PREFIX pv: <http://ld.company.org/prod-vocab/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?supplier ?label ( ROUND( AVG( ?amount ) * 100 ) / 100 AS ?avgPriceEUR ) WHERE {
  ?product pv:hasSupplier ?supplier .
  ?supplier a pv:Supplier .
  OPTIONAL {
    ?supplier rdfs:label ?label
  }
  ?product pv:price ?price .
  ?price pv:currency "EUR" .
  ?price pv:amount ?amount .
}
GROUP BY ?supplier ?label
ORDER BY ?supplier

For each supplier, the average price (in EUR) of what they sell is calculated by averaging the EUR prices of all products they supply. The result includes the supplier IRI, their label, and the average price rounded to two decimals.

For each supplier, what's the average price (in EUR) of what they sell, round reasonably?

[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:
ck25 at http://localhost:9333

You can use the following SPARQL prefixes implicitly in all functions:
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
ecc: <https://ns.eccenca.com/
owl: <http://www.w3.org/2002/07/owl#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
dct: <http://purl.org/dc/terms/
void: <http://rdfs.org/ns/void#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
vann: <http://purl.org/vocab/vann/
dbpedia: <http://dbpedia.org/resource/
wgs84: <http://www.w3.org/2003/01/geo/wgs84_pos#
pv: <http://ld.company.org/prod-vocab/
prodi: <http://ld.company.org/prod-instances/
skos: <http://www.w3.org/2004/02/skos/core#
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
schema: <http://schema.org/
geo: <http://www.opengis.net/ont/geosparql#
geosparql: <http://www.opengis.net/ont/geosparql#
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
wikibase: <http://wikiba.se/ontology#
qb: <http://purl.org/linked-data/cube#

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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. 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] For each supplier, what's the average price (in EUR) of what they sell, round reasonably?

[Assistant]
Let's break down the question:

1. We need to identify entities representing "suppliers".
2. For each supplier, we need to find the products they sell.
3. For each product, we need to find the price (in EUR).
4. We need to calculate the average price per supplier, rounding reasonably.

First, let's search for entities related to "supplier" in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Supplier (pv:Supplier): The Supplier of some item(s).
2. supplier (pv:hasSupplier): The supplier of a product., has domain Product, has range Supplier

[Assistant]
We have found an entity pv:Supplier representing suppliers, and a property pv:hasSupplier which links products to suppliers.

Next, we need to find how products are linked to prices, and specifically prices in EUR. Let's search for properties related to "price".

[Tool]
Top 10 property alternatives:
1. price (pv:price): The price specification of a product., has domain Product, has range Price
2. currency (pv:currency): has domain Price, The currency.
3. amount (pv:amount): has domain Price, The amount.
4. name (foaf:name):

5. name (pv:name): The name of something.
6. country (pv:country): The country where the supplier is located., has domain Supplier, has range Country
7. quantity (pv:quantity): The quantity needed., has domain BOM Part
8. member of (pv:memberOf): The department to which an agents belongs., has range Department, has domain Agent
9. ID (pv:id): The ID of a thing.
10. part (pv:hasPart): has domain BOM Part, The Product needed., has range Product

[Assistant]
We have found the following relevant properties:
- pv:price: links a Product to a Price.
- pv:currency: links a Price to its currency.
- pv:amount: links a Price to its amount.

Now, let's confirm how to get from a Supplier to the products they sell. Since pv:hasSupplier has domain Product and range Supplier, we can find all products for which a given supplier is the supplier.

Let's check a sample of triples with pv:hasSupplier to see how it is used.

[Tool]
Got 1,000 rows and 3 columns, showing the first 10 rows below:
| subject                                 | property                  | object                                                                                |
| --------------------------------------- | ------------------------- | --------------------------------------------------------------------------------------------- |
| hw J785 9314350 (prodi:hw-J785-9314350) | supplier (pv:hasSupplier) | suppl 1b032f32 5734 44da 8758 554ad059b03e (prodi:suppl-1b032f32-5734-44da-8758-554ad059b03e) |
| hw V156 6277722 (prodi:hw-V156-6277722) | supplier (pv:hasSupplier) | suppl f76eb805 4d84 4b4b 9aa3 95c287be41d0 (prodi:suppl-f76eb805-4d84-4b4b-9aa3-95c287be41d0) |
| hw W769 8151254 (prodi:hw-W769-8151254) | supplier (pv:hasSupplier) | suppl 4d849ba4 b932 4ffc 8b52 61a704dddf0b (prodi:suppl-4d849ba4-b932-4ffc-8b52-61a704dddf0b) |
| hw B918 9468392 (prodi:hw-B918-9468392) | supplier (pv:hasSupplier) | suppl 47528cbf c41b 4897 b917 6f4c1394fe1f (prodi:suppl-47528cbf-c41b-4897-b917-6f4c1394fe1f) |
| hw H374 8481414 (prodi:hw-H374-8481414) | supplier (pv:hasSupplier) | suppl 9a27c6be 84c6 4fe8 a671 d9d6a5ec7f6a (prodi:suppl-9a27c6be-84c6-4fe8-a671-d9d6a5ec7f6a) |
| hw K334 8882985 (prodi:hw-K334-8882985) | supplier (pv:hasSupplier) | suppl 06d152e4 f062 46da b6be 750b192a5a4b (prodi:suppl-06d152e4-f062-46da-b6be-750b192a5a4b) |
| hw L557 1467804 (prodi:hw-L557-1467804) | supplier (pv:hasSupplier) | suppl 4b796fba c152 4137 b01d fce80aef6e3c (prodi:suppl-4b796fba-c152-4137-b01d-fce80aef6e3c) |
| hw O875 5580798 (prodi:hw-O875-5580798) | supplier (pv:hasSupplier) | suppl fdd83431 425f 4291 b8e4 f08805b6b89d (prodi:suppl-fdd83431-425f-4291-b8e4-f08805b6b89d) |
| hw T808 9704137 (prodi:hw-T808-9704137) | supplier (pv:hasSupplier) | suppl 8f607810 ca93 4274 9c27 d0a8dcba7c4a (prodi:suppl-8f607810-ca93-4274-9c27-d0a8dcba7c4a) |
| hw J824 9483042 (prodi:hw-J824-9483042) | supplier (pv:hasSupplier) | suppl 33da751a 1358 4530 b0e5 e3b9a509e952 (prodi:suppl-33da751a-1358-4530-b0e5-e3b9a509e952) |
| ...                                     | ...                       | ...                                                                                |

[Assistant]
The property pv:hasSupplier links a product (subject) to a supplier (object). So, for each supplier, we can find all products they supply.

Next, let's check how the price is attached to a product. We'll look at a sample of triples with pv:price.

