PREFIX prodi: <http://ld.company.org/prod-instances/>
PREFIX pv: <http://ld.company.org/prod-vocab/>
SELECT ?supplier ( MAX( ?reliability ) AS ?maxReliability ) WHERE {
  ?product pv:hasCategory prodi:prod-cat-Inductor ; pv:hasSupplier ?supplier ; pv:reliabilityIndex ?reliability .
}
GROUP BY ?supplier
ORDER BY DESC ( ?maxReliability )
LIMIT 1

The supplier that delivers the most reliable Inductor is Adkins, Lopez and Boyd (Switzerland) (IRI: prodi:suppl-445081d6-305c-4fb7-b89e-82c86969d4bd), with a reliability index of 0.962.

Which supplier delivers the most reliable Inductor?

[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] Which supplier delivers the most reliable Inductor?

[Assistant]
Let's break down the question:

1. Entities and properties:
   - "Supplier": We need to identify entities representing suppliers.
   - "Inductor": We need to identify entities representing inductors (likely a product or component class).
   - "Delivers": We need to find the property that links suppliers to the products they deliver.
   - "Most reliable": We need to find a property that measures the reliability of an inductor, and then find the supplier that delivers the inductor with the highest reliability.

2. Step-by-step plan:
   - Search for the entity representing "Inductor".
   - Search for properties related to "reliability" for inductors.
   - Search for the property linking suppliers to delivered products.
   - Combine these to find, for each supplier, the reliability of the inductors they deliver, and select the supplier with the highest reliability.

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

[Tool]
Top 10 entity alternatives:
1. prod cat Inductor (prodi:prod-cat-Inductor): is a Product Category

[Assistant]
The entity for "Inductor" is prodi:prod-cat-Inductor, which is a Product Category.

Next, I need to find properties related to "reliability" for inductors. I'll search for properties with the keyword "reliability".

[Tool]
Top 10 property alternatives:
1. has reliability index (pv:reliabilityIndex): A computed KPI to have an reliablity indicator in the context of a supply chain., has domain Hardware
2. compatible product (pv:compatibleProduct): A compatible product., has domain Product, has range Product
3. supplier (pv:hasSupplier): The supplier of a product., has domain Product, has range Supplier
4. quantity (pv:quantity): The quantity needed., has domain BOM Part
5. is Defined By (rdfs:isDefinedBy)
6. type (rdf:type)
7. name (foaf:name):

8. name (pv:name): The name of something.
9. range (rdfs:range)
10. country (pv:country): The country where the supplier is located., has domain Supplier, has range Country

[Assistant]
The property "has reliability index" (pv:reliabilityIndex) seems to be the relevant property for measuring the reliability of a product, specifically hardware.

Now, I need to find the property that links suppliers to the products they deliver. From the search results, "supplier" (pv:hasSupplier) is a property that links a product to its supplier.

Next, I will check how inductors (prodi:prod-cat-Inductor) are linked to actual product instances, and how those products are linked to suppliers and reliability index. I'll list some triples where the subject is an inductor product category to see how products are modeled.

[Tool]
Got 3 rows and 3 columns:
| subject                                     | property           | object                                |
| ------------------------------------------- | ------------------ | ------------------------------------- |
| prod cat Inductor (prodi:prod-cat-Inductor) | type (rdf:type)    | Product Category (pv:ProductCategory) |
| prod cat Inductor (prodi:prod-cat-Inductor) | label (rdfs:label) | Inductor                              |
| prod cat Inductor (prodi:prod-cat-Inductor) | name (pv:name)     | Inductor                              |

[Assistant]
The product category "Inductor" (prodi:prod-cat-Inductor) is a Product Category, but to find actual inductor products, I need to see how products are linked to this category. I'll search for products that are instances of this category, possibly using a property like "category" or "type".

I'll search for properties related to "category" to see how products are linked to their categories.

[Tool]
Top 10 property alternatives:
1. has category (pv:hasCategory): The category name of a product., has range Product Category, has domain Product
2. label (rdfs:label)
3. country (pv:country): The country where the supplier is located., has domain Supplier, has range Country
4. type (rdf:type)
5. part (pv:hasPart): has domain BOM Part, The Product needed., has range Product
6. vocabulary (void:vocabulary)
7. name (foaf:name):

8. name (pv:name): The name of something.
9. sub Class Of (rdfs:subClassOf)
10. is Defined By (rdfs:isDefinedBy)

[Assistant]
The property "has category" (pv:hasCategory) links products to their product category.

Now, I'll look for products that have pv:hasCategory prodi:prod-cat-Inductor. This will give me the inductor products.

[Tool]
Got 98 rows and 3 columns, showing the first 10 rows below:
| subject                                 | property                      | object                                      |
| --------------------------------------- | ----------------------------- | ------------------------------------------- |
| hw A360 3041803 (prodi:hw-A360-3041803) | has category (pv:hasCategory) | prod cat Inductor (prodi:prod-cat-Inductor) |
| hw A509 5571891 (prodi:hw-A509-5571891) | has category (pv:hasCategory) | prod cat Inductor (prodi:prod-cat-Inductor) |
| hw A628 8869626 (prodi:hw-A628-8869626) | has category (pv:hasCategory) | prod cat Inductor (prodi:prod-cat-Inductor) |
| hw A688 6056899 (prodi:hw-A688-6056899) | has category (pv:hasCategory) | prod cat Inductor (prodi:prod-cat-Inductor) |
| hw B161 8326597 (prodi:hw-B161-8326597) | has category (pv:hasCategory) | prod cat Inductor (prodi:prod-cat-Inductor) |
| hw B387 9270009 (prodi:hw-B387-9270009) | has category (pv:hasCategory) | prod cat Inductor (prodi:prod-cat-Inductor) |
| hw B888 7564557 (prodi:hw-B888-7564557) | has category (pv:hasCategory) | prod cat Inductor (prodi:prod-cat-Inductor) |
| hw C375 1115425 (prodi:hw-C375-1115425) | has category (pv:hasCategory) | prod cat Inductor (prodi:prod-cat-Inductor) |
| hw C402 5072074 (prodi:hw-C402-5072074) | has category (pv:hasCategory) | prod cat Inductor (prodi:prod-cat-Inductor) |
| hw C710 5880579 (prodi:hw-C710-5880579) | has category (pv:hasCategory) | prod cat Inductor (prodi:prod-cat-Inductor) |
| ...                                     | ...                           | ...                                         |

[Assistant]
I have found multiple inductor products (e.g., prodi:hw-A360-3041803, prodi:hw-A509-5571891, etc.) that are linked to the Inductor category.

Next, I need to find for each of these inductor products:
- Their reliability index (pv:reliabilityIndex)
- Their supplier (pv:hasSupplier)

I'll check if these properties are used with one of the inductor products, for example, prodi:hw-A360-3041803.

[Tool]
Got 20 rows and 3 columns, showing the first 10 rows below:
| subject                                 | property                                   | object                                                                                |
| --------------------------------------- | ------------------------------------------ | -------------------------------------------------------------------------------------------------- |
| hw A360 3041803 (prodi:hw-A360-3041803) | type (rdf:type)                            | Hardware (pv:Hardware)                                                                             |
| hw A360 3041803 (prodi:hw-A360-3041803) | label (rdfs:label)                         | A360-3041803 - Inductor Transformer Warp                                                           |
| hw A360 3041803 (prodi:hw-A360-3041803) | has category (pv:hasCategory)              | prod cat Inductor (prodi:prod-cat-Inductor)                                                        |
| hw A360 3041803 (prodi:hw-A360-3041803) | compatible product (pv:compatibleProduct)  | hw U990 5234138 (prodi:hw-U990-5234138)                                                            |
| hw A360 3041803 (prodi:hw-A360-3041803) | name (pv:name)                             | Inductor Transformer Warp                                                                          |
| hw A360 3041803 (prodi:hw-A360-3041803) | ID (pv:id)                                 | A360-3041803                                                                                |
| hw A360 3041803 (prodi:hw-A360-3041803) | has product manager (pv:hasProductManager) | empl Marius Fux@company org (<http://ld.company.org/prod-instances/empl-Marius.Fux%40company.org>) |
| hw A360 3041803 (prodi:hw-A360-3041803) | price (pv:price)                           | price hw A360 3041803 EUR (prodi:price-hw-A360-3041803-EUR)                                        |
| hw A360 3041803 (prodi:hw-A360-3041803) | depth (mm) (pv:depth_mm)                   | 14 (xsd:int)                                                                                |
| hw A360 3041803 (prodi:hw-A360-3041803) | supplier (pv:hasSupplier)                  | suppl 29cf8eca 50be 460e 9816 5ae505fc9491 (prodi:suppl-29cf8eca-50be-460e-9816-5ae505fc9491)      |
| ...                                     | ...                                        | ...                                                                                |

[Tool]
Got 1 row and 3 columns:
| subject                                 | property                                    | object              |
| --------------------------------------- | ------------------------------------------- | ------------------- |
| hw A360 3041803 (prodi:hw-A360-3041803) | has reliability index (pv:reliabilityIndex) | 0.921 (xsd:decimal) |

[Assistant]
The inductor product prodi:hw-A360-3041803 has both a supplier (prodi:suppl-29cf8eca-50be-460e-9816-5ae505fc9491) and a reliability index (0.921).

