PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX schema: <http://schema.org/>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?generation ?label ?description ?birthYearStart ?birthYearEnd ?ageMin ?ageMax WHERE {
  VALUES ?generation {
    wd:Q3044693
  }
  OPTIONAL {
    ?generation rdfs:label ?label .
    FILTER ( LANG( ?label ) = "en" )
  }
  OPTIONAL {
    ?generation schema:description ?description .
    FILTER ( LANG( ?description ) = "en" )
  }
  BIND( STR( ?description ) AS ?descStr ) BIND( xsd:integer ( REPLACE( ?descStr , ".*born from ([0-9]{4}) to [0-9]{4}.*" , "$1" ) ) AS ?birthYearStart ) BIND( xsd:integer ( REPLACE( ?descStr , ".*born from [0-9]{4} to ([0-9]{4}).*" , "$1" ) ) AS ?birthYearEnd ) BIND( 2024 - ?birthYearEnd AS ?ageMin ) BIND( 2024 - ?birthYearStart AS ?ageMax )
}

After a thorough search, there are no structured properties (such as "start time" or "end time") on the Silent Generation entity or its class that encode the birth year range. Therefore, extracting the years from the description is the only available method in this case.

Here is the improved answer, explicitly noting this workaround:

The SPARQL query below extracts the birth year range for the Silent Generation from the entity's description (since no structured properties are available) and calculates the current age range as of 2024:

```sparql
SELECT ?generation ?label ?description ?birthYearStart ?birthYearEnd ?ageMin ?ageMax WHERE {
  VALUES ?generation { wd:Q3044693 }
  OPTIONAL { ?generation rdfs:label ?label. FILTER(LANG(?label) = "en") }
  OPTIONAL { ?generation schema:description ?description. FILTER(LANG(?description) = "en") }
  BIND(STR(?description) AS ?descStr)
  BIND(xsd:integer(REPLACE(?descStr, ".*born from ([0-9]{4}) to [0-9]{4}.*", "$1")) AS ?birthYearStart)
  BIND(xsd:integer(REPLACE(?descStr, ".*born from [0-9]{4} to ([0-9]{4}).*", "$1")) AS ?birthYearEnd)
  BIND(2024 - ?birthYearEnd AS ?ageMin)
  BIND(2024 - ?birthYearStart AS ?ageMax)
}
```

According to Wikidata, the Silent Generation consists of people born from 1928 to 1945. As of 2024, this means people who are approximately 79 to 96 years old belong to the Silent Generation. This age range is computed directly in SPARQL by extracting the years from the entity's description, as no structured properties are available.

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

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

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

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

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

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

[Assistant]
Let's break down the question:

1. The user is asking about the age range of people who belong to the "Silent Generation".
2. This requires identifying the entity for "Silent Generation" and then finding properties related to its age range, which is typically defined by birth years.

Step 1: 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 most relevant entity for the "Silent Generation" is wd:Q3044693, described as the cohort succeeding the Greatest Generation, born from 1928 to 1945.

Next, I need to find properties on this entity that specify the birth years or age range for the Silent Generation. This will help determine the current age range of people in this generation.

I will search for properties of wd:Q3044693 related to "birth year" or "period".

[Tool]
Top 10 property alternatives:
1. 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
2. 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)]
3. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
4. 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)]
5. Freebase ID, also known as Freebase, MID, Freebase identifier, FID (wd:P646 as p/wdt): identifier for a page in the Freebase database. Format: "/m/0" f...r IDs starting with "/g/", use Google Knowledge Graph ID (P2671)
6. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
7. 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

[Tool]
Top 10 property alternatives:
1. 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
2. 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)
3. 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)
4. 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)]
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. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)

No other items found

[Tool]
Got 124 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                                                                                |
| ...                             | ...                                                   | ...                                                                                |

[Tool] Got no rows and 3 columns

[Tool] Got no rows and 3 columns

[Tool] Got no rows and 3 columns

[Tool] Got no rows and 3 columns

[Tool] Got no rows and 3 columns

[Assistant]
The direct properties for start/end time, birth year, or period are not present on the "Silent Generation" entity (wd:Q3044693). However, the description from the search result states that the Silent Generation is "born from 1928 to 1945".

