PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT DISTINCT ?type ?typeLabel WHERE {
  wd:Q762 wdt:P800 ?work .
  ?work wdt:P31 ?type .
  OPTIONAL {
    ?type rdfs:label ?typeLabel .
    FILTER ( LANG( ?typeLabel ) = "en" )
  }
}

Got 14 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?type                             | ?typeLabel         |
| --------------------------------- | ------------------ |
| artistic theme (wd:Q1406161)      | artistic theme     |
| invention (wd:Q14208553)          | invention          |
| group of paintings (wd:Q18573970) | group of paintings |
| croquis (wd:Q217106)              | croquis            |
| study (wd:Q2647254)               | study              |
| ...                               | ...                |
| sketch (wd:Q5078274)              | sketch             |
| mirror writing (wd:Q835937)       | mirror writing     |
| Bible story (wd:Q856663)          | Bible story        |
| drawing (wd:Q93184)               | drawing            |
| wall painting (wd:Q99516640)      | wall painting      |

Leonardo da Vinci created various types of art, including paintings, drawings, and inventions.

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

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

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

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

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

[User] what type of art did leonardo da vinci make?

[Assistant] To answer the question about the types of art Leonardo da Vinci made, we need to identify the entity for Leonardo da Vinci and then find the types of art he created. We can start by searching for the entity "Leonardo da Vinci" in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Leonardo da Vinci (wd:Q762): Italian Renaissance polymath (1452−1519), architectural draftsperson, civil engineer, visual artist, mathematician, caricaturist, physiologist, philosopher, astronomer, architect, scientist, zoologist, anatomist, physicist, polymath, botanist, engineer, designer, composer, sculptor, inventor, diplomat, chemist, painter, writer
2. Leonardo da Vinci (wd:Q2530641): 1911 Conte di Cavour-class battleship
3. Leonardo da Vinci (wd:Q650366): 1939 Marconi-class submarine
4. Leonardo da Vinci: The Mind of the Renaissance, also known as Leonardo da Vinci (wd:Q101431569): 2001 documentary film by Jean-Claude Lubtchansky
5. Leonardo da Vinci (wd:Q18503359): human settlement
6. Leonardo da Vinci (wd:Q18498247): human settlement in Italy
7. Leonardo Da Vinci (wd:Q2115987): 1982 Sauro-class submarine
8. Rosa 'Leonardo da Vinci', also known as Leonardo da Vinci (wd:Q1819112): rose cultivar
9. RFA Maine, also known as Leonardo da Vinci (wd:Q3830354): steam ship
10. Leonardo da Vinci (wd:Q13749278): Dortmund –Milan passenger train

[Assistant] The top result for "Leonardo da Vinci" is the correct entity, which is `wd:Q762`. Now, we need to find out what types of art he created. We can look for properties related to his artistic works, such as paintings, sculptures, and drawings. Let's search for properties related to "art" or "works" for this entity.

[Tool]
Top 10 property alternatives:
1. notable work, also known as artwork, wrote, writer of, works, work (wd:P800 as p/wdt): notable scientific, artistic or literary work, or other work of significance among subject's works
2. Commons gallery, also known as gallery (wd:P935 as p/wdt): name of the Wikimedia Commons gallery page(s) related to this item (is suitable to allow multiple links to more gallery pages)
3. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as p/wdt): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
4. educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as p): educational institution attended by subject, affiliation
5. has works in the collection, also known as has items in the collection, works in collection, work in collection, museum housing this person's work, items in the collection (wd:P6379 as p/wdt): collection that has works of this person or organisation (use archives at [P485] for archives)
6. catalogue raisonné, also known as reasoned catalogue, artist catalogue, artist catalog, Art Catalog (wd:P9969 as p/wdt): comprehensive, annotated listing of all the known artworks by an artist either in a particular medium or all media., catalog
7. movement, also known as subculture, trend, scientific movement, school, philosophical movement (wd:P135 as p/wdt): literary, artistic, scientific or philosophical movement or scen...ed with this person or work. For political ideologies use P1142.
8. Artsy artist ID, also known as Artsy artist identifier, Artsy id (wd:P2042 as p/wdt): identifier at the Artsy website
9. 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)
10. Web Gallery of Art artist ID, also known as WGA artist id, WGA ID, Web Gallery of Art identifier, Web Gallery of Art ID (wd:P1882 as p/wdt): identifier for an artist in the Web Gallery of Art

No other items found

[Assistant]
From the search results, the property `wdt:P800` (notable work) seems to be the most relevant for finding the types of art Leonardo da Vinci created. We can use this property to find the specific works and then determine the types of art they represent. Let's execute a SPARQL query to retrieve the notable works of Leonardo da Vinci and their types.

### Step 1: Retrieve notable works of Leonardo da Vinci
We will start by retrieving the notable works of Leonardo da Vinci using the `wdt:P800` property.

```sparql
SELECT ?work ?workLabel
WHERE {
  wd:Q762 wdt:P800 ?work.
  OPTIONAL { ?work rdfs:label ?workLabel. FILTER(LANG(?workLabel) = "en") }
}
```

Let's execute this query to see the results.

[Tool]
Got 15 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?work                                             | ?workLabel                           |
| ------------------------------------------------- | ------------------------------------ |
| Annunciation (wd:Q1217213)                        | Annunciation                         |
| Mona Lisa (wd:Q12418)                             | Mona Lisa                            |
| The Last Supper (wd:Q128910)                      | The Last Supper                      |
| Annunciation (wd:Q154326)                         | Annunciation                         |
| Adoration of the Magi (wd:Q1638622)               | Adoration of the Magi                |
| ...                                               | ...                                  |
| The Virgin and Child with Saint Anne (wd:Q563727) | The Virgin and Child with Saint Anne |
| Portrait of Isabella d'Este (wd:Q591128)          | Portrait of Isabella d'Este          |
| Saint John the Baptist (wd:Q783215)               | Saint John the Baptist               |
| Head of a Woman (wd:Q797902)                      | Head of a Woman                      |
| Saint Jerome in the Wilderness (wd:Q972196)       | Saint Jerome in the Wilderness       |

[Assistant]
The query returned several notable works of Leonardo da Vinci. Next, we need to determine the types of these works. We can use the `wdt:P31` (instance of) property to find out what type of art each work is. Let's modify the query to include the type of each work.