Now, I will write a SPARQL query to:
- Get all inductor products (pv:hasCategory prodi:prod-cat-Inductor)
- For each, get their supplier (pv:hasSupplier) and reliability index (pv:reliabilityIndex)
- Return the supplier who delivers the inductor with the highest reliability index

I'll also include optional labels for the supplier and product for readability.

[Tool]
Got 1 row and 2 columns:
| supplier                                                                                | maxReliability      |
| --------------------------------------------------------------------------------------------- | ------------------- |
| suppl 445081d6 305c 4fb7 b89e 82c86969d4bd (prodi:suppl-445081d6-305c-4fb7-b89e-82c86969d4bd) | 0.962 (xsd:decimal) |

[Tool]
Got 10 rows and 3 columns:
| subject                                                                                | property                                     | object                               |
| --------------------------------------------------------------------------------------------- | -------------------------------------------- | ------------------------------------ |
| suppl 445081d6 305c 4fb7 b89e 82c86969d4bd (prodi:suppl-445081d6-305c-4fb7-b89e-82c86969d4bd) | type (rdf:type)                              | Supplier (pv:Supplier)               |
| suppl 445081d6 305c 4fb7 b89e 82c86969d4bd (prodi:suppl-445081d6-305c-4fb7-b89e-82c86969d4bd) | label (rdfs:label)                           | Adkins, Lopez and Boyd (Switzerland) |
| suppl 445081d6 305c 4fb7 b89e 82c86969d4bd (prodi:suppl-445081d6-305c-4fb7-b89e-82c86969d4bd) | name (pv:name)                               | Adkins, Lopez and Boyd               |
| suppl 445081d6 305c 4fb7 b89e 82c86969d4bd (prodi:suppl-445081d6-305c-4fb7-b89e-82c86969d4bd) | ID (pv:id)                                   | 445081d6-305c-4fb7-b89e-82c86969d4bd |
| suppl 445081d6 305c 4fb7 b89e 82c86969d4bd (prodi:suppl-445081d6-305c-4fb7-b89e-82c86969d4bd) | address country (pv:addressCountry)          | Switzerland                          |
| suppl 445081d6 305c 4fb7 b89e 82c86969d4bd (prodi:suppl-445081d6-305c-4fb7-b89e-82c86969d4bd) | address country code (pv:addressCountryCode) | CH                                   |
| suppl 445081d6 305c 4fb7 b89e 82c86969d4bd (prodi:suppl-445081d6-305c-4fb7-b89e-82c86969d4bd) | address locality (pv:addressLocality)        | Kriens                               |
| suppl 445081d6 305c 4fb7 b89e 82c86969d4bd (prodi:suppl-445081d6-305c-4fb7-b89e-82c86969d4bd) | lat (wgs84:lat)                              | 47.034146                            |
| suppl 445081d6 305c 4fb7 b89e 82c86969d4bd (prodi:suppl-445081d6-305c-4fb7-b89e-82c86969d4bd) | long (wgs84:long)                            | 8.2807994                            |
| suppl 445081d6 305c 4fb7 b89e 82c86969d4bd (prodi:suppl-445081d6-305c-4fb7-b89e-82c86969d4bd) | country (pv:country)                         | Switzerland (dbpedia:Switzerland)    |

[Tool] Stopped generation process


PREFIX prodi: <http://ld.company.org/prod-instances/>
PREFIX pv: <http://ld.company.org/prod-vocab/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?coil ?label ?width ?depth ?weight WHERE {
  ?coil pv:hasCategory prodi:prod-cat-Coil .
  ?coil pv:width_mm ?width .
  ?coil pv:depth_mm ?depth .
  ?coil pv:weight_g ?weight .
  OPTIONAL {
    ?coil rdfs:label ?label
  }
  FILTER ( ( ?width * ?depth ) <= 225 )
}
ORDER BY DESC ( ?weight )
LIMIT 1

The heaviest coil that does not exceed a base area of 15x15 millimeters is prodi:hw-N558-1730215 (N558-1730215 - Flow Coil Dipole Strain), with a width of 12 mm, depth of 14 mm, and weight of 14 grams.

What is the heaviest coil that does not exceed a base area of 15x15 milimeter?

[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 heaviest coil that does not exceed a base area of 15x15 milimeter?

[Assistant]
Let's break down the question:

1. We are looking for "coils" (likely a class or type of entity in the KG).
2. We want the "heaviest" coil, i.e., the one with the maximum weight.
3. The coil's "base area" must not exceed 15x15 millimeters (i.e., 225 mm²).

Step 1: Identify how "coil" is represented in the KG.
Step 2: Identify properties for "weight" and "base area" (or width and length).
Step 3: Find coils with base area ≤ 225 mm², and select the one with the maximum weight.

First, let's search for the entity "coil".

[Tool]
Top 10 entity alternatives:
1. prod cat Coil (prodi:prod-cat-Coil): is a Product Category

[Assistant]
The entity "prod cat Coil" (prodi:prod-cat-Coil) is a Product Category. Likely, individual coils are instances of a class or have a type/property linking them to this category.

Next, let's check how individual coils are represented. I'll search for entities related to "coil" that might represent individual products or items.

[Tool]
Top 10 entity alternatives:
1. prod cat Coil (prodi:prod-cat-Coil): is a Product Category

[Assistant]
It seems the only direct match is the product category. To find individual coils, let's check for entities that are instances of this category or have a type/property linking them to "prod-cat-Coil".

I'll search for properties related to "type", "category", or "instance of" to see how products are linked to categories.

[Tool]
Top 10 property alternatives:
1. has category (pv:hasCategory): The category name of a product., has range Product Category, has domain Product
2. label (rdfs:label)
3. country (pv:country): The country where the supplier is located., has domain Supplier, has range Country
4. type (rdf:type)
5. part (pv:hasPart): has domain BOM Part, The Product needed., has range Product
6. vocabulary (void:vocabulary)
7. name (foaf:name):

8. name (pv:name): The name of something.
9. sub Class Of (rdfs:subClassOf)
10. is Defined By (rdfs:isDefinedBy)

[Assistant]
The property pv:hasCategory links products to their category, with "Product" as the domain and "Product Category" as the range. So, individual coils should be products with pv:hasCategory prodi:prod-cat-Coil.

Next, let's list some products with pv:hasCategory prodi:prod-cat-Coil to see how individual coils are represented.

