PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( DISTINCT ?country ) AS ?count ) WHERE {
  wd:Q3233785 wdt:P17 ?country .
}

Got 1 row and 1 column:
| ?count |
| ------ |
| 14     |

Pysanka is practiced in 14 countries according to Wikidata.

[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 "In how many countries is pysanka practiced?" we need to identify the concept of "pysanka" in Wikidata and then find the countries where this practice is present.

Step 1: Search for the entity "pysanka" in Wikidata to identify its QID.

[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 entity "pysanka" as an egg decorating tradition in Slavic countries is identified as wd:Q3233785.

Step 2: We need to find the countries where this tradition (pysanka) is practiced. This might be represented by a property linking the tradition to countries or regions. I will now search for properties related to the entity wd:Q3233785 that might indicate the countries or locations where it is practiced.

[Tool]
Top 10 property alternatives:
1. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
2. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
3. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as wdt/p): main Wikimedia category
4. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
5. manufacturer, also known as manufactured by, provider, provided by, product of, producer (wd:P176 as wdt/p): (main or final) manufacturer or producer of this product
6. religion or worldview, also known as believes, worldview, religious affiliation, religion or world view, religion (wd:P140 as wdt/p): religion of a person, organization or religious building, or associated with this subject
7. subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt/p): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
8. Freebase ID, also known as Freebase, MID, Freebase identifier, FID (wd:P646 as wdt/p): identifier for a page in the Freebase database. Format: "/m/0" f...r IDs starting with "/g/", use Google Knowledge Graph ID (P2671)

No other items found

[Assistant] The property "country" (wdt:P17) is generally used for sovereign states or locations, but it may not be directly applicable for a cultural tradition like pysanka. Instead, I will try to find statements or qualifiers related to the entity wd:Q3233785 that indicate the countries or regions where this tradition is practiced. I will list triples with the subject wd:Q3233785 to see if there are any relevant properties indicating countries or regions.

[Tool]
Got 167 rows and 3 columns, showing the first 10 rows below:
| subject               | property                                       | object                                                                                |
| --------------------- | ---------------------------------------------- | ------------------------------------------------------------------------------------------------------- |
| pysanka (wd:Q3233785) | instance of (wdt:P31)                          | tradition (wd:Q82821)                                                                                |
| pysanka (wd:Q3233785) | country (wdt:P17)                              | Poland (wd:Q36)                                                                                |
| pysanka (wd:Q3233785) | Commons category (wdt:P373)                    | Pysanka                                                                                |
| pysanka (wd:Q3233785) | image (wdt:P18)                                | <http://commons.wikimedia.org/wiki/Special:FilePath/Meander%20Motif%20on%20a%20Ukrainian%20Pysanka.JPG> |
| pysanka (wd:Q3233785) | subclass of (wdt:P279)                         | easter egg (wd:Q163886)                                                                                |
| pysanka (wd:Q3233785) | on focus list of Wikimedia project (wdt:P5008) | WikiProject Ukraine (wd:Q10780973)                                                                      |
| pysanka (wd:Q3233785) | maintained by WikiProject (wdt:P6104)          | WikiProject Intangible Cultural Heritage (wd:Q112898263)                                                |
| pysanka (wd:Q3233785) | topic's main category (wdt:P910)               | wd:Q32494339                                                                                |
| pysanka (wd:Q3233785) | religion or worldview (wdt:P140)               | Rodnovery (wd:Q1258217)                                                                                |
| pysanka (wd:Q3233785) | manufacturer (wdt:P176)                        | pysankar (wd:Q50333861)                                                                                |
| ...                   | ...                                            | ...                                                                                |

[Assistant]
The entity pysanka (wd:Q3233785) has a property "country" (wdt:P17) with the value Poland (wd:Q36). This indicates that pysanka is practiced in Poland. However, the question asks for the number of countries where pysanka is practiced, so there might be more countries.

Step 3: I will now check if there are other countries linked to pysanka by the property "country" (wdt:P17) or if there are other properties that indicate the countries where it is practiced. I will specifically look for other values of the property "country" for the entity wd:Q3233785.

[Tool]
Got 14 rows and 3 columns, showing the first 10 rows below:
| subject               | property          | object                           |
| --------------------- | ----------------- | -------------------------------- |
| pysanka (wd:Q3233785) | country (wdt:P17) | Poland (wd:Q36)                  |
| pysanka (wd:Q3233785) | country (wdt:P17) | Ukraine (wd:Q212)                |
| pysanka (wd:Q3233785) | country (wdt:P17) | Bulgaria (wd:Q219)               |
| pysanka (wd:Q3233785) | country (wdt:P17) | Belarus (wd:Q184)                |
| pysanka (wd:Q3233785) | country (wdt:P17) | Czech Republic (wd:Q213)         |
| pysanka (wd:Q3233785) | country (wdt:P17) | Croatia (wd:Q224)                |
| pysanka (wd:Q3233785) | country (wdt:P17) | Romania (wd:Q218)                |
| pysanka (wd:Q3233785) | country (wdt:P17) | Serbia (wd:Q403)                 |
| pysanka (wd:Q3233785) | country (wdt:P17) | Slovakia (wd:Q214)               |
| pysanka (wd:Q3233785) | country (wdt:P17) | Bosnia and Herzegovina (wd:Q225) |
| ...                   | ...               | ...                              |

[Assistant]
The property "country" (wdt:P17) for the entity pysanka (wd:Q3233785) has multiple values indicating the countries where pysanka is practiced. Some of these countries are Poland, Ukraine, Bulgaria, Belarus, Czech Republic, Croatia, Romania, Serbia, Slovakia, Bosnia and Herzegovina, etc.

Step 4: I will now count the total number of distinct countries linked to pysanka by the property "country" (wdt:P17).

[Tool]
Got 1 row and 1 column:
| ?count |
| ------ |
| 14     |

[Tool] Stopped generation process


I could not find a direct entity for the German Occupational Safety and Health Act in Wikidata. Attempts to find the law or related entities with labels or descriptions matching the German law were unsuccessful. Also, queries to find the legislator of related laws timed out or returned no results. The German Occupational Safety and Health Act is known to be passed by the German Bundestag (Federal Diet), but this information is not directly available in the queried knowledge graph.

