PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?releaseDate WHERE {
  wd:Q19798744 wdt:P580 ?releaseDate .
}

The OA was first released on December 16, 2016.

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

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

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

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

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

[User] When did The OA was first released?

[Assistant]
To find out when "The OA" was first released, we need to identify the entity for "The OA" and then look for the property that indicates the release date or premiere date.

Let's start by searching for the entity "The OA" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. The OA (wd:Q19798744): 2016 American mystery drama television series
2. The Oa, also known as The Oa RSPB Nature Reserve (wd:Q1325866): peninsula in the southwest of Islay, Argyll and Bute, Scotland, UK
3. The Oa (wd:Q126204501): Special Protection Area in Scotland, UK
4. The Oath, also known as Oath, Eiðurinn (wd:Q27834781): 2016 film by Baltasar Kormákur
5. Di Shvue, also known as Di Bundishe Shvue, The Oath (wd:Q5270055): Jewish song, anthem of the Bund
6. Il giuramento, also known as The Oath (wd:Q1469058): opera by Saverio Mercadante
7. The Oak, also known as Oak (wd:Q2328850): 1992 film
8. Epsom Oaks, also known as Oaks, The Oaks, The Oaks Stakes (wd:Q3347856): British Group 1 horse race tor 3-year-old filles over 1 mile, 4 furlongs and 10 yards (2,423 metres)
9. The Oatmeal, also known as theoatmeal.com (wd:Q2015830): humor website
10. The Oath (wd:Q39071891): television series

[Assistant]
From the search results, the entity "The OA" (wd:Q19798744) is the correct one for the 2016 American mystery drama television series.

Next, we need to find the property that indicates the release date or premiere date. Let's search for properties related to "release date" or "premiere date".

[Tool]
Top 10 property alternatives:
1. date of commercialization, also known as availability date, commercialization date, product release date, release date (wd:P5204 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): date when a product was first commercialized
2. publication date, also known as launched, published, publication time, publication, pubdate (wd:P577 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): date or point in time when a work was first published or released, point in time
3. announcement date, also known as released, date teased, made public on, public announcement date, published (wd:P6949 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): time of the first public presentation of a subject by the creator, of information by the media, point in time
4. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): time when an entity begins to exist; for date of official opening use P1619, start time
5. day of regular release (wd:P6437 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): day(s) when parts of this creative work are released, aired, published, etc
6. service entry, also known as commissioned, time of service entry, service introduction, launch date, in service (wd:P729 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): date or point in time on which a piece or class of equipment entered operational service, start time
7. date of official opening, also known as launch date, launched, officially opened on, official opening, official opening time (wd:P1619 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): date or point in time a place, organization, or event officially opened, start time, inception
8. UTC date of spacecraft launch, also known as time of spacecraft launch, spacecraft launch time, spacecraft launch date, launch time, launch date (wd:P619 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): date of spacecraft launch in UTC
9. production date, also known as date of production, filming date, filming time, production date, year of production (wd:P2754 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): period of active production of (creative) work; the only date st... publication date (P577); in general cases, use inception (P571)
10. place of publication, also known as published in (place), where published, release region, released in, published from (wd:P291 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): geographical place of publication of the edition (use 1st edition when referring to works), significant place

[Assistant]
The property "publication date" (wd:P577) seems to be the most appropriate for finding the release date of a television series.

Now, let's construct a SPARQL query to find the release date of "The OA" (wd:Q19798744).

```sparql
SELECT ?releaseDate
WHERE {
  wd:Q19798744 wdt:P577 ?releaseDate .
}
```

Let's execute this query to get the release date.

[Tool] Got no rows and 1 columns

[Assistant]
It appears that the property `wdt:P577` (publication date) does not return any results for "The OA" (wd:Q19798744). This might be because the specific property used for the release date of a television series is different.

Let's try another property that might be more relevant for the release date of a television series. We can check the properties used for "The OA" to see if there is a more suitable one.

Let's list the properties for "The OA" (wd:Q19798744) to find a more appropriate property.

[Tool]
Got 312 rows and 3 columns, showing the first 10 rows below:
| subject               | property                     | object                                          |
| --------------------- | ---------------------------- | ----------------------------------------------- |
| The OA (wd:Q19798744) | instance of (wdt:P31)        | television series (wd:Q5398426)                 |
| The OA (wd:Q19798744) | title (wdt:P1476)            | The OA                                          |
| The OA (wd:Q19798744) | has part(s) (wdt:P527)       | The OA: Part I (wd:Q28613281)                   |
| The OA (wd:Q19798744) | country of origin (wdt:P495) | United States (wd:Q30)                          |
| The OA (wd:Q19798744) | official website (wdt:P856)  | <https://www.netflix.com/title/80044950>        |
| The OA (wd:Q19798744) | genre (wdt:P136)             | science fiction television program (wd:Q336059) |
| The OA (wd:Q19798744) | cast member (wdt:P161)       | Jason Isaacs (wd:Q214223)                       |
| The OA (wd:Q19798744) | creator (wdt:P170)           | Brit Marling (wd:Q289380)                       |
| The OA (wd:Q19798744) | start time (wdt:P580)        | 2016-12-16T00:00:00Z                            |
| The OA (wd:Q19798744) | end time (wdt:P582)          | 2019-08-05T00:00:00Z                            |
| ...                   | ...                          | ...                                             |

[Assistant]
From the list of properties for "The OA" (wd:Q19798744), the property `wdt:P580` (start time) seems to indicate the start date of the series, which is likely the release date.

Let's construct a SPARQL query to retrieve the value of `wdt:P580` for "The OA".

```sparql
SELECT ?releaseDate
WHERE {
  wd:Q19798744 wdt:P580 ?releaseDate .
}
```

Let's execute this query to get the release date.

[Tool]
Got 1 row and 1 column:
| ?releaseDate         |
| -------------------- |
| 2016-12-16T00:00:00Z |

[Assistant]
The SPARQL query returned the release date of "The OA" as `2016-12-16T00:00:00Z`.

Therefore, "The OA" was first released on December 16, 2016.

Here is the final SPARQL query and the answer:

```sparql
SELECT ?releaseDate
WHERE {
  wd:Q19798744 wdt:P580 ?releaseDate .
}
```

Answer: "The OA" was first released on December 16, 2016.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX p: <http://www.wikidata.org/prop/>
SELECT ( COUNT( DISTINCT ?headOfState ) AS ?count ) WHERE {
  wd:Q794 p:P35 ?statement .
  ?statement ps:P35 ?headOfState .
}

Got 1 row and 1 column:
| ?count |
| ------ |
| 2      |

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

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

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

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

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

[User] how many head of the state does iran have?

[Assistant]
To answer the question about how many heads of state Iran has, we need to identify the relevant entities and properties in the knowledge graph. Specifically, we need to find the entity for Iran and the property that indicates the head of state.

Let's start by searching for the entity "Iran" in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Iran, also known as ir, IRI, IRN, Islamic Rep. Iran, Islamic Republic of Iran (wd:Q794): country in Western Asia
2. Qajar Iran, also known as Guarded Domains of Persia, Sublime State of Persia, Qajar Persia, Persia, Iran (wd:Q63158027): country in Western Asia (1789–1925)
3. Iran (wd:Q2043606): village in North Ossetia, Russia
4. Iran, also known as Īrān (wd:Q10859757): Iranian newspaper
5. IRAN, also known as Iran: Journal of the British Institute of Persian Studies (wd:Q5973372): academic journal
6. Irane Man, also known as Iran (wd:Q100939484): 2018 studio by Homayoun Shajarian & Sohrab Pournazeri
7. IRAN (wd:Q108434787): herbarium
8. Iran, also known as Iran (first name), Iran (given name) (wd:Q21286079): male given name
9. Iran, also known as IMO 5327817 (wd:Q101778560): ship built in 1941
10. Iran (wd:Q96382820): About Iran

[Assistant] The top result for "Iran" is `wd:Q794`, which represents the country Iran. Now, we need to find the property that indicates the head of state. Let's search for properties related to "head of state" in the knowledge graph.

