Xu (wd:Q18659347)     | Shenzhen University (wd:Q1945756)                 |
| Daniel Xu (wd:Q18659347)     | Nanjing University (wd:Q683580)                   |
| Chen Yidan (wd:Q20689208)    | Shenzhen University (wd:Q1945756)                 |
| Chen Yidan (wd:Q20689208)    | Shenzhen Middle School (wd:Q7494378)              |

[Assistant]
From the results, we can see that multiple founders of Tencent were educated at the same universities. Specifically, Shenzhen University (wd:Q1945756) appears multiple times:

- Ma Huateng (wd:Q1739008)
- Daniel Xu (wd:Q18659347)
- Chen Yidan (wd:Q20689208)

Since at least three founders were educated at Shenzhen University, the answer to the question is "True".

Let's confirm this with an ASK query to ensure that at least two founders were educated at the same university.

[Tool] True

[Assistant]
The ASK query confirms that at least two of the founders of Tencent were educated at the same university. Therefore, the answer to the question is "True".

Here is the final SPARQL query and answer:

```sparql
ASK WHERE {
  {
    SELECT ?university (COUNT(DISTINCT ?founder) AS ?count)
    WHERE {
      ?founder wdt:P69 ?university .
      VALUES ?founder { wd:Q15934341 wd:Q1739008 wd:Q18653685 wd:Q18659347 wd:Q20689208 }
    }
    GROUP BY ?university
    HAVING (?count >= 2)
  }
}
```

Answer: True

[Tool] Stopped generation process


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 international airports are located within the city of Hamburg ?

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

[Tool]
Example 1:
Question:
How many airlines are there?

SPARQL:
SELECT ( COUNT( DISTINCT ?uri ) AS ?uriCount ) WHERE {
  ?uri wdt:P31 wd:Q46970
}

Using entities:
airline, also known as air company, air carrier (wd:Q46970): company that provides air transport services for traveling passengers and freight

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

Example 2:
Question:
Which airports does Air China serve?

SPARQL:
SELECT DISTINCT ?uri WHERE {
  wd:Q51747 wdt:P113 ?uri .
}

Using entities:
Air China, also known as CCA, Air China Limited, CA (wd:Q51747): flag carrier of the People's Republic of China

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

Example 3:
Question:
Give me all companies in Munich.

SPARQL:
SELECT DISTINCT ?uri WHERE {
  ?type wdt:P279 * wd:Q4830453 .
  ?uri wdt:P31 ?type ; wdt:P159 wd:Q1726 .
}

Using entities:
Munich, also known as Monachium, Münich, München, Munchen, Muenchen (wd:Q1726): capital and most populous city of Bavaria, Germany
business (wd:Q4830453): organization undertaking commercial, industrial, or professional activity

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
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)

[Assistant] Based on these examples, we need to identify the entity for Hamburg and the property for being an international airport. Let's first search for the entity representing Hamburg.

[Tool]
Top 10 entity alternatives:
1. Hamburg, also known as Free and Hanseatic City of Hamburg, Hamburg, Germany, Hamburg, Freie und Hansestadt (wd:Q1055): city and state in the North of Germany
2. Hamburger SV, also known as Hamburg SV, HSV, H.S.V., Hamburg Sport Club, HamburgerSV (wd:Q51974): German sports club based in Hamburg, with its largest branch being its football department
3. Hamburg, also known as Hamburg, IA, Hamburg, Iowa (wd:Q998718): city in Fremont County, Iowa, United States
4. Hamburg, also known as Hamburg, AR, Hamburg, Arkansas (wd:Q79657): city in Ashley County, Arkansas, United States
5. Hamburg, also known as Hamburg, Minnesota, Hamburg, MN (wd:Q1005682): city in Carver County, Minnesota, United States
6. Hamburg, also known as Hamburg, New Jersey, Hamburg, NJ (wd:Q1082931): borough in Sussex County, New Jersey, United States
7. Hamburg, also known as Hamburg, New York, Hamburg, NY (wd:Q742785): town in Erie County, New York, United States
8. Hamburg, also known as Hamburg, IL (wd:Q2672139): village in Calhoun County, Illinois, United States
9. Hamburg, also known as Hamburg, PA, Hamburg, Pennsylvania (wd:Q1181264): borough in Berks County, Pennsylvania, United States
10. Hamburg, also known as Hamburgh (wd:Q939795): breed of chicken developed in Germany and Holland prior to 1700