### Step 2: Retrieve the types of notable works
We will add the `wdt:P31` property to the query to get the type of each work.

```sparql
SELECT ?work ?workLabel ?type ?typeLabel
WHERE {
  wd:Q762 wdt:P800 ?work.
  OPTIONAL { ?work rdfs:label ?workLabel. FILTER(LANG(?workLabel) = "en") }
  ?work wdt:P31 ?type.
  OPTIONAL { ?type rdfs:label ?typeLabel. FILTER(LANG(?typeLabel) = "en") }
}
```

Let's execute this query to see the results.

[Tool]
Got 25 rows and 4 columns, showing the first 5 and last 5 rows below:
| ?work                                    | ?workLabel                  | ?type                             | ?typeLabel         |
| ---------------------------------------- | --------------------------- | --------------------------------- | ------------------ |
| Annunciation (wd:Q154326)                | Annunciation                | artistic theme (wd:Q1406161)      | artistic theme     |
| Virgin of the Rocks (wd:Q269342)         | Virgin of the Rocks         | artistic theme (wd:Q1406161)      | artistic theme     |
| Leonardo's aerial screw (wd:Q212042)     | Leonardo's aerial screw     | invention (wd:Q14208553)          | invention          |
| Virgin of the Rocks (wd:Q269342)         | Virgin of the Rocks         | group of paintings (wd:Q18573970) | group of paintings |
| Portrait of Isabella d'Este (wd:Q591128) | Portrait of Isabella d'Este | croquis (wd:Q217106)              | croquis            |
| ...                                      | ...                         | ...                               | ...                |
| Vitruvian Man (wd:Q215486)               | Vitruvian Man               | mirror writing (wd:Q835937)       | mirror writing     |
| Annunciation (wd:Q154326)                | Annunciation                | Bible story (wd:Q856663)          | Bible story        |
| Vitruvian Man (wd:Q215486)               | Vitruvian Man               | drawing (wd:Q93184)               | drawing            |
| Portrait of Isabella d'Este (wd:Q591128) | Portrait of Isabella d'Este | drawing (wd:Q93184)               | drawing            |
| The Last Supper (wd:Q128910)             | The Last Supper             | wall painting (wd:Q99516640)      | wall painting      |

[Assistant]
The query results show the types of notable works created by Leonardo da Vinci. From the results, we can see that Leonardo da Vinci created various types of art, including paintings, drawings, and inventions. Here are some specific examples:

- **Paintings**: "Mona Lisa", "The Last Supper", "Virgin of the Rocks"
- **Drawings**: "Vitruvian Man", "Portrait of Isabella d'Este"
- **Inventions**: "Leonardo's aerial screw"

To provide a concise answer to the user's question, we can summarize the types of art Leonardo da Vinci made. Let's finalize the answer.

### Final Answer
Leonardo da Vinci created various types of art, including:
- Paintings
- Drawings
- Inventions

Here is the final SPARQL query and answer:

```sparql
SELECT DISTINCT ?type ?typeLabel
WHERE {
  wd:Q762 wdt:P800 ?work.
  ?work wdt:P31 ?type.
  OPTIONAL { ?type rdfs:label ?typeLabel. FILTER(LANG(?typeLabel) = "en") }
}
```

The types of art Leonardo da Vinci made are paintings, drawings, and inventions.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?currency WHERE {
  wd:Q399 wdt:P38 ?currency
}

The currency of Armenia is the Armenian dram.

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

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

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

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

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

[User] what is armenian currency?

[Assistant] To find out the Armenian currency, we need to identify the country Armenia and then look for the property that indicates its currency. Let's start by searching for the entity representing Armenia.

[Tool]
Top 10 entity alternatives:
1. Armenia, also known as AM, ARM, Hayastan, Hayastani Hanrapetut’yun, Republic of Armenia (wd:Q399): sovereign state in the South Caucasus region of Eurasia
2. Armenia (wd:Q328518): capital of the Colombian department of Quindío
3. First Republic of Armenia, also known as Armenia (wd:Q139670): Armenian state existing from 1918–1920
4. 780 Armenia, also known as (780) Armenia, Armenia (wd:Q157057): main-belt asteroid
5. Roman Armenia, also known as Armenia (wd:Q1254480): Roman province
6. Armenia, also known as Armenia, Antioquia (wd:Q934767): Colombian municipality of the department of Antioquia
7. Armenia (wd:Q682015): district in Eastern Sonsonate, El Salvador
8. Armenia, also known as Armenia, WI (wd:Q2219381): town in Wisconsin, United States
9. Armenia, also known as Armenia (historical region) (wd:Q4069598): historical territory
10. Armênia, also known as Armenia, Ponte Pequena (wd:Q5244779): metro station in São Paulo, Brazil

[Assistant] The correct entity for Armenia is `wd:Q399`. Now, let's find the property that indicates the currency of a country. We can search for properties related to "currency".

[Tool]
Top 10 property alternatives:
1. currency, also known as base currency, used money (wd:P38 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): currency used by item, uses
2. ISO 4217 code, also known as currency code, ISO 4217, ISO 4217 alphabetic code, ISO currency code (wd:P498 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): identifier for a currency per ISO 4217
3. price, also known as cost, exchange rate, list price, MSRP, published price (wd:P2284 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): published price listed or paid for a product (use with unit of currency)
4. prize money, also known as money, purse, value (wd:P2121 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): amount in a specific currency
5. cash (wd:P2232 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): the value of cash and securities held by a state government
6. currency symbol description (wd:P489 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): item with description of currency symbol, notation
7. face value, also known as coin value, numeric value of coin, value of coin (wd:P3934 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): value printed on a coin, stamp or banknote by the issuing authority
8. quantity, also known as amount, total number, total, qty, occurrences (wd:P1114 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/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)
9. item of property constraint, also known as claim value, value, qid, property value, item qualifier (wd:P2305 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): qualifier to define a property constraint in combination with "property constraint" (P2302)
10. numeric value, also known as numerical value, value (wd:P1181 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): numerical value of a number, a mathematical constant, or a physical constant

[Assistant] The property `wd:P38` seems to be the correct one for indicating the currency used by a country. Let's use this property to find the currency of Armenia (`wd:Q399`).

[Tool]
Got 1 row and 1 column:
| ?currency                  |
| -------------------------- |
| Armenian dram (wd:Q130498) |

[Assistant]
The currency of Armenia is the Armenian dram, represented by the entity `wd:Q130498`.