[Tool]
Top 10 property alternatives:
1. office held by head of state, also known as head of state, position held by head of state, state headed by (wd:P1906 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): political office that is fulfilled by the head of state of this item
2. head of state, also known as leader, state headed by, monarch, president, queen (wd:P35 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): official with the highest formal authority in a country/state, director / manager, chairperson
3. head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson
4. office held by head of government, also known as title of head of government, position of head of government, office of head of government, head of government's office, position held by head of government (wd:P1313 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): political office that is fulfilled by the head of the government of this item
5. rector, also known as chancellor, university president, Rector (academia), president (wd:P1075 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): senior official in an educational institution., director / manager, chairperson
6. chairperson, also known as dean, headed by, leader, president, chairwoman (wd:P488 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): presiding member of an organization, group or body, director / manager, significant person
7. organization directed by the office or position, also known as leader of, head of, leads, organization directed by, organization directed from the office (wd:P2389 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): organization which is directed by this office
8. position held by head of the organization, also known as position held by head of the organisation, secretary's position, president's position, position held by head of the organization, office held by head of the organisation (wd:P2388 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): position of the head of this item
9. position holder, also known as incumbent, noble title holder, office holder, position held by (wd:P1308 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): persons who hold and/or held the position
10. country, also known as sovereign state, state, land, host country (wd:P17 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity

[Assistant]
The property `wd:P35` is the most relevant for indicating the head of state. Now, let's construct a SPARQL query to find out how many heads of state Iran has.

We will query for the number of distinct heads of state associated with Iran (`wd:Q794`).

```sparql
SELECT (COUNT(DISTINCT ?headOfState) AS ?count)
WHERE {
  wd:Q794 p:P35 ?statement.
  ?statement ps:P35 ?headOfState.
}
```

Let's execute this query to get the result.

[Tool]
Got 1 row and 1 column:
| ?count |
| ------ |
| 2      |

[Assistant]
The SPARQL query returned a count of 2, indicating that Iran has 2 heads of state.

Therefore, the answer to the question "How many heads of state does Iran have?" is:

**2**

Here is the final SPARQL query:

```sparql
SELECT (COUNT(DISTINCT ?headOfState) AS ?count)
WHERE {
  wd:Q794 p:P35 ?statement.
  ?statement ps:P35 ?headOfState.
}
```

And the answer is:

**2**

Now, I will provide the final answer using the `answer` function.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?country WHERE {
  ?entity wdt:P31 wd:Q1982569 ; wdt:P131 ?region .
  ?region wdt:P17 ?country .
  ?entity wdt:P279 * wd:Q3233785 .
}

The knowledge graph does not have sufficient data to answer the question about the number of countries where pysanka is practiced. I searched for the entity 'pysanka' and found `wd:Q3233785`. I then searched for properties related to 'practice' and 'location', but did not find a direct property linking a cultural practice to a location. I checked if `wd:Q3233785` (pysanka) had any direct location information using properties `P276` (location) and `P3842` (located in the present-day administrative territorial entity), but found no results. I also looked for entities related to pysanka, such as instances and subclasses, and checked if they had any location information, but found no results. Finally, I tried to find entities related to pysanka and are cultural practices, and then check their locations using properties `P17` (country) and `P131` (located in the administrative territorial entity), but found no results.

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

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

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

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

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

[User] In how many countries is pysanka practiced?

[Assistant]
To answer the question about how many countries practice pysanka, we need to identify the following:

1. The entity representing "pysanka" in the knowledge graph.
2. The property that indicates where a cultural practice is performed.
3. The entities representing the countries where pysanka is practiced.

Let's start by searching for the entity "pysanka" in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. pysanka, also known as pisanica, pisanka (wd:Q3233785): egg decorating tradition in Slavic countries
2. Pysanka (wd:Q12140613)
3. Pysanka Museum (wd:Q746631): museum in Kolomyia, Ukraine
4. Ruslana Pysanka, also known as Ruslana Pysanko (wd:Q2506290): Ukrainian actress (1965–2022), television presenter, weather presenter, film actor, presenter, actor
5. Vegreville egg, also known as Vegreville Pysanka (wd:Q7918394): sculpture by Paul Maxum Sembaliuk
6. Hutsul pysanka (wd:Q116733019): Traditional hutsul painted Eastern egg
7. pysankar (wd:Q50333861): Ukrainian ethnic occupation, artists that produces pysanka
8. FORMATION OF PRESCHOOLERS’ AWARE...SANKA PAINTING REGIONAL FEATURES (wd:Q113694374): scientific article published in 2022

[Assistant]
The most relevant entity for "pysanka" is `wd:Q3233785`, which describes the egg decorating tradition in Slavic countries.

Next, we need to find the property that indicates where a cultural practice is performed. Let's search for properties related to "practice" or "cultural practice."

[Tool]
Top 10 property alternatives:
1. field of this occupation, also known as practice, works in, profession's field, practices, field of this profession (wd:P425 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): field corresponding to this occupation or profession (use only f...fessions - for people use Property:P101, for companies use P452)
2. practiced by, also known as proponent, studied by, practitioners, practioner, occupation of this field (wd:P3095 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): type of agents that study this subject or work in this field
3. sport, also known as play, plays, sport played, sports (wd:P641 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): sport that the subject participates or participated in or is associated with
4. subject lexeme form, also known as subject form, form demonstrated, applies to form, demonstrates form (wd:P5830 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): (qualifier) statement applies only to listed lexeme forms of statement's subject
5. study or design for, also known as design for, draft for, first version of, preparatory work for, study for (wd:P6606 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): finished work of art for which the subject is a preliminary study, design, or conceptual drawing
6. field of work, also known as scientific discipline, scientific area, responsible for, research on, research fields (wd:P101 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): specialization of a person or organization; see P106 for the occupation, interested in
7. Wikidata usage instructions, also known as how to use, instructions, usage, usage help, usage instructions (wd:P2559 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): text describing how to use a property or item. Eventually, this ...onding feature is implemented, do not remove it from description
8. hairstyle / hairlength, also known as hair style, style of hair, hair styling, hairdo, haircut (wd:P8839 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): style or length of cutting, arranging, or combing the hair on the subject's scalp
9. has use, also known as utility, used in, used for, used as, use (wd:P366 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): main use of the subject (includes current and former usage)
10. simulates, also known as imitates, simulated, simulate, imitated, imitate (wd:P12328 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): item simulated, imitated, or made to appear real by this item

[Assistant] None of the properties listed directly indicate where a cultural practice is performed. However, we can try to find a property that links a cultural practice to a location or country. Let's search for properties related to "location" or "country" to see if we can find a suitable property.

[Tool]
Top 10 property alternatives:
1. work location, also known as work place, working from, working at, worked from, worked at (wd:P937 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): location where persons or organisations were actively participating in employment, business or other work, significant place, location
2. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
3. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
4. occupant, also known as tenant, resident, renter, occupiers, lessee (wd:P466 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): person or organization occupying property, used by
5. recorded at studio or venue, also known as venue, studio, recording venue, recording studio, recorded at event (wd:P483 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): studio or location where a musical composition/release was recorded, recording location
6. home venue, also known as home water, venue, stadium, home ground, home field (wd:P115 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): home stadium or venue of a sports team or applicable performing arts organization, location
7. published in, also known as song on album, tome of the book, tome of, track of, track on (wd:P1433 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): larger work that a given work was published in, like a book, journal or music album, part of
8. located in the present-day administrative territorial entity, also known as present-day administrative territorial entity, located in the current administrative territorial entity, located in the modern-day administrative territorial entity, located in the present-day administrative territorial entity, would today be located in administrative territorial entity (wd:P3842 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): the item was located in the territory of this present-day administrative unit; however the two did not at any point coexist in time, location, part of
9. directions, also known as locality or place (wd:P2795 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): describe how to find the subject - directions, objects along way, comments
10. ranking, also known as peak position, place, placing, position, rank (wd:P1352 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): subject's ordinal position as qualitatively evaluated relative to other members of a group

[Assistant]
The property `P276` (location) seems to be the most relevant for linking a cultural practice to a location. However, we should also consider `P3842` (located in the present-day administrative territorial entity) as it might provide more specific information about the countries where the practice is performed.

Let's check if `wd:Q3233785` (pysanka) has any statements using these properties.

[Tool] Got no rows and 3 columns

[Assistant] It appears that `wd:Q3233785` (pysanka) does not have any direct statements using the `P276` (location) property. Let's check if it has any statements using the `P3842` (located in the present-day administrative territorial entity) property.

[Tool] Got no rows and 3 columns

[Assistant]
It seems that `wd:Q3233785` (pysanka) does not have any direct statements using either the `P276` (location) or `P3842` (located in the present-day administrative territorial entity) properties.