[Tool]
Got 93 rows and 3 columns, showing the first 10 rows below:
| subject                                 | property                      | object                              |
| --------------------------------------- | ----------------------------- | ----------------------------------- |
| hw A145 1240844 (prodi:hw-A145-1240844) | has category (pv:hasCategory) | prod cat Coil (prodi:prod-cat-Coil) |
| hw A548 4778785 (prodi:hw-A548-4778785) | has category (pv:hasCategory) | prod cat Coil (prodi:prod-cat-Coil) |
| hw B120 9942467 (prodi:hw-B120-9942467) | has category (pv:hasCategory) | prod cat Coil (prodi:prod-cat-Coil) |
| hw B143 5457756 (prodi:hw-B143-5457756) | has category (pv:hasCategory) | prod cat Coil (prodi:prod-cat-Coil) |
| hw B150 4370781 (prodi:hw-B150-4370781) | has category (pv:hasCategory) | prod cat Coil (prodi:prod-cat-Coil) |
| hw B286 1369879 (prodi:hw-B286-1369879) | has category (pv:hasCategory) | prod cat Coil (prodi:prod-cat-Coil) |
| hw C171 3616793 (prodi:hw-C171-3616793) | has category (pv:hasCategory) | prod cat Coil (prodi:prod-cat-Coil) |
| hw C402 5072074 (prodi:hw-C402-5072074) | has category (pv:hasCategory) | prod cat Coil (prodi:prod-cat-Coil) |
| hw C717 1997689 (prodi:hw-C717-1997689) | has category (pv:hasCategory) | prod cat Coil (prodi:prod-cat-Coil) |
| hw C744 6535902 (prodi:hw-C744-6535902) | has category (pv:hasCategory) | prod cat Coil (prodi:prod-cat-Coil) |
| ...                                     | ...                           | ...                                 |

[Assistant]
We have found individual coil products, such as prodi:hw-A145-1240844, prodi:hw-A548-4778785, etc.

Next, we need to find properties for "weight" and "base area" (or "width" and "length") for these products. Let's search for properties related to "weight" first.

[Tool]
Top 10 property alternatives:
1. weight (g) (pv:weight_g): The weight of an item measured in grams., has domain Hardware
2. quantity (pv:quantity): The quantity needed., has domain BOM Part
3. amount (pv:amount): has domain Price, The amount.
4. height (mm) (pv:height_mm): The height of an item measured in millimeter., has domain Hardware
5. depth (mm) (pv:depth_mm): The depth of an item measured in millimeter., has domain Hardware
6. currency (pv:currency): has domain Price, The currency.
7. type (rdf:type)
8. name (foaf:name):

9. name (pv:name): The name of something.
10. width (mm) (pv:width_mm): The width of an item measured in millimeter., has domain Hardware

[Assistant]
The property pv:weight_g is used for the weight of an item in grams.

Now, let's search for properties related to "base area", "width", and "length" to see how the base area might be represented.

[Tool]
Top 10 property alternatives:
1. width (mm) (pv:width_mm): The width of an item measured in millimeter., has domain Hardware
2. depth (mm) (pv:depth_mm): The depth of an item measured in millimeter., has domain Hardware
3. height (mm) (pv:height_mm): The height of an item measured in millimeter., has domain Hardware
4. type (rdf:type)
5. quantity (pv:quantity): The quantity needed., has domain BOM Part
6. range (rdfs:range)
7. lat (wgs84:lat)
8. weight (g) (pv:weight_g): The weight of an item measured in grams., has domain Hardware
9. country (pv:country): The country where the supplier is located., has domain Supplier, has range Country
10. created (dct:created)

[Assistant]
We have found:
- pv:width_mm (width in millimeters)
- pv:depth_mm (depth in millimeters)
- pv:height_mm (height in millimeters)

For a "base area", it's common to use width × depth. So, we can use pv:width_mm and pv:depth_mm.

Now, let's check if these properties are present for a sample coil, e.g., prodi:hw-A145-1240844.

[Tool]
Got 18 rows and 3 columns, showing the first 10 rows below:
| subject                                 | property                                   | object                                                                                |
| --------------------------------------- | ------------------------------------------ | -------------------------------------------------------------------------------------------------------- |
| hw A145 1240844 (prodi:hw-A145-1240844) | type (rdf:type)                            | Hardware (pv:Hardware)                                                                                |
| hw A145 1240844 (prodi:hw-A145-1240844) | label (rdfs:label)                         | A145-1240844 - Bipolar-junction Coil Compensator Transducer                                              |
| hw A145 1240844 (prodi:hw-A145-1240844) | has category (pv:hasCategory)              | prod cat Compensator (prodi:prod-cat-Compensator)                                                        |
| hw A145 1240844 (prodi:hw-A145-1240844) | compatible product (pv:compatibleProduct)  | hw D729 5737042 (prodi:hw-D729-5737042)                                                                  |
| hw A145 1240844 (prodi:hw-A145-1240844) | name (pv:name)                             | Bipolar-junction Coil Compensator Transducer                                                             |
| hw A145 1240844 (prodi:hw-A145-1240844) | ID (pv:id)                                 | A145-1240844                                                                                |
| hw A145 1240844 (prodi:hw-A145-1240844) | has product manager (pv:hasProductManager) | empl Ratt Hartmann@company org (<http://ld.company.org/prod-instances/empl-Ratt.Hartmann%40company.org>) |
| hw A145 1240844 (prodi:hw-A145-1240844) | price (pv:price)                           | price hw A145 1240844 EUR (prodi:price-hw-A145-1240844-EUR)                                              |
| hw A145 1240844 (prodi:hw-A145-1240844) | depth (mm) (pv:depth_mm)                   | 20 (xsd:int)                                                                                |
| hw A145 1240844 (prodi:hw-A145-1240844) | supplier (pv:hasSupplier)                  | suppl 42a20063 bd30 49d3 8506 ceac4ceb2d9e (prodi:suppl-42a20063-bd30-49d3-8506-ceac4ceb2d9e)            |
| ...                                     | ...                                        | ...                                                                                |

[Tool]
Got 18 rows and 3 columns, showing the first 10 rows below:
| subject                                 | property                                   | object                                                                                |
| --------------------------------------- | ------------------------------------------ | -------------------------------------------------------------------------------------------------------- |
| hw A145 1240844 (prodi:hw-A145-1240844) | type (rdf:type)                            | Hardware (pv:Hardware)                                                                                |
| hw A145 1240844 (prodi:hw-A145-1240844) | label (rdfs:label)                         | A145-1240844 - Bipolar-junction Coil Compensator Transducer                                              |
| hw A145 1240844 (prodi:hw-A145-1240844) | has category (pv:hasCategory)              | prod cat Compensator (prodi:prod-cat-Compensator)                                                        |
| hw A145 1240844 (prodi:hw-A145-1240844) | compatible product (pv:compatibleProduct)  | hw D729 5737042 (prodi:hw-D729-5737042)                                                                  |
| hw A145 1240844 (prodi:hw-A145-1240844) | name (pv:name)                             | Bipolar-junction Coil Compensator Transducer                                                             |
| hw A145 1240844 (prodi:hw-A145-1240844) | ID (pv:id)                                 | A145-1240844                                                                                |
| hw A145 1240844 (prodi:hw-A145-1240844) | has product manager (pv:hasProductManager) | empl Ratt Hartmann@company org (<http://ld.company.org/prod-instances/empl-Ratt.Hartmann%40company.org>) |
| hw A145 1240844 (prodi:hw-A145-1240844) | price (pv:price)                           | price hw A145 1240844 EUR (prodi:price-hw-A145-1240844-EUR)                                              |
| hw A145 1240844 (prodi:hw-A145-1240844) | depth (mm) (pv:depth_mm)                   | 20 (xsd:int)                                                                                |
| hw A145 1240844 (prodi:hw-A145-1240844) | supplier (pv:hasSupplier)                  | suppl 42a20063 bd30 49d3 8506 ceac4ceb2d9e (prodi:suppl-42a20063-bd30-49d3-8506-ceac4ceb2d9e)            |
| ...                                     | ...                                        | ...                                                                                |

[Tool]
Got 1 row and 3 columns:
| subject                                 | property                 | object       |
| --------------------------------------- | ------------------------ | ------------ |
| hw A145 1240844 (prodi:hw-A145-1240844) | width (mm) (pv:width_mm) | 17 (xsd:int) |

[Tool]
Got 1 row and 3 columns:
| subject                                 | property                 | object       |
| --------------------------------------- | ------------------------ | ------------ |
| hw A145 1240844 (prodi:hw-A145-1240844) | weight (g) (pv:weight_g) | 14 (xsd:int) |

[Assistant]
For the sample coil prodi:hw-A145-1240844, we have:
- pv:width_mm = 17
- pv:depth_mm = 20
- pv:weight_g = 14

This means we can use pv:width_mm and pv:depth_mm to compute the base area, and pv:weight_g for the weight.

Now, let's write a SPARQL query to:
- Select all products with pv:hasCategory prodi:prod-cat-Coil
- Get their pv:width_mm, pv:depth_mm, and pv:weight_g
- Filter for width_mm * depth_mm ≤ 225
- Return the coil with the maximum weight

I'll include optional labels for readability.