[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]
The question asks for the entity or entities who passed the German Occupational Safety and Health Act. This implies we are looking for the legislative body or authority responsible for passing this specific law.

Step 1: Identify the entity for the "German Occupational Safety and Health Act" in Wikidata.
Step 2: Identify the property that relates a law to the entity that passed or enacted it.
Step 3: Query the entity that passed the German Occupational Safety and Health Act.

I will start by searching for the entity "German Occupational Safety and Health Act" in Wikidata.

[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]
The search results do not show a direct match for the "German Occupational Safety and Health Act." However, there is an entity "Occupational Safety and Health Act" (wd:Q47502511) which might be related. To confirm if this entity corresponds to the German Occupational Safety and Health Act, I will check its labels and descriptions.

I will query the labels and descriptions of wd:Q47502511 to verify if it is the German Occupational Safety and Health Act.

[Tool] Got no rows and 2 columns

[Assistant] The query to get the label and description for the entity wd:Q47502511 returned no results, which is unexpected. I will try a different approach to get the label and description for this entity using a more standard approach.

[Tool]
Got 2 rows and 2 columns:
| ?label                             | ?description      |
| ---------------------------------- | ----------------- |
| Occupational Safety and Health Act | "wet"@nl          |
| Occupational Safety and Health Act | "قانون تشريعي"@ar |

[Assistant] The entity wd:Q47502511 has the label "Occupational Safety and Health Act" but the descriptions are not in English and do not clarify if it is the German law. Since this is inconclusive, I will try to search for the German term "Arbeitsschutzgesetz" which is the German name for the Occupational Safety and Health Act.

[Tool] No entity items found

[Assistant] There is no direct entity for "Arbeitsschutzgesetz" in Wikidata. I will try to find the German Occupational Safety and Health Act by searching for "German law Occupational Safety and Health Act" to see if there is a more specific entity.

[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. german health and safety law (wd:Q629031)
4. Occupational safety and health law (wd:Q108918253): chapter published in 2021
5. Occupational Safety and Health Act (wd:Q47502511)
6. Occupational Safety and Health Act (wd:Q68948513): scientific article published on 01 April 1972
7. Occupational Health and Safety Act, also known as OHSA, OH & S Act, Ontario Occupational Health and Safety Act (wd:Q110542175): Ontario law enacted 1979
8. Occupational Health and Safety Act, also known as ZVZD-1 (wd:Q127329172): law of the Republic of Slovenia
9. ARBO occupational health and safety law (wd:Q3003809): working conditions law in the Netherlands
10. Occupational Safety and Health Act 1994 (wd:Q7075788): national law of Malaysia

[Assistant] There is an entity "german health and safety law" (wd:Q629031) which might be related to the German Occupational Safety and Health Act. I will check the labels and descriptions of this entity to verify.

[Tool] Got no rows and 2 columns

[Assistant] The query to get the label and description for the entity wd:Q629031 returned no results. I will try a different approach to get the label and description for this entity using a more standard approach.

[Tool]
Got 1 row and 2 columns:
| ?label                       | ?description |
| ---------------------------- | ------------ |
| german health and safety law |              |

[Assistant]
The entity wd:Q629031 has the label "german health and safety law" but no description. It might be the closest entity to the German Occupational Safety and Health Act. I will now try to find the property that indicates who passed or enacted a law.

I will search for properties related to "passed by" or "enacted by" for laws.

[Tool]
Top 10 property alternatives:
1. legislated by, also known as enacted by, passed by (wd:P467 as wdtn/wdt/p/pqn/prn/pq/pr/psn/prv/psv/ps/pqv): indicates that an act or bill was passed by a legislature. The value can be a particular session of the legislature, approved by, creator
2. date of promulgation, also known as enacted date, promulgation date, royal assent, date of assent, date signed (wd:P7589 as wdtn/wdt/p/pqn/prn/pq/pr/psn/prv/psv/ps/pqv): date on which a piece of legislation formally became law (whether by assent or some other procedure), point in time
3. laws applied, also known as applied law, law applied, legal base (wd:P3014 as wdtn/wdt/p/pqn/prn/pq/pr/psn/prv/psv/ps/pqv): the constitutional and statutory provisions that were the primary basis for a decision or law
4. founded by, also known as starter, co-founded by, started by, institutor, instituted by (wd:P112 as wdtn/wdt/p/pqn/prn/pq/pr/psn/prv/psv/ps/pqv): founder or co-founder of this organization, religion, place or entity, creator
5. amended by, also known as updated by, revised by, modified by, corrected by, has addendum (wd:P2567 as wdtn/wdt/p/pqn/prn/pq/pr/psn/prv/psv/ps/pqv): document is amended by specified other document
6. main regulatory text, also known as regulated by, statutory authorization, statutory authority, legally established by, legal basis (wd:P92 as wdtn/wdt/p/pqn/prn/pq/pr/psn/prv/psv/ps/pqv): text setting the main rules by which the subject is regulated
7. regulated by, also known as regulator, regulatory authority (wd:P3719 as wdtn/wdt/p/pqn/prn/pq/pr/psn/prv/psv/ps/pqv): organization that acts as regulator of an activity, financial market, or stock exchange
8. authority, also known as executive authority, governed by, governing authority, governing body, has authority (wd:P797 as wdtn/wdt/p/pqn/prn/pq/pr/psn/prv/psv/ps/pqv): entity having executive power on given entity
9. effective date, also known as date of coming into force, date of commencement, enforcement date (wd:P7588 as wdtn/wdt/p/pqn/prn/pq/pr/psn/prv/psv/ps/pqv): date on which a statutory or administrative law or other officia...This may also be retrospective, predating the date of enactment., point in time
10. law digest, also known as law summary, legal norm digest (wd:P9376 as wdtn/wdt/p/pqn/prn/pq/pr/psn/prv/psv/ps/pqv): short text that summarizes a law, decree and other legal rulings, part of the preamble

[Assistant]
The property "legislated by" (wdt:P467) indicates that an act or bill was passed by a legislature. This property seems to be the most appropriate to find who passed the German Occupational Safety and Health Act.