[Tool]
Got 1,009 rows and 3 columns, showing the first 10 rows below:
| subject                                   | property         | object                                                        |
| ----------------------------------------- | ---------------- | ------------------------------------------------------------- |
| srv P516 8211068 (prodi:srv-P516-8211068) | price (pv:price) | price srv P516 8211068 EUR (prodi:price-srv-P516-8211068-EUR) |
| srv Y704 9764759 (prodi:srv-Y704-9764759) | price (pv:price) | price srv Y704 9764759 EUR (prodi:price-srv-Y704-9764759-EUR) |
| srv Y274 1029755 (prodi:srv-Y274-1029755) | price (pv:price) | price srv Y274 1029755 EUR (prodi:price-srv-Y274-1029755-EUR) |
| srv D215 3449390 (prodi:srv-D215-3449390) | price (pv:price) | price srv D215 3449390 EUR (prodi:price-srv-D215-3449390-EUR) |
| srv P925 8919074 (prodi:srv-P925-8919074) | price (pv:price) | price srv P925 8919074 EUR (prodi:price-srv-P925-8919074-EUR) |
| srv N558 1730215 (prodi:srv-N558-1730215) | price (pv:price) | price srv N558 1730215 EUR (prodi:price-srv-N558-1730215-EUR) |
| srv O662 4012383 (prodi:srv-O662-4012383) | price (pv:price) | price srv O662 4012383 EUR (prodi:price-srv-O662-4012383-EUR) |
| srv U360 2815908 (prodi:srv-U360-2815908) | price (pv:price) | price srv U360 2815908 EUR (prodi:price-srv-U360-2815908-EUR) |
| hw J785 9314350 (prodi:hw-J785-9314350)   | price (pv:price) | price hw J785 9314350 EUR (prodi:price-hw-J785-9314350-EUR)   |
| hw V156 6277722 (prodi:hw-V156-6277722)   | price (pv:price) | price hw V156 6277722 EUR (prodi:price-hw-V156-6277722-EUR)   |
| ...                                       | ...              | ...                                                           |

[Assistant] The property pv:price links a product to a price entity. Now, let's check how to get the amount and currency from a price entity. We'll look at a sample of triples with pv:currency and pv:amount.

[Tool]
Got 1,009 rows and 3 columns, showing the first 10 rows below:
| subject                                                     | property               | object |
| ----------------------------------------------------------- | ---------------------- | ------ |
| price hw A145 1240844 EUR (prodi:price-hw-A145-1240844-EUR) | currency (pv:currency) | EUR    |
| price hw A166 3766336 EUR (prodi:price-hw-A166-3766336-EUR) | currency (pv:currency) | EUR    |
| price hw A181 1118563 EUR (prodi:price-hw-A181-1118563-EUR) | currency (pv:currency) | EUR    |
| price hw A225 1988393 EUR (prodi:price-hw-A225-1988393-EUR) | currency (pv:currency) | EUR    |
| price hw A243 3332548 EUR (prodi:price-hw-A243-3332548-EUR) | currency (pv:currency) | EUR    |
| price hw A315 1730287 EUR (prodi:price-hw-A315-1730287-EUR) | currency (pv:currency) | EUR    |
| price hw A360 3041803 EUR (prodi:price-hw-A360-3041803-EUR) | currency (pv:currency) | EUR    |
| price hw A391 9508821 EUR (prodi:price-hw-A391-9508821-EUR) | currency (pv:currency) | EUR    |
| price hw A403 4549719 EUR (prodi:price-hw-A403-4549719-EUR) | currency (pv:currency) | EUR    |
| price hw A464 7310986 EUR (prodi:price-hw-A464-7310986-EUR) | currency (pv:currency) | EUR    |
| ...                                                         | ...                    | ...    |

[Tool]
Got 1,009 rows and 3 columns, showing the first 10 rows below:
| subject                                                     | property           | object             |
| ----------------------------------------------------------- | ------------------ | ------------------ |
| price hw A145 1240844 EUR (prodi:price-hw-A145-1240844-EUR) | amount (pv:amount) | 3.72 (xsd:decimal) |
| price hw A166 3766336 EUR (prodi:price-hw-A166-3766336-EUR) | amount (pv:amount) | 1.27 (xsd:decimal) |
| price hw A181 1118563 EUR (prodi:price-hw-A181-1118563-EUR) | amount (pv:amount) | 3.7 (xsd:decimal)  |
| price hw A225 1988393 EUR (prodi:price-hw-A225-1988393-EUR) | amount (pv:amount) | 0.06 (xsd:decimal) |
| price hw A243 3332548 EUR (prodi:price-hw-A243-3332548-EUR) | amount (pv:amount) | 3.18 (xsd:decimal) |
| price hw A315 1730287 EUR (prodi:price-hw-A315-1730287-EUR) | amount (pv:amount) | 3.03 (xsd:decimal) |
| price hw A360 3041803 EUR (prodi:price-hw-A360-3041803-EUR) | amount (pv:amount) | 4.89 (xsd:decimal) |
| price hw A391 9508821 EUR (prodi:price-hw-A391-9508821-EUR) | amount (pv:amount) | 1.77 (xsd:decimal) |
| price hw A403 4549719 EUR (prodi:price-hw-A403-4549719-EUR) | amount (pv:amount) | 5.33 (xsd:decimal) |
| price hw A464 7310986 EUR (prodi:price-hw-A464-7310986-EUR) | amount (pv:amount) | 2.99 (xsd:decimal) |
| ...                                                         | ...                | ...                |

[Assistant]
We have confirmed the following path:
- Supplier (pv:Supplier) ← pv:hasSupplier ← Product → pv:price → Price → pv:currency ("EUR") and pv:amount (decimal).

Now, let's check if suppliers have a label or name property for human-readable output. We'll look at a sample of properties for a supplier entity.

[Tool]
Got 10 rows and 3 columns:
| subject                                                                                | property                                     | object                               |
| --------------------------------------------------------------------------------------------- | -------------------------------------------- | ------------------------------------ |
| suppl 1b032f32 5734 44da 8758 554ad059b03e (prodi:suppl-1b032f32-5734-44da-8758-554ad059b03e) | type (rdf:type)                              | Supplier (pv:Supplier)               |
| suppl 1b032f32 5734 44da 8758 554ad059b03e (prodi:suppl-1b032f32-5734-44da-8758-554ad059b03e) | label (rdfs:label)                           | Bryan-Jones (Algeria)                |
| suppl 1b032f32 5734 44da 8758 554ad059b03e (prodi:suppl-1b032f32-5734-44da-8758-554ad059b03e) | name (pv:name)                               | Bryan-Jones                          |
| suppl 1b032f32 5734 44da 8758 554ad059b03e (prodi:suppl-1b032f32-5734-44da-8758-554ad059b03e) | ID (pv:id)                                   | 1b032f32-5734-44da-8758-554ad059b03e |
| suppl 1b032f32 5734 44da 8758 554ad059b03e (prodi:suppl-1b032f32-5734-44da-8758-554ad059b03e) | address country (pv:addressCountry)          | Algeria                              |
| suppl 1b032f32 5734 44da 8758 554ad059b03e (prodi:suppl-1b032f32-5734-44da-8758-554ad059b03e) | address country code (pv:addressCountryCode) | DZ                                   |
| suppl 1b032f32 5734 44da 8758 554ad059b03e (prodi:suppl-1b032f32-5734-44da-8758-554ad059b03e) | address locality (pv:addressLocality)        | Bir el Djir                          |
| suppl 1b032f32 5734 44da 8758 554ad059b03e (prodi:suppl-1b032f32-5734-44da-8758-554ad059b03e) | lat (wgs84:lat)                              | 35.719874                            |
| suppl 1b032f32 5734 44da 8758 554ad059b03e (prodi:suppl-1b032f32-5734-44da-8758-554ad059b03e) | long (wgs84:long)                            | -0.5675118                           |
| suppl 1b032f32 5734 44da 8758 554ad059b03e (prodi:suppl-1b032f32-5734-44da-8758-554ad059b03e) | country (pv:country)                         | Algeria (dbpedia:Algeria)            |

[Assistant]
Suppliers have both rdfs:label and pv:name properties for human-readable names. We'll use rdfs:label in the output.

Now, let's construct the SPARQL query:
- For each supplier, find all products they supply.
- For each product, get its price entity, filter for EUR currency, and get the amount.
- Compute the average price per supplier.
- Return the supplier IRI and label, and the average price (rounded to 2 decimals).