Now, let's provide the final answer.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?language WHERE {
  wd:Q225 wdt:P37 ?language .
}

Got 3 rows and 1 column:
| ?language           |
| ------------------- |
| Croatian (wd:Q6654) |
| Serbian (wd:Q9299)  |
| Bosnian (wd:Q9303)  |

The languages spoken by people from Bosnia and Herzegovina are Croatian, Serbian, and Bosnian.

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

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

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

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

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

[User] what language do people from bosnia speak?

[Assistant]
To answer the question about the languages spoken by people from Bosnia, we need to identify the relevant entities and properties in the knowledge graph. Here's the step-by-step approach:

1. **Identify the entity for Bosnia**: We need to find the IRI for Bosnia.
2. **Identify the property for languages spoken**: We need to find the property that links a country to the languages spoken there.
3. **Construct the SPARQL query**: Using the identified entities and properties, we will construct a SPARQL query to retrieve the languages spoken in Bosnia.

Let's start by searching for the entity for Bosnia.

### Step 1: Search for the entity for Bosnia
I will use the `search_entity` function to find the IRI for Bosnia.

[Tool]
Top 10 entity alternatives:
1. Bosnia and Herzegovina, also known as Bosnia-Herzegovina, Bosnia & Herzegovina, Bosnia and Hercegovina, Bosnia, BIH (wd:Q225): country in Southeast Europe
2. Bosnia (wd:Q188736): region in Bosnia and Herzegovina
3. Bosnia (wd:Q4947317): live album by Grand Funk Railroad
4. Bosna, also known as Bosnia (song), Bosnia (wd:Q25502969): Croatian song
5. Bosnia (wd:Q10433448): 1996 live album by Ulf Lundell
6. Bosnia (wd:Q29021052): song by Argentine musician Luis Alberto Spinetta in the álbum Spinetta y los Socios del Desierto
7. Bosnia (wd:Q103894070): encyclopedia article
8. Bosnia (wd:Q119441173): painting by James Potter (active 1998–2000), Royal Military Police Museum
9. Bosnia (wd:Q74241437): scientific article published on January 10, 1998
10. Bosnia (wd:Q80218280): photograph by Ron Haviv

[Assistant]
The top result for "Bosnia" is "Bosnia and Herzegovina" (wd:Q225), which is the correct entity for the country.

### Step 2: Identify the property for languages spoken
Next, we need to find the property that links a country to the languages spoken there. We can search for properties related to "language" or "spoken language".

I will use the `search_property` function to find the relevant property.

[Tool]
Top 10 property alternatives:
1. programmed in, also known as language, programming language, written in (wd:P277 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): the programming language(s) in which the software is developed
2. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): language(s) that a person or a people speaks, writes or signs, including the native language(s)
3. language of work or name, also known as language of the reference, language of URL, language of website, language of work, named in language (wd:P407 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): language associated with this creative work (such as books, show...guage" (P103) and "languages spoken, written or signed" (P1412))
4. official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): language designated as official by this item, language used
5. language used, also known as languages used, medium of instruction, used language, uses language, working language (wd:P2936 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): language widely used (spoken or written) in this place or at this event or organisation
6. language style, also known as manner, term register, obsolete, register, sense register (wd:P6191 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): to denote of the way a sense of a word is used, e.g., slang, vulgarism, babytalk, colloquialism, etc.
7. native language, also known as first language, L1 speaker of, language native, mother tongue (wd:P103 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): language or languages a person has learned from early childhood, languages spoken, written or signed
8. writing language, also known as languages of writings, languages written, language written, writing languages, language of works (wd:P6886 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): language in which the writer has written their work, languages spoken, written or signed
9. Ethnologue language status, also known as EGIDS, language status (wd:P3823 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): language status identifier by Ethnologue.com using EGIDS scale
10. variety of lexeme, form or sense, also known as dialect, used in dialect, variety of form (wd:P7481 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): dialect, graphic or phonetic variety that this lexeme, form or sense is used in

[Assistant]
The property "languages spoken, written or signed" (wd:P1412) seems to be the most appropriate for our purpose. It indicates the languages that a person or a people speaks, writes, or signs, including the native languages.

### Step 3: Construct the SPARQL query
Now, we can construct a SPARQL query to retrieve the languages spoken in Bosnia and Herzegovina (wd:Q225).

Here is the initial SPARQL query:

```sparql
SELECT ?language WHERE {
  wd:Q225 wdt:P1412 ?language .
}
```

Let's execute this query to see the results.

[Tool] Got no rows and 1 columns

[Assistant]
It appears that the property `wdt:P1412` (languages spoken, written or signed) does not yield any results for Bosnia and Herzegovina (wd:Q225). This might be because the property is more commonly used for individuals rather than countries.

Let's try another property, `wdt:P37` (official language), which is more likely to be used for countries.

### Step 4: Try the property for official languages
We will use the property `wdt:P37` to find the official languages of Bosnia and Herzegovina.

Here is the updated SPARQL query:

```sparql
SELECT ?language WHERE {
  wd:Q225 wdt:P37 ?language .
}
```

Let's execute this query to see the results.

[Tool]
Got 3 rows and 1 column:
| ?language           |
| ------------------- |
| Croatian (wd:Q6654) |
| Serbian (wd:Q9299)  |
| Bosnian (wd:Q9303)  |

[Assistant]
The SPARQL query using the property `wdt:P37` (official language) returned the official languages of Bosnia and Herzegovina, which are:

- Croatian (wd:Q6654)
- Serbian (wd:Q9299)
- Bosnian (wd:Q9303)

These are the languages spoken by people in Bosnia and Herzegovina.

### Final Answer
The languages spoken by people from Bosnia and Herzegovina are Croatian, Serbian, and Bosnian.

Here is the final SPARQL query and answer:

```sparql
SELECT ?language WHERE {
  wd:Q225 wdt:P37 ?language .
}
```

Answer: The languages spoken by people from Bosnia and Herzegovina are Croatian, Serbian, and Bosnian.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX skos: <http://www.w3.org/2004/02/skos/core#>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?label ?altLabel WHERE {
  wd:Q9299 rdfs:label ?label .
  FILTER ( LANG( ?label ) = "en" ) OPTIONAL {
    wd:Q9299 skos:altLabel ?altLabel
  }
  FILTER ( LANG( ?altLabel ) = "en" )
}

Got 2 rows and 2 columns:
| ?label  | ?altLabel        |
| ------- | ---------------- |
| Serbian | Serbian language |
| Serbian | sr               |

The Serbian language is called 'Serbian' in English, and it is also known as 'Srpski'.