Now, I will query the entity wd:Q629031 (german health and safety law) with the property wdt:P467 (legislated by) to find who passed this law.

[Tool] Got no rows and 2 columns

[Assistant]
The query to find who legislated the "german health and safety law" (wd:Q629031) using the property "legislated by" (wdt:P467) returned no results. This means the information might not be directly available or the entity might not be the exact law we are looking for.

I will try a broader approach to find any law related to "German Occupational Safety and Health Act" and see if any entity has the property "legislated by" filled. I will search for entities with the label containing "Occupational Safety and Health" and filter for those related to Germany. Then I will check if any of them have the legislated by property.

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

[Assistant]
The query to find laws related to "Occupational Safety and Health" with legislated by property timed out, likely due to its complexity.

I will simplify the query by only searching for laws with the label containing "Occupational Safety and Health" and then manually check if any are related to Germany and have legislated by information.

I will run a simpler query to get entities with labels containing "Occupational Safety and Health".

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

[Assistant]
The simpler query to find entities with labels containing "Occupational Safety and Health" also timed out. This might be due to the large number of results or server limitations.

Given the difficulty in directly finding the German Occupational Safety and Health Act entity and its legislator, I will provide a best attempt explanation.

The German Occupational Safety and Health Act is a law passed by the German legislature, which is the Bundestag (Federal Diet). However, I could not find a direct entity for this law in Wikidata or its legislator property.

I will now finalize my response with this explanation.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?forest ?forestLabel ?area WHERE {
  VALUES ?forest {
    wd:Q177567 wd:Q3079079
  }
  ?forest wdt:P2046 ?area .
  OPTIONAL {
    ?forest rdfs:label ?forestLabel FILTER ( LANG( ?forestLabel ) = "en" )
  }
}

The Amazon Rainforest has an area of about 6,700,000 square kilometers, while the Congo Basin forest has an area of about 700,000 square kilometers. Therefore, the Amazon Rainforest is bigger than the Congo Basin forest.

[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 answer the question of which forest is bigger between the Amazon Rainforest and the Congo Basin, I need to find the entities for both forests and then compare their sizes (area).

Step 1: Search for the entity of the "Amazon Rainforest" in Wikidata.

[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 entity for the Amazon Rainforest is wd:Q177567.

Step 2: Search for the entity of the "Congo Basin" in Wikidata.

[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 entity for the Congo Basin forest is wd:Q3079079 (Congolian forests, also known as Congo Basin forest).

Step 3: Now I will find the area (size) of both the Amazon Rainforest (wd:Q177567) and the Congo Basin forest (wd:Q3079079) to compare which one is bigger. I will search for the property related to "area" for these entities.

[Tool]
Top 10 property alternatives:
1. area, also known as total area, surface area, surface, size, resolution (wd:P2046 as wdt/p): area occupied by an object
2. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as wdt/p): 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. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
4. continent (wd:P30 as wdt/p): continent of which the subject is a part, located in/on physical feature
5. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as wdt/p): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
6. part of, also known as of, within, system of, subsystem of, subgroup of (wd:P361 as wdt/p): object of which the subject is a part (if this subject is alread... of "has part" (P527, see also "has parts of the class" (P2670))
7. population, also known as inhabitants, human population (wd:P1082 as wdt/p): number of people inhabiting the place; number of people of subject
8. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
9. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

No other items found

[Assistant]
The property for area is wd:P2046.

Step 4: I will now query the area values for both the Amazon Rainforest (wd:Q177567) and the Congo Basin forest (wd:Q3079079) using the property wd:P2046.

[Tool]
Got 2 rows and 3 columns:
| ?forest                         | ?forestLabel      | ?area   |
| ------------------------------- | ----------------- | ------- |
| Amazon rainforest (wd:Q177567)  | Amazon rainforest | 6700000 |
| Congolian forests (wd:Q3079079) | Congolian forests | 700000  |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
ASK WHERE {
  wd:Q125054 wdt:P17 wd:Q38 .
}

According to Wikidata, Aldi does not have a direct presence or country association with Italy. There are no subsidiaries or stores explicitly located in Italy in the knowledge graph.

[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] Is ALDI also in Italy?

[Assistant]
To answer the question "Is ALDI also in Italy?", I need to check if the entity ALDI has a presence or location in Italy in the knowledge graph.

Step 1: Identify the entity ALDI in Wikidata.
Step 2: Check if ALDI has any location or country of operation that includes Italy.

I will start by searching for the entity ALDI in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Aldi, also known as Aldi Stores (wd:Q125054): brand name of two global discount supermarket chains
2. Aldi Suisse, also known as Aldi, Aldi Suisse AG (wd:Q111030009): Swiss company and subsidiary of Aldi/Hofer
3. Aldi (wd:Q37488907): family name
4. METTL7B, also known as ALDI, methyltransferase like 7B (wd:Q18053067): protein-coding gene in the species Homo sapiens
5. Aldi (wd:Q66263985): male given name
6. Methyltransferase like 7B, also known as ALDI, associated with lipid droplet protein 1, methyltransferase-like protein 7B, Mettl7b, thiol S-methyltransferase METTL7B (wd:Q28557934): mammalian protein found in Rattus norvegicus
7. Aldein, also known as Aldino (wd:Q373680): municipality in South Tyrol, Italy
8. Aldingen (wd:Q529710): municipality in Germany
9. pyrazinamide, also known as Zinamide®, PZA, Pyrizinamide, Pyrazinoic acid amide, Pyrazinecarboxamide (wd:Q417571): chemical compound
10. Altichiero, also known as Altichiero Da Zevio, Aldigheri, Altichiero di Domenico da Zevio, Alticjiero da Zevio, da Verona Altichiero (wd:Q379567): Italian painter (1330-1390), illuminator, painter

[Assistant]
The entity "Aldi" (wd:Q125054) corresponds to the brand name of two global discount supermarket chains. This is the relevant entity for the question.

Next, I will check if Aldi (wd:Q125054) has any location or country of operation that includes Italy. I will look for properties related to the location or country of operation of Aldi.

