PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT DISTINCT ?work ?workLabel ?type ?typeLabel WHERE {
  VALUES ( ?work ?type ) {
    ( wd:Q1217213 wd:Q3305213 ) ( wd:Q12418 wd:Q3305213 ) ( wd:Q128910 wd:Q99516640 ) ( wd:Q154326 wd:Q1406161 ) ( wd:Q154326 wd:Q375011 ) ( wd:Q474338 wd:Q3305213 ) ( wd:Q563727 wd:Q3305213 ) ( wd:Q591128 wd:Q217106 ) ( wd:Q591128 wd:Q2647254 ) ( wd:Q591128 wd:Q5078274 )
  }
  ?work rdfs:label ?workLabel .
  ?type rdfs:label ?typeLabel .
  FILTER ( LANG( ?workLabel ) = 'en' ) .
  FILTER ( LANG( ?typeLabel ) = 'en' )
}

Got 10 rows and 4 columns:
| ?work                                             | ?workLabel                           | ?type                                           | ?typeLabel                         |
| ------------------------------------------------- | ------------------------------------ | ----------------------------------------------- | ---------------------------------- |
| Annunciation (wd:Q1217213)                        | Annunciation                         | painting (wd:Q3305213)                          | painting                           |
| Mona Lisa (wd:Q12418)                             | Mona Lisa                            | painting (wd:Q3305213)                          | painting                           |
| The Last Supper (wd:Q128910)                      | The Last Supper                      | wall painting (wd:Q99516640)                    | wall painting                      |
| Annunciation (wd:Q154326)                         | Annunciation                         | artistic theme (wd:Q1406161)                    | artistic theme                     |
| Annunciation (wd:Q154326)                         | Annunciation                         | religious and cultural festive day (wd:Q375011) | religious and cultural festive day |
| Lady with an Ermine (wd:Q474338)                  | Lady with an Ermine                  | painting (wd:Q3305213)                          | painting                           |
| The Virgin and Child with Saint Anne (wd:Q563727) | The Virgin and Child with Saint Anne | painting (wd:Q3305213)                          | painting                           |
| Portrait of Isabella d'Este (wd:Q591128)          | Portrait of Isabella d'Este          | croquis (wd:Q217106)                            | croquis                            |
| Portrait of Isabella d'Este (wd:Q591128)          | Portrait of Isabella d'Este          | study (wd:Q2647254)                             | study                              |
| Portrait of Isabella d'Este (wd:Q591128)          | Portrait of Isabella d'Este          | sketch (wd:Q5078274)                            | sketch                             |

Leonardo da Vinci created various types of art, including paintings, wall paintings, and sketches. Some of his notable works include the 'Annunciation,' 'Mona Lisa,' 'The Last Supper,' 'Lady with an Ermine,' 'The Virgin and Child with Saint Anne,' and 'Portrait of Isabella d'Este.'

[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'll start by searching for 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

No other items found

[Assistant]
The top result for "Leonardo da Vinci" is the correct entity (wd:Q762). Next, we need to find the types of art he created. We will look for properties that indicate the type of art he produced, such as paintings, sculptures, etc.

Let's list the triples where Leonardo da Vinci (wd:Q762) is the subject to see what properties and objects are associated with him.

[Tool]
Got 2,190 rows and 3 columns, showing the first 10 rows below:
| subject                     | property                         | object                                                                                |
| --------------------------- | -------------------------------- | --------------------------------------------------------------------------------------------------------- |
| Leonardo da Vinci (wd:Q762) | instance of (wdt:P31)            | human (wd:Q5)                                                                                |
| Leonardo da Vinci (wd:Q762) | occupation (wdt:P106)            | writer (wd:Q36180)                                                                                |
| Leonardo da Vinci (wd:Q762) | sex or gender (wdt:P21)          | male (wd:Q6581097)                                                                                |
| Leonardo da Vinci (wd:Q762) | given name (wdt:P735)            | Leonardo (wd:Q18220847)                                                                                |
| Leonardo da Vinci (wd:Q762) | date of birth (wdt:P569)         | 1452-04-24T00:00:00Z                                                                                |
| Leonardo da Vinci (wd:Q762) | Commons category (wdt:P373)      | Leonardo da Vinci                                                                                |
| Leonardo da Vinci (wd:Q762) | image (wdt:P18)                  | <http://commons.wikimedia.org/wiki/Special:FilePath/Francesco%20Melzi%20-%20Portrait%20of%20Leonardo.png> |
| Leonardo da Vinci (wd:Q762) | country of citizenship (wdt:P27) | Republic of Florence (wd:Q148540)                                                                         |
| Leonardo da Vinci (wd:Q762) | family name (wdt:P734)           | da Vinci (wd:Q106449498)                                                                                |
| Leonardo da Vinci (wd:Q762) | described at URL (wdt:P973)      | <http://library.aur.edu/cgi-bin/koha/opac-authoritiesdetail.pl?marc=1&authid=26350>                       |
| ...                         | ...                              | ...                                                                                |

[Assistant]
From the list of triples, we can see that Leonardo da Vinci has various occupations listed, including "writer." However, we need to specifically find the types of art he created. One relevant property might be "notable work" (P800), which can give us an idea of the types of artworks he produced.

Let's search for the property "notable work" and see if it is used with Leonardo da Vinci.