Since this information is not encoded as a property but is present in the description, I will retrieve the description of the entity using the rdfs:label and schema:description properties to provide the answer, as this is the only available structured information.

I will write a SPARQL query to get the label and description for wd:Q3044693.

[Tool]
Got 1 row and 3 columns:
| generation                      | label                  | description                                                            |
| ------------------------------- | ---------------------- | ---------------------------------------------------------------------- |
| Silent Generation (wd:Q3044693) | Silent Generation (en) | cohort succeeding the Greatest Generation, born from 1928 to 1945 (en) |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The answer provides a correct interpretation of the description associated with the Silent Generation entity, and the SPARQL query correctly retrieves the relevant entity and its description. However, the query does not directly compute or return the age range (e.g., 79 to 96 years old as of 2024) as part of its result. The age range is inferred outside of SPARQL, which violates the instruction that all computation should be done within SPARQL. To improve, the query could attempt to calculate the current age range based on the birth years (1928-1945) using SPARQL's arithmetic capabilities, if supported, or at least return the birth years explicitly. The current output is sensible but could be refined to better align with the requirements.

[Assistant]
Thank you for the feedback. You are correct: the previous query only retrieved the description, and the age calculation was performed outside SPARQL. To fully comply with the instructions, I should attempt to compute or at least explicitly return the birth years in the SPARQL query, and, if possible, calculate the current age range (as of 2024) using SPARQL arithmetic.

Step-by-step plan:
1. Extract the birth years (1928–1945) from the description using SPARQL string functions, since they are not present as structured properties.
2. Use SPARQL arithmetic to compute the age range as of 2024.
3. Return the birth years and computed ages in the query result.

First, I will write a SPARQL query that extracts the years from the description using regex, and then calculates the ages as of 2024.

[Tool]
Got 1 row and 7 columns:
| generation                      | label                  | description                                                            | birthYearStart | birthYearEnd  | ageMin         | ageMax |
| ------------------------------- | ---------------------- | ---------------------------------------------------------------------- | -------------- | ------------- | -------------- | ------ |
| Silent Generation (wd:Q3044693) | Silent Generation (en) | cohort succeeding the Greatest Generation, born from 1928 to 1945 (en) |                | 194 (xsd:int) | 1830 (xsd:int) |        |

[Assistant]
The attempt to extract the birth years using SUBSTR and STRLEN did not work as intended, resulting in incorrect values. This is because the position calculation in SUBSTR is not accurately targeting the years in the description string.

To improve, I will use REGEX to extract the four-digit numbers (years) from the description. SPARQL's REGEX and REPLACE functions can help with this. I will extract both years and then compute the ages.

Let me try a query that uses REGEX to extract the years "1928" and "1945" from the description.

[Tool]
Got 1 row and 7 columns:
| generation                      | label                  | description                                                            | birthYearStart | birthYearEnd   | ageMin       | ageMax       |
| ------------------------------- | ---------------------- | ---------------------------------------------------------------------- | -------------- | -------------- | ------------ | ------------ |
| Silent Generation (wd:Q3044693) | Silent Generation (en) | cohort succeeding the Greatest Generation, born from 1928 to 1945 (en) | 1928 (xsd:int) | 1945 (xsd:int) | 79 (xsd:int) | 96 (xsd:int) |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query provides a sensible answer by extracting the birth year range from the description and calculating the current age range. However, extracting structured data from the description string is fragile and not ideal. If possible, the query should use structured properties (such as P569 for date of birth or other properties that directly encode the start and end years for the generation) instead of parsing the description. If such properties are not available, the current approach is acceptable, but it should be noted as a workaround. The query otherwise follows the rules, returning the IRI and optionally the label and description.

[Assistant]
Thank you for the feedback. You are correct: extracting data from the description is a workaround and not ideal. The preferred approach is to use structured properties if available.

Let me check once more if the Silent Generation entity (wd:Q3044693) or its class (such as "cultural generation of western society" wd:Q15925549) has any structured properties that encode the start and end years for the generation, such as "start time" (P580), "end time" (P582), or similar.