Let's write and execute the query.

[Tool]
Got 246 rows and 3 columns, showing the first 5 and last 5 rows below:
| supplier                                                                                | label                                | avgPriceEUR        |
| --------------------------------------------------------------------------------------------- | ------------------------------------ | ------------------ |
| suppl 0058fc5e e9e8 46eb ac6d 673e436a5d7a (prodi:suppl-0058fc5e-e9e8-46eb-ac6d-673e436a5d7a) | Allen-Short (South Africa)           | 1.29 (xsd:decimal) |
| suppl 0301f65d 2290 456b a3f7 b2096a632198 (prodi:suppl-0301f65d-2290-456b-a3f7-b2096a632198) | Maxwell Inc (India)                  | 1.27 (xsd:decimal) |
| suppl 034022f5 5327 45c2 aaff 524b1be2fbd5 (prodi:suppl-034022f5-5327-45c2-aaff-524b1be2fbd5) | Drake Ltd (Honduras)                 | 4.03 (xsd:decimal) |
| suppl 05b5a686 c821 41c4 bc2c b66d35bac1d8 (prodi:suppl-05b5a686-c821-41c4-bc2c-b66d35bac1d8) | Curtis, Doyle and Singleton (Canada) | 3.34 (xsd:decimal) |
| suppl 06034b22 8e1b 435f 902e 88739f77d86a (prodi:suppl-06034b22-8e1b-435f-902e-88739f77d86a) | Lee and Sons (Brazil)                | 1.89 (xsd:decimal) |
| ...                                                                                | ...                                  | ...                |
| suppl fbfe40db 81e4 4b35 93d5 a996307a266e (prodi:suppl-fbfe40db-81e4-4b35-93d5-a996307a266e) | Church Inc (Ukraine)                 | 2.2 (xsd:decimal)  |
| suppl fcdf3268 b0f0 4e2b 8fbd 6008cb4a6d0e (prodi:suppl-fcdf3268-b0f0-4e2b-8fbd-6008cb4a6d0e) | Carlson Inc (Brazil)                 | 2.98 (xsd:decimal) |
| suppl fd5556a6 46fc 4d68 846b e543ce6f4ec9 (prodi:suppl-fd5556a6-46fc-4d68-846b-e543ce6f4ec9) | Stevens Ltd (Peru)                   | 2.06 (xsd:decimal) |
| suppl fdd83431 425f 4291 b8e4 f08805b6b89d (prodi:suppl-fdd83431-425f-4291-b8e4-f08805b6b89d) | Thomas-Jenkins (Bangladesh)          | 3.02 (xsd:decimal) |
| suppl feeda1ce d6af 42b2 b6ff 7516ba39ad6c (prodi:suppl-feeda1ce-d6af-42b2-b6ff-7516ba39ad6c) | Calderon-Montgomery (Italy)          | 2.8 (xsd:decimal)  |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly computes the average price in EUR for each supplier, rounding to two decimals as requested. It returns the supplier IRI, an optional label, and the average price, fulfilling the requirements of the question. The query is well-structured, uses appropriate grouping and filtering, and the execution result matches expectations. No further refinement is needed.


PREFIX pv: <http://ld.company.org/prod-vocab/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
SELECT ?service ?serviceLabel ?amount ?currency WHERE {
  ?service a pv:Service .
  OPTIONAL {
    ?service rdfs:label ?serviceLabel
  }
  ?service pv:price ?price .
  ?price pv:amount ?amount .
  ?price pv:currency ?currency .
}
ORDER BY DESC ( xsd:decimal ( ?amount ) )
LIMIT 1

The most expensive service offered is 'D215-3449390 - Manual Inspection' (IRI: prodi:srv-D215-3449390) with a price of 1709.54 EUR.

What is the most expensive service we offer?

[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:
ck25 at http://localhost:9333

You can use the following SPARQL prefixes implicitly in all functions:
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
ecc: <https://ns.eccenca.com/
owl: <http://www.w3.org/2002/07/owl#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
dct: <http://purl.org/dc/terms/
void: <http://rdfs.org/ns/void#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
vann: <http://purl.org/vocab/vann/
dbpedia: <http://dbpedia.org/resource/
wgs84: <http://www.w3.org/2003/01/geo/wgs84_pos#
pv: <http://ld.company.org/prod-vocab/
prodi: <http://ld.company.org/prod-instances/
skos: <http://www.w3.org/2004/02/skos/core#
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
schema: <http://schema.org/
geo: <http://www.opengis.net/ont/geosparql#
geosparql: <http://www.opengis.net/ont/geosparql#
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
wikibase: <http://wikiba.se/ontology#
qb: <http://purl.org/linked-data/cube#

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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] What is the most expensive service we offer?

[Assistant]
Step 1: Determine possible entities and properties implied by the user question.

The question asks for the "most expensive service we offer." This implies:
- There are entities representing "services."
- Each service has a "price" or "cost" property.
- We need to find the service with the highest price.

Step 2: Search for entities and properties.

First, I will search for entities related to "service" to identify how services are represented in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Service (pv:Service): Some value added service realized based on other product(s)., is subclass of Product
2. account service outline svg?color=#D6AF00&format=svg (<https://api.iconify.design/mdi/account-service-outline.svg?color=%23D6AF00&format=svg>)

[Assistant]
The entity "Service" is represented as pv:Service in the knowledge graph. This is likely the class for services offered.

Next, I need to find the property that represents the "price" or "cost" of a service. I will search for properties related to "price".

[Tool]
Top 10 property alternatives:
1. price (pv:price): The price specification of a product., has domain Product, has range Price
2. currency (pv:currency): has domain Price, The currency.
3. amount (pv:amount): has domain Price, The amount.
4. name (foaf:name):

5. name (pv:name): The name of something.
6. country (pv:country): The country where the supplier is located., has domain Supplier, has range Country
7. quantity (pv:quantity): The quantity needed., has domain BOM Part
8. member of (pv:memberOf): The department to which an agents belongs., has range Department, has domain Agent
9. ID (pv:id): The ID of a thing.
10. part (pv:hasPart): has domain BOM Part, The Product needed., has range Product

[Assistant]
The property "price" is represented as pv:price, and its range is "Price". The "Price" entity likely contains further details such as the amount and currency.

To get the actual numeric value, I should look for the property "amount" (pv:amount), which has domain "Price".

So, the structure is likely:
- Service (pv:Service)
  - pv:price → Price
    - pv:amount → (numeric value)
    - pv:currency → (currency)

Next, I will verify this structure by listing some triples for a service entity with the pv:price property.

[Tool] Got no rows and 3 columns

[Assistant]
It appears that listing triples with subject pv:Service and property pv:price did not return any rows. This is likely because pv:Service is a class, not an instance.

To proceed, I need to find instances of pv:Service (i.e., actual services offered) and see how their price is represented. I will search for instances of pv:Service.

[Tool]
Got 9 rows and 1 column:
| service                                   |
| ----------------------------------------- |
| srv D215 3449390 (prodi:srv-D215-3449390) |
| srv I241 8776317 (prodi:srv-I241-8776317) |
| srv N558 1730215 (prodi:srv-N558-1730215) |
| srv O662 4012383 (prodi:srv-O662-4012383) |
| srv P516 8211068 (prodi:srv-P516-8211068) |
| srv P925 8919074 (prodi:srv-P925-8919074) |
| srv U360 2815908 (prodi:srv-U360-2815908) |
| srv Y274 1029755 (prodi:srv-Y274-1029755) |
| srv Y704 9764759 (prodi:srv-Y704-9764759) |

[Assistant]
I have found several instances of services, such as prodi:srv-D215-3449390, prodi:srv-I241-8776317, etc.