[Assistant] The correct entity for Hamburg, Germany is `wd:Q1055`. Next, let's search for the property that indicates an airport and specifically an international airport.

[Tool]
Top 10 property alternatives:
1. airline hub, also known as hub airport, hub (wd:P113 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): airport that serves as a hub for an airline
2. aerodrome reference point, also known as airfield reference point, airport reference point, ARP (wd:P2786 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): official coordinates for airport. Aeronautical publications use format with degrees, minutes and seconds concatenated, coordinate location
3. image of design plans, also known as plan view image, plan view, plan image, floor plan, design plan (wd:P3311 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): image representing the plan of a building or place, detail map
4. ICAO airport code, also known as ICAO aerodrome code, ICAO airfield code, International Civil Aviation Organization airport code (wd:P239 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): four-character alphanumeric identifier for designating airports (for airlines, see P230)
5. FAA airport code, also known as FAA LID (wd:P240 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): three-letter or four-letter alphanumeric code identifying United States airports
6. IATA airport code, also known as International Air Transport Association airport code, uio, IATA station code, IATA location identifier (wd:P238 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): three-letter identifier for designating airports, railway stations or cities (for airlines, see P229)
7. location of landing, also known as landing site, landing location (wd:P1158 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): location where the craft landed, significant place, location
8. runway, also known as RWY (wd:P529 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): name (direction) of runway at airport/airfield/airstrip
9. flight number (wd:P3090 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): identifier for a specific flight
10. UTC date of spacecraft landing, also known as landing time, time of spacecraft landing, spacecraft landing time, spacecraft landing date, landing date (wd:P620 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): date of spacecraft landing in UTC

[Assistant] From the list, the property `ICAO airport code` (`wd:P239`) seems to be a good indicator for airports. However, it doesn't specify whether the airport is international. We need to find a property that indicates an airport is international. Let's search for the property "international airport."

[Tool]
Top 10 property alternatives:
1. airline hub, also known as hub airport, hub (wd:P113 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): airport that serves as a hub for an airline
2. IATA airport code, also known as International Air Transport Association airport code, uio, IATA station code, IATA location identifier (wd:P238 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): three-letter identifier for designating airports, railway stations or cities (for airlines, see P229)
3. aerodrome reference point, also known as airfield reference point, airport reference point, ARP (wd:P2786 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): official coordinates for airport. Aeronautical publications use format with degrees, minutes and seconds concatenated, coordinate location
4. image of design plans, also known as plan view image, plan view, plan image, floor plan, design plan (wd:P3311 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): image representing the plan of a building or place, detail map
5. ICAO airport code, also known as ICAO aerodrome code, ICAO airfield code, International Civil Aviation Organization airport code (wd:P239 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): four-character alphanumeric identifier for designating airports (for airlines, see P230)
6. FAA airport code, also known as FAA LID (wd:P240 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): three-letter or four-letter alphanumeric code identifying United States airports
7. Ex-USSR internal airport code, also known as russian airport codes (wd:P5851 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): airport code similar to IATA codes but only for Russian and CEI airports
8. UTC date of spacecraft landing, also known as landing time, time of spacecraft landing, spacecraft landing time, spacecraft landing date, landing date (wd:P620 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): date of spacecraft landing in UTC
9. location of landing, also known as landing site, landing location (wd:P1158 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): location where the craft landed, significant place, location
10. Tierstimmenarchiv ID, also known as TSA, TSA ID (wd:P5397 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): identifier for a species in the Animal Sound Archive Berlin

[Assistant]
It appears that there is no direct property for "international airport." However, we can infer that an airport is international if it has an IATA code, which is typically assigned to international airports. Let's use the IATA code property (`wd:P238`) to identify international airports.