[Tool]
Got 1 row and 5 columns:
| coil                                    | label                                  | width        | depth        | weight       |
| --------------------------------------- | -------------------------------------- | ------------ | ------------ | ------------ |
| hw N558 1730215 (prodi:hw-N558-1730215) | N558-1730215 - Flow Coil Dipole Strain | 12 (xsd:int) | 14 (xsd:int) | 14 (xsd:int) |

[Tool] Stopped generation process


PREFIX prodi: <http://ld.company.org/prod-instances/>
PREFIX pv: <http://ld.company.org/prod-vocab/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?sabrina ?email WHERE {
  ?sabrina pv:memberOf prodi:dept-85880 .
  ?sabrina pv:email ?email .
  OPTIONAL {
    ?sabrina rdfs:label ?label
  }
}

Got 10 rows and 2 columns:
| sabrina                                                                                | email                        |
| -------------------------------------------------------------------------------------------------------------- | ---------------------------- |
| empl Baldwin Dirksen@company org (<http://ld.company.org/prod-instances/empl-Baldwin.Dirksen%40company.org>)   | Baldwin.Dirksen@company.org  |
| empl Bert Blumstein@company org (<http://ld.company.org/prod-instances/empl-Bert.Blumstein%40company.org>)     | Bert.Blumstein@company.org   |
| empl Dietlinde Boehme@company org (<http://ld.company.org/prod-instances/empl-Dietlinde.Boehme%40company.org>) | Dietlinde.Boehme@company.org |
| empl Henny Foth@company org (<http://ld.company.org/prod-instances/empl-Henny.Foth%40company.org>)             | Henny.Foth@company.org       |
| empl Kevin Feigenbaum@company org (<http://ld.company.org/prod-instances/empl-Kevin.Feigenbaum%40company.org>) | Kevin.Feigenbaum@company.org |
| empl Lambert Faust@company org (<http://ld.company.org/prod-instances/empl-Lambert.Faust%40company.org>)       | Lambert.Faust@company.org    |
| empl Liese Adam@company org (<http://ld.company.org/prod-instances/empl-Liese.Adam%40company.org>)             | Liese.Adam@company.org       |
| empl Sabrina Geiger@company org (<http://ld.company.org/prod-instances/empl-Sabrina.Geiger%40company.org>)     | Sabrina.Geiger@company.org   |
| empl Valda Everhart@company org (<http://ld.company.org/prod-instances/empl-Valda.Everhart%40company.org>)     | Valda.Everhart@company.org   |
| empl Yanka Schreiber@company org (<http://ld.company.org/prod-instances/empl-Yanka.Schreiber%40company.org>)   | Yanka.Schreiber@company.org  |

The email of Sabrina from Marketing is Sabrina.Geiger@company.org.

What is the email of Sabrina from Marketing?

[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 email of Sabrina from Marketing?

[Assistant]
Let's break down the question:

1. We are looking for the email address of a person named "Sabrina" who is associated with the "Marketing" department.
2. We need to identify:
   - The entity for "Sabrina"
   - The property for "email"
   - The property or entity for "Marketing" (likely a department or organizational unit)

Step 1: Search for the entity "Sabrina" in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. empl Sabrina Geiger@company org (<http://ld.company.org/prod-instances/empl-Sabrina.Geiger%40company.org>): is a Employee
2. empl Sabrina Bayer@company org (<http://ld.company.org/prod-instances/empl-Sabrina.Bayer%40company.org>): is a Employee

[Assistant]
There are two entities named "Sabrina" in the knowledge graph:
1. Sabrina Geiger
2. Sabrina Bayer

Next, we need to determine which of these is associated with the "Marketing" department. Let's search for the entity "Marketing" to see how departments are represented.

[Tool] No entity items found

[Assistant]
There is no direct entity labeled "Marketing" in the knowledge graph. It's possible that the department is represented differently, perhaps as a property or as part of an employee's attributes.

Let's check the properties associated with the "Sabrina Geiger" entity to see if there is any department or organizational unit information.

[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. has manager (pv:hasManager): The manager of the employee., has domain Employee, has range Manager
4. member of (pv:memberOf): The department to which an agents belongs., has range Department, has domain Agent
5. type (rdf:type)
6. name (pv:name): The name of something.
7. email (pv:email): The e-mail of an agent., has domain Agent
8. phone number (pv:phone): has domain Agent, A phone number.

No other items found

[Assistant] The property pv:memberOf is likely used to indicate the department to which an employee belongs. Let's check which department Sabrina Geiger is a member of by listing the values for pv:memberOf for her entity.

[Tool]
Got 1 row and 3 columns:
| subject                                                                                | property                | object                        |
| ---------------------------------------------------------------------------------------------------------- | ----------------------- | ----------------------------- |
| empl Sabrina Geiger@company org (<http://ld.company.org/prod-instances/empl-Sabrina.Geiger%40company.org>) | member of (pv:memberOf) | dept 85880 (prodi:dept-85880) |

[Assistant] Sabrina Geiger is a member of the department with the IRI prodi:dept-85880. Let's check if this department is "Marketing" by retrieving its label or name.

[Tool]
Got 16 rows and 3 columns, showing the first 10 rows below:
| subject                       | property                            | object                                    |
| ----------------------------- | ----------------------------------- | ----------------------------------------- |
| dept 85880 (prodi:dept-85880) | type (rdf:type)                     | Department (pv:Department)                |
| dept 85880 (prodi:dept-85880) | label (rdfs:label)                  | Marketing                                 |
| dept 85880 (prodi:dept-85880) | name (pv:name)                      | Marketing                                 |
| dept 85880 (prodi:dept-85880) | ID (pv:id)                          | 85880                                     |
| dept 85880 (prodi:dept-85880) | responsible for (pv:responsibleFor) | srv P516 8211068 (prodi:srv-P516-8211068) |
| dept 85880 (prodi:dept-85880) | responsible for (pv:responsibleFor) | srv O662 4012383 (prodi:srv-O662-4012383) |
| dept 85880 (prodi:dept-85880) | responsible for (pv:responsibleFor) | srv U360 2815908 (prodi:srv-U360-2815908) |
| dept 85880 (prodi:dept-85880) | responsible for (pv:responsibleFor) | hw C831 2580759 (prodi:hw-C831-2580759)   |
| dept 85880 (prodi:dept-85880) | responsible for (pv:responsibleFor) | hw D334 6681399 (prodi:hw-D334-6681399)   |
| dept 85880 (prodi:dept-85880) | responsible for (pv:responsibleFor) | hw D844 3535311 (prodi:hw-D844-3535311)   |
| ...                           | ...                                 | ...                                       |

[Assistant]
The department prodi:dept-85880 is indeed "Marketing" (as shown by its rdfs:label and pv:name).

Now, let's check if Sabrina Bayer is also a member of the Marketing department, to ensure we have the correct Sabrina.

[Tool]
Got 1 row and 3 columns:
| subject                                                                                | property                | object                        |
| -------------------------------------------------------------------------------------------------------- | ----------------------- | ----------------------------- |
| empl Sabrina Bayer@company org (<http://ld.company.org/prod-instances/empl-Sabrina.Bayer%40company.org>) | member of (pv:memberOf) | dept 66469 (prodi:dept-66469) |

[Assistant]
Sabrina Bayer is a member of a different department (prodi:dept-66469), not Marketing.

Therefore, the "Sabrina from Marketing" refers to Sabrina Geiger. Now, let's retrieve her email address using the pv:email property.

[Tool]
Got 1 row and 3 columns:
| subject                                                                                | property         | object                     |
| ---------------------------------------------------------------------------------------------------------- | ---------------- | -------------------------- |
| empl Sabrina Geiger@company org (<http://ld.company.org/prod-instances/empl-Sabrina.Geiger%40company.org>) | email (pv:email) | Sabrina.Geiger@company.org |

[Tool] Stopped generation process


PREFIX prodi: <http://ld.company.org/prod-instances/>
PREFIX pv: <http://ld.company.org/prod-vocab/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?oscillator ?name ?price ?amount WHERE {
  ?oscillator pv:hasCategory prodi:prod-cat-Oscillator .
  ?oscillator pv:price ?price .
  ?price pv:amount ?amount .
  OPTIONAL {
    ?oscillator rdfs:label ?name
  }
  OPTIONAL {
    ?oscillator pv:name ?name
  }
}
ORDER BY ASC ( ?amount )
LIMIT 1

The cheapest Oscillator is hw F388 7030185 (F388-7030185 - Oscillator Transistor Transducer) with a price of 0.1 (currency not specified, likely EUR).