[Tool]
Top 10 property alternatives:
1. notable work, also known as artwork, wrote, writer of, works, work (wd:P800 as wdt/p): notable scientific, artistic or literary work, or other work of significance among subject's works
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. 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 wdt/p): collection that has works of this person or organisation (use archives at [P485] for archives)
4. field of work, also known as scientific discipline, scientific area, responsible for, research on, research fields (wd:P101 as wdt/p): specialization of a person or organization; see P106 for the occupation, interested in
5. Notable Names Database, also known as NNDB ID, Notable Names Database people ID, Notable Names Database ID (wd:P1263 as wdt/p): identifier in the Notable Names Database, a biographical database: only for people entries
6. catalogue raisonné, also known as reasoned catalogue, artist catalogue, artist catalog, Art Catalog (wd:P9969 as wdt/p): comprehensive, annotated listing of all the known artworks by an artist either in a particular medium or all media., catalog
7. 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)
8. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as wdt/p): work where this item is described, attested in
9. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as wdt/p): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
10. different from, also known as not to be confused with, to be distinguished from, similar to, see also, rejected match (wd:P1889 as wdt/p): item that is different from another item, with which it may be confused

No other items found

[Assistant]
The property "notable work" (P800) is indeed used with Leonardo da Vinci. Let's use this property to find the notable works of Leonardo da Vinci and then determine the types of art these works represent.

We will execute a SPARQL query to retrieve the notable works of Leonardo da Vinci and their types.

[Tool]
Got 10 rows and 2 columns:
| ?work                      | ?workLabel            |
| -------------------------- | --------------------- |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt     |
| Annunciation (wd:Q1217213) | "Angyali üdvözlet"@hu |
| Annunciation (wd:Q1217213) | Annunciation          |
| Annunciation (wd:Q1217213) | "Annunciazione"@it    |
| Annunciation (wd:Q1217213) | "Anunciación"@es      |
| Annunciation (wd:Q1217213) | "Anunciación"@gl      |
| Annunciation (wd:Q1217213) | "Bebådelsen"@sv       |
| Annunciation (wd:Q1217213) | "Bebudelsen"@da       |
| Annunciation (wd:Q1217213) | "Buna Vestire"@ro     |
| Annunciation (wd:Q1217213) | "Cyfarchiad Mair"@cy  |

[Assistant]
It seems that the query returned multiple labels for the same work, "Annunciation." To get a clearer picture, we should limit the results to distinct works and also try to find the types of these works. We can use the property "instance of" (P31) to determine the type of each work.

Let's refine the query to include the type of each notable work.

[Tool]
Got 10 rows and 4 columns:
| ?work                      | ?workLabel        | ?type                  | ?typeLabel     |
| -------------------------- | ----------------- | ---------------------- | -------------- |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "bức tranh"@vi |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "dipinto"@it   |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "festmény"@hu  |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "Gemälde"@de   |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "glezna"@lv    |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "livadur"@br   |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "lukisan"@id   |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "maal"@et      |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "maalaus"@fi   |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "malba"@cs     |

[Assistant]
The query results show that the notable work "Annunciation" is classified as a painting. To get a more comprehensive list of the types of art Leonardo da Vinci created, we should expand the query to include more of his notable works and their types.

Let's execute a query to retrieve the notable works and their types, ensuring we get a variety of works and their classifications.

[Tool]
Got 20 rows and 4 columns, showing the first 5 and last 5 rows below:
| ?work                      | ?workLabel        | ?type                  | ?typeLabel     |
| -------------------------- | ----------------- | ---------------------- | -------------- |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "bức tranh"@vi |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "dipinto"@it   |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "festmény"@hu  |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "Gemälde"@de   |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "glezna"@lv    |
| ...                        | ...               | ...                    | ...            |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "Malōnek"@szl  |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "margolan"@eu  |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "mólba"@hsb    |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "Moleri"@srn   |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "obraz"@pl     |

[Assistant]
It appears that the query is still returning multiple labels for the same work, "Annunciation," and the type is consistently "painting." To get a more diverse set of works and their types, we need to ensure we are retrieving distinct works and their types.

Let's refine the query to ensure we get distinct works and their types, and limit the results to a reasonable number to check the variety of types of art.

[Tool]
Got 20 rows and 4 columns, showing the first 5 and last 5 rows below:
| ?work                      | ?workLabel        | ?type                  | ?typeLabel     |
| -------------------------- | ----------------- | ---------------------- | -------------- |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "bức tranh"@vi |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "dipinto"@it   |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "festmény"@hu  |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "Gemälde"@de   |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "glezna"@lv    |
| ...                        | ...               | ...                    | ...            |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "Malōnek"@szl  |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "margolan"@eu  |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "mólba"@hsb    |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "Moleri"@srn   |
| Annunciation (wd:Q1217213) | "A Anunciação"@pt | painting (wd:Q3305213) | "obraz"@pl     |

[Assistant]
It seems that the query is still returning multiple labels for the same work, "Annunciation," and the type is consistently "painting." This suggests that the notable works of Leonardo da Vinci are primarily paintings. However, to ensure we are capturing all types of art he created, we should also look at other properties that might indicate different types of art, such as "genre" (P136) or "medium" (P186).

Let's execute a query to include these additional properties to get a more comprehensive view of the types of art Leonardo da Vinci created.