If such properties are not available, I will note in the answer that extracting from the description is a workaround due to the lack of structured data.

First, I will check for properties of the type "start time" or "end time" on the Silent Generation entity.

[Tool]
Top 10 property alternatives:
1. 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)]
2. 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
3. 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)]
4. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
5. 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)
6. 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)
7. 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

[Tool]
Top 10 property alternatives:
1. 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)]
2. 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)]
3. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
4. 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. Freebase ID, also known as Freebase, MID, Freebase identifier, FID (wd:P646 as p/wdt): identifier for a page in the Freebase database. Format: "/m/0" f...r IDs starting with "/g/", use Google Knowledge Graph ID (P2671)
6. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
7. 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

[Tool]
Top 10 property alternatives:
1. topic's main template, also known as topic has template, topic's main module, topic's main infobox, topic infobox, main template (wd:P1424 as p/wdt): the main template relating to a topic
2. subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as p/wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain

No other items found

[Tool]
Top 10 property alternatives:
1. 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
2. topic's main template, also known as topic has template, topic's main module, topic's main infobox, topic infobox, main template (wd:P1424 as p/wdt): the main template relating to a topic

No other items found

[Assistant]
After a thorough search, there are no structured properties (such as "start time" or "end time") on the Silent Generation entity or its class that encode the birth year range. Therefore, extracting the years from the description is the only available method in this case.

Here is the improved answer, explicitly noting this workaround:

The SPARQL query below extracts the birth year range for the Silent Generation from the entity's description (since no structured properties are available) and calculates the current age range as of 2024:

```sparql
SELECT ?generation ?label ?description ?birthYearStart ?birthYearEnd ?ageMin ?ageMax WHERE {
  VALUES ?generation { wd:Q3044693 }
  OPTIONAL { ?generation rdfs:label ?label. FILTER(LANG(?label) = "en") }
  OPTIONAL { ?generation schema:description ?description. FILTER(LANG(?description) = "en") }
  BIND(STR(?description) AS ?descStr)
  BIND(xsd:integer(REPLACE(?descStr, ".*born from ([0-9]{4}) to [0-9]{4}.*", "$1")) AS ?birthYearStart)
  BIND(xsd:integer(REPLACE(?descStr, ".*born from [0-9]{4} to ([0-9]{4}).*", "$1")) AS ?birthYearEnd)
  BIND(2024 - ?birthYearEnd AS ?ageMin)
  BIND(2024 - ?birthYearStart AS ?ageMax)
}
```

According to Wikidata, the Silent Generation consists of people born from 1928 to 1945. As of 2024, this means people who are approximately 79 to 96 years old belong to the Silent Generation. This age range is computed directly in SPARQL by extracting the years from the entity's description, as no structured properties are available.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?founder ?founderLabel WHERE {
  wd:Q479361 wdt:P112 ?founder .
  OPTIONAL {
    ?founder rdfs:label ?founderLabel FILTER ( lang( ?founderLabel ) = "en" )
  }
}

Got 3 rows and 2 columns:
| founder                      | founderLabel         |
| ---------------------------- | -------------------- |
| Fritz Mackensen (wd:Q448400) | Fritz Mackensen (en) |
| Hans am Ende (wd:Q561091)    | Hans am Ende (en)    |
| Otto Modersohn (wd:Q71425)   | Otto Modersohn (en)  |

The Worpswede artist colony was founded by Fritz Mackensen (wd:Q448400), Hans am Ende (wd:Q561091), and Otto Modersohn (wd:Q71425).

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

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

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

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

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

[User] Who founded the Worpswede artist colony ?

[Assistant]
Let's break down the question:

1. The main entity is "Worpswede artist colony".
2. The property of interest is "founded by" or "founder".

First, I will search for the entity "Worpswede artist colony" in Wikidata to get its identifier.

[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 most relevant entity is "Worpswede artist colony" with the identifier wd:Q479361.

Next, I need to find the property that links an entity to its founder(s). I will search for properties related to "founder" or "founded by".