What is the cheapest Oscillator we have?

[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 cheapest Oscillator we have?

[Assistant]
Let's break down the question:

1. The entity of interest is "Oscillator". I need to identify how oscillators are represented in the knowledge graph.
2. The property of interest is "cheapest", which likely refers to a price or cost property. I need to find the property that represents the price or cost of an oscillator.
3. The question asks for the cheapest oscillator, so I will need to sort oscillators by price and select the one with the lowest value.

First, I will search for the entity "Oscillator" in the knowledge graph to see how it is represented.

[Tool]
Top 10 entity alternatives:
1. prod cat Oscillator (prodi:prod-cat-Oscillator): is a Product Category

[Assistant]
The search result shows that "Oscillator" is represented as a product category: prodi:prod-cat-Oscillator.

Next, I need to find products that are instances of this category. Usually, there is a property linking products to their category. I will search for properties related to "category" to find the correct one.

[Tool]
Top 10 property alternatives:
1. has category (pv:hasCategory): The category name of a product., has range Product Category, has domain Product
2. label (rdfs:label)
3. country (pv:country): The country where the supplier is located., has domain Supplier, has range Country
4. type (rdf:type)
5. part (pv:hasPart): has domain BOM Part, The Product needed., has range Product
6. vocabulary (void:vocabulary)
7. name (foaf:name):

8. name (pv:name): The name of something.
9. sub Class Of (rdfs:subClassOf)
10. is Defined By (rdfs:isDefinedBy)

[Assistant]
The property pv:hasCategory links a product to its category, which matches our need.

Now, I need to find the property that represents the price or cost of a product. 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 pv:price links a product to a price specification, and pv:amount gives the numeric value of the price.

So, to find the cheapest oscillator, I need to:
- Find all products with pv:hasCategory prodi:prod-cat-Oscillator.
- Get their pv:price, then the pv:amount of that price.
- Sort by pv:amount ascending and select the first one.

Now, I will write a SPARQL query to do this. I will also try to get the product's label or name if available.

[Tool]
Got 1 row and 4 columns:
| oscillator                              | name                                            | price                                                       | amount            |
| --------------------------------------- | ----------------------------------------------- | ----------------------------------------------------------- | ----------------- |
| hw F388 7030185 (prodi:hw-F388-7030185) | F388-7030185 - Oscillator Transistor Transducer | price hw F388 7030185 EUR (prodi:price-hw-F388-7030185-EUR) | 0.1 (xsd:decimal) |

[Tool] Stopped generation process


PREFIX dbpedia: <http://dbpedia.org/resource/>
PREFIX prodi: <http://ld.company.org/prod-instances/>
PREFIX pv: <http://ld.company.org/prod-vocab/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?product ?supplier ?amount ?currency ?productLabel ?supplierLabel WHERE {
  ?product pv:hasCategory prodi:prod-cat-Encoder ; pv:hasSupplier ?supplier ; pv:price ?price .
  ?supplier pv:country ?country .
  ?price pv:amount ?amount ; pv:currency ?currency .
  OPTIONAL {
    ?product rdfs:label ?productLabel
  }
  OPTIONAL {
    ?supplier rdfs:label ?supplierLabel
  }
  FILTER ( ?country IN ( dbpedia:France , dbpedia:Germany ) )
}
ORDER BY ASC ( ?amount )
LIMIT 1

The cheapest Encoder from a French or German supplier is 'P453-8155326 - Encoder Breaker' (prodi:hw-P453-8155326), supplied by 'Fletcher, Pierce and Navarro (France)' (prodi:suppl-9e95d78d-7f95-4752-9e1f-d522e67e63d7), at a price of 0.39 EUR.

What is the cheapest Encoder we can get from a french or german supplier?

[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 cheapest Encoder we can get from a french or german supplier?

[Assistant]
Let's break down the question:

1. We are looking for "Encoder" products.
2. The supplier should be from France or Germany.
3. We want the cheapest such Encoder.

Step 1: Identify the entity for "Encoder".
Step 2: Identify properties for supplier, supplier country, and price.
Step 3: Find suppliers from France or Germany.
Step 4: Find Encoders supplied by those suppliers.
Step 5: Find the price and select the cheapest.

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

[Tool]
Top 10 entity alternatives:
1. prod cat Encoder (prodi:prod-cat-Encoder): is a Product Category

[Assistant]
The entity "prod cat Encoder" (prodi:prod-cat-Encoder) is a Product Category for Encoders. Next, I need to identify properties related to supplier, supplier country, and price for products in this category.

I'll search for properties related to "supplier" to find how products are linked to suppliers.

[Tool]
Top 10 property alternatives:
1. supplier (pv:hasSupplier): The supplier of a product., has domain Product, has range Supplier
2. compatible product (pv:compatibleProduct): A compatible product., has domain Product, has range Product
3. contributor (dct:contributor)
4. publisher (dct:publisher)
5. quantity (pv:quantity): The quantity needed., has domain BOM Part
6. part (pv:hasPart): has domain BOM Part, The Product needed., has range Product
7. country (pv:country): The country where the supplier is located., has domain Supplier, has range Country
8. label (rdfs:label)
9. has product manager (pv:hasProductManager): The employee acting as the product manager of the product., has range Employee, has domain Product
10. member of (pv:memberOf): The department to which an agents belongs., has range Department, has domain Agent

[Assistant]
The relevant properties are:
- pv:hasSupplier (links Product to Supplier)
- pv:country (links Supplier to Country)

Next, I need to find how price is represented for products. I'll 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 relevant properties for price are:
- pv:price (links Product to Price)
- pv:amount (links Price to the numeric amount)
- pv:currency (links Price to the currency)

Now, let's identify how to get suppliers from France or Germany. I'll search for country entities for "France" and "Germany".

[Tool]
Top 10 entity alternatives:
1. France (dbpedia:France)

[Tool]
Top 10 entity alternatives:
1. Germany (dbpedia:Germany)

[Assistant]
The country entities are:
- France: dbpedia:France
- Germany: dbpedia:Germany

Now, let's summarize the plan for the SPARQL query:
- Find products of category prodi:prod-cat-Encoder.
- Get their suppliers (pv:hasSupplier).
- Filter suppliers whose pv:country is dbpedia:France or dbpedia:Germany.
- Get the price (pv:price → pv:amount).
- Select the product with the minimum price.

Before building the final query, let's check how products are linked to categories. I'll search for properties related to "category".

[Tool]
Top 10 property alternatives:
1. has category (pv:hasCategory): The category name of a product., has range Product Category, has domain Product
2. label (rdfs:label)
3. country (pv:country): The country where the supplier is located., has domain Supplier, has range Country
4. type (rdf:type)
5. part (pv:hasPart): has domain BOM Part, The Product needed., has range Product
6. vocabulary (void:vocabulary)
7. name (foaf:name):

8. name (pv:name): The name of something.
9. sub Class Of (rdfs:subClassOf)
10. is Defined By (rdfs:isDefinedBy)

[Assistant]
Products are linked to categories using pv:hasCategory.

Now, I have all the necessary properties and entities:
- Product: ?product
- Category: pv:hasCategory prodi:prod-cat-Encoder
- Supplier: pv:hasSupplier ?supplier
- Supplier country: pv:country ?country (filter for dbpedia:France or dbpedia:Germany)
- Price: pv:price ?price, then ?price pv:amount ?amount

Let's build the SPARQL query to find the cheapest Encoder from a French or German supplier, returning the product, supplier, price, and optionally their labels.

[Tool]
SPARQL execution failed:
Invalid SPARQL query: Variable ?product is selected but not aggregated. All non-aggregated variables must be part of the GROUP BY clause. Note: The GROUP BY in this query is implicit because an aggregate expression was used in the SELECT clause

[Assistant]
The error is due to using SAMPLE() without a GROUP BY clause. Since we only want the cheapest Encoder, we can avoid aggregation and just order by price, limiting the result to 1.