Next, I will check how the price is represented for one of these service instances, for example, prodi:srv-D215-3449390, by listing its properties.

[Tool]
Got 262 rows and 3 columns, showing the first 10 rows below:
| subject                                   | property                                   | object                                                                                |
| ----------------------------------------- | ------------------------------------------ | ------------------------------------------------------------------------------------------------ |
| srv D215 3449390 (prodi:srv-D215-3449390) | type (rdf:type)                            | Service (pv:Service)                                                                             |
| srv D215 3449390 (prodi:srv-D215-3449390) | label (rdfs:label)                         | D215-3449390 - Manual Inspection                                                                 |
| srv D215 3449390 (prodi:srv-D215-3449390) | eligible for (pv:eligibleFor)              | hw A166 3766336 (prodi:hw-A166-3766336)                                                          |
| srv D215 3449390 (prodi:srv-D215-3449390) | name (pv:name)                             | Manual Inspection                                                                                |
| srv D215 3449390 (prodi:srv-D215-3449390) | ID (pv:id)                                 | D215-3449390                                                                                |
| srv D215 3449390 (prodi:srv-D215-3449390) | has product manager (pv:hasProductManager) | empl Ida Halle@company org (<http://ld.company.org/prod-instances/empl-Ida.Halle%40company.org>) |
| srv D215 3449390 (prodi:srv-D215-3449390) | price (pv:price)                           | price srv D215 3449390 EUR (prodi:price-srv-D215-3449390-EUR)                                    |
| srv D215 3449390 (prodi:srv-D215-3449390) | eligible for (pv:eligibleFor)              | hw A225 1988393 (prodi:hw-A225-1988393)                                                          |
| srv D215 3449390 (prodi:srv-D215-3449390) | eligible for (pv:eligibleFor)              | hw A315 1730287 (prodi:hw-A315-1730287)                                                          |
| srv D215 3449390 (prodi:srv-D215-3449390) | eligible for (pv:eligibleFor)              | hw A529 2906246 (prodi:hw-A529-2906246)                                                          |
| ...                                       | ...                                        | ...                                                                                |

[Assistant]
The property pv:price is indeed used for the service instance prodi:srv-D215-3449390, and it points to another entity prodi:price-srv-D215-3449390-EUR.

Next, I will list the properties of prodi:price-srv-D215-3449390-EUR to confirm how the amount and currency are represented.

[Tool]
Got 4 rows and 3 columns:
| subject                                                       | property               | object                |
| ------------------------------------------------------------- | ---------------------- | --------------------- |
| price srv D215 3449390 EUR (prodi:price-srv-D215-3449390-EUR) | type (rdf:type)        | Price (pv:Price)      |
| price srv D215 3449390 EUR (prodi:price-srv-D215-3449390-EUR) | label (rdfs:label)     | 1709,54 EUR           |
| price srv D215 3449390 EUR (prodi:price-srv-D215-3449390-EUR) | amount (pv:amount)     | 1709.54 (xsd:decimal) |
| price srv D215 3449390 EUR (prodi:price-srv-D215-3449390-EUR) | currency (pv:currency) | EUR                   |

[Assistant]
The price entity has:
- pv:amount (numeric value, e.g., 1709.54)
- pv:currency (e.g., EUR)

Now, I can construct a SPARQL query to find all services, their prices, and select the one with the highest amount.

I will write a query to:
- Get all services (?service) of type pv:Service
- Get their price entity (?price)
- Get the amount (?amount) and currency (?currency)
- Order by descending amount and limit to 1 (the most expensive)

I will also optionally get the service label for readability.

[Tool]
Got 1 row and 4 columns:
| service                                   | serviceLabel                     | amount                | currency |
| ----------------------------------------- | -------------------------------- | --------------------- | -------- |
| srv D215 3449390 (prodi:srv-D215-3449390) | D215-3449390 - Manual Inspection | 1709.54 (xsd:decimal) | EUR      |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the most expensive service by ordering all services by their price amount in descending order and limiting the result to one. The query returns the service IRI, label, amount, and currency, and the answer matches the query result. All required rules are followed, and the answer is complete and correct.


PREFIX pv: <http://ld.company.org/prod-vocab/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
PREFIX wgs84: <http://www.w3.org/2003/01/geo/wgs84_pos#>
SELECT ?supplier ?name ?label ?addressCountry ?addressCountryCode ?addressLocality ?lat ?long WHERE {
  ?supplier rdf:type pv:Supplier .
  OPTIONAL {
    ?supplier pv:name ?name .
  }
  OPTIONAL {
    ?supplier rdfs:label ?label .
  }
  OPTIONAL {
    ?supplier pv:addressCountry ?addressCountry .
  }
  OPTIONAL {
    ?supplier pv:addressCountryCode ?addressCountryCode .
  }
  OPTIONAL {
    ?supplier pv:addressLocality ?addressLocality .
  }
  OPTIONAL {
    ?supplier wgs84:lat ?lat .
  }
  OPTIONAL {
    ?supplier wgs84:long ?long .
  }
}

Here are all suppliers with their names and address details (country, country code, locality, latitude, longitude). Each row contains the supplier IRI, name, label, and all available address information.

I need to update my supplier rolodex, give me every supplier's name and all address details.

[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:
ck25 at http://localhost:9333

You can use the following SPARQL prefixes implicitly in all functions:
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
ecc: <https://ns.eccenca.com/
owl: <http://www.w3.org/2002/07/owl#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
dct: <http://purl.org/dc/terms/
void: <http://rdfs.org/ns/void#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
vann: <http://purl.org/vocab/vann/
dbpedia: <http://dbpedia.org/resource/
wgs84: <http://www.w3.org/2003/01/geo/wgs84_pos#
pv: <http://ld.company.org/prod-vocab/
prodi: <http://ld.company.org/prod-instances/
skos: <http://www.w3.org/2004/02/skos/core#
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
schema: <http://schema.org/
geo: <http://www.opengis.net/ont/geosparql#
geosparql: <http://www.opengis.net/ont/geosparql#
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
wikibase: <http://wikiba.se/ontology#
qb: <http://purl.org/linked-data/cube#

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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. 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] I need to update my supplier rolodex, give me every supplier's name and all address details.

[Assistant]
Step 1: Determine possible entities and properties implied by the user question.

The user is asking for:
- Every supplier's name
- All address details for each supplier

So, I need to identify:
- The entity type for "supplier"
- The property for "name" of a supplier
- The property or linked entity for "address" and its details (such as street, city, postal code, etc.)

Step 2: Search for the entities and properties in the knowledge graph.

First, I will search for the entity "supplier" to find its class or type.

[Tool]
Top 10 entity alternatives:
1. Supplier (pv:Supplier): The Supplier of some item(s).
2. supplier (pv:hasSupplier): The supplier of a product., has domain Product, has range Supplier

[Assistant]
I found that "Supplier" is represented as pv:Supplier in the knowledge graph. Next, I need to find the property for the supplier's name. Common properties for names are often rdfs:label, foaf:name, or schema:name, but I should verify which is used for pv:Supplier.

I will search for properties related to "name" for the entity pv:Supplier.

[Tool]
Top 10 property alternatives:
1. label (rdfs:label)
2. type (rdf:type)
3. comment (rdfs:comment)
4. is Defined By (rdfs:isDefinedBy)
5. depiction (foaf:depiction)

No other items found

[Assistant]
The property rdfs:label is likely used for the supplier's name. Now, I need to find how addresses are linked to suppliers and what properties are used for address details.