[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/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): 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/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): 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/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): 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/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): 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/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): 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/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): 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/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): 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/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): 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/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): 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/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): most specific known birth location of a person, animal or fictional character, location

[Assistant]
The most relevant property is "founded by" (wdt:P112).

Now, I will construct a SPARQL query to find the founder(s) of the Worpswede artist colony (wd:Q479361) using the property "founded by" (wdt:P112). I will also try to retrieve optional labels for the founders.

[Tool]
Got 3 rows and 2 columns:
| founder                      | founderLabel         |
| ---------------------------- | -------------------- |
| Fritz Mackensen (wd:Q448400) | Fritz Mackensen (en) |
| Hans am Ende (wd:Q561091)    | Hans am Ende (en)    |
| Otto Modersohn (wd:Q71425)   | Otto Modersohn (en)  |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the founders of the Worpswede artist colony using the appropriate property (wdt:P112) and entity (wd:Q479361). The query returns the IRIs of the founders as required, and the answer matches the query result. No further refinement is needed.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
ASK {
  wd:Q860580 wdt:P112 ?founder1 , ?founder2 .
  FILTER ( ?founder1 != ?founder2 ) ?founder1 wdt:P69 ?university .
  ?founder2 wdt:P69 ?university .
}

Yes, at least two of the founders of Tencent were educated at the same university.

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

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

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

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

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

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

[Assistant]
Let's break down the question:

1. We need to identify the founders of Tencent.
2. For each founder, we need to find their university education.
3. We need to check if at least two founders were educated at the same university.
4. Since the question is yes/no, we should construct an ASK query that returns true if at least two founders share a university.

First, let's search for the entity "Tencent" in Wikidata to get its IRI.

[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 entity for Tencent (the company) is wd:Q860580.

Next, we need to find the founders of Tencent. Let's search for properties related to "founder" for this entity.

[Tool]
Top 10 property alternatives:
1. founded by, also known as starter, co-founded by, started by, institutor, instituted by (wd:P112 as p/wdt): founder or co-founder of this organization, religion, place or entity, creator
2. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as p/wdt): time when an entity begins to exist; for date of official opening use P1619, start time
3. owned by, also known as belongs to, stockholders, stockholder, shareholders, shareholder (wd:P127 as p/wdt): owner of the subject
4. chief executive officer, also known as executive director, CEO, chief executive (wd:P169 as p/wdt): highest-ranking corporate officer appointed as the CEO within an organization, director / manager, corporate officer
5. owner of, also known as owns, owns property, shareholder of (wd:P1830 as p/wdt): entities owned by the subject
6. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
7. product, material, or service produced or provided, also known as products, product or service provided, product, material, or service produced or provided, product, output (wd:P1056 as p/wdt): material or product produced or sold by an organization, industry, facility, or process, material or product produced by an organization, industry, facility, or process, immediate cause of
8. member of, also known as band member of, membership, member of musical group, in musical group, be member of (wd:P463 as p/wdt): organization, club or musical group to which the subject belongs...ical position, such as a member of parliament (use P39 for that), part of
9. official name, also known as long title, name, official title, registered name, full title (wd:P1448 as p/wdt): official name of the subject in its official language(s), name
10. has subsidiary, also known as subordinate body, subsidiary body, subordinate unit, subsidiary, subsidiary company (wd:P355 as p/wdt): subsidiary of a company or organization; generally a fully owned...siness division" (P199). Opposite of parent organization (P749)., has part(s), owner of

No other items found

[Assistant] The property "founded by" (wdt:P112) is used to indicate the founders of an organization. Let's list the values for this property for Tencent (wd:Q860580) to get its founders.

[Tool]
Got 5 rows and 3 columns:
| subject              | property              | object                       |
| -------------------- | --------------------- | ---------------------------- |
| Tencent (wd:Q860580) | founded by (wdt:P112) | Ma Huateng (wd:Q1739008)     |
| Tencent (wd:Q860580) | founded by (wdt:P112) | Zhang Zhidong (wd:Q15934341) |
| Tencent (wd:Q860580) | founded by (wdt:P112) | Chen Yidan (wd:Q20689208)    |
| Tencent (wd:Q860580) | founded by (wdt:P112) | Zeng Liqing (wd:Q18653685)   |
| Tencent (wd:Q860580) | founded by (wdt:P112) | Daniel Xu (wd:Q18659347)     |

[Assistant]
Tencent has five founders according to Wikidata:
- Ma Huateng (wd:Q1739008)
- Zhang Zhidong (wd:Q15934341)
- Chen Yidan (wd:Q20689208)
- Zeng Liqing (wd:Q18653685)
- Daniel Xu (wd:Q18659347)

Next, we need to find the universities these founders attended. Let's search for properties related to "educated at" for one of the founders, e.g., Ma Huateng.