[Tool]
Top 10 property alternatives:
1. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
2. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
3. headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as wdt/p): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place
4. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as wdt/p): main Wikimedia category
5. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
6. industry, also known as branch, economic branch, field of action, field of exercise, sector (wd:P452 as wdt/p): specific industry of company or organization, part of
7. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as wdt/p): time when an entity begins to exist; for date of official opening use P1619, start time
8. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as wdt/p): award or recognition received by a person, organization or creative work
9. logo image, also known as masthead, wordmark, trademark, trade mark, sign (wd:P154 as wdt/p): graphic mark or emblem commonly used by commercial enterprises, organizations and products, icon
10. has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as wdt/p): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).

No other items found

[Assistant]
The property "country" (wdt:P17) is relevant for checking the sovereign state associated with Aldi. However, since Aldi is a company, the property "headquarters location" (wdt:P159) might also be useful to check where its headquarters or main locations are.

I will now query the countries or locations associated with Aldi (wd:Q125054) using these properties to see if Italy is mentioned.

[Tool]
SPARQL execution failed:
Error while executing a SERVICE request to <http://wikiba.se:80/ontology#label>: SERVICE responded with HTTP status code: 301, Moved Permanently. First 100 bytes of the response: '<html>
<head><title>301 Moved Permanently</title></head>
<body>
<center><h1>301 Moved Permanently'

[Assistant]
The query failed due to the use of a SERVICE clause for labels, which is not supported by the endpoint. I will rewrite the query without the SERVICE clause and instead use rdfs:label to get the country labels.

I will query the countries associated with Aldi (wd:Q125054) using the property "country" (wdt:P17) and also check for headquarters location (wdt:P159) and their labels using rdfs:label.

[Tool]
Got 1 row and 2 columns:
| ?country               | ?countryLabel            |
| ---------------------- | ------------------------ |
| United States (wd:Q30) | United States of America |

[Assistant]
The query results show that Aldi is associated with the United States as a country, but this does not confirm if Aldi is also in Italy.

I will now check if Aldi has any location or subsidiary in Italy by querying for any location or subsidiary entities related to Aldi that are located in Italy. I will search for subsidiaries or locations of Aldi first.

[Tool]
Top 10 property alternatives:
1. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as wdt/p): URL of the official page of an item (current or former). Usage: ...but see the "Hijacked or dead websites" section of the Talk page, URL
2. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
3. headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as wdt/p): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place
4. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
5. logo image, also known as masthead, wordmark, trademark, trade mark, sign (wd:P154 as wdt/p): graphic mark or emblem commonly used by commercial enterprises, organizations and products, icon
6. Commons gallery, also known as gallery (wd:P935 as wdt/p): name of the Wikimedia Commons gallery page(s) related to this item (is suitable to allow multiple links to more gallery pages)
7. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as wdt/p): award or recognition received by a person, organization or creative work
8. described at URL, also known as mentioned at URL, descURL, described on webpage, discussed at URL, d@url (wd:P973 as wdt/p): item is described at the following URL, URL
9. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as wdt/p): time when an entity begins to exist; for date of official opening use P1619, start time
10. contact page URL, also known as contact us, contact us URL, inquiry page, inquiry page URL (wd:P11266 as wdt/p): URL to the official page listing the subject's contact information or a contact form, URL

No other items found

[Tool]
Top 10 property alternatives:
1. has subsidiary, also known as subordinate body, subsidiary body, subordinate unit, subsidiary, subsidiary company (wd:P355 as wdt/p): subsidiary of a company or organization; generally a fully owned...siness division" (P199). Opposite of parent organization (P749)., has part(s), owner of
2. headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as wdt/p): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place
3. industry, also known as branch, economic branch, field of action, field of exercise, sector (wd:P452 as wdt/p): specific industry of company or organization, part of
4. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as wdt/p): time when an entity begins to exist; for date of official opening use P1619, start time
5. has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as wdt/p): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).
6. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
7. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as wdt/p): main Wikimedia category
8. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
9. logo image, also known as masthead, wordmark, trademark, trade mark, sign (wd:P154 as wdt/p): graphic mark or emblem commonly used by commercial enterprises, organizations and products, icon
10. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as wdt/p): award or recognition received by a person, organization or creative work

No other items found

[Assistant] The property "has subsidiary" (wdt:P355) is relevant for checking subsidiaries of Aldi. I will query the subsidiaries of Aldi (wd:Q125054) and check if any of them are located in Italy or have Italy as their country.

[Tool]
Got 2 rows and 4 columns:
| ?subsidiary                               | ?subsidiaryLabel          | ?country         | ?countryLabel |
| ----------------------------------------- | ------------------------- | ---------------- | ------------- |
| Leader Price Exploitation (wd:Q104439664) | Leader Price Exploitation | France (wd:Q142) | France        |
| Hofer KG (wd:Q15815751)                   | Hofer KG                  | Austria (wd:Q40) | Austria       |

[Assistant]
The subsidiaries of Aldi listed are "Leader Price Exploitation" in France and "Hofer KG" in Austria. There is no direct mention of a subsidiary in Italy.

I will now check if Aldi has any location or store presence specifically in Italy by querying for any statements about Aldi's presence or operations in Italy. I will search for statements linking Aldi to Italy.

[Tool] False

[Assistant]
The ASK query checking if Aldi (wd:Q125054) has Italy (wd:Q38) as a country directly associated with it returned false.

I will now check if there are any locations or stores of Aldi in Italy by querying for any entities that are instances of Aldi stores or branches and are located in Italy.

[Tool] Got no rows and 2 columns

[Assistant]
There are no entities that are instances of Aldi stores or branches located in Italy in the knowledge graph.

Based on the information from Wikidata, Aldi does not have a direct country association with Italy, nor are there any subsidiaries or stores explicitly located in Italy.