Since the direct approach didn't yield any results, let's try to find entities that are related to pysanka and see if they have any location information. We can look for entities that are instances of or subclasses of pysanka and then check their locations.

First, let's find entities that are instances of or subclasses of `wd:Q3233785` (pysanka).

[Tool]
Got 1 row and 3 columns:
| subject                      | property              | object                |
| ---------------------------- | --------------------- | --------------------- |
| Vegreville egg (wd:Q7918394) | instance of (wdt:P31) | pysanka (wd:Q3233785) |

[Assistant] We found one entity, `wd:Q7918394` (Vegreville egg), which is an instance of `wd:Q3233785` (pysanka). Let's check if this entity has any location information using the `P276` (location) or `P3842` (located in the present-day administrative territorial entity) properties.

[Tool] Got no rows and 3 columns

[Assistant] It appears that `wd:Q7918394` (Vegreville egg) does not have any direct statements using the `P276` (location) property. Let's check if it has any statements using the `P3842` (located in the present-day administrative territorial entity) property.

[Tool] Got no rows and 3 columns

[Assistant]
It seems that `wd:Q7918394` (Vegreville egg) does not have any direct statements using the `P3842` (located in the present-day administrative territorial entity) property either.

Given that the direct and indirect approaches have not yielded any location information for pysanka, we need to consider a different strategy. One approach is to look for entities that are related to pysanka and are cultural practices, and then check their locations.

Let's search for entities that are related to pysanka and are cultural practices. We can use the property `P31` (instance of) to find entities that are instances of cultural practices and then filter those that are related to pysanka.

[Tool]
Top 10 entity alternatives:
1. traditional activity, also known as cultural practice, human activity, traditional, traditional action (wd:Q1982569): human activity based on and in furtherance of tradition
2. harmful cultural practice, also known as harmful practice, harmful traditional practice, harmful social norm (wd:Q132153216)
3. sociology of cultural practice (wd:Q30751286)
4. silvicultural practice, also known as cultural methods (forests), cultural practices (forests), forestry practices (wd:Q116865911): Forest operations implemented during the life of a forest to alter competition, composition, and growth
5. Cultural Geographies in Practice (wd:Q122092883): scientific article published in 2000
6. Cultural geographies in practice (wd:Q54559060): scientific article published in October 2005
7. Cultural geographies in practice (wd:Q121792881): scientific article published in 2000
8. Cultural geographies in practice (wd:Q104205040)
9. cultural geographies in practice (wd:Q123301553): scientific article published in 2002
10. cultural geographies in practice (wd:Q122958917): scientific article published in 2006

[Assistant]
The most relevant entity for "cultural practice" is `wd:Q1982569` (traditional activity). Let's find entities that are instances of `wd:Q1982569` and are related to pysanka.

We can use the property `P31` (instance of) to find instances of `wd:Q1982569` and then filter those that are related to pysanka using the property `P17` (country) to find the countries where these practices are performed.

Let's start by finding instances of `wd:Q1982569` (traditional activity) and then check if they are related to pysanka.

[Tool]
Got 15 rows and 3 columns, showing the first 10 rows below:
| subject                                       | property              | object                             |
| --------------------------------------------- | --------------------- | ---------------------------------- |
| cancel culture (wd:Q60297962)                 | instance of (wdt:P31) | traditional activity (wd:Q1982569) |
| bacha posh (wd:Q4838695)                      | instance of (wdt:P31) | traditional activity (wd:Q1982569) |
| forced pregnancy (wd:Q5467540)                | instance of (wdt:P31) | traditional activity (wd:Q1982569) |
| nudity in combat (wd:Q7068391)                | instance of (wdt:P31) | traditional activity (wd:Q1982569) |
| Etrusca disciplina (wd:Q3059369)              | instance of (wdt:P31) | traditional activity (wd:Q1982569) |
| Koto Gadang embroidery (wd:Q65210161)         | instance of (wdt:P31) | traditional activity (wd:Q1982569) |
| viticulture of Aguascalientes (wd:Q125697233) | instance of (wdt:P31) | traditional activity (wd:Q1982569) |
| maewaewa (wd:Q130359875)                      | instance of (wdt:P31) | traditional activity (wd:Q1982569) |
| Sarbacane (wd:Q3473509)                       | instance of (wdt:P31) | traditional activity (wd:Q1982569) |
| sugaring season traditions (wd:Q110727390)    | instance of (wdt:P31) | traditional activity (wd:Q1982569) |
| ...                                           | ...                   | ...                                |

[Assistant]
None of the instances of `wd:Q1982569` (traditional activity) listed seem to be directly related to pysanka. Given this, we need to take a different approach.

Since we couldn't find direct or indirect location information for pysanka, we can try to find countries where pysanka is practiced by looking for statements where pysanka is mentioned in the context of cultural practices or traditions.

Let's search for statements where `wd:Q3233785` (pysanka) is mentioned and see if we can find any countries or locations associated with it.

[Tool]
Got 51 rows and 3 columns, showing the first 10 rows below:
| subject                                                                     | property                                                       | object                |
| --------------------------------------------------------------------------- | -------------------------------------------------------------- | --------------------- |
| Vegreville egg (wd:Q7918394)                                                | instance of (wdt:P31)                                          | pysanka (wd:Q3233785) |
| Polish pisanka (wd:Q1404341)                                                | subclass of (wdt:P279)                                         | pysanka (wd:Q3233785) |
| wd:Q32440049                                                                | category combines topics (wdt:P971)                            | pysanka (wd:Q3233785) |
| Czesława Konopka (wd:Q97185992)                                             | field of work (wdt:P101)                                       | pysanka (wd:Q3233785) |
| Vegreville egg (wd:Q7918394)                                                | depicts (wdt:P180)                                             | pysanka (wd:Q3233785) |
| pysankar (wd:Q50333861)                                                     | product, material, or service produced or provided (wdt:P1056) | pysanka (wd:Q3233785) |
| <https://arz.wikipedia.org/wiki/%D8%A8%D9%8A%D8%B3%D8%A7%D9%86%D9%83%D8%A7> | schema:about                                                   | pysanka (wd:Q3233785) |
| wd:Q16834744                                                                | owl:sameAs                                                     | pysanka (wd:Q3233785) |
| s:Q7918394-8a84a81b-4fcd-2f00-79bb-6a5c2bc960f6                             | instance of (ps:P31)                                           | pysanka (wd:Q3233785) |
| Hutsul pysanka (wd:Q116733019)                                              | subclass of (wdt:P279)                                         | pysanka (wd:Q3233785) |
| ...                                                                         | ...                                                            | ...                   |

[Assistant]
From the results, we can see that `wd:Q3233785` (pysanka) is mentioned in several contexts, including instances and subclasses. However, none of these directly link to countries or locations.

One potential approach is to look for entities that are related to pysanka and then check if these entities have location information. For example, we can look at entities that are subclasses of pysanka and see if they have any location information.

Let's list the subclasses of `wd:Q3233785` (pysanka) and check if they have any location information using the `P276` (location) or `P3842` (located in the present-day administrative territorial entity) properties.

[Tool]
Got 6 rows and 3 columns:
| subject                          | property               | object                |
| -------------------------------- | ---------------------- | --------------------- |
| Polish pisanka (wd:Q1404341)     | subclass of (wdt:P279) | pysanka (wd:Q3233785) |
| Hutsul pysanka (wd:Q116733019)   | subclass of (wdt:P279) | pysanka (wd:Q3233785) |
| Russian pisanka (wd:Q16619215)   | subclass of (wdt:P279) | pysanka (wd:Q3233785) |
| Ukrainian pysanky (wd:Q55722017) | subclass of (wdt:P279) | pysanka (wd:Q3233785) |
| kroszonka (wd:Q86687104)         | subclass of (wdt:P279) | pysanka (wd:Q3233785) |
| wd:Q125522673                    | subclass of (wdt:P279) | pysanka (wd:Q3233785) |

[Assistant]
We have identified several subclasses of `wd:Q3233785` (pysanka):

1. `wd:Q1404341` (Polish pisanka)
2. `wd:Q116733019` (Hutsul pysanka)
3. `wd:Q16619215` (Russian pisanka)
4. `wd:Q55722017` (Ukrainian pysanky)
5. `wd:Q86687104` (kroszonka)
6. `wd:Q125522673`

Let's check if any of these subclasses have location information using the `P276` (location) or `P3842` (located in the present-day administrative territorial entity) properties.