[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 p/wdt): educational institution attended by subject, affiliation
2. occupation, also known as job, work, vocation, profession, employment (wd:P106 as p/wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
3. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as p/wdt): most specific known birth location of a person, animal or fictional character, location
4. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as p/wdt): date on which the subject was born, inception
5. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as p/wdt): the object is a country that recognizes the subject as its citizen, country
6. spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as p/wdt): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative
7. employer, also known as working at, working for, working place, works at, works for (wd:P108 as p/wdt): person or organization for which the subject works or worked, affiliation
8. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as p/wdt): language(s) that a person or a people speaks, writes or signs, including the native language(s)
9. residence, also known as living in, place of residence, resided at, resided in, resident in (wd:P551 as p/wdt): the place where the person is or has been, resident, location
10. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as p/wdt): award or recognition received by a person, organization or creative work

No other items found

[Assistant]
The property "educated at" (wdt:P69) is used to indicate the university or educational institution attended by a person.

Now, let's list the "educated at" property for each of the five founders to see which universities they attended. I'll start by listing for Ma Huateng.

[Tool]
Got 2 rows and 3 columns:
| subject                  | property              | object                               |
| ------------------------ | --------------------- | ------------------------------------ |
| Ma Huateng (wd:Q1739008) | educated at (wdt:P69) | Shenzhen University (wd:Q1945756)    |
| Ma Huateng (wd:Q1739008) | educated at (wdt:P69) | Shenzhen Middle School (wd:Q7494378) |

[Tool]
Got 2 rows and 3 columns:
| subject                      | property              | object                                            |
| ---------------------------- | --------------------- | ------------------------------------------------- |
| Zhang Zhidong (wd:Q15934341) | educated at (wdt:P69) | Shenzhen University (wd:Q1945756)                 |
| Zhang Zhidong (wd:Q15934341) | educated at (wdt:P69) | South China University of Technology (wd:Q835366) |

[Tool]
Got 2 rows and 3 columns:
| subject                   | property              | object                               |
| ------------------------- | --------------------- | ------------------------------------ |
| Chen Yidan (wd:Q20689208) | educated at (wdt:P69) | Shenzhen University (wd:Q1945756)    |
| Chen Yidan (wd:Q20689208) | educated at (wdt:P69) | Shenzhen Middle School (wd:Q7494378) |

[Tool]
Got 1 row and 3 columns:
| subject                    | property              | object                         |
| -------------------------- | --------------------- | ------------------------------ |
| Zeng Liqing (wd:Q18653685) | educated at (wdt:P69) | Xidian University (wd:Q649906) |

[Tool]
Got 2 rows and 3 columns:
| subject                  | property              | object                            |
| ------------------------ | --------------------- | --------------------------------- |
| Daniel Xu (wd:Q18659347) | educated at (wdt:P69) | Nanjing University (wd:Q683580)   |
| Daniel Xu (wd:Q18659347) | educated at (wdt:P69) | Shenzhen University (wd:Q1945756) |

[Assistant]
From the data, we see the following universities attended by the founders:
- Ma Huateng: Shenzhen University
- Zhang Zhidong: Shenzhen University, South China University of Technology
- Chen Yidan: Shenzhen University
- Zeng Liqing: Xidian University
- Daniel Xu: Nanjing University, Shenzhen University

Shenzhen University appears for four founders.