I'll search for properties related to "address" for the entity pv:Supplier.

[Tool]
Top 10 property alternatives:
1. label (rdfs:label)
2. comment (rdfs:comment)
3. type (rdf:type)
4. depiction (foaf:depiction)
5. is Defined By (rdfs:isDefinedBy)

No other items found

[Assistant] No direct "address" property is listed for pv:Supplier. It's possible that the address is linked via another property or as a related entity. To investigate further, I'll list all properties used with pv:Supplier instances to see if any relate to addresses.

[Tool]
Got 5 rows and 3 columns:
| subject                | property                         | object                                                                                |
| ---------------------- | -------------------------------- | -------------------------------------------------------------------------------------------------------------- |
| Supplier (pv:Supplier) | type (rdf:type)                  | Class (owl:Class)                                                                                |
| Supplier (pv:Supplier) | label (rdfs:label)               | Supplier (en)                                                                                |
| Supplier (pv:Supplier) | is Defined By (rdfs:isDefinedBy) | pv: Products - Vocab (pv:)                                                                                |
| Supplier (pv:Supplier) | comment (rdfs:comment)           | The Supplier of some item(s). (en)                                                                             |
| Supplier (pv:Supplier) | depiction (foaf:depiction)       | company svg?color=#D6AF00&format=svg (<https://api.iconify.design/mdi/company.svg?color=%23D6AF00&format=svg>) |

[Assistant]
The properties listed are for the class itself, not for instances. To find how addresses are linked, I should look at actual instances of suppliers and see what properties are used.

I'll search for some instances of pv:Supplier.

[Tool]
Top 10 entity alternatives:
1. Supplier (pv:Supplier): The Supplier of some item(s).
2. supplier (pv:hasSupplier): The supplier of a product., has domain Product, has range Supplier

[Tool]
Got 250 rows and 3 columns, showing the first 10 rows below:
| subject                                                                                | property        | object                 |
| --------------------------------------------------------------------------------------------- | --------------- | ---------------------- |
| suppl 0058fc5e e9e8 46eb ac6d 673e436a5d7a (prodi:suppl-0058fc5e-e9e8-46eb-ac6d-673e436a5d7a) | type (rdf:type) | Supplier (pv:Supplier) |
| suppl 0301f65d 2290 456b a3f7 b2096a632198 (prodi:suppl-0301f65d-2290-456b-a3f7-b2096a632198) | type (rdf:type) | Supplier (pv:Supplier) |
| suppl 034022f5 5327 45c2 aaff 524b1be2fbd5 (prodi:suppl-034022f5-5327-45c2-aaff-524b1be2fbd5) | type (rdf:type) | Supplier (pv:Supplier) |
| suppl 05b5a686 c821 41c4 bc2c b66d35bac1d8 (prodi:suppl-05b5a686-c821-41c4-bc2c-b66d35bac1d8) | type (rdf:type) | Supplier (pv:Supplier) |
| suppl 06034b22 8e1b 435f 902e 88739f77d86a (prodi:suppl-06034b22-8e1b-435f-902e-88739f77d86a) | type (rdf:type) | Supplier (pv:Supplier) |
| suppl 06d152e4 f062 46da b6be 750b192a5a4b (prodi:suppl-06d152e4-f062-46da-b6be-750b192a5a4b) | type (rdf:type) | Supplier (pv:Supplier) |
| suppl 07335cfb 9bbc 4be5 b546 bdd8af104e7e (prodi:suppl-07335cfb-9bbc-4be5-b546-bdd8af104e7e) | type (rdf:type) | Supplier (pv:Supplier) |
| suppl 0817f6f5 8011 4c46 aeab ba89def6df14 (prodi:suppl-0817f6f5-8011-4c46-aeab-ba89def6df14) | type (rdf:type) | Supplier (pv:Supplier) |
| suppl 092bb1b2 b39f 4521 9c21 c853db9d9a09 (prodi:suppl-092bb1b2-b39f-4521-9c21-c853db9d9a09) | type (rdf:type) | Supplier (pv:Supplier) |
| suppl 0c327a40 c6d8 44da ba2d e84f924c5208 (prodi:suppl-0c327a40-c6d8-44da-ba2d-e84f924c5208) | type (rdf:type) | Supplier (pv:Supplier) |
| ...                                                                                | ...             | ...                    |

[Assistant] I now have some example supplier instance IRIs, such as prodi:suppl-0058fc5e-e9e8-46eb-ac6d-673e436a5d7a. Next, I will list all properties for one of these supplier instances to see if any address-related properties or linked address entities are present.

[Tool]
Got 10 rows and 3 columns:
| subject                                                                                | property                                     | object                               |
| --------------------------------------------------------------------------------------------- | -------------------------------------------- | ------------------------------------ |
| suppl 0058fc5e e9e8 46eb ac6d 673e436a5d7a (prodi:suppl-0058fc5e-e9e8-46eb-ac6d-673e436a5d7a) | type (rdf:type)                              | Supplier (pv:Supplier)               |
| suppl 0058fc5e e9e8 46eb ac6d 673e436a5d7a (prodi:suppl-0058fc5e-e9e8-46eb-ac6d-673e436a5d7a) | label (rdfs:label)                           | Allen-Short (South Africa)           |
| suppl 0058fc5e e9e8 46eb ac6d 673e436a5d7a (prodi:suppl-0058fc5e-e9e8-46eb-ac6d-673e436a5d7a) | name (pv:name)                               | Allen-Short                          |
| suppl 0058fc5e e9e8 46eb ac6d 673e436a5d7a (prodi:suppl-0058fc5e-e9e8-46eb-ac6d-673e436a5d7a) | ID (pv:id)                                   | 0058fc5e-e9e8-46eb-ac6d-673e436a5d7a |
| suppl 0058fc5e e9e8 46eb ac6d 673e436a5d7a (prodi:suppl-0058fc5e-e9e8-46eb-ac6d-673e436a5d7a) | address country (pv:addressCountry)          | South Africa                         |
| suppl 0058fc5e e9e8 46eb ac6d 673e436a5d7a (prodi:suppl-0058fc5e-e9e8-46eb-ac6d-673e436a5d7a) | address country code (pv:addressCountryCode) | ZA                                   |
| suppl 0058fc5e e9e8 46eb ac6d 673e436a5d7a (prodi:suppl-0058fc5e-e9e8-46eb-ac6d-673e436a5d7a) | address locality (pv:addressLocality)        | Mondlo                               |
| suppl 0058fc5e e9e8 46eb ac6d 673e436a5d7a (prodi:suppl-0058fc5e-e9e8-46eb-ac6d-673e436a5d7a) | lat (wgs84:lat)                              | -27.958203                           |
| suppl 0058fc5e e9e8 46eb ac6d 673e436a5d7a (prodi:suppl-0058fc5e-e9e8-46eb-ac6d-673e436a5d7a) | long (wgs84:long)                            | 30.7196884                           |
| suppl 0058fc5e e9e8 46eb ac6d 673e436a5d7a (prodi:suppl-0058fc5e-e9e8-46eb-ac6d-673e436a5d7a) | country (pv:country)                         | South Africa (dbpedia:South_Africa)  |

[Assistant]
From the supplier instance, I see the following address-related properties:
- pv:addressCountry
- pv:addressCountryCode
- pv:addressLocality
- wgs84:lat
- wgs84:long

Additionally, there is a name property (pv:name) and a label (rdfs:label).

To get all suppliers with their names and all address details, I should select all instances of pv:Supplier and retrieve their pv:name, rdfs:label, and all address-related properties.

Step 3: Build the SPARQL query.