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

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

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

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

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

[User] what is serbian language called?

[Assistant]
To answer the question "What is Serbian language called?", we need to identify the entity representing the Serbian language in the knowledge graph and then retrieve its label or alternative names.

First, let's search for the entity representing the Serbian language in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Serbian, also known as Srpski, Serbian language (wd:Q9299): standardized variety of Serbo-Croatian language used by Serbs
2. Sorbian, also known as Serbian language, Wendic language, Wendish (wd:Q25442): Lechitic language spoken by the Sorbs
3. Serbian language (wd:L616516-S1)
4. Serbian (language) (wd:L613158-S1)
5. History of Serbian, also known as Serbian language history (wd:Q31183797)
6. Serbian Sign Language (wd:Q113203025)
7. Serbian language in Croatia, also known as use of the Serbian language in Croatia (wd:Q20974148): overview about the use of the Serbian language in Croatia
8. Institute for Serbian Language (wd:Q16082649)
9. Serbian language in Montenegro (wd:Q65201055)
10. romanization of Serbian, also known as romanisation of Serbian, romanization of the Serbian language (wd:Q7362708): overview about the romanization of the Serbian language

[Assistant]
The top result for the search query "Serbian language" is the entity `wd:Q9299`, which represents the Serbian language. Now, let's retrieve the label and alternative names for this entity to see what it is called.

I will execute a SPARQL query to get the label and alternative names for the Serbian language.

[Tool]
Got 40,533 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?label               | ?altLabel            |
| -------------------- | -------------------- |
| "Afaan Sarbiyaa"@om  | "Amanung Serbiu"@pam |
| "Amanung Serbyu"@pam | "Amanung Serbiu"@pam |
| "an tSeirbis"@ga     | "Amanung Serbiu"@pam |
| "Bahasa Serbia"@kge  | "Amanung Serbiu"@pam |
| "Bahasa Serbia"@ms   | "Amanung Serbiu"@pam |
| ...                  | ...                  |
| "塞爾維亞文"@yue          | "塞爾維亞語"@zh           |
| "塞爾維亞語"@zh-hant      | "塞爾維亞語"@zh           |
| "塞爾維亞語"@zh-hk        | "塞爾維亞語"@zh           |
| "塞爾維亞語"@zh-mo        | "塞爾維亞語"@zh           |
| "塞爾維亞語"@zh-tw        | "塞爾維亞語"@zh           |

[Assistant]
The results show various labels and alternative labels for the Serbian language in different languages. However, the primary label in English is "Serbian," and some alternative labels include "Srpski."

To provide a clear and concise answer, I will focus on the English label and the most common alternative label.

Here is the final SPARQL query and answer:

```sparql
SELECT ?label ?altLabel WHERE {
  wd:Q9299 rdfs:label ?label .
  FILTER(LANG(?label) = "en")
  OPTIONAL { wd:Q9299 skos:altLabel ?altLabel }
  FILTER(LANG(?altLabel) = "en")
}
```

The Serbian language is called "Serbian" in English, and it is also known as "Srpski."

Now, I will provide the final answer.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?instrument ?instrumentLabel WHERE {
  wd:Q191499 wdt:P1303 ?instrument .
  OPTIONAL {
    ?instrument rdfs:label ?instrumentLabel .
    FILTER ( LANG( ?instrumentLabel ) = "en" )
  }
}

Got 4 rows and 2 columns:
| ?instrument         | ?instrumentLabel |
| ------------------- | ---------------- |
| cornet (wd:Q202027) | cornet           |
| piano (wd:Q5994)    | piano            |
| guitar (wd:Q6607)   | guitar           |
| violin (wd:Q8355)   | violin           |

Scott Joplin played the cornet, piano, guitar, and violin.

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

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

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

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

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

[User] what did scott joplin play?

[Assistant] To answer the question "What did Scott Joplin play?", we need to identify Scott Joplin as an entity and then find out what instruments he played. Let's start by searching for Scott Joplin in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Scott Joplin, also known as The king of Ragtime (wd:Q191499): American composer, musician, and pianist, jazz musician, banjoist, composer, pianist
2. Scott Joplin (wd:Q12127336): 1977 film by Jeremy Kagan
3. Scott Joplin (wd:Q28730081): painting by Ellen Banks
4. Scott Joplinlaan (wd:Q19513256): street in Eindhoven, the Netherlands
5. Scott Joplinrode (wd:Q19513257): street in Zoetermeer, the Netherlands
6. Scott Joplin: Piano Rags (wd:Q7436590): album by Joshua Rifkin
7. Scott Joplin's foot (wd:Q30538526): scientific article published on July 1, 1998
8. Scott Joplin: Questions Remain (wd:Q113214829): scientific article published on 18 April 2006
9. Scott Joplin: Complete Piano Works, also known as The Collected Works of Scott Joplin (wd:Q28156183): book by Scott Joplin
10. Scott Joplin’s New Rag (wd:Q29003610): ragtime composition for piano by Scott Joplin

[Assistant]
The top result for "Scott Joplin" is the American composer, musician, and pianist, which is the entity we are looking for. The IRI for this entity is `wd:Q191499`. Next, we need to find out what instruments he played. We can search for properties related to instruments or musical activities associated with Scott Joplin.

Let's search for properties related to instruments or musical activities for Scott Joplin.

[Tool]
Top 10 property alternatives:
1. instrument, also known as uses this instrument, teaches instrument, instruments, plays this instrument, plays instrument (wd:P1303 as p/wdt): musical instrument that a person plays or teaches or used in a music occupation, uses
2. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as p/wdt): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
3. 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. 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
5. signature, also known as signature image, image of signature, facsimiles, autograph (wd:P109 as p/wdt): image of a person's signature, image
6. 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)
7. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as p/wdt): work where this item is described, attested in
8. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as p/wdt): main Wikimedia category
9. 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)
10. notable work, also known as artwork, wrote, writer of, works, work (wd:P800 as p/wdt): notable scientific, artistic or literary work, or other work of significance among subject's works

No other items found

[Assistant]
The top result for properties related to instruments or musical activities is `wd:P1303`, which stands for "instrument" or "plays this instrument". This property indicates the musical instrument that a person plays. Let's use this property to find out what instruments Scott Joplin played.

We will execute a SPARQL query to retrieve the instruments associated with Scott Joplin.

```sparql
SELECT ?instrument WHERE {
  wd:Q191499 wdt:P1303 ?instrument .
}
```

Let's run this query.