Now, let's construct an ASK query to check if there exist at least two distinct founders of Tencent who were educated at the same university.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is correct for the question. It uses an ASK query to check if there exist at least two distinct founders of Tencent who attended the same university. The query returns True, which directly answers the user's question. The query uses the correct properties (P112 for founders and P69 for education) and does not include any unnecessary computation or non-standard clauses. No further refinement is needed.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ( COUNT( DISTINCT ?airport ) AS ?count ) WHERE {
  ?airport wdt:P31 / wdt:P279 * wd:Q644371 .
  ?airport wdt:P131 * wd:Q1055 .
}

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

There is 1 international airport located within the city of Hamburg.

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

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

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

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

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

[User] How many international airports are located within the city of Hamburg ?

[Assistant]
Let's break down the question:

1. We need to identify "international airports".
2. We need to identify the city of "Hamburg".
3. We need to find which international airports are located within Hamburg.
4. We need to count the number of such airports.

First, let's search for the entity representing "Hamburg" in Wikidata.

[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 the city of Hamburg in Germany is wd:Q1055.

Next, let's search for the concept of "international airport" in Wikidata to identify the relevant class or property.

[Tool]
Top 10 entity alternatives:
1. international airport (wd:Q644371): airport serving international destinations
2. International Airport (wd:Q55614529): 1985 film directed by Don Chaffey
3. Domodedovo International Airport, also known as Moscow-Domodedovo Airport, UUDD, Moscow International Airport, Moscow Domodedovo Airport, Moscow Airport (wd:Q186614): international airport serving Moscow, Russia
4. John F. Kennedy International Airport, also known as Kennedy International Airport, New York International Airport, KJFK, JFK International Airport, Kennedy International (wd:Q8685): international airport in New York, United States
5. John F. Kennedy International Airport, also known as Idlewild Airport, Kennedy International, JFK International Airport, KJFK, JFK Airport (wd:Q8685): international airport in New York, United States
6. Sheremetyevo International Airport, also known as Moscow Airport, Moscow International Airport, Sheremetyevo Airport, SVO, UUEE (wd:Q192733): international airport serving Moscow, Russia
7. Istanbul-Atatürk, also known as LTBA, Istanbul Atatürk Airport, Istanbul Ataturk Airport, ISL, Atatürk International Airport (wd:Q86473): international airport in Istanbul, Turkey
8. Dubai International Airport, also known as DXB, OMDB (wd:Q193439): international airport in Dubai, United Arab Emirates
9. Singapore Changi Airport, also known as WSSS, Changi Airport Singapore, SIN, Changi Airport, Changi International Airport (wd:Q32159): international airport in Singapore
10. Tokyo International Airport, also known as Haneda Airport, HND, RJTT (wd:Q204853): international airport serving Tokyo, Japan

[Assistant]
The correct entity for the class "international airport" is wd:Q644371.

Now, we need to find airports that are instances of "international airport" (wd:Q644371) and are located within Hamburg (wd:Q1055).

To do this, we need to:
- Find the property for "instance of".
- Find the property for "located in the administrative territorial entity" or similar.

Let's search for the property "instance of" first.

[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 pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
2. Wikidata property example, also known as e.g., Wikidata property sample, property sample, property example, for example (wd:P1855 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): example where this Wikidata property is used; target item is one...ualifier the property being described given the associated value
3. quantity, also known as amount, total number, total, qty, occurrences (wd:P1114 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): number of instances of this subject in the universe of the subje...e actual number of instances in Wikidata may be lower or higher)
4. subproperty of, also known as subclass of property, superproperty, subPropertyOf, rdfs:subPropertyOf, parent property (wd:P1647 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): all resources related by this property are also related by that property, related property
5. partially coincident with, also known as intersecting with, has overlap with, has common parts with, has common members with, has common instances with (wd:P1382 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): object that partially overlaps with the subject in its instances, parts, or members, different from
6. model item, also known as specimen, sample, featured item, example item, best example (wd:P5869 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): defines which item is a best practice example of modelling a sub...lue of this property, usage instructions at Wikidata:Model items
7. permanent duplicated item, also known as same concept as, same as, duplicate of, permanently duplicated item, duplicate of item (wd:P2959 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): this item duplicates another item and the two can't be merged, a... cdowiki, gomwiki, nanwiki).  Use P31=Q17362920 for other wikis.
8. exemplar of, also known as contains work, includes work, contents (wd:P1574 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): Links an individual copy of a work to the item for that work or edition, instance of
9. usage example, also known as sentence, use in a sentence, example sentence (wd:P5831 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): example of how a lexeme (sense) might be used
10. fictional or mythical analog of, also known as fictionalisation of, mythical analog of, fictional version of, fictionalization of, fictional analog of (wd:P1074 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): used to link an entity or class of entities appearing in a creat...with the analogous entity or class of entities in the real world, inspired by

[Assistant]
The property "instance of" is wd:P31.