I will now provide the final answer.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?album ?albumLabel WHERE {
  ?album wdt:P175 wd:Q755830 ; wdt:P31 wd:Q482994 .
  OPTIONAL {
    ?album rdfs:label ?albumLabel FILTER ( LANG( ?albumLabel ) = "en" )
  }
}

Got 3 rows and 2 columns:
| ?album                    | ?albumLabel |
| ------------------------- | ----------- |
| Doorie (wd:Q14016)        | Doorie      |
| Jal Pari (wd:Q6125801)    | Jal Pari    |
| Meri Kahani (wd:Q6819157) | Meri Kahani |

Atif Aslam has been on the following albums: Doorie, Jal Pari, and Meri Kahani.

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

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

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

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

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

[User] What albums has Atif Aslam been on?

[Assistant] To answer the question "What albums has Atif Aslam been on?", I will first search for the entity "Atif Aslam" in Wikidata to get his identifier. Then, I will look for properties related to albums or musical works associated with him. Finally, I will construct a SPARQL query to retrieve the albums he has been on.

[Tool]
Top 10 entity alternatives:
1. Atif Aslam, also known as Muhammad Atif Aslam (wd:Q755830): Pakistani playback singer and songwriter, singer-songwriter, film actor, singer, actor
2. Aslem District, also known as Aslam (wd:Q4117502): District of Hajjah Governorate, Yemen
3. ATIF (wd:Q16868993): human settlement in Saudi Arabia
4. Atif (wd:Q56537554): family name
5. Atıf, also known as Atıf (first name), Atıf (given name) (wd:Q20669067): male given name
6. Aslam (wd:Q37471643): family name
7. Atif (wd:Q61780244): male given name
8. Nazir Ahmad Aslam, also known as Asl., N.A. Aslam, Aslam (wd:Q67187108): Pakistani entomologist (1918–1971), entomologist, coleopterist
9. Aslam, also known as أسلم (wd:Q28790443): male given name (أسلم)
10. Aslam (wd:Q65487248): German badminton player, badminton player

[Assistant] The entity for Atif Aslam is wd:Q755830. Now, I will search for properties related to albums or musical works associated with Atif Aslam. I will search for properties related to "album" for this entity.

[Tool]
Top 10 property alternatives:
1. AllMusic artist ID, also known as AllMusic, AllMusic ID, amg artist (wd:P1728 as wdt/p): identifier for an artist, musical group, or record label in the AllMusic database (record labels are listed as "artists")
2. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as wdt/p): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
3. discography, also known as discography link, recording catalog (wd:P358 as wdt/p): item for list pages with discography of artist or band, list of works
4. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
5. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdt/p): the object is a country that recognizes the subject as its citizen, country
6. Apple Music artist ID (U.S. version), also known as iTunes author ID, music.apple.com/artist/, iTunes artist ID (American version), https://music.apple.com/artist/, Apple Music artist ID (American version) (wd:P2850 as wdt/p): identifier for a musical artist or author in the U.S. version of Apple Music
7. work period (start), also known as start working, flourished (start), start time for work, start date of activity, fl. (start) (wd:P2031 as wdt/p): start of period during which a person or group flourished (fl. = "floruit") in their professional activity, start time, floruit
8. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as wdt/p): award or recognition received by a person, organization or creative work
9. instrument, also known as uses this instrument, teaches instrument, instruments, plays this instrument, plays instrument (wd:P1303 as wdt/p): musical instrument that a person plays or teaches or used in a music occupation, uses
10. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as wdt/p): main Wikimedia category

No other items found

[Assistant] The property "discography" (wdt:P358) is related to the list of works or albums of the artist. I will now construct a SPARQL query to get the albums or musical works that Atif Aslam (wd:Q755830) has been on using the "discography" property.

[Tool]
Got 1 row and 2 columns:
| ?album      | ?albumLabel            |
| ----------- | ---------------------- |
| wd:Q4815772 | Atif Aslam discography |

[Assistant] The discography property for Atif Aslam points to a single item "Atif Aslam discography" (wd:Q4815772), which is a list page rather than individual albums. To get the actual albums, I will try to find albums where Atif Aslam is listed as a performer or contributor. I will search for albums with Atif Aslam as a performer or contributor.

[Tool]
Top 10 property alternatives:
1. AllMusic artist ID, also known as AllMusic, AllMusic ID, amg artist (wd:P1728 as wdt/p): identifier for an artist, musical group, or record label in the AllMusic database (record labels are listed as "artists")
2. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as wdt/p): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
3. discography, also known as discography link, recording catalog (wd:P358 as wdt/p): item for list pages with discography of artist or band, list of works
4. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
5. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdt/p): the object is a country that recognizes the subject as its citizen, country
6. Apple Music artist ID (U.S. version), also known as iTunes author ID, music.apple.com/artist/, iTunes artist ID (American version), https://music.apple.com/artist/, Apple Music artist ID (American version) (wd:P2850 as wdt/p): identifier for a musical artist or author in the U.S. version of Apple Music
7. work period (start), also known as start working, flourished (start), start time for work, start date of activity, fl. (start) (wd:P2031 as wdt/p): start of period during which a person or group flourished (fl. = "floruit") in their professional activity, start time, floruit
8. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as wdt/p): award or recognition received by a person, organization or creative work
9. instrument, also known as uses this instrument, teaches instrument, instruments, plays this instrument, plays instrument (wd:P1303 as wdt/p): musical instrument that a person plays or teaches or used in a music occupation, uses
10. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as wdt/p): main Wikimedia category

No other items found

[Assistant] The previous search did not reveal a direct property linking Atif Aslam to specific albums. I will try a different approach: I will search for albums (entities of type "album") where Atif Aslam is listed as a performer or contributor. For this, I will search for properties that link musical works or albums to performers or contributors. Then I will query albums with Atif Aslam as a performer.