[Tool]
Got 4 rows and 1 column:
| ?instrument         |
| ------------------- |
| cornet (wd:Q202027) |
| piano (wd:Q5994)    |
| guitar (wd:Q6607)   |
| violin (wd:Q8355)   |

[Assistant]
The SPARQL query returned the following instruments that Scott Joplin played:

- Cornet (wd:Q202027)
- Piano (wd:Q5994)
- Guitar (wd:Q6607)
- Violin (wd:Q8355)

To provide a more readable answer, we can include the labels of these instruments. However, since the question does not explicitly request labels, we will include them in optional clauses.

Here is the final SPARQL query:

```sparql
SELECT ?instrument ?instrumentLabel WHERE {
  wd:Q191499 wdt:P1303 ?instrument .
  OPTIONAL { ?instrument rdfs:label ?instrumentLabel . FILTER(LANG(?instrumentLabel) = "en") }
}
```

Let's run this query to get the final answer.

[Tool]
Got 4 rows and 2 columns:
| ?instrument         | ?instrumentLabel |
| ------------------- | ---------------- |
| cornet (wd:Q202027) | cornet           |
| piano (wd:Q5994)    | piano            |
| guitar (wd:Q6607)   | guitar           |
| violin (wd:Q8355)   | violin           |

[Assistant]
The final SPARQL query has successfully retrieved the instruments that Scott Joplin played along with their labels. Here are the results:

- Cornet (wd:Q202027)
- Piano (wd:Q5994)
- Guitar (wd:Q6607)
- Violin (wd:Q8355)

Therefore, the answer to the question "What did Scott Joplin play?" is:

Scott Joplin played the cornet, piano, guitar, and violin.

Here is the final SPARQL query and answer:

```sparql
SELECT ?instrument ?instrumentLabel WHERE {
  wd:Q191499 wdt:P1303 ?instrument .
  OPTIONAL { ?instrument rdfs:label ?instrumentLabel . FILTER(LANG(?instrumentLabel) = "en") }
}
```

Answer: Scott Joplin played the cornet, piano, guitar, and violin.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?job ?jobLabel WHERE {
  wd:Q81960 wdt:P106 ?job .
  OPTIONAL {
    ?job rdfs:label ?jobLabel .
    FILTER ( LANG( ?jobLabel ) = "en" )
  }
}

Got 5 rows and 2 columns:
| ?job                        | ?jobLabel    |
| --------------------------- | ------------ |
| farmer (wd:Q131512)         | farmer       |
| musicologist (wd:Q14915627) | musicologist |
| writer (wd:Q36180)          | writer       |
| poet (wd:Q49757)            | poet         |
| songwriter (wd:Q753110)     | songwriter   |

Robert Burns had the following jobs: Farmer, Musicologist, Writer, Poet, Songwriter.

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

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

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

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

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

[User] what jobs did robert burns have?

[Assistant]
To answer the question about the jobs Robert Burns had, we need to identify the entity for Robert Burns and then look for the property that represents his occupations or jobs.

First, let's search for the entity "Robert Burns" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Robert Burns, also known as Robbie Burns, Robden of Solway Firth, Scotland's favorite son, The Bard, Rabbie Burns (wd:Q81960): Scottish poet and lyricist (1759–1796), musicologist, songwriter, farmer, writer, poet
2. Robert Hunter, also known as Robert C. Christie Hunter, Robert Burns (wd:Q1375663): American lyricist, musician, singer-songwriter, translator, and poet, songwriter, translator, guitarist, lyricist, musician, writer, singer, poet
3. Bob Burns, also known as Robin Burn, Robin William Burn, Robert Burns, Robbie Burn (wd:Q887831): American musical comedian (1890–1956), radio personality, businessperson, film actor, comedian, musician
4. Robert Burns, also known as Robert Clayton Burns (wd:Q7342516): British artist (1869-1941), visual artist, art educator, designer, painter
5. Robert Burns (wd:Q27824730): Australian cyclist, sport cyclist
6. Robert Burns (wd:Q2156654): American politician (1792-1866), politician
7. Robert Burns, also known as William Robert Burns (wd:Q15997904): American attorney and politician in Oklahoma (1874-1950), politician, lawyer
8. Robert Burns (wd:Q3434685): Canadian politician (1936–2014), trade unionist, politician, lawyer, judge
9. Bob Burns III, also known as Bob Burns, Robert Burns, Kogar (wd:Q4931984): American film historian and actor, property designer, film historian, film actor
10. Robert H. Burns, also known as Robert Burns (wd:Q16066723): American politician in Wisconsin (1870-19__), politician

[Assistant]
The top result for "Robert Burns" is the Scottish poet and lyricist, which matches the context of the question. Let's use this entity (wd:Q81960) and find the property that represents his occupations or jobs.

Next, let's search for the property that represents occupation or job in Wikidata.

[Tool]
Top 10 property alternatives:
1. occupation, also known as job, work, vocation, profession, employment (wd:P106 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
2. field of this occupation, also known as practice, works in, profession's field, practices, field of this profession (wd:P425 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): field corresponding to this occupation or profession (use only f...fessions - for people use Property:P101, for companies use P452)
3. members have occupation, also known as profession of members, organization of, organization for, organisation of, organisation for (wd:P3989 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): some or all members of this group share the occupation
4. practiced by, also known as proponent, studied by, practitioners, practioner, occupation of this field (wd:P3095 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): type of agents that study this subject or work in this field
5. position held, also known as function, held position, holds position, job, office held (wd:P39 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): subject currently or formerly holds the object position or public office
6. employer, also known as working at, working for, working place, works at, works for (wd:P108 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): person or organization for which the subject works or worked, affiliation
7. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): the object is a country that recognizes the subject as its citizen, country
8. occupant, also known as tenant, resident, renter, occupiers, lessee (wd:P466 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): person or organization occupying property, used by
9. field of work, also known as scientific discipline, scientific area, responsible for, research on, research fields (wd:P101 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): specialization of a person or organization; see P106 for the occupation, interested in
10. work location, also known as work place, working from, working at, worked from, worked at (wd:P937 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): location where persons or organisations were actively participating in employment, business or other work, significant place, location

[Assistant]
The property "occupation" (wd:P106) is the most relevant for finding the jobs or professions of a person. Now, let's construct a SPARQL query to find the occupations of Robert Burns (wd:Q81960).