Next, we need to find the property that indicates the location of the airport within Hamburg. The property `located in the administrative territorial entity` (`wdt:P131`) might be useful for this purpose. Let's confirm this property.

[Tool]
Top 10 property alternatives:
1. located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
2. contains the administrative territorial entity, also known as has shires, has rural cities, has regions, has municipalities, has members (wd:P150 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): (list of) direct subdivisions of an administrative territorial entity, has part(s)
3. 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 pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): 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
4. located in the statistical territorial entity, also known as located in statistical territorial entity, statistical territorial entity (wd:P8138 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): statistical territorial entity in which a place is located or is...nty is split into or part of several regions: add several values, location
5. territory overlaps, also known as partially overlaps, partially coincident with, partly coincident with, partly located in territorial entity, partly overlaps (wd:P3179 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): part or all of the area associated with (this) entity overlaps part or all of the area associated with that entity, partially coincident with
6. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
7. capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): seat of government of a country, province, state or other type of administrative territorial entity
8. located in the religious territorial entity, also known as Deanery, Vicariate, religious territorial entity, Parish, located in the ecclesiastical territorial entity (wd:P5607 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): the item is located on the territory of the following religious entity. Use P708 (diocese) for dioceses, location, part of
9. capital of, also known as national capital of, parish seat of, provincial capital of, seat of, state capital (wd:P1376 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): country, state, department, canton or other administrative division of which the municipality is the governmental seat, located in the administrative territorial entity
10. contains the statistical territorial entity, also known as contains statistical territorial entity (wd:P10888 as pqn/pqv/psn/psv/prn/prv/p/pr/ps/pq/wdt/wdtn): (list of) statistical territorial entities which are direct subd...ions of another statistical or administrative territorial entity, has part(s)

[Assistant]
The property `located in the administrative territorial entity` (`wdt:P131`) is indeed the correct property to use for determining if an airport is located within Hamburg.

Now, let's construct a SPARQL query to count the number of international airports located within the city of Hamburg. We will use the IATA code property (`wdt:P238`) to identify international airports and the `located in the administrative territorial entity` property (`wdt:P131`) to ensure they are within Hamburg.

Here is the initial SPARQL query:

```sparql
SELECT (COUNT(DISTINCT ?airport) AS ?count)
WHERE {
  ?airport wdt:P238 ?iataCode ;
           wdt:P131 wd:Q1055 .
}
```

Let's execute this query to get the result.

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

[Assistant]
The query returned a count of 0, which suggests that there might be no airports with an IATA code directly linked to Hamburg. This could be due to the way the data is structured in Wikidata. Let's try a different approach by first finding all airports in Hamburg and then checking if they have an IATA code.

We can use the property `instance of` (`wdt:P31`) to find entities that are airports and then filter those that are located in Hamburg and have an IATA code.

Here is the revised SPARQL query:

```sparql
SELECT (COUNT(DISTINCT ?airport) AS ?count)
WHERE {
  ?airport wdt:P31 wd:Q1248784 ;  # Airport
           wdt:P131 wd:Q1055 ;    # Located in Hamburg
           wdt:P238 ?iataCode .   # Has an IATA code
}
```

Let's execute this query to get the result.

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

[Assistant]
The revised query also returned a count of 0, which suggests that there might be no airports in Hamburg with an IATA code directly linked to them in the way we are querying.

Let's try another approach by first finding all airports in Hamburg and then checking if they have an IATA code, even if it's not directly linked. We can use the `instance of` property to find airports and then check for the presence of an IATA code.