We'll start with `wd:Q1404341` (Polish pisanka).

[Tool] Got no rows and 3 columns

[Assistant] It appears that `wd:Q1404341` (Polish pisanka) does not have any direct statements using the `P276` (location) property. Let's check if it has any statements using the `P3842` (located in the present-day administrative territorial entity) property.

[Tool] Got no rows and 3 columns

[Assistant]
It seems that `wd:Q1404341` (Polish pisanka) does not have any direct statements using the `P3842` (located in the present-day administrative territorial entity) property either.

Let's move on to the next subclass, `wd:Q116733019` (Hutsul pysanka), and check if it has any location information using the `P276` (location) or `P3842` (located in the present-day administrative territorial entity) properties.

First, let's check the `P276` (location) property for `wd:Q116733019` (Hutsul pysanka).

[Tool] Got no rows and 3 columns

[Assistant] It appears that `wd:Q116733019` (Hutsul pysanka) does not have any direct statements using the `P276` (location) property. Let's check if it has any statements using the `P3842` (located in the present-day administrative territorial entity) property.

[Tool] Got no rows and 3 columns

[Assistant]
It seems that `wd:Q116733019` (Hutsul pysanka) does not have any direct statements using the `P3842` (located in the present-day administrative territorial entity) property either.

Let's move on to the next subclass, `wd:Q16619215` (Russian pisanka), and check if it has any location information using the `P276` (location) or `P3842` (located in the present-day administrative territorial entity) properties.

First, let's check the `P276` (location) property for `wd:Q16619215` (Russian pisanka).

[Tool] Got no rows and 3 columns

[Assistant] It appears that `wd:Q16619215` (Russian pisanka) does not have any direct statements using the `P276` (location) property. Let's check if it has any statements using the `P3842` (located in the present-day administrative territorial entity) property.

[Tool] Got no rows and 3 columns

[Assistant]
It seems that `wd:Q16619215` (Russian pisanka) does not have any direct statements using the `P3842` (located in the present-day administrative territorial entity) property either.

Let's move on to the next subclass, `wd:Q55722017` (Ukrainian pysanky), and check if it has any location information using the `P276` (location) or `P3842` (located in the present-day administrative territorial entity) properties.

First, let's check the `P276` (location) property for `wd:Q55722017` (Ukrainian pysanky).

[Tool] Got no rows and 3 columns

[Assistant] It appears that `wd:Q55722017` (Ukrainian pysanky) does not have any direct statements using the `P276` (location) property. Let's check if it has any statements using the `P3842` (located in the present-day administrative territorial entity) property.

[Tool] Got no rows and 3 columns

[Assistant]
It seems that `wd:Q55722017` (Ukrainian pysanky) does not have any direct statements using the `P3842` (located in the present-day administrative territorial entity) property either.

Let's move on to the next subclass, `wd:Q86687104` (kroszonka), and check if it has any location information using the `P276` (location) or `P3842` (located in the present-day administrative territorial entity) properties.

First, let's check the `P276` (location) property for `wd:Q86687104` (kroszonka).

[Tool] Got no rows and 3 columns

[Assistant] It appears that `wd:Q86687104` (kroszonka) does not have any direct statements using the `P276` (location) property. Let's check if it has any statements using the `P3842` (located in the present-day administrative territorial entity) property.

[Tool] Got no rows and 3 columns

[Assistant]
It seems that `wd:Q86687104` (kroszonka) does not have any direct statements using the `P3842` (located in the present-day administrative territorial entity) property either.

Finally, let's check the last subclass, `wd:Q125522673`, and see if it has any location information using the `P276` (location) or `P3842` (located in the present-day administrative territorial entity) properties.

First, let's check the `P276` (location) property for `wd:Q125522673`.

[Tool] Got no rows and 3 columns

[Assistant] It appears that `wd:Q125522673` does not have any direct statements using the `P276` (location) property. Let's check if it has any statements using the `P3842` (located in the present-day administrative territorial entity) property.

[Tool] Got no rows and 3 columns

[Assistant]
It seems that `wd:Q125522673` does not have any direct statements using the `P3842` (located in the present-day administrative territorial entity) property either.

Given that none of the subclasses of `wd:Q3233785` (pysanka) have any location information, we need to take a different approach. One possible approach is to look for entities that are related to pysanka and are cultural practices, and then check if these entities have any location information.

Let's try to find entities that are related to pysanka and are cultural practices, and then check their locations. We can use the property `P17` (country) to find the countries where these practices are performed.

Let's construct a SPARQL query to find entities related to pysanka and their associated countries.

[Tool] Got no rows and 1 columns

[Assistant]
It seems that the SPARQL query did not return any results, indicating that there are no entities directly linked to pysanka that have a country specified using the `P17` (country) property.

Given the lack of direct location information for pysanka and its related entities, we need to consider a more indirect approach. One possibility is to look for entities that are related to pysanka and are cultural practices, and then check if these entities have any location information through other means, such as events or organizations.

Let's try to find entities that are related to pysanka and are cultural practices, and then check if these entities have any location information through events or organizations.

We can use the property `P131` (located in the administrative territorial entity) to find the administrative regions where these practices are performed, and then map these regions to countries.

Let's construct a SPARQL query to find entities related to pysanka and their associated administrative regions, and then map these regions to countries.

[Tool] Got no rows and 1 columns

[Assistant]
It seems that the SPARQL query did not return any results, indicating that there are no entities directly linked to pysanka that have a country specified through the `P131` (located in the administrative territorial entity) property.

Given the lack of direct and indirect location information for pysanka and its related entities, it appears that the knowledge graph does not have sufficient data to answer the question about the number of countries where pysanka is practiced.

Therefore, I must conclude that I cannot provide a satisfactory SPARQL query to answer the question. Here is my best attempt at a SPARQL query, but it did not yield any results.

I will now provide a detailed explanation and my best attempt at a SPARQL query.

### Explanation
1. **Entity Search**: I searched for the entity "pysanka" and found `wd:Q3233785`.
2. **Property Search**: I searched for properties related to "practice" and "location" but did not find a direct property linking a cultural practice to a location.
3. **Direct Location Check**: I checked if `wd:Q3233785` (pysanka) had any direct location information using properties `P276` (location) and `P3842` (located in the present-day administrative territorial entity), but found no results.
4. **Related Entities**: I looked for entities related to pysanka, such as instances and subclasses, and checked if they had any location information, but found no results.
5. **Indirect Approach**: I tried to find entities related to pysanka and are cultural practices, and then check their locations using properties `P17` (country) and `P131` (located in the administrative territorial entity), but found no results.

### Best Attempt at a SPARQL Query
```sparql
SELECT DISTINCT ?country WHERE {
  ?entity wdt:P31 wd:Q1982569 ;
          wdt:P131 ?region .
  ?region wdt:P17 ?country .
  ?entity wdt:P279* wd:Q3233785 .
}
```

This query attempts to find entities related to pysanka that are cultural practices and are located in administrative regions, and then map these regions to countries. However, it did not return any results.

### Conclusion
The knowledge graph does not have sufficient data to answer the question about the number of countries where pysanka is practiced. Therefore, I cannot provide a satisfactory SPARQL query to answer the question.

I will now call the `cancel` function with this explanation and my best attempt at a SPARQL query.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?act ?actLabel WHERE {
  ?act wdt:P31 wd:Q13406468 .
  ?act rdfs:label ?actLabel .
  FILTER ( LANG( ?actLabel ) = "de" || LANG( ?actLabel ) = "en" ) FILTER ( CONTAINS( LCASE( ?actLabel ) , "arbeitsschutz" ) || CONTAINS( LCASE( ?actLabel ) , "sicherheit" ) || CONTAINS( LCASE( ?actLabel ) , "gesundheit" ) || CONTAINS( LCASE( ?actLabel ) , "arbeitsrecht" ) )
}

Despite multiple attempts to search for the German Occupational Safety and Health Act and the relevant ministry, no relevant entities were found in the Wikidata knowledge graph. The specific act and the entity responsible for its passage might not be present in the data in a form that can be easily queried.

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

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

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

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

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

[User] Who passed the German Occupational Safety and Health Act?

[Assistant] To answer the question "Who passed the German Occupational Safety and Health Act?", we need to identify the entity representing the German Occupational Safety and Health Act and then find out who was responsible for passing it. Let's start by searching for the entity representing the act.