I will construct a query that retrieves:
- The supplier IRI
- The supplier's name (pv:name)
- The supplier's label (rdfs:label)
- The address country (pv:addressCountry)
- The address country code (pv:addressCountryCode)
- The address locality (pv:addressLocality)
- The latitude (wgs84:lat)
- The longitude (wgs84:long)

I will use OPTIONAL for each property in case some suppliers are missing some details.

Step 4: Execute the query to verify results.

[Tool]
Got 250 rows and 8 columns, showing the first 5 and last 5 rows below:
| supplier                                                                                | name                        | label                                | addressCountry | addressCountryCode | addressLocality | lat         | long               |
| --------------------------------------------------------------------------------------------- | --------------------------- | ------------------------------------ | -------------- | ------------------ | --------------- | ----------- | ------------------ |
| suppl 0058fc5e e9e8 46eb ac6d 673e436a5d7a (prodi:suppl-0058fc5e-e9e8-46eb-ac6d-673e436a5d7a) | Allen-Short                 | Allen-Short (South Africa)           | South Africa   | ZA                 | Mondlo          | -27.958203  | 30.7196884         |
| suppl 0301f65d 2290 456b a3f7 b2096a632198 (prodi:suppl-0301f65d-2290-456b-a3f7-b2096a632198) | Maxwell Inc                 | Maxwell Inc (India)                  | India          | IN                 | Naraini         | 25.1893967  | 80.51807042643755  |
| suppl 034022f5 5327 45c2 aaff 524b1be2fbd5 (prodi:suppl-034022f5-5327-45c2-aaff-524b1be2fbd5) | Drake Ltd                   | Drake Ltd (Honduras)                 | Honduras       | HN                 | El Paraíso      | 13.9619941  | -86.56279208240295 |
| suppl 05b5a686 c821 41c4 bc2c b66d35bac1d8 (prodi:suppl-05b5a686-c821-41c4-bc2c-b66d35bac1d8) | Curtis, Doyle and Singleton | Curtis, Doyle and Singleton (Canada) | Canada         | CA                 | West Hill       | 43.7689144  | -79.1872905        |
| suppl 06034b22 8e1b 435f 902e 88739f77d86a (prodi:suppl-06034b22-8e1b-435f-902e-88739f77d86a) | Lee and Sons                | Lee and Sons (Brazil)                | Brazil         | BR                 | Bandeirantes    | -23.107788  | -50.370407         |
| ...                                                                                | ...                         | ...                                  | ...            | ...                | ...             | ...         | ...                |
| suppl fbfe40db 81e4 4b35 93d5 a996307a266e (prodi:suppl-fbfe40db-81e4-4b35-93d5-a996307a266e) | Church Inc                  | Church Inc (Ukraine)                 | Ukraine        | UA                 | Molodohvardiisk | 48.3459067  | 39.6524188         |
| suppl fcdf3268 b0f0 4e2b 8fbd 6008cb4a6d0e (prodi:suppl-fcdf3268-b0f0-4e2b-8fbd-6008cb4a6d0e) | Carlson Inc                 | Carlson Inc (Brazil)                 | Brazil         | BR                 | Canguçu         | -31.398276  | -52.6773522        |
| suppl fd5556a6 46fc 4d68 846b e543ce6f4ec9 (prodi:suppl-fd5556a6-46fc-4d68-846b-e543ce6f4ec9) | Stevens Ltd                 | Stevens Ltd (Peru)                   | Peru           | PE                 | Chiclayo        | -6.7716146  | -79.8387175        |
| suppl fdd83431 425f 4291 b8e4 f08805b6b89d (prodi:suppl-fdd83431-425f-4291-b8e4-f08805b6b89d) | Thomas-Jenkins              | Thomas-Jenkins (Bangladesh)          | Bangladesh     | BD                 | Muktāgācha      | 24.73300275 | 90.22841510134836  |
| suppl feeda1ce d6af 42b2 b6ff 7516ba39ad6c (prodi:suppl-feeda1ce-d6af-42b2-b6ff-7516ba39ad6c) | Calderon-Montgomery         | Calderon-Montgomery (Italy)          | Italy          | IT                 | Gallarate       | 45.6598951  | 8.7932013          |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves all suppliers along with their names and all available address details, including country, country code, locality, latitude, and longitude. The query returns the supplier IRIs as required, and all additional information is included via OPTIONAL clauses, which is appropriate since not all suppliers may have every address detail. The execution result shows a comprehensive set of results, matching the user's request. No further refinement is necessary.


PREFIX pv: <http://ld.company.org/prod-vocab/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
SELECT ?manager ( SAMPLE( ?label ) AS ?managerLabel ) ( COUNT( ?teamMember ) AS ?teamSize ) ( SUM( IF( ?teamDept = ?managerDept , 1 , 0 ) ) AS ?sameDeptCount ) ( ( SUM( IF( ?teamDept = ?managerDept , 1 , 0 ) ) * 100.0 ) / COUNT( ?teamMember ) AS ?sameDeptPercent ) WHERE {
  ?manager rdf:type pv:Manager .
  OPTIONAL {
    ?manager rdfs:label ?label
  }
  ?teamMember pv:hasManager ?manager .
  ?manager pv:memberOf ?managerDept .
  ?teamMember pv:memberOf ?teamDept .
}
GROUP BY ?manager

Got 6 rows and 5 columns:
| manager                                                                                | managerLabel      | teamSize     | sameDeptCount | sameDeptPercent   |
| ---------------------------------------------------------------------------------------------------------------- | ----------------- | ------------ | ------------- | ----------------- |
| empl Dietlinde Boehme@company org (<http://ld.company.org/prod-instances/empl-Dietlinde.Boehme%40company.org>)   | Dietlinde Boehme  | 9 (xsd:int)  | 9 (xsd:int)   | 100 (xsd:decimal) |
| empl Elena Herzog@company org (<http://ld.company.org/prod-instances/empl-Elena.Herzog%40company.org>)           | Elena Herzog      | 9 (xsd:int)  | 9 (xsd:int)   | 100 (xsd:decimal) |
| empl Franz Kornhaeusel@company org (<http://ld.company.org/prod-instances/empl-Franz.Kornhaeusel%40company.org>) | Franz Kornhaeusel | 12 (xsd:int) | 12 (xsd:int)  | 100 (xsd:decimal) |
| empl Reiner Widmann@company org (<http://ld.company.org/prod-instances/empl-Reiner.Widmann%40company.org>)       | Reiner Widmann    | 4 (xsd:int)  | 4 (xsd:int)   | 100 (xsd:decimal) |
| empl Thomas Mueller@company org (<http://ld.company.org/prod-instances/empl-Thomas.Mueller%40company.org>)       | Thomas Mueller    | 5 (xsd:int)  | 5 (xsd:int)   | 100 (xsd:decimal) |
| empl Waldtraud Kuttner@company org (<http://ld.company.org/prod-instances/empl-Waldtraud.Kuttner%40company.org>) | Waldtraud Kuttner | 8 (xsd:int)  | 8 (xsd:int)   | 100 (xsd:decimal) |

For each manager, 100% of their team members work in the same department as the manager. The query returns the manager IRIs, their labels, team size, and the percentage (which is 100% for all managers in this dataset).

For each manager, what percentage of their entire team work in the same department as the manager?