[Tool]
SPARQL execution failed:
HTTPSConnectionPool(host='qlever.cs.uni-freiburg.de', port=443): Read timed out. (read timeout=30)

[Assistant]
It seems that the query timed out due to the complexity and the amount of data being retrieved. To avoid this, we can break down the query into smaller parts and focus on retrieving distinct works and their types first, and then separately retrieve the genres and mediums for those works.

Let's start by retrieving distinct works and their types, and then we can run a separate query to get the genres and mediums for those works.

### Step 1: Retrieve distinct works and their types
First, let's get a list of distinct works and their types.

[Tool]
SPARQL execution failed:
Tried to allocate 5.7 GB, but only 3.7 GB were available. Clear the cache or allow more memory for QLever during startup

[Assistant]
It seems that even the simpler query is running into memory issues. To address this, we can further simplify the query by removing the optional labels and focusing on the distinct works and their types. We can then retrieve the labels in a separate step if needed.

Let's start by retrieving the distinct works and their types without the labels.

### Step 1: Retrieve distinct works and their types without labels
We will focus on getting the IRIs of the works and their types first.

[Tool]
Got 20 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?work                                             | ?type                                           |
| ------------------------------------------------- | ----------------------------------------------- |
| Annunciation (wd:Q1217213)                        | painting (wd:Q3305213)                          |
| Mona Lisa (wd:Q12418)                             | painting (wd:Q3305213)                          |
| The Last Supper (wd:Q128910)                      | wall painting (wd:Q99516640)                    |
| Annunciation (wd:Q154326)                         | artistic theme (wd:Q1406161)                    |
| Annunciation (wd:Q154326)                         | religious and cultural festive day (wd:Q375011) |
| ...                                               | ...                                             |
| Lady with an Ermine (wd:Q474338)                  | painting (wd:Q3305213)                          |
| The Virgin and Child with Saint Anne (wd:Q563727) | painting (wd:Q3305213)                          |
| Portrait of Isabella d'Este (wd:Q591128)          | croquis (wd:Q217106)                            |
| Portrait of Isabella d'Este (wd:Q591128)          | study (wd:Q2647254)                             |
| Portrait of Isabella d'Este (wd:Q591128)          | sketch (wd:Q5078274)                            |

[Assistant]
The query has successfully returned a list of distinct works and their types. From the results, we can see that Leonardo da Vinci created various types of art, including:

- Paintings (e.g., "Annunciation," "Mona Lisa," "Lady with an Ermine")
- Wall paintings (e.g., "The Last Supper")
- Sketches and studies (e.g., "Portrait of Isabella d'Este")

To provide a more complete answer, we can now retrieve the labels for these works and their types. However, since the previous attempts to retrieve labels caused performance issues, we will limit the number of results and ensure the query is efficient.

Let's retrieve the labels for the top 10 works and their types.

### Step 2: Retrieve labels for the top 10 works and their types
We will use the IRIs from the previous query to fetch the labels.

[Tool]
Got 10 rows and 4 columns:
| ?work                                             | ?workLabel                           | ?type                                           | ?typeLabel                         |
| ------------------------------------------------- | ------------------------------------ | ----------------------------------------------- | ---------------------------------- |
| Annunciation (wd:Q1217213)                        | Annunciation                         | painting (wd:Q3305213)                          | painting                           |
| Mona Lisa (wd:Q12418)                             | Mona Lisa                            | painting (wd:Q3305213)                          | painting                           |
| The Last Supper (wd:Q128910)                      | The Last Supper                      | wall painting (wd:Q99516640)                    | wall painting                      |
| Annunciation (wd:Q154326)                         | Annunciation                         | artistic theme (wd:Q1406161)                    | artistic theme                     |
| Annunciation (wd:Q154326)                         | Annunciation                         | religious and cultural festive day (wd:Q375011) | religious and cultural festive day |
| Lady with an Ermine (wd:Q474338)                  | Lady with an Ermine                  | painting (wd:Q3305213)                          | painting                           |
| The Virgin and Child with Saint Anne (wd:Q563727) | The Virgin and Child with Saint Anne | painting (wd:Q3305213)                          | painting                           |
| Portrait of Isabella d'Este (wd:Q591128)          | Portrait of Isabella d'Este          | croquis (wd:Q217106)                            | croquis                            |
| Portrait of Isabella d'Este (wd:Q591128)          | Portrait of Isabella d'Este          | study (wd:Q2647254)                             | study                              |
| Portrait of Isabella d'Este (wd:Q591128)          | Portrait of Isabella d'Este          | sketch (wd:Q5078274)                            | sketch                             |

[Assistant]
The query has successfully returned the labels for the top 10 works and their types. Based on these results, we can see that Leonardo da Vinci created various types of art, including:

- **Paintings**: "Annunciation," "Mona Lisa," "Lady with an Ermine," "The Virgin and Child with Saint Anne"
- **Wall Paintings**: "The Last Supper"
- **Sketches and Studies**: "Portrait of Isabella d'Este"

These results indicate that Leonardo da Vinci was primarily known for his paintings, but he also created wall paintings and sketches.

### Final Answer
Leonardo da Vinci created various types of art, including paintings, wall paintings, and sketches. Some of his notable works include the "Annunciation," "Mona Lisa," "The Last Supper," "Lady with an Ermine," "The Virgin and Child with Saint Anne," and "Portrait of Isabella d'Este."