Now, let's search for the property "located in the administrative territorial entity" to link airports to Hamburg.

[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/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
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/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): (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/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): 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/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): 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/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): 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/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
7. capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): 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/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): 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/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): 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/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): (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" is wd:P131.

Now, let's put it all together:
- We want all entities that are instances of "international airport" (wd:P31 wd:Q644371)
- And are located in the administrative territorial entity "Hamburg" (wd:P131 wd:Q1055)
- We want to count the number of such entities.

Let's write a SPARQL query to count the number of international airports located within Hamburg.

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

[Assistant]
According to the Wikidata knowledge graph, there are 0 international airports located within the city of Hamburg (wd:Q1055) as classified by the instance of "international airport" (wd:Q644371) and the administrative territorial entity property.

Here is the SPARQL query used:

SELECT (COUNT(DISTINCT ?airport) AS ?count) WHERE {
  ?airport wdt:P31 wd:Q644371 .
  ?airport wdt:P131 wd:Q1055 .
}

Answer: 0

[User]
Feedback (status=refine):
The SPARQL query is technically correct in its structure and follows the rules: it counts the number of international airports (wd:Q644371) located in Hamburg (wd:Q1055) using the administrative territorial entity property (wd:P131). However, there is a potential issue with the completeness of the answer: some airports might not be directly linked to Hamburg via P131, but rather to a district or sub-entity within Hamburg, or they might be classified under a different but related class (e.g., just 'airport' with an additional qualifier for international status). To improve the query, consider including subclasses of 'international airport' and checking for airports located within administrative sub-entities of Hamburg. This will ensure that no relevant airports are missed due to data modeling variations in Wikidata.

[Assistant]
Thank you for the feedback. To address it, I will:

1. Include all subclasses of "international airport" (wd:Q644371) to capture airports that may be classified under a more specific subclass.
2. Consider airports that are located in any administrative sub-entity of Hamburg, not just directly in wd:Q1055.

To do this, I need:
- The property for "subclass of" (likely wd:P279).
- To find all entities that are either Hamburg (wd:Q1055) or its administrative sub-entities (using wd:P131 recursively or via the "contains administrative territorial entity" property).

First, let's confirm the property for "subclass of".

[Tool]
Top 10 property alternatives:
1. subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
2. is metaclass for, also known as instances are a subclass of, instances are subclasses of, instances are subclass of, is a metaclass for, is a metaclass of (wd:P8225 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): all instances of the subject are subclasses of the object
3. subproperty of, also known as subclass of property, superproperty, subPropertyOf, rdfs:subPropertyOf, parent property (wd:P1647 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): all resources related by this property are also related by that property, related property
4. facet of, also known as subitem of, topic of, subtopic of, subject in, section in (wd:P1269 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): topic of which this item is an aspect; item that offers a broader perspective on the same topic
5. narrower external class, also known as external subclass (wd:P3950 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): more specific subclass included in other ontology but not in Wikidata
6. metasubclass of, also known as metaclass of (wd:P2445 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): relation between two metaclasses: instances of this metaclass ar...subclasses of classes that are instances of the target metaclass
7. part of, also known as of, within, system of, subsystem of, subgroup of (wd:P361 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): object of which the subject is a part (if this subject is alread... of "has part" (P527, see also "has parts of the class" (P2670))
8. equivalent in higher rank taxon, also known as term in larger group, closest concept in higher taxon, term in higher taxon, term in higher-order taxon, subclass of higher-taxon concept (wd:P10019 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): an equivalent class that is species-neutral or scoped to higher ranking taxa, subclass of
9. equivalent class, also known as schema.org type, same kind of thing, same grouping, same class, external class (wd:P1709 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): equivalent class in other ontologies (use property URI), exact match, URL
10. part of the series, also known as series, video game series, subseries, part of series, listed in (wd:P179 as pqn/pqv/p/pq/ps/wdt/psn/prn/psv/prv/wdtn/pr): series which contains the subject, part of

[Assistant]
The property "subclass of" is wd:P279.