Here is the initial SPARQL query:

```sparql
SELECT ?job WHERE {
  wd:Q81960 wdt:P106 ?job .
}
```

Let's execute this query to see the results.

[Tool]
Got 5 rows and 1 column:
| ?job                        |
| --------------------------- |
| farmer (wd:Q131512)         |
| musicologist (wd:Q14915627) |
| writer (wd:Q36180)          |
| poet (wd:Q49757)            |
| songwriter (wd:Q753110)     |

[Assistant]
The SPARQL query has returned the following occupations for Robert Burns:

- Farmer (wd:Q131512)
- Musicologist (wd:Q14915627)
- Writer (wd:Q36180)
- Poet (wd:Q49757)
- Songwriter (wd:Q753110)

These results match the expected occupations of Robert Burns. To provide a more complete answer, we can include the labels of these occupations in the query. However, since the labels are optional, we will use an `OPTIONAL` clause to fetch them.

Here is the refined SPARQL query:

```sparql
SELECT ?job ?jobLabel WHERE {
  wd:Q81960 wdt:P106 ?job .
  OPTIONAL { ?job rdfs:label ?jobLabel . FILTER(LANG(?jobLabel) = "en") }
}
```

Let's execute this query to get the labels as well.

[Tool]
Got 5 rows and 2 columns:
| ?job                        | ?jobLabel    |
| --------------------------- | ------------ |
| farmer (wd:Q131512)         | farmer       |
| musicologist (wd:Q14915627) | musicologist |
| writer (wd:Q36180)          | writer       |
| poet (wd:Q49757)            | poet         |
| songwriter (wd:Q753110)     | songwriter   |

[Assistant]
The refined SPARQL query has successfully returned the occupations of Robert Burns along with their labels:

- Farmer (wd:Q131512)
- Musicologist (wd:Q14915627)
- Writer (wd:Q36180)
- Poet (wd:Q49757)
- Songwriter (wd:Q753110)

These results provide a clear and complete answer to the question. Therefore, we can finalize the answer.

Here is the final SPARQL query and the answer:

```sparql
SELECT ?job ?jobLabel WHERE {
  wd:Q81960 wdt:P106 ?job .
  OPTIONAL { ?job rdfs:label ?jobLabel . FILTER(LANG(?jobLabel) = "en") }
}
```

Answer: Robert Burns had the following jobs:
- Farmer
- Musicologist
- Writer
- Poet
- Songwriter

Now, let's provide the final answer using the `answer` function.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?zipCode WHERE {
  wd:Q5083 wdt:P281 ?zipCode .
}

One of the zip codes for Seattle, Washington is 98101. Note that Seattle has multiple zip codes, and this is just one of them.

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

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

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

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

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

[User] what the zip code for seattle washington?

[Assistant] To find the zip code for Seattle, Washington, we need to identify the entity for Seattle and then look for a property that represents the zip code or postal code. Let's start by searching for the entity representing Seattle.

[Tool]
Top 10 entity alternatives:
1. Seattle, also known as Seattle, WA, Seattle, Washington, Duwamps, New York Alki (wd:Q5083): city in and county seat of King County, State of Washington, United States
2. Seattle Washington Temple (wd:Q3844785): temple of the Church of Jesus Christ of Latter-day Saints in Bellevue, Washington
3. Washington Park, also known as Washington Park, Seattle (wd:Q7972093)
4. "Carole, Seattle, Washington" (wd:Q64144357): photograph in the National Gallery of Art (NGA 135163)
5. East Seattle, also known as East Seattle, WA, East Seattle, Washington (wd:Q122593560): populated place in King County, Washington, United States
6. Seattle, Washington Auditions (wd:Q114507485): episode of American Idol (S6 E2)
7. Seattleites, also known as Seattle, Washington, residents, Seattlites, Seattlers (wd:Q55779668): people from or residents of Seattle, Washington
8. Seattle Hill, also known as Seattle Hill, WA, Seattle Hill, Washington (wd:Q122540504): populated place in Snohomish County, Washington, United States
9. Seattle Heights, also known as Seattle Heights, WA, Seattle Heights, Washington (wd:Q122543838): neighborhood in Snohomish County, Washington, United States
10. University of Washington, also known as UW, washington.edu, UW-Seattle, U. of W., U of W (wd:Q219563): public research university in Seattle, Washington, United States

[Assistant] The top result for "Seattle, Washington" is `wd:Q5083`, which represents the city of Seattle. Now, let's find the property that represents the zip code or postal code. We can search for properties related to "zip code" or "postal code" and see if they are used for the entity `wd:Q5083`.

[Tool]
Top 10 property alternatives:
1. postal code, also known as pincode, PIN Code, postal index number, post code, postcode (wd:P281 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): identifier assigned by postal authorities for the subject area or building
2. local dialing code, also known as area code, dialling code, local calling code, local dialling code, STD code (wd:P473 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): identifier dedicated to subject city by the area communication network
3. country calling code, also known as calling code, country code, country dialing code, dialing code, phone code (wd:P474 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): identifier for a country - dialed on phone after the international dialing prefix (precede value by +)
4. location code (wd:P13262 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): an assigned code for the location (physical or virtual) within a given system (please use more specific property if available), catalog code
5. CDDA designationTypeCode, also known as designated area code, CDDA type ID, CDDA type, CDDA, CDDA code (wd:P9800 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): code for the national designation type used in the Common Database on Designated Areas inventory (CDDA)
6. Dictionary of Occupational Titles Code (fourth edition, revised), also known as DOT code (wd:P8679 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): occupation code from the Dictionary of Occupational Titles, fourth edition, revised
7. post office box, also known as PO Box, Post Office Box, P.O. Box, P. O. Box, P O Box (wd:P2918 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): post office box number, as part of an address
8. quantity, also known as amount, total number, total, qty, occurrences (wd:P1114 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/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)
9. series ordinal, also known as ordinal, unit number, sort order, sorting order, series number (wd:P1545 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): position of an item in its parent series (most frequently a 1-ba...d from "ranking" defined as a property for evaluating a quality)
10. issue, also known as number, no., issue number (wd:P433 as pqv/psv/wdt/pq/psn/p/pqn/prn/ps/wdtn/prv/pr): issue of a newspaper, a scientific journal or magazine for reference purpose

[Assistant] The property `wd:P281` represents the postal code or zip code. Let's check if this property is used for the entity `wd:Q5083` (Seattle, Washington).