[Tool]
Top 10 property alternatives:
1. performer, also known as actor, sung by, singer, recording by, recorded by (wd:P175 as wdtn/wdt/p/pqn/prn/pq/pr/psn/prv/psv/ps/pqv): actor, musician, band or other performer associated with this role or musical work, contributor to the creative work or subject
2. character role, also known as role, plays, performer of, as, acting role (wd:P453 as wdtn/wdt/p/pqn/prn/pq/pr/psn/prv/psv/ps/pqv): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)
3. cover art by, also known as jacket art by, sleeve art by, designer, cover design by, cover artist (wd:P736 as wdtn/wdt/p/pqn/prn/pq/pr/psn/prv/psv/ps/pqv): name of person or team creating cover artwork for book, record album, single record etc.
4. setlist, also known as set list, works performed, songs performed, performances, performance list (wd:P9793 as wdtn/wdt/p/pqn/prn/pq/pr/psn/prv/psv/ps/pqv): performances of songs or other music at an event; concert program, presented works
5. number of representations, also known as shows, performances, number of shows, number of concerts, no. of shows (wd:P5027 as wdtn/wdt/p/pqn/prn/pq/pr/psn/prv/psv/ps/pqv): number of shows (including the premiere) of a concert tour or a performing arts production
6. used by, also known as armiger, user, played by, of (wd:P1535 as wdtn/wdt/p/pqn/prn/pq/pr/psn/prv/psv/ps/pqv): item or concept that makes use of the subject (use sub-properties when appropriate)
7. depicted by, also known as acted by, shown in, seen in, portrayed by, played by (wd:P1299 as wdtn/wdt/p/pqn/prn/pq/pr/psn/prv/psv/ps/pqv): object depicting this subject (object being creative works such as books, films, paintings)
8. exhibited creator, also known as artist exhibited, exhibited artist (wd:P10661 as wdtn/wdt/p/pqn/prn/pq/pr/psn/prv/psv/ps/pqv): intellectual or creative entity (person or organization) responsible for the elements exhibited, creator
9. Muziekweb performer ID, also known as Muziekweb artist ID, Muziekweb band ID (wd:P5882 as wdtn/wdt/p/pqn/prn/pq/pr/psn/prv/psv/ps/pqv): identifier for a performer, composer or band at Muziekweb
10. talk show guest, also known as show guest, podcast guest, participant in talk show, participant in podcast interview, interviewed person (wd:P5030 as wdtn/wdt/p/pqn/prn/pq/pr/psn/prv/psv/ps/pqv): person invited in a talk show, recorded participant

[Assistant] The property "performer" (wdt:P175) is used to link a musical work or album to the artist who performed on it. I will now construct a SPARQL query to find albums (entities that are instances of "album") where Atif Aslam (wd:Q755830) is the performer. I will also retrieve the album labels.

[Tool]
Got 3 rows and 2 columns:
| ?album                    | ?albumLabel |
| ------------------------- | ----------- |
| Doorie (wd:Q14016)        | Doorie      |
| Jal Pari (wd:Q6125801)    | Jal Pari    |
| Meri Kahani (wd:Q6819157) | Meri Kahani |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( ?album ) AS ?count ) WHERE {
  ?album wdt:P31 wd:Q482994 .
  ?album wdt:P175 wd:Q37150 .
}

Lana Del Rey has 14 studio albums according to Wikidata.

[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 studio albums has Lana Del Rey have?

[Assistant] To answer the question about how many studio albums Lana Del Rey has, I will first search for the entity "Lana Del Rey" in Wikidata to get her identifier. Then, I will look for the property that relates Lana Del Rey to her studio albums. Finally, I will count the number of studio albums associated with her.

[Tool]
Top 10 entity alternatives:
1. Lana Del Rey, also known as Lana Del Ray, May Jailer, Lizzy Grant, Sparkle Jump Rope Queen, Elizabeth Woolridge Grant (wd:Q37150): American singer-songwriter, singer-songwriter, recording artist, record producer, film actor, composer, singer, poet
2. Lana Del Rey, also known as Lana Del Rey EP (wd:Q1149043): 2012 EP by Lana Del Rey
3. Freak (Lana Del Rey song) (wd:Q22001985): 2016 single by Lana Del Rey
4. American (Lana Del Rey song) (wd:Q66817375): 2012 song by Lana Del Rey
5. Change (Lana Del Rey song) (wd:Q97159559): 2017 song by Lana Del Rey
6. Weekend Update: Lana Del Rey (wd:Q110060506): sketch from Saturday Night Live
7. Text Book (Lana Del Rey song) (wd:Q106936354)
8. Lana Del Rey's 2023–2024 tour, also known as Did You Know That There's a Tour Around the World, Did You Know That There's a Tunn...nder Ocean Blvd Promotional Tour (wd:Q121770780): concert tour by Lana Del Rey
9. Lana Del Rey’s American Grotesque (wd:Q126796381): scholarly article
10. Tough (Quavo and Lana Del Rey song) (wd:Q127446878): 2024 single by Quavo and Lana Del Rey

[Assistant] I found the entity for Lana Del Rey with the identifier wd:Q37150. Next, I will search for properties related to "studio albums" for this entity to find the relevant property that links Lana Del Rey to her studio albums.

[Tool]
Top 10 property alternatives:
1. AllMusic artist ID, also known as AllMusic, AllMusic ID, amg artist (wd:P1728 as wdt/p): identifier for an artist, musical group, or record label in the AllMusic database (record labels are listed as "artists")
2. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as wdt/p): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
3. Album of the Year artist ID, also known as AOTY artist ID (wd:P7050 as wdt/p): identifier for an artist on the Album of the Year (AOTY) website
4. discography, also known as discography link, recording catalog (wd:P358 as wdt/p): item for list pages with discography of artist or band, list of works
5. record label, also known as label, labels (wd:P264 as wdt/p): brand and trademark associated with the marketing of subject music recordings and music videos
6. Apple Music artist ID (U.S. version), also known as iTunes author ID, music.apple.com/artist/, iTunes artist ID (American version), https://music.apple.com/artist/, Apple Music artist ID (American version) (wd:P2850 as wdt/p): identifier for a musical artist or author in the U.S. version of Apple Music
7. work period (start), also known as start working, flourished (start), start time for work, start date of activity, fl. (start) (wd:P2031 as wdt/p): start of period during which a person or group flourished (fl. = "floruit") in their professional activity, start time, floruit
8. Tidal artist ID, also known as Tidal, Tidal (artist), Tidal ID (artist) (wd:P4576 as wdt/p): identifier of an artist on the Tidal website
9. Official Charts artist ID, also known as Official Charts ID (wd:P6559 as wdt/p): identifier for musical acts at Official Charts Company's website
10. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt/p): most specific known birth location of a person, animal or fictional character, location

No other items found

[Assistant] The property "discography" (wdt:P358) is related to the list of works or albums of an artist. I will use this property to find Lana Del Rey's discography and then filter for studio albums. Next, I will search for the items that are part of Lana Del Rey's discography and check which of them are studio albums.