I'll remove the SAMPLE() and just use OPTIONAL for labels, ordering by amount and limiting to 1. Let's try the corrected query.

[Tool]
Got 1 row and 6 columns:
| product                                 | supplier                                                                                | amount             | currency | productLabel                   | supplierLabel                         |
| --------------------------------------- | --------------------------------------------------------------------------------------------- | ------------------ | -------- | ------------------------------ | ------------------------------------- |
| hw P453 8155326 (prodi:hw-P453-8155326) | suppl 9e95d78d 7f95 4752 9e1f d522e67e63d7 (prodi:suppl-9e95d78d-7f95-4752-9e1f-d522e67e63d7) | 0.39 (xsd:decimal) | EUR      | P453-8155326 - Encoder Breaker | Fletcher, Pierce and Navarro (France) |

[Tool] Stopped generation process


PREFIX foaf: <http://xmlns.com/foaf/0.1/>
PREFIX prodi: <http://ld.company.org/prod-instances/>
PREFIX pv: <http://ld.company.org/prod-vocab/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?expert ?label WHERE {
  ?expert pv:areaOfExpertise prodi:prod-cat-Sensor .
  OPTIONAL {
    ?expert rdfs:label ?label
  }
  OPTIONAL {
    ?expert foaf:name ?label
  }
}

Got 7 rows and 2 columns:
| expert                                                                                | label               |
| -------------------------------------------------------------------------------------------------------------------- | ------------------- |
| empl Anamchara Foerstner@company org (<http://ld.company.org/prod-instances/empl-Anamchara.Foerstner%40company.org>) | Anamchara Foerstner |
| empl Arendt Beitel@company org (<http://ld.company.org/prod-instances/empl-Arendt.Beitel%40company.org>)             | Arendt Beitel       |
| empl Gretel Roth@company org (<http://ld.company.org/prod-instances/empl-Gretel.Roth%40company.org>)                 | Gretel Roth         |
| empl Liese Adam@company org (<http://ld.company.org/prod-instances/empl-Liese.Adam%40company.org>)                   | Liese Adam          |
| empl Lili Geier@company org (<http://ld.company.org/prod-instances/empl-Lili.Geier%40company.org>)                   | Lili Geier          |
| empl Sylvester Brant@company org (<http://ld.company.org/prod-instances/empl-Sylvester.Brant%40company.org>)         | Sylvester Brant     |
| empl Xochitl Aue@company org (<http://ld.company.org/prod-instances/empl-Xochitl.Aue%40company.org>)                 | Xochitl Aue         |

The Sensor experts are: Anamchara Foerstner, Arendt Beitel, Gretel Roth, Liese Adam, Lili Geier, Sylvester Brant, and Xochitl Aue.

[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] Who is our Sensor expert?

[Assistant]
Let's break down the question:

1. The user is asking for the "Sensor expert"—likely a person with expertise in sensors.
2. I need to identify how "expert" and "sensor" are represented in the knowledge graph.
3. I should search for entities related to "sensor" and properties or roles related to "expert".

First, I'll search for entities related to "sensor".

[Tool]
Top 10 entity alternatives:
1. prod cat Sensor (prodi:prod-cat-Sensor): is a Product Category

[Assistant]
I found an entity "prod cat Sensor" (prodi:prod-cat-Sensor) which represents the product category "Sensor".

Next, I need to find how "expert" is represented—possibly as a role, skill, or property linking a person to a product category. I'll search for properties related to "expert".

[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. contributor (dct:contributor)
3. member of (pv:memberOf): The department to which an agents belongs., has range Department, has domain Agent
4. ID (pv:id): The ID of a thing.
5. creator (dct:creator)
6. created (dct:created)
7. type (rdf:type)
8. name (foaf:name):

9. name (pv:name): The name of something.
10. responsible for (pv:responsibleFor): The product for which a department is responsible., has domain Department, has range Product

[Assistant]
The property "area of expertise" (pv:areaOfExpertise) links an agent (likely a person) to a product category for which they are an expert.

Now, I will search for agents (people) whose area of expertise is the "Sensor" product category (prodi:prod-cat-Sensor). I'll construct a SPARQL query to find such agents and optionally retrieve their labels or names.

[Tool]
Got 7 rows and 2 columns:
| expert                                                                                | label               |
| -------------------------------------------------------------------------------------------------------------------- | ------------------- |
| empl Anamchara Foerstner@company org (<http://ld.company.org/prod-instances/empl-Anamchara.Foerstner%40company.org>) | Anamchara Foerstner |
| empl Arendt Beitel@company org (<http://ld.company.org/prod-instances/empl-Arendt.Beitel%40company.org>)             | Arendt Beitel       |
| empl Gretel Roth@company org (<http://ld.company.org/prod-instances/empl-Gretel.Roth%40company.org>)                 | Gretel Roth         |
| empl Liese Adam@company org (<http://ld.company.org/prod-instances/empl-Liese.Adam%40company.org>)                   | Liese Adam          |
| empl Lili Geier@company org (<http://ld.company.org/prod-instances/empl-Lili.Geier%40company.org>)                   | Lili Geier          |
| empl Sylvester Brant@company org (<http://ld.company.org/prod-instances/empl-Sylvester.Brant%40company.org>)         | Sylvester Brant     |
| empl Xochitl Aue@company org (<http://ld.company.org/prod-instances/empl-Xochitl.Aue%40company.org>)                 | Xochitl Aue         |

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX prodi: <http://ld.company.org/prod-instances/>
PREFIX pv: <http://ld.company.org/prod-vocab/>
PREFIX dbpedia: <http://dbpedia.org/resource/>
SELECT DISTINCT ?product ?productLabel ?supplier ?supplierLabel WHERE {
  ?product pv:compatibleProduct prodi:hw-U990-5234138 .
  ?product pv:hasSupplier ?supplier .
  ?supplier pv:country dbpedia:United_States .
  OPTIONAL {
    ?product rdfs:label ?productLabel
  }
  OPTIONAL {
    ?supplier rdfs:label ?supplierLabel
  }
}

You can get the following products from US suppliers that are compatible with the U990 LCD Inductor:

1. A360-3041803 - Inductor Transformer Warp (prodi:hw-A360-3041803) from Fernandez-Roberts (United States) (prodi:suppl-29cf8eca-50be-460e-9816-5ae505fc9491)
2. A509-5571891 - Multiplexer Inductor (prodi:hw-A509-5571891) from Collins and Sons (United States) (prodi:suppl-afa65b2a-f046-47f4-b352-97b579c77c21)

The query returns the IRIs of the products and suppliers as well as their labels.

What products can I get from US suppliers that are compatible with the U990 LCD Inductor?

[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 products can I get from US suppliers that are compatible with the U990 LCD Inductor?

[Assistant]
Let's break down the question:

1. Entities:
   - "U990 LCD Inductor" (likely a product or component)
   - "US suppliers" (suppliers located in the United States)
   - "products ... compatible with the U990 LCD Inductor"

2. Properties:
   - Compatibility (products compatible with another product)
   - Supplier location (supplier is in the US)
   - Supplier of product

Step 1: Find the entity for "U990 LCD Inductor".

[Tool]
Top 10 entity alternatives:
1. prod cat LCD (prodi:prod-cat-LCD): is a Product Category
2. prod cat Inductor (prodi:prod-cat-Inductor): is a Product Category
3. hw U990 5234138 (prodi:hw-U990-5234138): is a Hardware
4. bom part 18 U990 5234138 (prodi:bom-part-18-U990-5234138): is a BOM Part
5. bom part 5 U990 5234138 (prodi:bom-part-5-U990-5234138): is a BOM Part
6. price hw U990 5234138 EUR (prodi:price-hw-U990-5234138-EUR): is a Price

[Assistant]
From the search results, the most likely entity for "U990 LCD Inductor" is "hw U990 5234138" (prodi:hw-U990-5234138), which is a hardware product. There are also BOM parts related to U990, but for compatibility, the hardware entity is the best candidate.

Next, I need to identify how "compatibility" is represented in the knowledge graph. I'll search for properties related to "compatible" or "compatibility".