Now, to include all subclasses of "international airport", I will use a transitive closure on wd:P279.

Next, to include all administrative sub-entities of Hamburg, I need to find entities that are either Hamburg (wd:Q1055) or are located within Hamburg (directly or indirectly) via the "located in the administrative territorial entity" property (wd:P131). This can be done with a transitive closure on wd:P131.

Let's construct a query that:
- Finds all airports that are instances of "international airport" or any subclass thereof.
- Are located in Hamburg or any of its administrative sub-entities (using transitive closure on wd:P131).

I'll write the improved SPARQL query accordingly.

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

[Tool]
Got 1 row and 1 column:
| airport                     |
| --------------------------- |
| Hamburg Airport (wd:Q27706) |

[Tool]
Got 1 row and 1 column:
| airport                     |
| --------------------------- |
| Hamburg Airport (wd:Q27706) |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The query is mostly correct but could be improved for clarity and precision. The use of '?airport wdt:P31/wdt:P279* ?airportClass . ?airportClass wdt:P279* wd:Q644371 .' is unnecessarily complex. Instead, '?airport wdt:P31/wdt:P279* wd:Q644371' directly finds instances and subclasses of international airports. Also, the FILTER on ?place = wd:Q1055 is fine, but using '?airport wdt:P131* wd:Q1055' directly is clearer and more standard. The query should also ensure that only the IRIs are returned (which is the case here, as only the count is returned). Overall, the answer is correct, but the query can be simplified for maintainability and clarity.

[Tool] Stopped generation process


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 http://amur:7001

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

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

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

[User] When was HIV first identified?

[Assistant]
Let's break down the question:

1. The user is asking about the date when HIV was first identified.
2. The key entity is "HIV".
3. The property we need is something like "date of discovery", "date of identification", or similar.

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

[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 most relevant entity for "HIV" as a virus is wd:Q15787 (human immunodeficiency virus).

Next, I need to find a property related to "date of discovery" or "date of identification" for this entity. I will search for properties related to "discovery" for this entity.

[Tool]
Top 10 property alternatives:
1. 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
2. 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
3. has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as p/wdt): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).
4. has effect, also known as has symptom, implies, leads to, led to, outcome (wd:P1542 as p/wdt): effect of this item, followed by
5. ScienceDirect topic ID, also known as Science Direct topic ID, Science Direct topic identifier, ScienceDirect topic identifier (wd:P10376 as p/wdt): identifier for a topic on the research publication website ScienceDirect
6. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
7. external data available at URL, also known as data, external data URL, URL with external data (wd:P1325 as p/wdt): URL where external data on this item can be found
8. 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)
9. pronunciation audio, also known as listen, audio pronunciation (wd:P443 as p/wdt): audio file with pronunciation, audio
10. prevalence (wd:P1193 as p/wdt): portion in percent of a population with a given disease or disorder

No other items found

[Assistant]
The property "time of discovery or invention" (wdt:P575) is the most relevant for finding when HIV was first identified.

Next, I will construct a SPARQL query to retrieve the value of wdt:P575 for wd:Q15787 (HIV). I will also optionally retrieve a label for the date if available.

[Tool]
SPARQL execution failed:
Tried to allocate 5.9 GB, but only 1 GB were available. Clear the cache or allow more memory for QLever during startup

[Assistant] It seems the query failed due to a memory issue, likely because of the OPTIONAL clause on the date label. To avoid this, I will simplify the query to only retrieve the date value for the discovery of HIV, without the optional label.

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

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the date when HIV (wd:Q15787) was first identified using the property 'time of discovery or invention' (wdt:P575). The result matches the expected answer, and the query follows all required rules. No further refinement is needed.