Here is the final SPARQL query and answer:

[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 the Armenian currency, I will first search for Armenia as a country and then look for the property that indicates its currency.

[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

No other items found

[Assistant] From the search results, the correct entity for Armenia is `wd:Q399`. Now, I will look for the property that indicates the currency of a country.

[Tool]
Top 10 property alternatives:
1. currency, also known as base currency, used money (wd:P38 as wdt/p): currency used by item, uses
2. nominal GDP, also known as GDP, GDP, nominal, gross domestic product, nominal GDP, nominal gross domestic product (wd:P2131 as wdt/p): market value of all officially recognized final goods and services produced within a country in a given period of time
3. central bank (wd:P1304 as p/wdt): country's central bank
4. flag, also known as flag description (wd:P163 as p/wdt): subject's flag
5. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
6. VAT rate, also known as goods and services tax rate, GST, sales tax, taxation rate for sales, tax rate for sales (wd:P2855 as wdt/p): percentage value-added tax in this country or region. Do not use for sales tax. For specialised rates, use qualifiers
7. 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)
8. continent (wd:P30 as wdt/p): continent of which the subject is a part, located in/on physical feature
9. capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as wdt/p): seat of government of a country, province, state or other type of administrative territorial entity
10. located in time zone, also known as TZ, time zone, timezone (wd:P421 as wdt/p): time zone for this item

No other items found

[Assistant] The property that indicates the currency of a country is `wd:P38`. Now, I will construct a SPARQL query 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 (`wd:Q130498`).

[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 in 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 in Bosnia, I'll start by identifying the entity for Bosnia and then look for properties related to languages spoken there.

First, I need to find the correct entity for Bosnia. I will use the search function to find it.

[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

No other items found

[Assistant]
The top result for "Bosnia" is "Bosnia and Herzegovina" (wd:Q225), which is the country in Southeast Europe. This is the entity I will use to find out the languages spoken there.

Next, I need to identify the property that links a country to the languages spoken in it. I will search for properties related to "language" with the constraint that the subject is "Bosnia and Herzegovina".

[Tool]
Top 10 property alternatives:
1. official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as wdt/p): language designated as official by this item, language used
2. language used, also known as languages used, medium of instruction, used language, uses language, working language (wd:P2936 as p/wdt): language widely used (spoken or written) in this place or at this event or organisation
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. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as p/wdt): label for the items in their official language  or their original language, name
5. culture, also known as archaeological culture, civilisation, civilization (wd:P2596 as p/wdt): human culture or people (or several cultures) associated with this item, part of
6. name in native language, also known as native name (wd:P1559 as p/wdt): name of a person in their native language, name
7. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
8. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as wdt/p): work where this item is described, attested in
9. religion or worldview, also known as believes, worldview, religious affiliation, religion or world view, religion (wd:P140 as p/wdt): religion of a person, organization or religious building, or associated with this subject
10. Unicode character, also known as emoji, emote, pictograph, Unicode symbol (wd:P487 as wdt/p): Unicode character representing the item (only if this is not a c...acter or a compatiblity character: in that case, use only P4213)

No other items found

[Assistant]
The top relevant property for finding the languages spoken in Bosnia and Herzegovina is "official language" (wdt:P37). This property indicates the language designated as official by the country.

I will now construct a SPARQL query to retrieve the languages spoken in Bosnia and Herzegovina using this property.

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

Let's execute this query to get the results.

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

[Assistant]
The SPARQL query returned the languages spoken in Bosnia and Herzegovina:

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

These are the official languages of the country.

Now, I will provide the final answer to the user question.

[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 .
  OPTIONAL {
    wd:Q9299 skos:altLabel ?altLabel
  }
}

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           |

The Serbian language is called 'Serbian' and is also known as 'Srpski' and 'Serbian language.'

[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 about what the Serbian language is 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.

[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

No other items found

[Assistant]
From the search results, the most relevant entity for the Serbian language is `wd:Q9299`, which is labeled as "Serbian" and also known as "Srpski" and "Serbian language."

Next, let's confirm this by retrieving the label and alternative names for this entity.

[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       |
| "Afaan Sarbiyaa"@om | "bahasa Serbia"@id         |
| "Afaan Sarbiyaa"@om | "Gjuha serbe"@sq           |
| "Afaan Sarbiyaa"@om | "idioma serbio"@es         |
| "Afaan Sarbiyaa"@om | "jezik srpskoga naroda"@hr |
| ...                 | ...                        |
| "塞爾維亞語"@zh-tw       | "سربیائی زبان"@ur          |
| "塞爾維亞語"@zh-tw       | "صربية"@ar                 |
| "塞爾維亞語"@zh-tw       | "صربی"@fa                  |
| "塞爾維亞語"@zh-tw       | "لغة صربية"@ar             |
| "塞爾維亞語"@zh-tw       | "塞爾維亞語"@zh                 |

[Assistant]
The results show that the Serbian language is primarily labeled as "Serbian" and has several alternative labels such as "Srpski," "bahasa Serbia," "idioma serbio," and others in different languages.

To provide a clear and concise answer, we can focus on the primary label and a few common alternative labels.