[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:
ck25 at http://localhost:9333

You can use the following SPARQL prefixes implicitly in all functions:
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
ecc: <https://ns.eccenca.com/
owl: <http://www.w3.org/2002/07/owl#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
dct: <http://purl.org/dc/terms/
void: <http://rdfs.org/ns/void#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
vann: <http://purl.org/vocab/vann/
dbpedia: <http://dbpedia.org/resource/
wgs84: <http://www.w3.org/2003/01/geo/wgs84_pos#
pv: <http://ld.company.org/prod-vocab/
prodi: <http://ld.company.org/prod-instances/
skos: <http://www.w3.org/2004/02/skos/core#
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
schema: <http://schema.org/
geo: <http://www.opengis.net/ont/geosparql#
geosparql: <http://www.opengis.net/ont/geosparql#
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
wikibase: <http://wikiba.se/ontology#
qb: <http://purl.org/linked-data/cube#

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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
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 just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. 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] For each manager, what percentage of their entire team work in the same department as the manager?

[Assistant]
Let's break down the question:

1. We need to identify all managers.
2. For each manager, we need to find their team members.
3. For each manager, we need to know their department.
4. For each team member, we need to know their department.
5. For each manager, we need to calculate the percentage of their team members who work in the same department as the manager.

First, I will search for entities and properties related to "manager", "team", and "department" in the knowledge graph to identify the correct identifiers to use.

Let's start by searching for the entity "manager".

[Tool]
Top 10 entity alternatives:
1. Manager (pv:Manager): An employee with some direct reports and management duties., is subclass of Employee
2. has manager (pv:hasManager): The manager of the employee., has domain Employee, has range Manager
3. manager svg?color=#D6AF00&format=svg (<https://api.iconify.design/hugeicons/manager.svg?color=%23D6AF00&format=svg>)
4. has product manager (pv:hasProductManager): The employee acting as the product manager of the product., has range Employee, has domain Product

[Tool]
Top 10 property alternatives:
1. name (foaf:name):

2. name (pv:name): The name of something.
3. member of (pv:memberOf): The department to which an agents belongs., has range Department, has domain Agent
4. price (pv:price): The price specification of a product., has domain Product, has range Price
5. country (pv:country): The country where the supplier is located., has domain Supplier, has range Country
6. contributor (dct:contributor)
7. part (pv:hasPart): has domain BOM Part, The Product needed., has range Product
8. created (dct:created)
9. area of expertise (pv:areaOfExpertise): The product category agent is expert for., has range Product Category, has domain Agent
10. type (rdf:type)

[Tool]
Top 10 property alternatives:
1. area of expertise (pv:areaOfExpertise): The product category agent is expert for., has range Product Category, has domain Agent
2. label (rdfs:label)
3. country (pv:country): The country where the supplier is located., has domain Supplier, has range Country
4. part (pv:hasPart): has domain BOM Part, The Product needed., has range Product
5. has manager (pv:hasManager): The manager of the employee., has domain Employee, has range Manager
6. responsible for (pv:responsibleFor): The product for which a department is responsible., has domain Department, has range Product
7. sub Class Of (rdfs:subClassOf)
8. quantity (pv:quantity): The quantity needed., has domain BOM Part
9. member of (pv:memberOf): The department to which an agents belongs., has range Department, has domain Agent
10. type (rdf:type)

[Tool]
Top 10 property alternatives:
1. comment (rdfs:comment)
2. responsible for (pv:responsibleFor): The product for which a department is responsible., has domain Department, has range Product
3. ID (pv:id): The ID of a thing.
4. contributor (dct:contributor)
5. quantity (pv:quantity): The quantity needed., has domain BOM Part
6. name (foaf:name):

7. name (pv:name): The name of something.
8. has manager (pv:hasManager): The manager of the employee., has domain Employee, has range Manager
9. address text (pv:addressText): The address text., has domain Agent
10. supplier (pv:hasSupplier): The supplier of a product., has domain Product, has range Supplier

[Tool]
Got 47 rows and 3 columns, showing the first 10 rows below:
| subject                                                                                | property                    | object                                                                                |
| -------------------------------------------------------------------------------------------------------------- | --------------------------- | ---------------------------------------------------------------------------------------------------------------- |
| empl Wolfgang Martin@company org (<http://ld.company.org/prod-instances/empl-Wolfgang.Martin%40company.org>)   | has manager (pv:hasManager) | empl Elena Herzog@company org (<http://ld.company.org/prod-instances/empl-Elena.Herzog%40company.org>)           |
| empl Corinna Ludwig@company org (<http://ld.company.org/prod-instances/empl-Corinna.Ludwig%40company.org>)     | has manager (pv:hasManager) | empl Thomas Mueller@company org (<http://ld.company.org/prod-instances/empl-Thomas.Mueller%40company.org>)       |
| empl Franziska Acker@company org (<http://ld.company.org/prod-instances/empl-Franziska.Acker%40company.org>)   | has manager (pv:hasManager) | empl Franz Kornhaeusel@company org (<http://ld.company.org/prod-instances/empl-Franz.Kornhaeusel%40company.org>) |
| empl Bert Blumstein@company org (<http://ld.company.org/prod-instances/empl-Bert.Blumstein%40company.org>)     | has manager (pv:hasManager) | empl Dietlinde Boehme@company org (<http://ld.company.org/prod-instances/empl-Dietlinde.Boehme%40company.org>)   |
| empl Elisabeth Harman@company org (<http://ld.company.org/prod-instances/empl-Elisabeth.Harman%40company.org>) | has manager (pv:hasManager) | empl Waldtraud Kuttner@company org (<http://ld.company.org/prod-instances/empl-Waldtraud.Kuttner%40company.org>) |
| empl Baldwin Guenther@company org (<http://ld.company.org/prod-instances/empl-Baldwin.Guenther%40company.org>) | has manager (pv:hasManager) | empl Reiner Widmann@company org (<http://ld.company.org/prod-instances/empl-Reiner.Widmann%40company.org>)       |
| empl Gretel Roth@company org (<http://ld.company.org/prod-instances/empl-Gretel.Roth%40company.org>)           | has manager (pv:hasManager) | empl Elena Herzog@company org (<http://ld.company.org/prod-instances/empl-Elena.Herzog%40company.org>)           |
| empl Herr Haan Bader@company org (<http://ld.company.org/prod-instances/empl-Herr.Haan.Bader%40company.org>)   | has manager (pv:hasManager) | empl Thomas Mueller@company org (<http://ld.company.org/prod-instances/empl-Thomas.Mueller%40company.org>)       |
| empl Karch Moeller@company org (<http://ld.company.org/prod-instances/empl-Karch.Moeller%40company.org>)       | has manager (pv:hasManager) | empl Thomas Mueller@company org (<http://ld.company.org/prod-instances/empl-Thomas.Mueller%40company.org>)       |
| empl Karen Brant@company org (<http://ld.company.org/prod-instances/empl-Karen.Brant%40company.org>)           | has manager (pv:hasManager) | empl Thomas Mueller@company org (<http://ld.company.org/prod-instances/empl-Thomas.Mueller%40company.org>)       |
| ...                                                                                | ...                         | ...                                                                                |