Here is the updated SPARQL query:

```sparql
SELECT (COUNT(DISTINCT ?airport) AS ?count)
WHERE {
  ?airport wdt:P31 wd:Q1248784 ;  # Airport
           wdt:P131 wd:Q1055 .    # Located in Hamburg
  OPTIONAL { ?airport wdt:P238 ?iataCode }  # Optional IATA code
  FILTER (BOUND(?iataCode))  # Ensure the IATA code is present
}
```

Let's execute this query to get the result.

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

[Assistant]
The query still returns a count of 0, which suggests that there might be no airports in Hamburg with an IATA code directly linked to them in the way we are querying.

Given this, let's take a different approach by listing all airports in Hamburg and manually checking if they have an IATA code. This will help us understand if the data is structured differently or if there are any other properties we should consider.

Here is the SPARQL query to list all airports in Hamburg:

```sparql
SELECT ?airport ?iataCode
WHERE {
  ?airport wdt:P31 wd:Q1248784 ;  # Airport
           wdt:P131 wd:Q1055 .    # Located in Hamburg
  OPTIONAL { ?airport wdt:P238 ?iataCode }  # Optional IATA code
}
```

Let's execute this query to get the list of airports and their IATA codes.

[Tool] Got no rows and 2 columns

[Assistant]
The query returned no results, which suggests that there might be no airports in Hamburg that are directly linked with the properties we are using. This could be due to the data being structured differently or the properties not being used as expected.

Let's try a more general approach by listing all entities that are airports and then filtering those that are located in Hamburg. We can also include the `located in the present-day administrative territorial entity` property (`wdt:P3842`) to see if it provides any additional results.

Here is the updated SPARQL query:

```sparql
SELECT ?airport ?iataCode
WHERE {
  ?airport wdt:P31 wd:Q1248784 .  # Airport
  OPTIONAL { ?airport wdt:P131 wd:Q1055 } .  # Located in Hamburg (administrative territorial entity)
  OPTIONAL { ?airport wdt:P3842 wd:Q1055 } .  # Located in Hamburg (present-day administrative territorial entity)
  OPTIONAL { ?airport wdt:P238 ?iataCode } .  # Optional IATA code
}
```

Let's execute this query to get the list of airports and their IATA codes.

[Tool]
Got 24,402 rows and 2 columns, showing the first 5 and last 5 rows below:
| airport                                            | iataCode |
| -------------------------------------------------- | -------- |
| Jinggangshan Airport (wd:Q1000018)                 | JGS      |
| Changde Taohuayuan Airport (wd:Q1000025)           | CGD      |
| Jiujiang Lushan Airport (wd:Q1002604)              | JIU      |
| Aksu Hongqipo Airport (wd:Q1006478)                | AKU      |
| Mohe Gulian Airport (wd:Q1006900)                  | OHE      |
| ...                                                | ...      |
| Krasnoshchelye (wd:Q99746020)                      |          |
| Umba (wd:Q99746045)                                |          |
| Hazrat Sultan International Airport (wd:Q99776256) | HSA      |
| Santarém Airport (wd:Q998862)                      |          |
| Aeroparque Jorge Newbery (wd:Q999047)              | AEP      |

[Assistant]
The query returned a large number of airports, but it seems that most of them are not located in Hamburg. This suggests that the properties `wdt:P131` and `wdt:P3842` might not be sufficient to filter airports specifically located in Hamburg.

Let's try a more targeted approach by listing all entities that are airports and then filtering those that are located in Hamburg using the `located in the administrative territorial entity` property (`wdt:P131`). We will also include the `located in the present-day administrative territorial entity` property (`wdt:P3842`) to ensure we capture all relevant airports.

Here is the updated SPARQL query:

```sparql
SELECT ?airport ?iataCode
WHERE {
  ?airport wdt:P31 wd:Q1248784 .  # Airport
  ?airport wdt:P131* wd:Q1055 .   # Located in Hamburg (administrative territorial entity, including sub-regions)
  OPTIONAL { ?airport wdt:P238 ?iataCode } .  # Optional IATA code
}
```

This query uses the `*` operator to allow for multiple levels of administrative territorial entities, which might help capture airports located in sub-regions of Hamburg.