[Tool]
Got 1 row and 3 columns:
| subject            | property               | object |
| ------------------ | ---------------------- | ------ |
| Seattle (wd:Q5083) | postal code (wdt:P281) | 98101  |

[Assistant]
The entity `wd:Q5083` (Seattle, Washington) has the postal code `98101`. However, it's important to note that Seattle has multiple zip codes, and this is just one of them. To get a more comprehensive list of zip codes for Seattle, we can modify the query to return all zip codes associated with the city.

Let's execute a SPARQL query to retrieve all zip codes for Seattle, Washington.

[Tool]
Got 1 row and 1 column:
| ?zipCode |
| -------- |
| 98101    |

[Assistant]
The SPARQL query returned only one zip code, `98101`, for Seattle, Washington. However, Seattle has multiple zip codes. This suggests that the data in Wikidata might be incomplete or that there might be other entities or properties that represent additional zip codes for Seattle.

To get a more comprehensive list, we can try to find other entities that are part of Seattle and check if they have their own zip codes. For example, neighborhoods or specific locations within Seattle might have their own zip codes.

Let's search for entities that are part of Seattle and then check if they have zip codes.

[Tool]
Top 10 entity alternatives:
1. Active Seattle: achieving walkability in diverse neighborhoods (wd:Q38433285): scientific article published on December 2009
2. Seattle, also known as Seattle, WA, Seattle, Washington, Duwamps, New York Alki (wd:Q5083): city in and county seat of King County, State of Washington, United States
3. Chief Seattle, also known as See-ahth, Noah, Sealth, Seathl, Seattle (wd:Q216477): traditional leader or chief, Duwamish chief
4. Neighborhoods (wd:Q930644): album by Blink-182
5. Star City, also known as Seattle, Starling City (wd:Q1419655): fictional city in DC comics
6. Seattle (wd:Q7442047): song composed in the late 1960s
7. Seattle (wd:Q7442046): album by Perry Como
8. Seattle (wd:Q17462536): arcade system board
9. Dahlia 'Seattle', also known as Seattle (wd:Q21160665): Dahlia cultivar
10. Neighborhoods (wd:Q6988056): album by Olu Dara

[Assistant]
The search for "Seattle neighborhoods" did not return any specific neighborhoods within Seattle. Instead, it returned the city of Seattle itself and some unrelated entities.

Since the direct search for neighborhoods did not yield useful results, let's try a different approach. We can look for entities that are part of Seattle and then check if they have zip codes. For example, we can search for specific locations or landmarks within Seattle and see if they have zip codes.

Let's search for specific locations within Seattle and check if they have zip codes.

[Tool]
Top 10 entity alternatives:
1. Seattle, also known as Seattle, WA, Seattle, Washington, Duwamps, New York Alki (wd:Q5083): city in and county seat of King County, State of Washington, United States
2. Chief Seattle, also known as See-ahth, Noah, Sealth, Seathl, Seattle (wd:Q216477): traditional leader or chief, Duwamish chief
3. Star City, also known as Seattle, Starling City (wd:Q1419655): fictional city in DC comics
4. Seattle (wd:Q7442047): song composed in the late 1960s
5. Seattle (wd:Q7442046): album by Perry Como
6. Seattle (wd:Q17462536): arcade system board
7. Dahlia 'Seattle', also known as Seattle (wd:Q21160665): Dahlia cultivar
8. Seattle (wd:Q16164200): single
9. SEATTLE (wd:Q130951105): scientific article published on 03 March 2011
10. SEATTLE (wd:Q127035753): hymn tune

[Assistant]
The search for "Seattle locations" also did not return any specific locations within Seattle. It seems that the search terms might need to be more specific to find entities that are part of Seattle.

Let's try a more targeted approach by searching for specific well-known locations within Seattle, such as the Space Needle, Pike Place Market, or the Seattle Center, and check if they have zip codes.

I'll start with the Space Needle.

[Tool]
Top 10 entity alternatives:
1. Space Needle (wd:Q5317): Observation tower in Seattle, Washington, U.S.
2. Space Needle (wd:Q7572437): American rock band
3. Gatlinburg Space Needle (wd:Q5527454): 407 feet (124 m) tall observation tower in Gatlinburg, Tennessee, United States
4. Golden Space Needle, also known as Golden Space Needle Award (wd:Q16034443)
5. Space Needle VR (wd:Q124073923): 2017 video game
6. The Needles the Space (wd:Q7753364): album by Straylight Run
7. A Shock at the Space Needle (wd:Q114536451): episode of Top Chef: Seattle (S10 E2)
8. Photonic Needle and Paravertebral Space Detection (wd:Q64645642): clinical trial
9. Veres needle in the pleural space (wd:Q71084596): scientific article published on 01 November 1983
10. The Moray Eels Eat the Space Needle (wd:Q7752231): album by Space Needle

[Assistant] The top result for "Space Needle" is `wd:Q5317`, which represents the Space Needle in Seattle, Washington. Let's check if this entity has a zip code associated with it.

[Tool] Got no rows and 3 columns

[Assistant]
It appears that the Space Needle entity (`wd:Q5317`) does not have a zip code associated with it in Wikidata. Let's try another well-known location in Seattle, such as Pike Place Market, to see if it has a zip code.

I'll search for Pike Place Market next.

[Tool]
Top 10 entity alternatives:
1. Pike Place Market, also known as Pike Place Public Market Historic District, The Market, Pike Market (wd:Q1373418): public market and tourist attraction in Seattle, Washington
2. Pike Place Fish Market (wd:Q7193593): fish market in Seattle, Washington
3. history of the Pike Place Market, also known as Pike Place Market history, the Pike Place Market history (wd:Q5870226): aspect of history
4. Pike Place Market Centennial (wd:Q133170057): online exhibition from Seattle Municipal Archives
5. Pike Place Market Foundation (wd:Q30268105): nonprofit organization in Seattle, United States
6. History of Pike Place Market (wd:Q116007248)
7. The Pike Place Market Foundation (wd:Q54812379): American nonprofit organization
8. Mandi, also known as Market Place (wd:Q6748044): 1983 film by Shyam Benegal
9. Mandi, also known as Market Place (wd:Q6748044): 1983 film by Shyam Benegal
10. Victoria Square, also known as Market Place, Market Square (wd:Q14702857): square in central Christchurch, New Zealand

[Assistant] The top result for "Pike Place Market" is `wd:Q1373418`, which represents the Pike Place Market in Seattle, Washington. Let's check if this entity has a zip code associated with it.