[Tool]
Got 53 rows and 3 columns, showing the first 10 rows below:
| subject                                                                                | property                | object                        |
| -------------------------------------------------------------------------------------------------------------- | ----------------------- | ----------------------------- |
| empl Wolfgang Martin@company org (<http://ld.company.org/prod-instances/empl-Wolfgang.Martin%40company.org>)   | member of (pv:memberOf) | dept 41622 (prodi:dept-41622) |
| empl Thomas Mueller@company org (<http://ld.company.org/prod-instances/empl-Thomas.Mueller%40company.org>)     | member of (pv:memberOf) | dept 73191 (prodi:dept-73191) |
| empl Franziska Acker@company org (<http://ld.company.org/prod-instances/empl-Franziska.Acker%40company.org>)   | member of (pv:memberOf) | dept 22183 (prodi:dept-22183) |
| empl Bert Blumstein@company org (<http://ld.company.org/prod-instances/empl-Bert.Blumstein%40company.org>)     | member of (pv:memberOf) | dept 85880 (prodi:dept-85880) |
| empl Elisabeth Harman@company org (<http://ld.company.org/prod-instances/empl-Elisabeth.Harman%40company.org>) | member of (pv:memberOf) | dept 84279 (prodi:dept-84279) |
| empl Reiner Widmann@company org (<http://ld.company.org/prod-instances/empl-Reiner.Widmann%40company.org>)     | member of (pv:memberOf) | dept 66469 (prodi:dept-66469) |
| empl Gretel Roth@company org (<http://ld.company.org/prod-instances/empl-Gretel.Roth%40company.org>)           | member of (pv:memberOf) | dept 41622 (prodi:dept-41622) |
| empl Elena Herzog@company org (<http://ld.company.org/prod-instances/empl-Elena.Herzog%40company.org>)         | member of (pv:memberOf) | dept 41622 (prodi:dept-41622) |
| empl Kevin Feigenbaum@company org (<http://ld.company.org/prod-instances/empl-Kevin.Feigenbaum%40company.org>) | member of (pv:memberOf) | dept 85880 (prodi:dept-85880) |
| empl Manfred Foth@company org (<http://ld.company.org/prod-instances/empl-Manfred.Foth%40company.org>)         | member of (pv:memberOf) | dept 73191 (prodi:dept-73191) |
| ...                                                                                | ...                     | ...                           |

[Tool]
Got 6 rows and 3 columns:
| subject                                                                                | property        | object               |
| ---------------------------------------------------------------------------------------------------------------- | --------------- | -------------------- |
| empl Thomas Mueller@company org (<http://ld.company.org/prod-instances/empl-Thomas.Mueller%40company.org>)       | type (rdf:type) | Manager (pv:Manager) |
| empl Elena Herzog@company org (<http://ld.company.org/prod-instances/empl-Elena.Herzog%40company.org>)           | type (rdf:type) | Manager (pv:Manager) |
| empl Franz Kornhaeusel@company org (<http://ld.company.org/prod-instances/empl-Franz.Kornhaeusel%40company.org>) | type (rdf:type) | Manager (pv:Manager) |
| empl Reiner Widmann@company org (<http://ld.company.org/prod-instances/empl-Reiner.Widmann%40company.org>)       | type (rdf:type) | Manager (pv:Manager) |
| empl Dietlinde Boehme@company org (<http://ld.company.org/prod-instances/empl-Dietlinde.Boehme%40company.org>)   | type (rdf:type) | Manager (pv:Manager) |
| empl Waldtraud Kuttner@company org (<http://ld.company.org/prod-instances/empl-Waldtraud.Kuttner%40company.org>) | type (rdf:type) | Manager (pv:Manager) |

[Tool]
Got 1 row and 3 columns:
| subject                          | property         | object       |
| -------------------------------- | ---------------- | ------------ |
| eccenca Gmb H (ecc:eccenca-GmbH) | name (foaf:name) | eccenca GmbH |

[Tool]
Got 2,620 rows and 3 columns, showing the first 10 rows below:
| subject                                   | property           | object                                |
| ----------------------------------------- | ------------------ | ------------------------------------- |
| Hardware (pv:Hardware)                    | label (rdfs:label) | Hardware (en)                         |
| Price (pv:Price)                          | label (rdfs:label) | Price (en)                            |
| srv P516 8211068 (prodi:srv-P516-8211068) | label (rdfs:label) | P516-8211068 - IoT Data Marketing     |
| srv Y704 9764759 (prodi:srv-Y704-9764759) | label (rdfs:label) | Y704-9764759 - Product Analysis       |
| srv Y274 1029755 (prodi:srv-Y274-1029755) | label (rdfs:label) | Y274-1029755 - Industry-Grade Hacking |
| srv D215 3449390 (prodi:srv-D215-3449390) | label (rdfs:label) | D215-3449390 - Manual Inspection      |
| Supplier (pv:Supplier)                    | label (rdfs:label) | Supplier (en)                         |
| srv P925 8919074 (prodi:srv-P925-8919074) | label (rdfs:label) | P925-8919074 - Predictive Maintenance |
| srv N558 1730215 (prodi:srv-N558-1730215) | label (rdfs:label) | N558-1730215 - Sensor Adjustment      |
| BOM Part (pv:BomPart)                     | label (rdfs:label) | BOM Part (en)                         |
| ...                                       | ...                | ...                                   |

[Assistant]
Here is my plan based on the information gathered:

- Managers are identified by rdf:type pv:Manager.
- Team members are those employees who have pv:hasManager pointing to a manager.
- Department membership is given by pv:memberOf.
- To get the percentage for each manager: For each manager, count the number of their direct reports (team members), and count how many of those are in the same department as the manager. Then, calculate the percentage.

I will write a SPARQL query that:
1. Finds all managers.
2. For each manager, finds their department.
3. For each manager, finds their direct reports (team members).
4. For each team member, finds their department.
5. Groups by manager and calculates the percentage of team members in the same department as the manager.

I will also try to include the manager's label if available.

Let's construct and execute the query.

[Tool]
SPARQL execution failed:
Invalid SPARQL query: The target ?managerLabel of an AS clause was already used in the query body.

[Assistant]
The error occurred because I used the same variable name (?managerLabel) in both the SELECT and the SAMPLE() aggregation. I will fix this by using a different variable name for the aggregation result.

Let me update the query to avoid this conflict.

[Tool]
Got 6 rows and 5 columns:
| manager                                                                                | managerLabel      | teamSize     | sameDeptCount | sameDeptPercent   |
| ---------------------------------------------------------------------------------------------------------------- | ----------------- | ------------ | ------------- | ----------------- |
| empl Dietlinde Boehme@company org (<http://ld.company.org/prod-instances/empl-Dietlinde.Boehme%40company.org>)   | Dietlinde Boehme  | 9 (xsd:int)  | 9 (xsd:int)   | 100 (xsd:decimal) |
| empl Elena Herzog@company org (<http://ld.company.org/prod-instances/empl-Elena.Herzog%40company.org>)           | Elena Herzog      | 9 (xsd:int)  | 9 (xsd:int)   | 100 (xsd:decimal) |
| empl Franz Kornhaeusel@company org (<http://ld.company.org/prod-instances/empl-Franz.Kornhaeusel%40company.org>) | Franz Kornhaeusel | 12 (xsd:int) | 12 (xsd:int)  | 100 (xsd:decimal) |
| empl Reiner Widmann@company org (<http://ld.company.org/prod-instances/empl-Reiner.Widmann%40company.org>)       | Reiner Widmann    | 4 (xsd:int)  | 4 (xsd:int)   | 100 (xsd:decimal) |
| empl Thomas Mueller@company org (<http://ld.company.org/prod-instances/empl-Thomas.Mueller%40company.org>)       | Thomas Mueller    | 5 (xsd:int)  | 5 (xsd:int)   | 100 (xsd:decimal) |
| empl Waldtraud Kuttner@company org (<http://ld.company.org/prod-instances/empl-Waldtraud.Kuttner%40company.org>) | Waldtraud Kuttner | 8 (xsd:int)  | 8 (xsd:int)   | 100 (xsd:decimal) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is correct and complete. It returns the IRIs of the managers, their labels, the team size, the count of team members in the same department, and the percentage of team members in the same department as the manager. The computation is performed entirely within SPARQL, and the results are as expected. No further refinement is necessary.