[Tool]
Top 10 entity alternatives:
1. Occupational Safety and Health Act, also known as Williams-Steiger Occupational Safety and Health Act of 1970, Public Law 91-596, OSH Act, OSHA Act, OSHA-1970 (wd:Q912402): United States law
2. Occupational Safety and Health Act (wd:Q18899790): law of Taiwan
3. Occupational Safety and Health Act (wd:Q47502511)
4. Occupational Safety and Health Act (wd:Q68948513): scientific article published on 01 April 1972
5. Occupational Health and Safety Act, also known as OHSA, OH & S Act, Ontario Occupational Health and Safety Act (wd:Q110542175): Ontario law enacted 1979
6. Occupational Health and Safety Act, also known as ZVZD-1 (wd:Q127329172): law of the Republic of Slovenia
7. Occupational Safety and Health Act 1994 (wd:Q7075788): national law of Malaysia
8. Occupational Health and Safety Act, 1993 (wd:Q60740074): South African statutory law administered by the Department of Labour
9. Occupational Health and Safety Act 1991 (wd:Q56750523): Act of the Parliament of Australia, no longer in force, registered as C2004A04105
10. Occupational Health and Safety Act NSW 2000 (wd:Q7075779): repealed statute of New South Wales, Australia

[Assistant]
None of the top 10 results specifically mention the German Occupational Safety and Health Act. However, we can try to refine our search by looking for a more specific term or by searching for "German" along with "Occupational Safety and Health Act."

Let's try searching for "German Occupational Safety and Health Act" again, but this time with a more specific query.

[Tool]
Top 10 entity alternatives:
1. Occupational Safety and Health Act, also known as Williams-Steiger Occupational Safety and Health Act of 1970, Public Law 91-596, OSH Act, OSHA Act, OSHA-1970 (wd:Q912402): United States law
2. Occupational Safety and Health Act (wd:Q18899790): law of Taiwan
3. Occupational Safety and Health Act (wd:Q47502511)
4. Occupational Safety and Health Act (wd:Q68948513): scientific article published on 01 April 1972
5. Occupational Health and Safety Act, also known as OHSA, OH & S Act, Ontario Occupational Health and Safety Act (wd:Q110542175): Ontario law enacted 1979
6. Occupational Health and Safety Act, also known as ZVZD-1 (wd:Q127329172): law of the Republic of Slovenia
7. Occupational Safety and Health Act 1994 (wd:Q7075788): national law of Malaysia
8. Occupational Health and Safety Act, 1993 (wd:Q60740074): South African statutory law administered by the Department of Labour
9. Occupational Health and Safety Act 1991 (wd:Q56750523): Act of the Parliament of Australia, no longer in force, registered as C2004A04105
10. Occupational Health and Safety Act NSW 2000 (wd:Q7075779): repealed statute of New South Wales, Australia

[Assistant] It seems that the specific entity for the German Occupational Safety and Health Act is not among the top results. Let's try a different approach by searching for "Arbeitsschutzgesetz," which is the German term for the Occupational Safety and Health Act.

[Tool] No entity items found

[Assistant]
It appears that the term "Arbeitsschutzgesetz" did not yield any results. Let's try another approach by searching for "German labor law" or "German occupational safety law" to see if we can find a relevant entity.

Let's search for "German labor law" and see if we can find any related entities.

[Tool]
Top 10 entity alternatives:
1. The Identification of Labor Relations in German Law (wd:Q119502449): scholarly article in Jinan Journal (Philosophy & Social Science Edition), no. 6, 2017
2. labor law, also known as employment law, labour law (wd:Q628967): mediates the relationship between workers, employers, trade unions and the government
3. law of Germany, also known as German law (wd:Q695742): positive law
4. German law (wd:Q883199): for law historians, the law that is based on Germanic ideas on law (as opposed to Roman law)
5. Labor Law, also known as n15 Sm15 Labor Law (wd:Q104710726): subject category of the 20th Century Press Archives
6. Labor law (wd:Q81804851): scientific article published on 01 July 2008
7. labor law (wd:L992052-S2)
8. labor law (wd:L992051-S2)
9. German Labor Front (wd:Q312526): Association of employers and employees during the Nazi era
10. United States labor law, also known as labor law in the United States, US labor law (wd:Q3039782): labor law in the USA

[Assistant]
The search for "German labor law" did not yield a specific entity for the German Occupational Safety and Health Act. However, we can try to search for "occupational safety and health" in the context of German law to see if we can find a more relevant entity.

Let's search for "German occupational safety and health" to see if we can find the specific act or related entities.

[Tool]
Top 10 entity alternatives:
1. occupational health and safety, also known as WSH, work safety and health, work health and safety, WHS, OSH (wd:Q629029): area concerned with the safety, health and welfare of people at occupation
2. Occupational safety and health (wd:Q46154347): scientific article published in October 1975
3. Occupational safety and health (wd:Q56931190): article
4. Occupational safety and health (wd:Q69450179): scientific article published on 01 April 1989
5. Occupational safety and health (wd:Q74719223): scientific article published on 01 January 1979
6. Occupational safety and health (wd:Q79510649): scientific article published on 01 January 2003
7. Occupational Safety and Health (wd:Q57701688): article
8. Occupational Safety and Health (wd:Q95540422)
9. Occupational health and safety (wd:Q27038378): book
10. Occupational health and safety (wd:Q67711117): scientific article published on 01 August 1977

[Assistant]
The search for "German occupational safety and health" did not yield a specific entity for the German Occupational Safety and Health Act. Given that the direct search for the act has not been successful, let's try a different approach by searching for the entity that represents the German government or the legislative body that would be responsible for passing such an act.

We can search for "Bundestag" (the federal parliament of Germany) and see if we can find any information about the passage of the act through this entity.

Let's search for "Bundestag" and see if we can find any relevant information.

[Tool]
Top 10 entity alternatives:
1. German Bundestag, also known as Bundestag of Germany, German parliament (wd:Q154797): legislature of Germany; parliament
2. President of the Bundestag, also known as Bundestagspräsident, Präsident des Deutschen Bundestages (wd:Q56024): presiding member of the parliament of Germany
3. Bundestag metro station, also known as U-Bahnhof Bundestag, U-Bahnhof Reichstag (wd:Q694848): Berlin U-Bahn station
4. FC Bundestag (wd:Q1386958): parliamentary association football team of the German Bundestag
5. German federal election, also known as Bundestag election, German federal elections (wd:Q1007356): election to the German Bundestag
6. Bundestag Parliamentary Group, also known as Bundestagsgruppe (wd:Q1007351): German parliamentary group
7. bundestag.de (wd:Q15948832): website of the Bundestag of Germany
8. Bundestag fraction, also known as Fraktionsgemeinschaft (wd:Q1440595): political fraction in German parliament
9. Bundestag committee (wd:Q1007311): parliamentary committee of the Bundestag of Germany
10. Bundestagszusammenfasser (wd:Q131149112): digital project to make the German legislative process more transparent

[Assistant]
The search for "Bundestag" has yielded the entity `wd:Q154797`, which represents the German Bundestag, the federal parliament of Germany. Since the Bundestag is the legislative body that would be responsible for passing laws, including the German Occupational Safety and Health Act, we can use this entity to find out who passed the act.

Let's execute a SPARQL query to find out if there is any information linking the German Bundestag to the passage of the German Occupational Safety and Health Act. We will look for any statements where the Bundestag is involved in the creation or passage of the act.

Here is the initial SPARQL query:

```sparql
SELECT ?act ?actLabel WHERE {
  wd:Q154797 wdt:P31 wd:Q13406468 .  # Check if the Bundestag is a legislative body
  ?act wdt:P31 wd:Q13406468 .         # Find entities that are laws
  ?act rdfs:label ?actLabel .
  FILTER(LANG(?actLabel) = "en")
  FILTER(CONTAINS(LCASE(?actLabel), "german occupational safety and health"))
}
```

This query checks if the Bundestag is a legislative body and then looks for laws that contain the phrase "German Occupational Safety and Health" in their label. Let's execute this query to see if we can find the act and any information about its passage.

[Tool] Got no rows and 2 columns

[Assistant]
The initial query did not return any results, indicating that the specific label "German Occupational Safety and Health Act" might not be present in the data. Let's try a more general approach by searching for laws related to occupational safety and health in Germany and then checking if the Bundestag is involved in their passage.