Here is the final SPARQL query and answer:

```sparql
SELECT ?label ?altLabel WHERE {
  wd:Q9299 rdfs:label ?label .
  OPTIONAL { wd:Q9299 skos:altLabel ?altLabel }
}
```

The Serbian language is called "Serbian" and is also known as "Srpski" and "Serbian language."

[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 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

No other items found

[Assistant]
The top result for "Scott Joplin" is the American composer, musician, and pianist, which is the correct entity we are looking for. His identifier 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 list the properties and objects associated with Scott Joplin to find relevant information.

[Tool]
Got 633 rows and 3 columns, showing the first 10 rows below:
| subject                   | property                         | object                                                                          |
| ------------------------- | -------------------------------- | ------------------------------------------------------------------------------- |
| Scott Joplin (wd:Q191499) | instance of (wdt:P31)            | human (wd:Q5)                                                                   |
| Scott Joplin (wd:Q191499) | occupation (wdt:P106)            | composer (wd:Q36834)                                                            |
| Scott Joplin (wd:Q191499) | sex or gender (wdt:P21)          | male (wd:Q6581097)                                                              |
| Scott Joplin (wd:Q191499) | given name (wdt:P735)            | Scott (wd:Q2260734)                                                             |
| Scott Joplin (wd:Q191499) | date of birth (wdt:P569)         | 1868-01-01T00:00:00Z                                                            |
| Scott Joplin (wd:Q191499) | Commons category (wdt:P373)      | Scott Joplin                                                                    |
| Scott Joplin (wd:Q191499) | image (wdt:P18)                  | <http://commons.wikimedia.org/wiki/Special:FilePath/Scott%20Joplin%2019072.jpg> |
| Scott Joplin (wd:Q191499) | country of citizenship (wdt:P27) | United States (wd:Q30)                                                          |
| Scott Joplin (wd:Q191499) | family name (wdt:P734)           | Japlin (wd:Q16871206)                                                           |
| Scott Joplin (wd:Q191499) | place of birth (wdt:P19)         | Bowie County (wd:Q108612)                                                       |
| ...                       | ...                              | ...                                                                             |

[Assistant]
From the list of properties and objects associated with Scott Joplin, we can see that he was a composer, but we need to find out what specific instruments he played. One common property for indicating instruments played by a musician is `instrument (wdt:P1303)`.

Let's check if Scott Joplin has any values for the `instrument` property.

[Tool]
Got 4 rows and 3 columns:
| subject                   | property               | object              |
| ------------------------- | ---------------------- | ------------------- |
| Scott Joplin (wd:Q191499) | instrument (wdt:P1303) | guitar (wd:Q6607)   |
| Scott Joplin (wd:Q191499) | instrument (wdt:P1303) | piano (wd:Q5994)    |
| Scott Joplin (wd:Q191499) | instrument (wdt:P1303) | violin (wd:Q8355)   |
| Scott Joplin (wd:Q191499) | instrument (wdt:P1303) | cornet (wd:Q202027) |

[Assistant]
Scott Joplin played several instruments, including the guitar, piano, violin, and cornet. Now, let's construct a SPARQL query to retrieve these instruments and their identifiers.

Here is the SPARQL query:

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

Let's execute this query to get the results.

[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 SPARQL query 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)

Now, let's provide the final answer.

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, and 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, I need to first identify the entity for Robert Burns and then find the properties related to his occupations or jobs.

### Step 1: Identify Robert Burns
I will start by searching for the entity representing Robert Burns in the knowledge graph.

#### Search for Robert Burns
I will use the `search` function to find the entity for Robert Burns.

```json
{
  "name": "search",
  "arguments": {
    "kg": "wikidata",
    "position": "subject",
    "query": "Robert Burns"
  }
}
```

Let's execute this search.

[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

No other items found

[Assistant]
From the search results, the entity that represents Robert Burns, the Scottish poet and lyricist, is `wd:Q81960`.

### Step 2: Find Properties Related to Jobs
Next, I need to find the properties that relate to jobs or occupations. The most common property for this is `wdt:P106` (occupation).

#### List Triples for Robert Burns with Property `wdt:P106`
I will use the `list` function to find the triples where Robert Burns (`wd:Q81960`) has the property `wdt:P106`.

```json
{
  "name": "list",
  "arguments": {
    "kg": "wikidata",
    "subject": "wd:Q81960",
    "property": "wdt:P106"
  }
}
```

Let's execute this list query.

[Tool]
Got 5 rows and 3 columns:
| subject                  | property              | object                      |
| ------------------------ | --------------------- | --------------------------- |
| Robert Burns (wd:Q81960) | occupation (wdt:P106) | writer (wd:Q36180)          |
| Robert Burns (wd:Q81960) | occupation (wdt:P106) | poet (wd:Q49757)            |
| Robert Burns (wd:Q81960) | occupation (wdt:P106) | farmer (wd:Q131512)         |
| Robert Burns (wd:Q81960) | occupation (wdt:P106) | songwriter (wd:Q753110)     |
| Robert Burns (wd:Q81960) | occupation (wdt:P106) | musicologist (wd:Q14915627) |

[Assistant]
The list query returned the following occupations for Robert Burns:
- Writer (`wd:Q36180`)
- Poet (`wd:Q49757`)
- Farmer (`wd:Q131512`)
- Songwriter (`wd:Q753110`)
- Musicologist (`wd:Q14915627`)

### Step 3: Build the Final SPARQL Query
Now, I will construct a SPARQL query to retrieve these occupations along with their labels for better readability.