[Tool]
Top 10 property alternatives:
1. compatible product (pv:compatibleProduct): A compatible product., has domain Product, has range Product
2. eligible for (pv:eligibleFor): Valid product service combinations (bundles, accessories)., has domain Service, has range Product
3. supplier (pv:hasSupplier): The supplier of a product., has domain Product, has range Supplier
4. width (mm) (pv:width_mm): The width of an item measured in millimeter., has domain Hardware
5. type (rdf:type)
6. version Info (owl:versionInfo)
7. created (dct:created)
8. depth (mm) (pv:depth_mm): The depth of an item measured in millimeter., has domain Hardware
9. license (<http://creativecommons.org/ns#license>)
10. height (mm) (pv:height_mm): The height of an item measured in millimeter., has domain Hardware

[Assistant]
The property "compatible product" (pv:compatibleProduct) is the most relevant for finding products compatible with the U990 LCD Inductor.

Next, I need to identify how to find products from "US suppliers". I'll search for properties related to "supplier" and then check how to filter for US-based suppliers.

[Tool]
Top 10 property alternatives:
1. supplier (pv:hasSupplier): The supplier of a product., has domain Product, has range Supplier
2. compatible product (pv:compatibleProduct): A compatible product., has domain Product, has range Product
3. contributor (dct:contributor)
4. publisher (dct:publisher)
5. quantity (pv:quantity): The quantity needed., has domain BOM Part
6. part (pv:hasPart): has domain BOM Part, The Product needed., has range Product
7. country (pv:country): The country where the supplier is located., has domain Supplier, has range Country
8. label (rdfs:label)
9. has product manager (pv:hasProductManager): The employee acting as the product manager of the product., has range Employee, has domain Product
10. member of (pv:memberOf): The department to which an agents belongs., has range Department, has domain Agent

[Assistant]
The property "supplier" (pv:hasSupplier) links a product to its supplier. The property "country" (pv:country) links a supplier to a country.

Now, let's confirm the country entity for the United States. I'll search for "United States" in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. United States (dbpedia:United_States)
2. United Kingdom (dbpedia:United_Kingdom)

[Assistant]
The entity for the United States is dbpedia:United_States.

Now, let's summarize the plan for the SPARQL query:
- Find products (?product) that are compatible with prodi:hw-U990-5234138 using pv:compatibleProduct.
- For each such product, find its supplier (?supplier) using pv:hasSupplier.
- For each supplier, check if their country (pv:country) is dbpedia:United_States.

I'll write a SPARQL query to retrieve the IRIs of such products, their suppliers, and optionally their labels.

[Tool]
Got 2 rows and 4 columns:
| product                                 | productLabel                             | supplier                                                                                | supplierLabel                     |
| --------------------------------------- | ---------------------------------------- | --------------------------------------------------------------------------------------------- | --------------------------------- |
| hw A360 3041803 (prodi:hw-A360-3041803) | A360-3041803 - Inductor Transformer Warp | suppl 29cf8eca 50be 460e 9816 5ae505fc9491 (prodi:suppl-29cf8eca-50be-460e-9816-5ae505fc9491) | Fernandez-Roberts (United States) |
| hw A509 5571891 (prodi:hw-A509-5571891) | A509-5571891 - Multiplexer Inductor      | suppl afa65b2a f046 47f4 b352 97b579c77c21 (prodi:suppl-afa65b2a-f046-47f4-b352-97b579c77c21) | Collins and Sons (United States)  |

[Tool] Stopped generation process


PREFIX pv: <http://ld.company.org/prod-vocab/>
SELECT ?bom ( AVG( ?amount ) AS ?avgUnitCost ) WHERE {
  ?bom a pv:BillOfMaterial .
  ?bom pv:hasBomPart ?bomPart .
  ?bomPart pv:hasPart ?part .
  ?part a pv:Hardware .
  ?part pv:price ?priceEntity .
  ?priceEntity pv:amount ?amount .
}
GROUP BY ?bom
ORDER BY DESC ( ?avgUnitCost )
LIMIT 1

The Bill-of-Material with the highest average unit cost of its hardware parts is prodi:bom-8 (MotoSync QuantumWave), with an average unit cost of 4.

Which Bill-of-Material has the highest average unit cost of its hardware parts, and what is that average?

[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] Which Bill-of-Material has the highest average unit cost of its hardware parts, and what is that average?

[Assistant]
Let's break down the question:

1. We need to identify all Bill-of-Material (BoM) entities.
2. For each BoM, we need to find its hardware parts.
3. For each hardware part, we need to get its unit cost.
4. For each BoM, calculate the average unit cost of its hardware parts.
5. Find the BoM with the highest average unit cost and return that BoM and the average.

First, I need to search for entities related to "Bill-of-Material" and "hardware part" in the knowledge graph to identify their IRIs.

[Tool] No entity items found

[Assistant] No entity was found for "Bill-of-Material". It's possible that a different naming convention is used in the knowledge graph, such as "BOM", "bill of material", or similar. I will try searching for "BOM" next.

[Tool]
Top 10 entity alternatives:
1. BOM Part (pv:BomPart): A (number of) part(s) in a BOM.
2. bom 4 (prodi:bom-4): is a Bill of Material (BOM)
3. bom 19 (prodi:bom-19): is a Bill of Material (BOM)
4. bom 12 (prodi:bom-12): is a Bill of Material (BOM)
5. bom 2 (prodi:bom-2): is a Bill of Material (BOM)
6. bom 11 (prodi:bom-11): is a Bill of Material (BOM)
7. bom 18 (prodi:bom-18): is a Bill of Material (BOM)
8. bom 6 (prodi:bom-6): is a Bill of Material (BOM)
9. bom 15 (prodi:bom-15): is a Bill of Material (BOM)
10. bom 5 (prodi:bom-5): is a Bill of Material (BOM)

[Assistant]
I found several entities for Bill-of-Material (BoM), such as prodi:bom-4, prodi:bom-19, etc. There is also a class/entity called "BOM Part" (pv:BomPart), which likely represents parts within a BoM.

Next, I need to identify how hardware parts are represented. I will search for "hardware" to see if there is a specific class or property for hardware parts.

[Tool]
Top 10 entity alternatives:
1. Hardware (pv:Hardware): The hardware products produced., is subclass of Product
2. hardware chip outline svg?color=#D6AF00&format=svg (<https://api.iconify.design/ion/hardware-chip-outline.svg?color=%23D6AF00&format=svg>)

[Assistant]
There is an entity called "Hardware" (pv:Hardware), which is a subclass of Product. This likely represents hardware parts.

Now, I need to determine how BoMs are linked to their parts, and how to filter those parts to only include hardware. I will look at the properties of a BoM entity (e.g., prodi:bom-4) to see how parts are associated.

[Tool]
Got 18 rows and 3 columns, showing the first 10 rows below:
| subject             | property                     | object                                                  |
| ------------------- | ---------------------------- | ------------------------------------------------------- |
| bom 4 (prodi:bom-4) | type (rdf:type)              | Bill of Material (BOM) (pv:BillOfMaterial)              |
| bom 4 (prodi:bom-4) | label (rdfs:label)           | PulseCraft Vertex                                       |
| bom 4 (prodi:bom-4) | name (pv:name)               | PulseCraft Vertex                                       |
| bom 4 (prodi:bom-4) | has BOM Part (pv:hasBomPart) | bom part 4 A750 6901242 (prodi:bom-part-4-A750-6901242) |
| bom 4 (prodi:bom-4) | has BOM Part (pv:hasBomPart) | bom part 4 C794 6433363 (prodi:bom-part-4-C794-6433363) |
| bom 4 (prodi:bom-4) | has BOM Part (pv:hasBomPart) | bom part 4 D605 8095260 (prodi:bom-part-4-D605-8095260) |
| bom 4 (prodi:bom-4) | has BOM Part (pv:hasBomPart) | bom part 4 F661 8988230 (prodi:bom-part-4-F661-8988230) |
| bom 4 (prodi:bom-4) | has BOM Part (pv:hasBomPart) | bom part 4 H634 7337115 (prodi:bom-part-4-H634-7337115) |
| bom 4 (prodi:bom-4) | has BOM Part (pv:hasBomPart) | bom part 4 J859 3337215 (prodi:bom-part-4-J859-3337215) |
| bom 4 (prodi:bom-4) | has BOM Part (pv:hasBomPart) | bom part 4 K926 9334427 (prodi:bom-part-4-K926-9334427) |
| ...                 | ...                          | ...                                                     |

[Assistant]
The property pv:hasBomPart links a BoM to its parts, which are entities like prodi:bom-part-4-A750-6901242. Next, I need to see how these BOM Part entities are described, especially how they are linked to the actual product/part and its type (e.g., hardware) and cost.