[Tool] Got no rows and 3 columns

[Assistant]
It appears that the Pike Place Market entity (`wd:Q1373418`) also does not have a zip code associated with it in Wikidata. Given that the main entity for Seattle (`wd:Q5083`) and some well-known locations within Seattle do not have zip codes listed, it suggests that the data in Wikidata might be incomplete for this specific information.

However, we can still provide the zip code that we found earlier, which is `98101`, and note that Seattle has multiple zip codes. Here is the final SPARQL query and answer:

```sparql
SELECT ?zipCode WHERE {
  wd:Q5083 wdt:P281 ?zipCode .
}
```

Answer: One of the zip codes for Seattle, Washington is 98101. Note that Seattle has multiple zip codes, and this is just one of them.

Let's finalize this with the answer function.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?boyfriend WHERE {
  wd:Q575689 wdt:P451 ?boyfriend .
}

Kourtney Kardashian's boyfriends are Younes Bendjima and Scott Disick.

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

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

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

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

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

[User] what kourtney kardashian boyfriends name?

[Assistant] To find Kourtney Kardashian's boyfriend's name, we need to identify Kourtney Kardashian in the knowledge graph and then look for her relationships, specifically her current or past boyfriends. Let's start by searching for Kourtney Kardashian.

[Tool]
Top 10 entity alternatives:
1. Kourtney Kardashian, also known as Kourtney Kardashian Barker, Kourtney Mary Kardashian, Kourtney (wd:Q575689): American media personality, model and businesswoman (born 1979), media personality, fashion designer, television actor, businessperson, entrepreneur, socialite, celebrity, actor, model
2. Kardashian (wd:Q56538884): family name
3. Kourtney (wd:Q101065644): unisex given name
4. Kanye West, also known as Ye, Kanye Omari West, Yeezy, Kanye Kardashian, Kanye (wd:Q15935): American rapper, record producer, singer and fashion designer (born 1977), fashion designer, record producer, businessperson, entrepreneur, songwriter, director, singer, rapper
5. Kim Kardashian, also known as Kim Kardashian West, Kim K, Kim K., Kimberly Noel Kardashian-West, Kim Kardashian-West (wd:Q186304): American media personality, businesswoman, model and actress (born 1980), erotic photography model, television producer, fashion designer, entrepreneur, voice actor, celebrity, socialite, blogger, actor, model
6. Khloé Kardashian, also known as Khloé Kardashian Odom, Khloé Kardashian-Odom, Khloe Kardashian Odom, Khloe Kardashian, Khloe Odom (wd:Q231270): American media personality,influencer, businesswoman (born 1984), radio personality, television actor, fashion designer, film producer, manufacturer, entrepreneur, film actor, socialite, celebrity, novelist, writer, actor, model
7. Kris Jenner, also known as Kristen Mary Jenner, Kristen Jenner, Kristen Mary Houghton, Kristen Mary "Kris" Jenner, Chris Jenner (wd:Q1138235): American media personality, socialite, and businesswoman, television presenter, television producer, flight attendant, celebrity, socialite, author, actor
8. Robert Kardashian, also known as Robert George Kardashian, Rob Kardashian, Robert G. Kardashian (wd:Q1816737): American attorney and businessman (1944–2003), entrepreneur, jurist, lawyer
9. Rob Kardashian, also known as Robert Arthur Kardashian (wd:Q26318): American television personality and businessman, television actor, businessperson, socialite, model
10. Kardashian-Jenner family, also known as Kardashian family, Kardashians (wd:Q95747857): American family prominent in entertainment, business, and fashion

[Assistant]
The top result for Kourtney Kardashian is `wd:Q575689`. Now, let's find out who her current or past boyfriends are. We will look for properties related to relationships, such as "spouse," "partner," or "boyfriend."

First, let's search for properties related to relationships for Kourtney Kardashian.

[Tool]
Top 10 property alternatives:
1. unmarried partner, also known as romantic partner, partner of, partners, posslq, relationship (wd:P451 as p/wdt): someone with whom the person is in a relationship without being married. Use "spouse" (P26) for married couples, significant person
2. 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
3. relative, also known as relatives, grandparent, relation, non-binary parent, niece (wd:P1038 as p/wdt): family member (qualify with "kinship to subject", P1039; for direct family member please use specific property), significant person
4. father, also known as son of, child of, parent, is son of, is daughter of (wd:P22 as p/wdt): male parent of the subject. For stepfather, use "stepparent" (P3448), parent
5. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as p/wdt): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)
6. sibling, also known as is sister of, is the brother of, is the sibling of, is the sister of, sib (wd:P3373 as p/wdt): the subject and the object have at least one common parent (brot...law, etc.) and step-siblings (step-brothers, step-sisters, etc.), relative
7. Instagram username, also known as IG username, www.instagram.com, urinsta, ufinsta, Insta ID (wd:P2003 as p/wdt): item's username on Instagram, website username or ID
8. stepparent, also known as step-parent, step parent, stepmother, step-mother, step mother (wd:P3448 as p/wdt): subject has the object as their stepparent, relative
9. child, also known as has son, kids, mother of, kid, issue (wd:P40 as p/wdt): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative
10. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)

No other items found

[Assistant]
The property `wdt:P451` (unmarried partner) seems to be the most relevant for finding Kourtney Kardashian's boyfriend. Let's execute a SPARQL query to find the value of this property for Kourtney Kardashian.

Here is the SPARQL query:

```sparql
SELECT ?boyfriend
WHERE {
  wd:Q575689 wdt:P451 ?boyfriend .
}
```

Let's run this query to find the name of Kourtney Kardashian's boyfriend.

[Tool]
Got 2 rows and 1 column:
| ?boyfriend                     |
| ------------------------------ |
| Younes Bendjima (wd:Q55200042) |
| Scott Disick (wd:Q7883337)     |

[Assistant]
The SPARQL query returned two results for Kourtney Kardashian's boyfriends: Younes Bendjima and Scott Disick. To provide a more complete answer, we can include both names in our response.

Here is the final SPARQL query and the answer:

```sparql
SELECT ?boyfriend
WHERE {
  wd:Q575689 wdt:P451 ?boyfriend .
}
```

Answer: Kourtney Kardashian's boyfriends are Younes Bendjima and Scott Disick.

Let's finalize this with the answer function.

[Tool] Stopped generation process