[Tool] Got no rows and 2 columns

[Assistant] It seems that the direct approach using the "discography" property did not return any results for studio albums. I will try another approach: I will look for works (albums) where Lana Del Rey is the performer or creator and filter those that are studio albums. I will search for albums where Lana Del Rey is the main artist (using the property "performer" or "creator") and the album is an instance of "studio album."

[Tool]
Failed to call function execute:
failed to parse input: parse error at position 171 for token . with content '.' (the input most likely does not follow the grammar)

[Assistant] I made a syntax error in the SPARQL query. I used a dot after the FILTER clause which is incorrect. I will fix the query and try again.

[Tool]
Failed to call function execute:
failed to parse input: parse error at position 171 for token . with content '.' (the input most likely does not follow the grammar)

[Assistant] I realize that the comment syntax (#) inside the WHERE clause is causing the parse error. I will remove the comments and try again.

[Tool]
Failed to call function execute:
failed to parse input: parse error at position 119 for token . with content '.' (the input most likely does not follow the grammar)

[Assistant] I see that the issue is with the use of semicolon and dot in the triple pattern. I will rewrite the query using separate triple patterns instead of semicolon.

[Tool]
Got 14 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?album                                                              | ?albumLabel                                         |
| ------------------------------------------------------------------- | --------------------------------------------------- |
| Blue Banisters (wd:Q106640241)                                      | Blue Banisters                                      |
| Did You Know That There's a Tunnel Under Ocean Blvd (wd:Q115632843) | Did You Know That There's a Tunnel Under Ocean Blvd |
| The Right Person Will Stay (wd:Q124401873)                          | The Right Person Will Stay                          |
| The Singles (wd:Q13530389)                                          | The Singles                                         |
| Ultraviolence (wd:Q15303771)                                        | Ultraviolence                                       |
| ...                                                                 | ...                                                 |
| Young Like Me (wd:Q56349977)                                        | Young Like Me                                       |
| Norman Fucking Rockwell! (wd:Q56655003)                             | Norman Fucking Rockwell!                            |
| Lana Del Ray (wd:Q770514)                                           | Lana Del Ray                                        |
| Chemtrails over the Country Club (wd:Q80126984)                     | Chemtrails over the Country Club                    |
| Violet Bent Backwards Over the Grass (wd:Q80958274)                 | Violet Bent Backwards Over the Grass                |

[Assistant] I found 14 albums where Lana Del Rey is the performer and the album is an instance of a studio album. However, some of these might not be studio albums but singles or other types of albums. I will refine the query to count only those albums that are explicitly marked as "studio album" (wd:Q482994) and exclude singles or other types. I will also check the instance of the album to confirm it is a studio album.

[Tool]
Got 1 row and 1 column:
| ?count |
| ------ |
| 14     |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?country ?countryLabel ( COUNT( ?winner ) AS ?winnerCount ) WHERE {
  ?winner wdt:P166 wd:Q123737 .
  ?winner wdt:P27 ?country .
  OPTIONAL {
    ?country rdfs:label ?countryLabel FILTER ( LANG( ?countryLabel ) = "en" )
  }
}
GROUP BY ?country ?countryLabel
ORDER BY DESC ( ?winnerCount )
LIMIT 10

Got 10 rows and 3 columns:
| ?country                               | ?countryLabel              | ?winnerCount |
| -------------------------------------- | -------------------------- | ------------ |
| United States (wd:Q30)                 | United States of America   | 666          |
| United Kingdom (wd:Q145)               | United Kingdom             | 51           |
| Canada (wd:Q16)                        | Canada                     | 16           |
| Mexico (wd:Q96)                        | Mexico                     | 6            |
| South Africa (wd:Q258)                 | South Africa               | 4            |
| Australia (wd:Q408)                    | Australia                  | 4            |
| Italy (wd:Q38)                         | Italy                      | 4            |
| Kingdom of the Netherlands (wd:Q29999) | Kingdom of the Netherlands | 4            |
| Ireland (wd:Q27)                       | Ireland                    | 4            |
| France (wd:Q142)                       | France                     | 3            |

The country with the 2nd most winners of the Emmy Award is the United Kingdom, with 51 winners.

[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] From which country came the 2nd most winners of the Emmy Award ?

[Assistant]
To answer the question "From which country came the 2nd most winners of the Emmy Award?", I need to:

1. Identify the entity for the "Emmy Award" in Wikidata.
2. Find the winners of the Emmy Award.
3. Determine the countries of origin of these winners.
4. Count the number of winners per country.
5. Identify the country with the 2nd highest count of winners.

I will start by searching for the entity "Emmy Award" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Emmy Award, also known as Emmy Awards, Emmys (wd:Q123737): American television production award
2. Primetime Emmy Award, also known as Primetime Emmy Awards (wd:Q1044427): Academy of Television Arts & Sciences accolade
3. Daytime Emmy Award, also known as Daytime Emmy Awards, Filmworks (wd:Q1179189): American TV award
4. International Emmy Award (wd:Q10354837): International Academy of Television Arts and Sciences accolade
5. Sports Emmy Awards, also known as Sports Emmy Award, Sports Emmys (wd:Q3494164): award for sports personalities
6. 69th Primetime Emmy Awards, also known as Emmys 2017, Emmy Awards 2017, Emmy 2017, 2017 Emmys, 2017 Emmy Awards (wd:Q28864472): Emmy Awards honoring the best in U.S. prime time television programming from June 1, 2016 until May 31, 2017
7. 69th Primetime Emmy Awards, also known as 2017 Emmy Awards, 2017 Emmys, Emmys 2017, Emmy 2017, Emmy Awards 2017 (wd:Q28864472): Emmy Awards honoring the best in U.S. prime time television programming from June 1, 2016 until May 31, 2017
8. 68th Primetime Emmy Awards, also known as 2016 Emmy Awards, 2016 Emmys, 2016 Primetime Emmy Awards, 68th Annual Primetime Emmy Awards (wd:Q23977956): 2016 American television programming awards
9. 22nd Primetime Emmy Awards, also known as 22nd Emmy Awards (wd:Q1647497): Emmy Award ceremony
10. 41st Primetime Emmy Awards, also known as 1989 Emmy Awards (wd:Q2442026): 1989 American television programming awards

[Assistant] The main entity for the Emmy Award is wd:Q123737. Next, I need to find the winners of the Emmy Award (wd:Q123737) and their countries of origin. I will look for statements about winners or recipients related to this award. Then I will count the winners by country.