We can use the property `P31` (instance of) to find laws and then filter by the label to include terms like "Arbeitsschutz" or "occupational safety and health" in German or English.

Here is the updated SPARQL query:

```sparql
SELECT ?act ?actLabel WHERE {
  ?act wdt:P31 wd:Q13406468 .  # Find entities that are laws
  ?act rdfs:label ?actLabel .
  FILTER(LANG(?actLabel) = "de" || LANG(?actLabel) = "en")
  FILTER(CONTAINS(LCASE(?actLabel), "arbeitsschutz") || CONTAINS(LCASE(?actLabel), "occupational safety and health"))
}
```

This query looks for laws that have labels containing "arbeitsschutz" or "occupational safety and health" in either German or English. Let's execute this query to see if we can find the relevant act.

[Tool] Got no rows and 2 columns

[Assistant]
The query did not return any results, which suggests that the specific label or term we are looking for might not be present in the data. Given this, let's take a different approach by searching for the entity representing the German Occupational Safety and Health Act directly using a broader search term and then checking if the Bundestag is involved in its passage.

We can try searching for "Arbeitsschutzgesetz" again, but this time with a broader search to see if we can find any related entities.

Let's execute a broader search for "Arbeitsschutzgesetz" and see if we can find any related entities or laws.

[Tool] No entity items found

[Assistant]
The search for "Arbeitsschutzgesetz" did not yield any results, which suggests that the specific term might not be present in the knowledge graph. Given this, let's try a more general approach by searching for "occupational safety and health" in the context of German legislation.

We can search for "German law" and then filter the results to find laws related to occupational safety and health. Let's try this approach.

Let's search for "German law" and then filter the results to find laws related to occupational safety and health.

[Tool]
Top 10 entity alternatives:
1. law of Germany, also known as German law (wd:Q695742): positive law
2. German law (wd:Q883199): for law historians, the law that is based on Germanic ideas on law (as opposed to Roman law)
3. German town law (wd:Q16981896): late-Mediaeval European form of municipal governance
4. German Military Tribunal, also known as German military law (wd:Q873952)
5. copyright law of Germany, also known as copyright law (Germany), copyright law in Germany, German copyright law (wd:Q1206081): area of intellectual property law in Germany
6. German Law Journal, also known as GLJ (wd:Q1513942): Canadian-American online law journal, reporting on the developments of German, European, and international jurisprudence
7. German nationality law, also known as Germany nationality law, Germany's nationality law, nationality law (Germany), nationality law in Germany, nationality law of Germany (wd:Q100694580): law in Germany
8. German labour law (wd:Q628937): governs the legal relationships between individual workers and e...esenting workers and employers (collective labor law) in Germany
9. German patent law, also known as patent law in Germany, patent law of Germany, patent law (Germany), Germany's patent law (wd:Q2056721): law
10. constitutional law of Germany, also known as German constitutional law (wd:Q2801632): branch of German political science and law

[Assistant]
The search for "German law" did not yield a specific entity for the German Occupational Safety and Health Act. However, we can try to search for "German labour law" and see if there are any related laws or acts that might be relevant.

Let's search for "German labour law" and see if we can find any related entities or laws that might include the German Occupational Safety and Health Act.

Let's execute this search:

[Tool]
Top 10 entity alternatives:
1. German labour law (wd:Q628937): governs the legal relationships between individual workers and e...esenting workers and employers (collective labor law) in Germany
2. labor law, also known as employment law, labour law (wd:Q628967): mediates the relationship between workers, employers, trade unions and the government
3. law of Germany, also known as German law (wd:Q695742): positive law
4. German law (wd:Q883199): for law historians, the law that is based on Germanic ideas on law (as opposed to Roman law)
5. Labour Law (wd:Q130530362): book by  James Odartey Mills
6. Indian labour law (wd:Q15240923): laws regulating labour in India
7. European labour law (wd:Q368611): EU employment legislation
8. International labour law (wd:Q6054717): law
9. French labour law (wd:Q628943): law in France
10. German town law (wd:Q16981896): late-Mediaeval European form of municipal governance

[Assistant]
The search for "German labour law" returned the entity `wd:Q628937`, which represents German labour law. This entity might contain information about various laws and regulations, including the German Occupational Safety and Health Act.

Let's execute a SPARQL query to find out if there are any specific laws or acts related to occupational safety and health under German labour law. We will look for any statements where `wd:Q628937` (German labour law) is related to laws or acts that contain the terms "Arbeitsschutz" or "occupational safety and health" in their labels.

Here is the SPARQL query:

```sparql
SELECT ?act ?actLabel WHERE {
  wd:Q628937 wdt:P31 wd:Q13406468 .  # Check if German labour law is a law
  ?act wdt:P31 wd:Q13406468 .         # Find entities that are laws
  ?act rdfs:label ?actLabel .
  FILTER(LANG(?actLabel) = "de" || LANG(?actLabel) = "en")
  FILTER(CONTAINS(LCASE(?actLabel), "arbeitsschutz") || CONTAINS(LCASE(?actLabel), "occupational safety and health"))
}
```

This query checks if German labour law is a law and then looks for laws that contain the terms "Arbeitsschutz" or "occupational safety and health" in their labels. Let's execute this query to see if we can find the relevant act.

[Tool] Got no rows and 2 columns

[Assistant]
The query did not return any results, which suggests that the specific terms "Arbeitsschutz" or "occupational safety and health" might not be directly linked to the German labour law entity in the way we expected.

Given this, let's take a different approach by searching for the entity representing the German Occupational Safety and Health Act directly using a broader search term and then checking if the Bundestag is involved in its passage.

We can try searching for "Arbeitsschutz" and see if we can find any related entities or laws.

Let's execute a search for "Arbeitsschutz" and see if we can find any relevant entities or laws.

[Tool]
Top 10 entity alternatives:
1. Arbeitsschutzmanagement (wd:Q629019)
2. Deutsches Arbeitsschutzmuseum (wd:Q91949428): former exhibition, from 1930 Reich authority, on occupational health and safety in Berlin (1903-1914, 1922-1945)
3. Nationale Arbeitsschutzkonferenz (wd:Q1967943)
4. Zentralblatt fur Arbeitsmedizin, Arbeitsschutz und Prophylaxe, also known as Zentralbl Arbeitsmed Arbeitsschutz Prophyl (wd:Q27713978): journal
5. Forschungsgesellschaft für Arbeitsphysiologie und Arbeitsschutz (wd:Q74526749): organisation involved in scholarly research
6. Zentralblatt für Arbeitsmedizin,...schutz, Prophylaxe und Ergonomie, also known as Zentralbl Arbeitsmed Arbeitsschutz Prophyl Ergonomie (wd:Q27713979): journal
7. Zentralblatt fur Arbeitsmedizin und Arbeitsschutz, also known as Zentralbl Arbeitsmed (wd:Q27713977): journal
8. Schriftenreihe Zentralblatt fur ...in, Arbeitsschutz und Prophylaxe, also known as Schriftenr Zentralbl Arbeitsmed Arbeitsschutz Prophyl (wd:Q27713397): journal
9. Zentralblatt für Arbeitsmedizin, Arbeitsschutz und Ergonomie (wd:Q190266): periodical literature
10. Arbeitsort Privathaushalt: eine arbeitsschutzfreie Zone? (wd:Q130169450): scholarly article published in 2015

[Assistant]
The search for "Arbeitsschutz" did not yield the specific entity for the German Occupational Safety and Health Act. However, it did return several entities related to occupational safety and health in Germany.

Given that the specific act is not directly listed, we can try a more general approach by searching for "Arbeitsschutzgesetz" in a broader context and then checking if the Bundestag is involved in its passage.

Let's try a more general search for "Arbeitsschutzgesetz" and see if we can find any related entities or laws.

Here is the SPARQL query to search for any laws or acts related to "Arbeitsschutzgesetz":

```sparql
SELECT ?act ?actLabel WHERE {
  ?act wdt:P31 wd:Q13406468 .  # Find entities that are laws
  ?act rdfs:label ?actLabel .
  FILTER(LANG(?actLabel) = "de" || LANG(?actLabel) = "en")
  FILTER(CONTAINS(LCASE(?actLabel), "arbeitsschutzgesetz"))
}
```

This query looks for laws that have labels containing "arbeitsschutzgesetz" in either German or English. Let's execute this query to see if we can find the relevant act.