#### Final 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 final answer.

[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 SPARQL query successfully retrieved the occupations of Robert Burns along with their labels. The jobs Robert Burns had are:

- Farmer
- Musicologist
- Writer
- Poet
- Songwriter

### Final Answer
Robert Burns had the following jobs: Farmer, Musicologist, Writer, Poet, and Songwriter.

I will now provide the final SPARQL query and answer.

```json
{
  "name": "answer",
  "arguments": {
    "kg": "wikidata",
    "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, and Songwriter."
  }
}
```

Let's finalize this.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?zipCode WHERE {
  ?entity wdt:P281 ?zipCode ; wdt:P131 wd:Q5083
}

The zip codes for Seattle, Washington are: 98004, 98006, 98101, 98102, 98103, ..., 98195-7735, 98195-7920, 98195-8280, 98199, WA 98195-4360.

[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 find the property that represents the zip 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. 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

No other items found

[Assistant] The top result for "Seattle" is the city in Washington, which is what we're looking for. The corresponding entity is `wd:Q5083`. Next, we need to find the property that represents the zip code. We can search for properties related to zip codes.

[Tool]
Top 10 property alternatives:
1. postal code, also known as pincode, PIN Code, postal index number, post code, postcode (wd:P281 as p/wdt/prn/ps/pq/psn/pqn/wdtn/pr/pqv/prv/psv): 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 p/wdt/prn/ps/pq/psn/pqn/wdtn/pr/pqv/prv/psv): 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 p/wdt/prn/ps/pq/psn/pqn/wdtn/pr/pqv/prv/psv): identifier for a country - dialed on phone after the international dialing prefix (precede value by +)
4. location code (wd:P13262 as p/wdt/prn/ps/pq/psn/pqn/wdtn/pr/pqv/prv/psv): 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 p/wdt/prn/ps/pq/psn/pqn/wdtn/pr/pqv/prv/psv): 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 p/wdt/prn/ps/pq/psn/pqn/wdtn/pr/pqv/prv/psv): 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 p/wdt/prn/ps/pq/psn/pqn/wdtn/pr/pqv/prv/psv): post office box number, as part of an address
8. quantity, also known as amount, total number, total, qty, occurrences (wd:P1114 as p/wdt/prn/ps/pq/psn/pqn/wdtn/pr/pqv/prv/psv): 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 p/wdt/prn/ps/pq/psn/pqn/wdtn/pr/pqv/prv/psv): 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 p/wdt/prn/ps/pq/psn/pqn/wdtn/pr/pqv/prv/psv): issue of a newspaper, a scientific journal or magazine for reference purpose

No other items found

[Assistant]
The property `wd:P281` represents the postal code, which is what we need. Now, let's construct a SPARQL query to find the zip code for Seattle, Washington.

We will query for the postal code of the entity `wd:Q5083` (Seattle).

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

[Assistant]
The SPARQL query returned a single zip code for Seattle, Washington, which is 98101. However, Seattle has multiple zip codes, and this query only returns one of them. To get a more comprehensive list, we should consider using a different approach or property that might provide more detailed information about the zip codes in Seattle.

Let's try to find more detailed information about the zip codes in Seattle by looking for properties that might provide a list of zip codes or related areas.

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

[Assistant]
The list function confirms that the only postal code directly associated with Seattle (wd:Q5083) is 98101. However, this is likely an incomplete representation, as Seattle has many zip codes.

To get a more comprehensive list, we might need to look at the administrative divisions or neighborhoods of Seattle and their respective zip codes. Let's search for properties related to administrative divisions or neighborhoods of Seattle.

First, let's find the properties that might represent administrative divisions or neighborhoods.

[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 p/wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
2. capital of, also known as national capital of, parish seat of, provincial capital of, seat of, state capital (wd:P1376 as p/wdt): country, state, department, canton or other administrative division of which the municipality is the governmental seat, located in the administrative territorial entity
3. located in the statistical territorial entity, also known as located in statistical territorial entity, statistical territorial entity (wd:P8138 as wdt/p): statistical territorial entity in which a place is located or is...nty is split into or part of several regions: add several values, location
4. legislative body, also known as aboriginal council, Zila, Tehsil, rural council, representative body (wd:P194 as wdt/p): legislative body governing this entity; political institution wi...ted representatives, such as a parliament/legislature or council
5. territory overlaps, also known as partially overlaps, partially coincident with, partly coincident with, partly located in territorial entity, partly overlaps (wd:P3179 as wdt/p): 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. House Divided ID (wd:P8400 as wdt/p): identifier of a topic in House Divided: The Civil War Research Engine at Dickinson College
7. twinned administrative body, also known as twin cities, twin town, twin city, sister town, sister city (wd:P190 as wdt/p): twin towns, sister cities, twinned municipalities and other loca..., either legally or informally acknowledged by their governments
8. area, also known as total area, surface area, surface, size, resolution (wd:P2046 as wdt/p): area occupied by an object
9. Library of Congress authority ID, also known as LCSH Authority File ID, LC Name Authority ID, LCSH ID, LCSH LCCN, LC Subject Heading ID (wd:P244 as p/wdt/wdtn): Library of Congress name authority (persons, families, corporate...lowed by 8-10 digits (see regex). For manifestations, use P1144]
10. shares border with, also known as shares borders with, next to, bordered by, border, borders clockwise (wd:P47 as p/wdt): countries or administrative subdivisions, of equal level, that t...rders, either by land or water. A single common point is enough.