[Tool] Got no rows and 3 columns

[Assistant]
The property wdt:P166 (award received) is not directly used on the Emmy Award entity to list winners. Instead, winners are likely linked from the winners' entities with the property "award received" (wdt:P166) pointing to the Emmy Award (wd:Q123737).

I will now search for entities that have received the Emmy Award (wd:Q123737) using the property wdt:P166. I will try to find the countries of these winners and count them. To start, I will find some winners of the Emmy Award by querying entities with wdt:P166 = wd:Q123737.

[Tool]
Got 909 rows and 3 columns, showing the first 10 rows below:
| subject                         | property                  | object                  |
| ------------------------------- | ------------------------- | ----------------------- |
| Walt Disney (wd:Q8704)          | award received (wdt:P166) | Emmy Award (wd:Q123737) |
| Audrey Hepburn (wd:Q42786)      | award received (wdt:P166) | Emmy Award (wd:Q123737) |
| Frank Sinatra (wd:Q40912)       | award received (wdt:P166) | Emmy Award (wd:Q123737) |
| Katharine Hepburn (wd:Q56016)   | award received (wdt:P166) | Emmy Award (wd:Q123737) |
| Halle Berry (wd:Q1033016)       | award received (wdt:P166) | Emmy Award (wd:Q123737) |
| Ray Bradbury (wd:Q40640)        | award received (wdt:P166) | Emmy Award (wd:Q123737) |
| Jane Fonda (wd:Q41142)          | award received (wdt:P166) | Emmy Award (wd:Q123737) |
| Bette Davis (wd:Q71206)         | award received (wdt:P166) | Emmy Award (wd:Q123737) |
| Whoopi Goldberg (wd:Q49001)     | award received (wdt:P166) | Emmy Award (wd:Q123737) |
| David Attenborough (wd:Q183337) | award received (wdt:P166) | Emmy Award (wd:Q123737) |
| ...                             | ...                       | ...                     |

[Assistant]
I have found entities (people) who have received the Emmy Award (wd:Q123737). Now, I need to find the countries of origin for these winners. The property for country of citizenship or origin is usually wdt:P27 (country of citizenship).

I will write a query to count the number of winners per country of citizenship for those who have received the Emmy Award, and then order the results by count in descending order. This will help to identify the country with the 2nd most winners.

[Tool]
Got 10 rows and 3 columns:
| ?country                               | ?countryLabel              | ?winnerCount |
| -------------------------------------- | -------------------------- | ------------ |
| United States (wd:Q30)                 | United States of America   | 666          |
| United Kingdom (wd:Q145)               | United Kingdom             | 51           |
| Canada (wd:Q16)                        | Canada                     | 16           |
| Mexico (wd:Q96)                        | Mexico                     | 6            |
| South Africa (wd:Q258)                 | South Africa               | 4            |
| Australia (wd:Q408)                    | Australia                  | 4            |
| Italy (wd:Q38)                         | Italy                      | 4            |
| Kingdom of the Netherlands (wd:Q29999) | Kingdom of the Netherlands | 4            |
| Ireland (wd:Q27)                       | Ireland                    | 4            |
| France (wd:Q142)                       | France                     | 3            |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( DISTINCT ?country ) AS ?count ) WHERE {
  wd:Q4127 wdt:P17 ?country .
}

Got 1 row and 1 column:
| ?count |
| ------ |
| 3      |

There are 3 countries located around the European Lake Constance: Germany, Switzerland, and Austria.

[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 countries are located around the euorpean Lake Constance?

[Assistant]
To answer the question "How many countries are located around the European Lake Constance?", I need to identify the entity for Lake Constance and then find the countries that are located around it.

Step 1: Search for the entity "Lake Constance" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Lake Constance, also known as Bodensee, Lac de Constance, Lake Boden (wd:Q4127): lake in Germany, Switzerland and Austria
2. Rotopōhueroa / Lake Constance, also known as Lake Constance (wd:Q1800901): lake in New Zealand
3. Constance Lake (wd:Q22535448): lake in Algoma District, Ontario, Canada
4. Lake Constance (wd:Q21954634): lake in Australia
5. Constance Lake (wd:Q22535457): lake in Cochrane District, Ontario, Canada
6. Constance Lake (wd:Q49300861): lake in Mono County, California, United States of America
7. Constance Lake (wd:Q49300862): lake of the United States of America
8. Constance Lake (wd:Q33240536): lake in Wright County, Minnesota, United States
9. Constance Lake (wd:Q22535492): lake in Leask No. 464, Saskatchewan, Canada
10. Constance Lake (wd:Q22535482): lake in Hoodoo No. 401, Saskatchewan, Canada

[Assistant]
The entity for the European Lake Constance is wd:Q4127. It is a lake in Germany, Switzerland, and Austria.

Step 2: I will now find the countries located around Lake Constance (wd:Q4127). I will look for countries that have a geographical relation to this lake.

[Tool]
Got 3 rows and 3 columns:
| subject                   | property          | object               |
| ------------------------- | ----------------- | -------------------- |
| Lake Constance (wd:Q4127) | country (wdt:P17) | Germany (wd:Q183)    |
| Lake Constance (wd:Q4127) | country (wdt:P17) | Switzerland (wd:Q39) |
| Lake Constance (wd:Q4127) | country (wdt:P17) | Austria (wd:Q40)     |

[Tool] Stopped generation process