[Tool] Got no rows and 2 columns

[Assistant]
The query did not return any results, which suggests that the specific term "Arbeitsschutzgesetz" might not be present in the data. Given this, let's take a different approach by searching for the entity representing the German Occupational Safety and Health Act using a broader search term and then checking if the Bundestag is involved in its passage.

Since the direct search for "Arbeitsschutzgesetz" and related terms has not been successful, we can try a more general search for "occupational safety and health" in the context of German legislation and then manually check the results.

Let's execute a broader search for "occupational safety and health" in the context of German legislation and see if we can find any relevant entities or laws.

Here is the SPARQL query to search for any laws or acts related to "occupational safety and health" in Germany:

```sparql
SELECT ?act ?actLabel WHERE {
  ?act wdt:P31 wd:Q13406468 .  # Find entities that are laws
  ?act rdfs:label ?actLabel .
  FILTER(LANG(?actLabel) = "de" || LANG(?actLabel) = "en")
  FILTER(CONTAINS(LCASE(?actLabel), "sicherheit") && CONTAINS(LCASE(?actLabel), "gesundheit"))
}
```

This query looks for laws that have labels containing both "sicherheit" (safety) and "gesundheit" (health) in either German or English. Let's execute this query to see if we can find the relevant act.

[Tool] Got no rows and 2 columns

[Assistant]
The query did not return any results, which suggests that the specific terms "sicherheit" and "gesundheit" together might not be present in the labels of the relevant laws. Given this, let's try a more general approach by searching for "Arbeitsschutz" and "Gesetz" (law) separately and then checking if the Bundestag is involved in the passage of any relevant laws.

Let's execute a search for "Arbeitsschutz" and "Gesetz" and see if we can find any relevant entities or laws.

Here is the SPARQL query to search for any laws or acts related to "Arbeitsschutz" and "Gesetz":

```sparql
SELECT ?act ?actLabel WHERE {
  ?act wdt:P31 wd:Q13406468 .  # Find entities that are laws
  ?act rdfs:label ?actLabel .
  FILTER(LANG(?actLabel) = "de" || LANG(?actLabel) = "en")
  FILTER(CONTAINS(LCASE(?actLabel), "arbeitsschutz") || CONTAINS(LCASE(?actLabel), "gesetz"))
}
```

This query looks for laws that have labels containing "arbeitsschutz" or "gesetz" in either German or English. Let's execute this query to see if we can find the relevant act.

[Tool] Got no rows and 2 columns

[Assistant]
The query did not return any results, which suggests that the specific terms "arbeitsschutz" and "gesetz" might not be present in the labels of the relevant laws in the way we expected. Given this, let's take a different approach by searching for the entity representing the German Occupational Safety and Health Act using a broader search term and then checking if the Bundestag is involved in its passage.

Since the direct search for "Arbeitsschutzgesetz" and related terms has not been successful, we can try a more general search for "occupational safety and health" in the context of German legislation and then manually check the results.

Let's execute a broader search for "occupational safety and health" in the context of German legislation and see if we can find any relevant entities or laws.

Here is the SPARQL query to search for any laws or acts related to "occupational safety and health" in Germany:

```sparql
SELECT ?act ?actLabel WHERE {
  ?act wdt:P31 wd:Q13406468 .  # Find entities that are laws
  ?act rdfs:label ?actLabel .
  FILTER(LANG(?actLabel) = "de" || LANG(?actLabel) = "en")
  FILTER(CONTAINS(LCASE(?actLabel), "sicherheit") || CONTAINS(LCASE(?actLabel), "gesundheit"))
}
```

This query looks for laws that have labels containing "sicherheit" (safety) or "gesundheit" (health) in either German or English. Let's execute this query to see if we can find the relevant act.

[Tool] Got no rows and 2 columns

[Assistant]
The query did not return any results, which suggests that the specific terms "sicherheit" and "gesundheit" might not be present in the labels of the relevant laws in the way we expected. Given this, let's take a different approach by searching for the entity representing the German Occupational Safety and Health Act using a broader search term and then checking if the Bundestag is involved in its passage.

Since the direct search for "Arbeitsschutzgesetz" and related terms has not been successful, we can try a more general search for "occupational safety and health" in the context of German legislation and then manually check the results.

Let's execute a broader search for "occupational safety and health" in the context of German legislation and see if we can find any relevant entities or laws.

Here is the SPARQL query to search for any laws or acts related to "occupational safety and health" in Germany:

```sparql
SELECT ?act ?actLabel WHERE {
  ?act wdt:P31 wd:Q13406468 .  # Find entities that are laws
  ?act rdfs:label ?actLabel .
  FILTER(LANG(?actLabel) = "de" || LANG(?actLabel) = "en")
  FILTER(CONTAINS(LCASE(?actLabel), "arbeitsschutz") || CONTAINS(LCASE(?actLabel), "sicherheit") || CONTAINS(LCASE(?actLabel), "gesundheit"))
}
```

This query looks for laws that have labels containing "arbeitsschutz" (occupational safety), "sicherheit" (safety), or "gesundheit" (health) in either German or English. Let's execute this query to see if we can find the relevant act.

[Tool] Got no rows and 2 columns

[Assistant]
The query did not return any results, which suggests that the specific terms "arbeitsschutz," "sicherheit," and "gesundheit" might not be present in the labels of the relevant laws in the way we expected. Given this, let's take a different approach by searching for the entity representing the German Occupational Safety and Health Act using a broader search term and then checking if the Bundestag is involved in its passage.

Since the direct search for "Arbeitsschutzgesetz" and related terms has not been successful, we can try a more general search for "occupational safety and health" in the context of German legislation and then manually check the results.

Let's execute a broader search for "occupational safety and health" in the context of German legislation and see if we can find any relevant entities or laws.

Here is the SPARQL query to search for any laws or acts related to "occupational safety and health" in Germany:

```sparql
SELECT ?act ?actLabel WHERE {
  ?act wdt:P31 wd:Q13406468 .  # Find entities that are laws
  ?act rdfs:label ?actLabel .
  FILTER(LANG(?actLabel) = "de" || LANG(?actLabel) = "en")
  FILTER(CONTAINS(LCASE(?actLabel), "arbeitsschutz") || CONTAINS(LCASE(?actLabel), "sicherheit") || CONTAINS(LCASE(?actLabel), "gesundheit") || CONTAINS(LCASE(?actLabel), "occupational safety and health"))
}
```

This query looks for laws that have labels containing "arbeitsschutz" (occupational safety), "sicherheit" (safety), "gesundheit" (health), or "occupational safety and health" in either German or English. Let's execute this query to see if we can find the relevant act.

[Tool] Got no rows and 2 columns

[Assistant]
The query did not return any results, which suggests that the specific terms "arbeitsschutz," "sicherheit," "gesundheit," and "occupational safety and health" might not be present in the labels of the relevant laws in the way we expected. Given this, let's take a different approach by searching for the entity representing the German Occupational Safety and Health Act using a broader search term and then checking if the Bundestag is involved in its passage.

Since the direct search for "Arbeitsschutzgesetz" and related terms has not been successful, we can try a more general search for "occupational safety and health" in the context of German legislation and then manually check the results.

Let's execute a broader search for "occupational safety and health" in the context of German legislation and see if we can find any relevant entities or laws.

Here is the SPARQL query to search for any laws or acts related to "occupational safety and health" in Germany:

```sparql
SELECT ?act ?actLabel WHERE {
  ?act wdt:P31 wd:Q13406468 .  # Find entities that are laws
  ?act rdfs:label ?actLabel .
  FILTER(LANG(?actLabel) = "de" || LANG(?actLabel) = "en")
  FILTER(CONTAINS(LCASE(?actLabel), "arbeitsschutz") || CONTAINS(LCASE(?actLabel), "sicherheit") || CONTAINS(LCASE(?actLabel), "gesundheit") || CONTAINS(LCASE(?actLabel), "arbeitsrecht"))
}
```

This query looks for laws that have labels containing "arbeitsschutz" (occupational safety), "sicherheit" (safety), "gesundheit" (health), or "arbeitsrecht" (labor law) in either German or English. Let's execute this query to see if we can find the relevant act.

[Tool] Got no rows and 2 columns

[Assistant]
The query did not return any results, which suggests that the specific terms "arbeitsschutz," "sicherheit," "gesundheit," and "arbeitsrecht" might not be present in the labels of the relevant laws in the way we expected. Given this, it seems that the specific entity for the German Occupational Safety and Health Act might not be available in the Wikidata knowledge graph with the labels we are searching for.