No other items found

[Assistant]
The property `wd:P131` (located in the administrative territorial entity) seems relevant for finding the administrative divisions or neighborhoods of Seattle. We can use this property to find the neighborhoods or smaller administrative units within Seattle and then check if they have their own zip codes.

Let's start by finding the neighborhoods or administrative divisions of Seattle using the `wd:P131` property.

[Tool]
Got 1,952 rows and 1 column, showing the first 5 and last 5 rows below:
| ?neighborhood                                                                      |
| ---------------------------------------------------------------------------------- |
| University of Washington Southeast Asia Center (wd:Q100252662)                     |
| University of Washington Libraries Near East Section (wd:Q100319894)               |
| University of Washington Libraries International Studies (wd:Q100319927)           |
| Epiphany Music Academy (wd:Q100701144)                                             |
| University of Washington Institute for Protein Design (wd:Q100701233)              |
| ...                                                                                |
| Bagley Hall (wd:Q99705102)                                                         |
| University of Washington Institute for Nano-Engineered Systems (wd:Q99705798)      |
| Nano Engineering and Sciences Building (wd:Q99705827)                              |
| University of Washington Latin A...an and Caribbean Studies Program (wd:Q99864848) |
| University of Washington South Asia Center (wd:Q99866754)                          |

[Assistant]
The query returned a large number of results, including various buildings, centers, and programs within the University of Washington. These are not the neighborhoods or administrative divisions we are looking for. We need to refine our search to focus specifically on neighborhoods or significant administrative divisions within Seattle.

Let's try to find more specific properties or constraints that can help us identify the neighborhoods or significant administrative divisions of Seattle. We can also look for properties that directly relate to zip codes or postal codes for these neighborhoods.

Let's search for properties that might represent neighborhoods or significant administrative divisions within a city.

[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 p/wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
2. area, also known as total area, surface area, surface, size, resolution (wd:P2046 as wdt/p): area occupied by an object
3. shares border with, also known as shares borders with, next to, bordered by, border, borders clockwise (wd:P47 as p/wdt): countries or administrative subdivisions, of equal level, that t...rders, either by land or water. A single common point is enough.
4. number of households, also known as dwellings, households (wd:P1538 as wdt/p): total number of households in this place, includes dwellings of all types
5. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
6. located in or next to body of water, also known as located on body of water, ocean, on bay, next to lake, on coast of (wd:P206 as p/wdt): body of water on or next to which a place is located, location
7. territory overlaps, also known as partially overlaps, partially coincident with, partly coincident with, partly located in territorial entity, partly overlaps (wd:P3179 as wdt/p): part or all of the area associated with (this) entity overlaps part or all of the area associated with that entity, partially coincident with
8. legislative body, also known as aboriginal council, Zila, Tehsil, rural council, representative body (wd:P194 as wdt/p): legislative body governing this entity; political institution wi...ted representatives, such as a parliament/legislature or council
9. postal code, also known as pincode, PIN Code, postal index number, post code, postcode (wd:P281 as wdt/p): identifier assigned by postal authorities for the subject area or building
10. twinned administrative body, also known as twin cities, twin town, twin city, sister town, sister city (wd:P190 as wdt/p): twin towns, sister cities, twinned municipalities and other loca..., either legally or informally acknowledged by their governments

No other items found

[Assistant]
The search for properties related to "neighborhood" did not yield a specific property that directly represents neighborhoods. However, we can try to use the `wd:P131` property again but with a more specific filter to find significant administrative divisions or neighborhoods within Seattle.

Let's try to find the neighborhoods or significant administrative divisions of Seattle by filtering for entities that are more likely to be neighborhoods. We can use the `wdt:P31` property to filter for entities that are instances of a neighborhood or a similar concept.

First, let's find the entity that represents a neighborhood or a similar concept.

[Tool]
Top 10 entity alternatives:
1. neighborhood, also known as city section, district, neighbourhood, quarter, subdistrict (wd:Q123705): geographically localized community within a larger city, town or suburb
2. environment, also known as medium, neighborhood, reservoir, setting, surroundings (wd:Q2920644): in systems and engineering, part of the universe outside the boundaries of a system
3. local community, also known as neighborhood, suburb (wd:Q490933): term describing people living in a common location
4. Neighborhood, also known as Lin, Neighbourhood (wd:Q129381571): the smallest administrative unit in Taiwan
5. neighborhood, also known as vicinity (wd:Q2678710): hamlet
6. gentrification, also known as community displacement, neighborhood revitalization (wd:Q119380): urban socioeconomic process
7. gay village, also known as LGBT+ village, queer village, LGBT village, gayvenue, gaytto (wd:Q748198): geographical area within a city that is inhabited or frequented by LGBT people
8. neighborhood watch, also known as crime watch, neighborhood crime watch, neighbourhood crime watch, neighbourhood watch (wd:Q127930): organization of residents watching for crimes
9. bicycle boulevard, also known as bicycle street, cycle street, neighborhood bikeway, neighborhood byway, neighborhood greenway (wd:Q1249483): street that is designed as a bicycle route
10. neighborhood association, also known as community association, NA, neighborhood committee, neighborhood community association, neighborhood organization (wd:Q2867476): group of residents or property owners who advocate for or organize activities within a neighborhood

No other items found

No literal items found

[Assistant]
The top result for "neighborhood" is `wd:Q123705`, which represents a geographically localized community within a larger city, town, or suburb. This is the entity we are looking for.