Let's execute this query to get the list of airports and their IATA codes.

[Tool] Got no rows and 2 columns

[Assistant]
The query still returned no results, which suggests that there might be no airports in Hamburg that are directly linked with the properties we are using. This could be due to the data being structured differently or the properties not being used as expected.

Given the lack of results, let's take a different approach by listing all entities that are airports and then manually checking if they are located in Hamburg. We can use the `located in the administrative territorial entity` property (`wdt:P131`) and the `located in the present-day administrative territorial entity` property (`wdt:P3842`) to filter the results.

Here is the updated SPARQL query to list all airports and their locations:

```sparql
SELECT ?airport ?location ?iataCode
WHERE {
  ?airport wdt:P31 wd:Q1248784 .  # Airport
  OPTIONAL { ?airport wdt:P131 ?location } .  # Located in administrative territorial entity
  OPTIONAL { ?airport wdt:P3842 ?location } .  # Located in present-day administrative territorial entity
  OPTIONAL { ?airport wdt:P238 ?iataCode } .  # Optional IATA code
}
LIMIT 100
```

Let's execute this query to get the list of airports, their locations, and their IATA codes.

[Tool]
Got 100 rows and 3 columns, showing the first 5 and last 5 rows below:
| airport                                  | location                           | iataCode |
| ---------------------------------------- | ---------------------------------- | -------- |
| Jinggangshan Airport (wd:Q1000018)       | Taihe County (wd:Q1375378)         | JGS      |
| Changde Taohuayuan Airport (wd:Q1000025) | Hunan (wd:Q45761)                  | CGD      |
| Jiujiang Lushan Airport (wd:Q1002604)    | Jiujiang (wd:Q216077)              | JIU      |
| Aksu Hongqipo Airport (wd:Q1006478)      | Hongqipo (wd:Q14122604)            | AKU      |
| Mohe Gulian Airport (wd:Q1006900)        | Heilongjiang (wd:Q19206)           | OHE      |
| ...                                      | ...                                | ...      |
| Arvika Airport (wd:Q10418979)            | Arvika Municipality (wd:Q511365)   |          |
| Boden Heliport (wd:Q10431979)            | Boden Municipality (wd:Q509476)    |          |
| Tenzing-Hillary Airport (wd:Q1043277)    | Solukhumbu District (wd:Q28363)    | LUA      |
| Borås Airport (wd:Q10433395)             | Borås Municipality (wd:Q894327)    |          |
| Brandholmen Airport (wd:Q10434726)       | Nyköping Municipality (wd:Q500267) |          |

[Assistant]
The query returned a list of airports along with their locations and IATA codes, but none of them are located in Hamburg. This suggests that the data for airports in Hamburg might be structured differently or not directly linked to the properties we are using.

Given the lack of results, let's manually verify if there are any known international airports in Hamburg and then check if they are represented in Wikidata. The main international airport in Hamburg is Hamburg Airport (HAM).

Let's search for the entity representing Hamburg Airport in Wikidata.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?date WHERE {
  wd:Q15787 wdt:P575 ?date .
}

HIV was first identified in 1983.

[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 HIV first identified?

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

[Tool] No examples found

[Assistant] Since we couldn't find any similar examples, let's start by searching for the entity "HIV" in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. HIV, also known as AIDS virus, human immunodeficiency virus (wd:Q15787): human retrovirus, cause of AIDS
2. Hiv (wd:Q5959052): village in Iran
3. .hiv (wd:Q20573587): top level domain
4. human immunodeficiency virus infectious disease, also known as HIV+, HIV infection, HIV infections, HIV-positive (wd:Q18556697): disease affecting the human immune system
5. HIV/AIDS in Ethiopia, also known as HIV (wd:Q65409016): Ethiopia faces an epidemic among sub-populations and geographic areas
6. HyperChem Input File, also known as HIV, .hin, HyperChem molecule file format, HIV molecule file format (wd:Q28530466): file format
7. HIV (wd:Q87558374): scientific article published on 01 August 2014
8. HIV (wd:Q93531156)
9. HIV. (wd:Q43247940): scientific article published in February 1998
10. HIV. (wd:Q45982420): scientific article published in February 2001

[Assistant] The first result, "HIV, also known as AIDS virus, human immunodeficiency virus (wd:Q15787)", seems to be the correct entity for our query. Now, let's look for properties related to "identification" or "discovery" for this entity.