Given the lack of success in finding the specific act, let's take a different approach by searching for the entity representing the German Federal Ministry of Labour and Social Affairs (Bundesministerium für Arbeit und Soziales), which is typically responsible for such legislation. We can then check if this ministry is involved in the passage of the act.

Let's search for the entity representing the German Federal Ministry of Labour and Social Affairs.

Here is the search query:

```sparql
SELECT ?ministry ?ministryLabel WHERE {
  ?ministry wdt:P31 wd:Q13406468 .  # Find entities that are organizations
  ?ministry rdfs:label ?ministryLabel .
  FILTER(LANG(?ministryLabel) = "de" || LANG(?ministryLabel) = "en")
  FILTER(CONTAINS(LCASE(?ministryLabel), "bundesministerium für arbeit und soziales") || CONTAINS(LCASE(?ministryLabel), "federal ministry of labour and social affairs"))
}
```

This query looks for organizations that have labels containing "Bundesministerium für Arbeit und Soziales" (Federal Ministry of Labour and Social Affairs) in either German or English. Let's execute this query to see if we can find the relevant ministry.

[Tool] Got no rows and 2 columns

[Assistant]
The query did not return any results, which suggests that the specific entity for the German Federal Ministry of Labour and Social Affairs might not be present in the Wikidata knowledge graph with the labels we are searching for. Given this, it seems that the specific entity for the German Occupational Safety and Health Act and the relevant ministry might not be available in the current data.

Given the lack of success in finding the specific act and the relevant ministry, it is likely that the information we are looking for is not present in the Wikidata knowledge graph in a form that can be easily queried.

Therefore, I will have to conclude that I cannot find a satisfactory SPARQL query to answer the question "Who passed the German Occupational Safety and Health Act?" based on the available data.

Here is my final response:

```json
{
  "explanation": "Despite multiple attempts to search for the German Occupational Safety and Health Act and the relevant ministry, no relevant entities were found in the Wikidata knowledge graph. The specific act and the entity responsible for its passage might not be present in the data in a form that can be easily queried.",
  "best_attempt": {
    "sparql": "SELECT ?act ?actLabel WHERE { ?act wdt:P31 wd:Q13406468 . ?act rdfs:label ?actLabel . FILTER(LANG(?actLabel) = \"de\" || LANG(?actLabel) = \"en\") FILTER(CONTAINS(LCASE(?actLabel), \"arbeitsschutz\") || CONTAINS(LCASE(?actLabel), \"sicherheit\") || CONTAINS(LCASE(?actLabel), \"gesundheit\") || CONTAINS(LCASE(?actLabel), \"arbeitsrecht\")) }",
    "kg": "wikidata"
  }
}
```

I will now call the `cancel` function to stop the generation process.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?forest ?area WHERE {
  VALUES ?forest {
    wd:Q177567 wd:Q932289
  }
  ?forest wdt:P2046 ?area .
}

The Amazon Rainforest is bigger than the Congo Basin.

[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] which forest is bigger, Amazon Rainforest or Congo Basin?

[Assistant] To determine which forest is bigger, we need to identify the entities for the Amazon Rainforest and the Congo Basin, and then find their respective areas. Let's start by searching for these entities in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Amazon rainforest, also known as Brazilian Amazon, Amazon rain forest, Amazonian rainforest, Amazonia, Amazon forest (wd:Q177567): large rainforest in South America
2. deforestation of the Amazon Rainforest, also known as amazonian deforestation, Amazon Rainforest's deforestation, deforestation (Amazon Rainforest), deforestation of Amazon, Amazon deforestation (wd:Q5251697): overview about the deforestation of the Amazon Rainforest
3. 2019 Amazon rainforest wildfires, also known as 2019 Brazilian wildfires, 2019 Brazil wildfires (wd:Q66677938): Wildfires in Brazil Amazon fire forest
4. fauna of the Amazon rainforest (wd:Q107210685): native animals of the Amazon rainforest
5. Amazon rainforest, people and biodiversity (wd:Q128357663): scholarly article
6. Linked Brazilian Amazon Rainforest Data (wd:Q120984755): article published in the Semantic Web Journal
7. Selective logging in the Amazon rainforest (wd:Q7447772)
8. Acid rain in an Amazon rainforest (wd:Q114603945): scientific article published in 1983
9. Isoprene photochemistry over the Amazon rainforest (wd:Q28828668): scientific article
10. Drought Sensitivity of the Amazon Rainforest (wd:Q30046261): scientific article (publication date: 6 March 2009)

[Assistant] The top result for "Amazon Rainforest" is `wd:Q177567`. Now let's search for the Congo Basin.

[Tool]
Top 10 entity alternatives:
1. Congo basin (wd:Q932289): basin of the Congo River in west equatorial Africa
2. Congo basin, also known as Zaire basin (wd:Q124044461): lowland in central Africa
3. Congolian forests, also known as Congo Basin forest, Congolian forests (wd:Q3079079): tropical rainforest, in Central Africa.
4. Congo Basin Forest Partnership (wd:Q5160495): Conservation initiative
5. Colonization of the Congo Basin (wd:Q2984278): European colonization of Africa's Congo Basin
6. Deforestation of the Congo Basin (wd:Q97366409)
7. Onchocerciasis in the Congo basin (wd:Q54052595): scientific article
8. Neogene congo basin rain forest (wd:Q46832519): scientific article published in August 1985
9. Tropical forests: Include Congo basin (wd:Q54119974): scientific article
10. Congo Basin Hydrology, Climate, and Biogeochemistry (wd:Q111634509): scientific article published on 25 February 2022

[Assistant]
The top result for "Congo Basin" is `wd:Q932289`. Now that we have the entities, let's find the area of each forest. We will look for the property that represents the area of a geographical region.

Let's search for the property "area" in the knowledge graph.

[Tool]
Top 10 property alternatives:
1. area, also known as total area, surface area, surface, size, resolution (wd:P2046 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): area occupied by an object
2. field of work, also known as scientific discipline, scientific area, responsible for, research on, research fields (wd:P101 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): specialization of a person or organization; see P106 for the occupation, interested in
3. applies to part, also known as when viewed as, valid for part, section, region, per (wd:P518 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): part, aspect, or form of the item to which the claim applies
4. applies to jurisdiction, also known as belongs to jurisdiction, applies to territorial jurisdiction, applies to region, applies to place, applies to geographic place (wd:P1001 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): the item (institution, law, public office, public register...) o...a territorial jurisdiction: a country, state, municipality, ...), significant place, characteristic of, operating area
5. operating area, also known as province served, serves jurisdiction, serves geographic region, serves geographic area, serves area (wd:P2541 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): geographic area or jurisdiction an organisation or industry operates in, serves, or has responsibility for, location
6. water area (wd:P8887 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): area/surface of a geographical entity that is covered by water, area
7. interested in, also known as area of interest, area of research, field of interest, field of research, field of study (wd:P2650 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): item of special or vested interest to this person or organisation
8. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
9. 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 pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
10. electoral district, also known as riding, seat, ward, electoral area, electorate (wd:P768 as pqv/psn/psv/pqn/prn/pq/prv/p/ps/wdt/wdtn/pr): electoral district this person is representing, or of the office... or "office contested" (P541) or "candidacy in election" (P3602)

[Assistant]
The top result for "area" is `wd:P2046`. Now we can construct a SPARQL query to retrieve the areas of both the Amazon Rainforest and the Congo Basin.

Let's execute the SPARQL query to get the areas.

[Tool]
Got 2 rows and 2 columns:
| ?forest                        | ?area   |
| ------------------------------ | ------- |
| Amazon rainforest (wd:Q177567) | 6700000 |
| Congo basin (wd:Q932289)       | 1000000 |

[Assistant]
The results show that the area of the Amazon Rainforest is 6,700,000 square kilometers, while the area of the Congo Basin is 1,000,000 square kilometers. Therefore, the Amazon Rainforest is larger than the Congo Basin.

Here is the final SPARQL query and answer:

```sparql
SELECT ?forest ?area WHERE {
  VALUES ?forest { wd:Q177567 wd:Q932289 }
  ?forest wdt:P2046 ?area .
}
```

The Amazon Rainforest is bigger than the Congo Basin.

[Tool] Stopped generation process