Now, let's use this entity to filter the results and find the neighborhoods or significant administrative divisions of Seattle. We will use the `wdt:P31` property to filter for entities that are instances of a neighborhood (`wd:Q123705`) and are located in Seattle (`wd:Q5083`).

Let's construct the SPARQL query to find these neighborhoods and their zip codes.

[Tool]
Got 67 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?neighborhood                 | ?zipCode |
| ----------------------------- | -------- |
| Capitol Hill (wd:Q1041704)    |          |
| Mount Baker (wd:Q12062108)    | 98144    |
| Madison Valley (wd:Q14713802) |          |
| Meridian (wd:Q14713815)       |          |
| Africatown (wd:Q16205464)     |          |
| ...                           | ...      |
| Wedgwood (wd:Q7979189)        |          |
| Windermere (wd:Q8024113)      |          |
| Yesler Terrace (wd:Q8052916)  |          |
| Belltown (wd:Q967732)         |          |
| Jackson Park (wd:Q98398937)   |          |

[Assistant]
The query returned a list of neighborhoods in Seattle, but many of them do not have a zip code associated with them. This suggests that the zip codes for these neighborhoods might not be directly linked in the Wikidata graph.

To get a more comprehensive list of zip codes for Seattle, we can try a different approach. We can look for entities that are directly associated with zip codes and are located in Seattle. This might include post offices, addresses, or other entities that have a zip code property.

Let's try to find entities that have a zip code and are located in Seattle.

[Tool]
Got 255 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?entity                                                                            | ?zipCode   |
| ---------------------------------------------------------------------------------- | ---------- |
| University of Washington Southeast Asia Center (wd:Q100252662)                     | 98195-3650 |
| University of Washington Asian Law Center (wd:Q100709311)                          | 98195-3020 |
| University of Washington eScience Institute (wd:Q101097636)                        | 98195-1570 |
| Northwest Climate Adaptation Science Center (wd:Q101576883)                        | 98195-5674 |
| University of Washington Computational Neuroscience Center (wd:Q102047439)         | 98195      |
| ...                                                                                | ...        |
| University of Washington Center for Urban Horticulture (wd:Q99703417)              | 98105      |
| University of Washington Institute for Nano-Engineered Systems (wd:Q99705798)      | 98195      |
| Nano Engineering and Sciences Building (wd:Q99705827)                              | 98195      |
| University of Washington Latin A...an and Caribbean Studies Program (wd:Q99864848) | 98195-3650 |
| University of Washington South Asia Center (wd:Q99866754)                          | 98195-3650 |

[Assistant]
The query returned a list of entities that have a zip code and are located in Seattle. While these entities are primarily related to the University of Washington, they provide a more comprehensive list of zip codes for the Seattle area.

However, to get a more general and complete list of zip codes for Seattle, we can try to find entities that are more broadly representative of the city, such as post offices or other significant locations.

Let's try to find post offices in Seattle and their associated zip codes. Post offices are typically good indicators of the zip codes for a city.

[Tool] Got no rows and 2 columns

[Assistant]
It appears that there are no post offices in Seattle that are directly linked to zip codes in the Wikidata graph. This suggests that the data for post offices and their zip codes might not be well-represented in Wikidata.

Given the limitations of the data in Wikidata, the most comprehensive list of zip codes for Seattle that we can obtain from the current data is the one we retrieved earlier, which includes various entities like buildings and centers within the University of Washington.

Since this is the best data we can get from Wikidata, let's summarize the unique zip codes from the previous query and provide them as the answer.

Here is the final SPARQL query to extract the unique zip codes for Seattle:

[Tool]
Got 102 rows and 1 column, showing the first 5 and last 5 rows below:
| ?zipCode      |
| ------------- |
| 98004         |
| 98006         |
| 98101         |
| 98102         |
| 98103         |
| ...           |
| 98195-7735    |
| 98195-7920    |
| 98195-8280    |
| 98199         |
| WA 98195-4360 |

[Assistant]
The final SPARQL query has returned a list of unique zip codes for Seattle, Washington. Here are the zip codes:

```
98004, 98006, 98101, 98102, 98103, ..., 98195-7735, 98195-7920, 98195-8280, 98199, WA 98195-4360
```

These zip codes represent various areas within Seattle. Given the data available in Wikidata, this is the most comprehensive list we can provide.

Here is the final SPARQL query and the answer:

```sparql
SELECT DISTINCT ?zipCode WHERE {
  ?entity wdt:P281 ?zipCode ;
          wdt:P131 wd:Q5083
}
```

The zip codes for Seattle, Washington are:
98004, 98006, 98101, 98102, 98103, ..., 98195-7735, 98195-7920, 98195-8280, 98199, WA 98195-4360.

[Tool] Stopped generation process