[Tool]
Top 10 property alternatives:
1. FAST ID, also known as Faceted Application of Subject Terminology ID, FAST subject heading, fst, worldcat.org/fast (wd:P2163 as wdtn/p/wdt): authority control identifier in WorldCat's “FAST Linked Data” authority file
2. Library of Congress authority ID, also known as LCSH Authority File ID, LC Name Authority ID, LCSH ID, LCSH LCCN, LC Subject Heading ID (wd:P244 as wdtn/p/wdt): Library of Congress name authority (persons, families, corporate...lowed by 8-10 digits (see regex). For manifestations, use P1144]
3. Australian Educational Vocabulary ID, also known as AEV ID, AEV identifier, Australian Educational Vocabulary identifier, Schools Online Thesaurus ID, Schools Online Thesaurus identifier (wd:P7033 as wdtn/p/wdt): ID for curriculum term in one of the controlled vocabularies at Australian education vocabularies
4. time of discovery or invention, also known as invented in, time of invention, time of discovery, invention time, invented on (wd:P575 as p/wdt): date or point in time when the item was discovered or invented
5. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as p/wdt): work where this item is described, attested in
6. Encyclopædia Britannica Online ID, also known as Encyclopaedia Britannica Online ID, Encyclopedia Britannica Online ID, EBID, EB ID, Britannica online ID (wd:P1417 as p/wdt): identifier for an article in the online version of Encyclopædia Britannica
7. Golden ID (wd:P7502 as p/wdt): ID page in Golden knowledge base
8. National Library of Spain ID, also known as BNE ID, BNE identifier, LEM ID, National Library of Spain ID, National Library of Spain identifier (wd:P950 as wdtn/p/wdt): identifier from the authority file of the National Library of Spain. Format for persons: "XX" followed by 4 to 7 digits
9. GND ID, also known as Deutschen Nationalbibliothek ID, Universal Authority File, Integrated Authority File, IndividualisedGnd, GND-IDN (wd:P227 as wdtn/p/wdt): identifier from an international authority file of names, subjects, and organizations
10. NL CR AUT ID, also known as Czech National Authority Database, NLCR AUT ID (wd:P691 as p/wdt): identifier in the Czech National Authority Database of National Library of the Czech Republic (NL CR)

No other items found

[Assistant] The property "time of discovery or invention" (wd:P575) seems to be the most relevant for our query. Let's check if this property is associated with the entity "HIV" (wd:Q15787).

[Tool]
Got 1 row and 3 columns:
| subject         | property                                  | object                              |
| --------------- | ----------------------------------------- | ----------------------------------- |
| HIV (wd:Q15787) | time of discovery or invention (wdt:P575) | 1983-01-01T00:00:00Z (xsd:dateTime) |

[Assistant]
We found that the time of discovery or invention for HIV is recorded as 1983-01-01. Let's construct a SPARQL query to confirm this information and return it as the answer.

Here is the SPARQL query:

```sparql
SELECT ?date
WHERE {
  wd:Q15787 wdt:P575 ?date .
}
```

Let's execute this query to get the result.

[Tool]
Got 1 row and 1 column:
| date                                |
| ----------------------------------- |
| 1983-01-01T00:00:00Z (xsd:dateTime) |

[Assistant]
The SPARQL query confirms that HIV was first identified in 1983.

Here is the final SPARQL query and the answer:

```sparql
SELECT ?date
WHERE {
  wd:Q15787 wdt:P575 ?date .
}
```

Answer: HIV was first identified in 1983.

[Tool] Stopped generation process