I'll inspect one of these BOM Part entities (e.g., prodi:bom-part-4-A750-6901242) to see its properties.

[Tool]
Got 4 rows and 3 columns:
| subject                                                 | property               | object                                  |
| ------------------------------------------------------- | ---------------------- | --------------------------------------- |
| bom part 4 A750 6901242 (prodi:bom-part-4-A750-6901242) | type (rdf:type)        | BOM Part (pv:BomPart)                   |
| bom part 4 A750 6901242 (prodi:bom-part-4-A750-6901242) | label (rdfs:label)     | A750-6901242 (44)                       |
| bom part 4 A750 6901242 (prodi:bom-part-4-A750-6901242) | quantity (pv:quantity) | 44                                      |
| bom part 4 A750 6901242 (prodi:bom-part-4-A750-6901242) | part (pv:hasPart)      | hw A750 6901242 (prodi:hw-A750-6901242) |

[Assistant] The BOM Part entity uses pv:hasPart to link to the actual part (e.g., prodi:hw-A750-6901242). Now, I need to check the properties of this part entity to see how its type (hardware) and unit cost are represented.

[Tool]
Got 16 rows and 3 columns, showing the first 10 rows below:
| subject                                 | property                                   | object                                                                                |
| --------------------------------------- | ------------------------------------------ | ---------------------------------------------------------------------------------------------------------- |
| hw A750 6901242 (prodi:hw-A750-6901242) | type (rdf:type)                            | Hardware (pv:Hardware)                                                                                |
| hw A750 6901242 (prodi:hw-A750-6901242) | label (rdfs:label)                         | A750-6901242 - Film Resistor Memristor Meter                                                               |
| hw A750 6901242 (prodi:hw-A750-6901242) | has category (pv:hasCategory)              | prod cat Memristor (prodi:prod-cat-Memristor)                                                              |
| hw A750 6901242 (prodi:hw-A750-6901242) | compatible product (pv:compatibleProduct)  | hw F574 4728030 (prodi:hw-F574-4728030)                                                                    |
| hw A750 6901242 (prodi:hw-A750-6901242) | name (pv:name)                             | Film Resistor Memristor Meter                                                                              |
| hw A750 6901242 (prodi:hw-A750-6901242) | ID (pv:id)                                 | A750-6901242                                                                                |
| hw A750 6901242 (prodi:hw-A750-6901242) | has product manager (pv:hasProductManager) | empl Kristen Bauers@company org (<http://ld.company.org/prod-instances/empl-Kristen.Bauers%40company.org>) |
| hw A750 6901242 (prodi:hw-A750-6901242) | price (pv:price)                           | price hw A750 6901242 EUR (prodi:price-hw-A750-6901242-EUR)                                                |
| hw A750 6901242 (prodi:hw-A750-6901242) | depth (mm) (pv:depth_mm)                   | 19 (xsd:int)                                                                                |
| hw A750 6901242 (prodi:hw-A750-6901242) | supplier (pv:hasSupplier)                  | suppl 79274f67 b225 49fa ad8c fb20560cb1d5 (prodi:suppl-79274f67-b225-49fa-ad8c-fb20560cb1d5)              |
| ...                                     | ...                                        | ...                                                                                |

[Assistant]
The part entity prodi:hw-A750-6901242 is of type pv:Hardware and has a property pv:price, which points to another entity (prodi:price-hw-A750-6901242-EUR). To get the unit cost, I need to check the properties of this price entity.

I'll inspect prodi:price-hw-A750-6901242-EUR to see if it contains the unit cost.

[Tool]
Got 4 rows and 3 columns:
| subject                                                     | property               | object             |
| ----------------------------------------------------------- | ---------------------- | ------------------ |
| price hw A750 6901242 EUR (prodi:price-hw-A750-6901242-EUR) | type (rdf:type)        | Price (pv:Price)   |
| price hw A750 6901242 EUR (prodi:price-hw-A750-6901242-EUR) | label (rdfs:label)     | 5,49 EUR           |
| price hw A750 6901242 EUR (prodi:price-hw-A750-6901242-EUR) | amount (pv:amount)     | 5.49 (xsd:decimal) |
| price hw A750 6901242 EUR (prodi:price-hw-A750-6901242-EUR) | currency (pv:currency) | EUR                |

[Assistant]
The price entity has the property pv:amount, which gives the unit cost (5.49 EUR in this case).

Now, to summarize the plan for the SPARQL query:
- For each BoM (pv:BillOfMaterial), get its BOM Parts (pv:hasBomPart).
- For each BOM Part, get the actual part (pv:hasPart).
- Filter parts to only those of type pv:Hardware.
- For each hardware part, get its price (pv:price) and then the amount (pv:amount).
- For each BoM, calculate the average unit cost of its hardware parts.
- Return the BoM with the highest average unit cost and the average.

Before writing the final query, I need to confirm the class IRI for Bill-of-Material. From earlier, it appears to be pv:BillOfMaterial. I'll check the properties of prodi:bom-4 to confirm.

[Tool]
Got 18 rows and 3 columns, showing the first 10 rows below:
| subject             | property                     | object                                                  |
| ------------------- | ---------------------------- | ------------------------------------------------------- |
| bom 4 (prodi:bom-4) | type (rdf:type)              | Bill of Material (BOM) (pv:BillOfMaterial)              |
| bom 4 (prodi:bom-4) | label (rdfs:label)           | PulseCraft Vertex                                       |
| bom 4 (prodi:bom-4) | name (pv:name)               | PulseCraft Vertex                                       |
| bom 4 (prodi:bom-4) | has BOM Part (pv:hasBomPart) | bom part 4 A750 6901242 (prodi:bom-part-4-A750-6901242) |
| bom 4 (prodi:bom-4) | has BOM Part (pv:hasBomPart) | bom part 4 C794 6433363 (prodi:bom-part-4-C794-6433363) |
| bom 4 (prodi:bom-4) | has BOM Part (pv:hasBomPart) | bom part 4 D605 8095260 (prodi:bom-part-4-D605-8095260) |
| bom 4 (prodi:bom-4) | has BOM Part (pv:hasBomPart) | bom part 4 F661 8988230 (prodi:bom-part-4-F661-8988230) |
| bom 4 (prodi:bom-4) | has BOM Part (pv:hasBomPart) | bom part 4 H634 7337115 (prodi:bom-part-4-H634-7337115) |
| bom 4 (prodi:bom-4) | has BOM Part (pv:hasBomPart) | bom part 4 J859 3337215 (prodi:bom-part-4-J859-3337215) |
| bom 4 (prodi:bom-4) | has BOM Part (pv:hasBomPart) | bom part 4 K926 9334427 (prodi:bom-part-4-K926-9334427) |
| ...                 | ...                          | ...                                                     |

[Assistant]
Confirmed: BoMs are of type pv:BillOfMaterial.

Now, I will write the SPARQL query to:
- Select all BoMs of type pv:BillOfMaterial.
- For each, get hardware parts and their unit costs.
- Calculate the average unit cost per BoM.
- Return the BoM with the highest average and the average value.

Here is the SPARQL query.

[Tool]
Got 1 row and 2 columns:
| bom                 | avgUnitCost     |
| ------------------- | --------------- |
| bom 8 (prodi:bom-8) | 4 (xsd:decimal) |

[Tool]
Got 8 rows and 3 columns:
| subject             | property                     | object                                                  |
| ------------------- | ---------------------------- | ------------------------------------------------------- |
| bom 8 (prodi:bom-8) | type (rdf:type)              | Bill of Material (BOM) (pv:BillOfMaterial)              |
| bom 8 (prodi:bom-8) | label (rdfs:label)           | MotoSync QuantumWave                                    |
| bom 8 (prodi:bom-8) | name (pv:name)               | MotoSync QuantumWave                                    |
| bom 8 (prodi:bom-8) | has BOM Part (pv:hasBomPart) | bom part 8 G625 4620445 (prodi:bom-part-8-G625-4620445) |
| bom 8 (prodi:bom-8) | has BOM Part (pv:hasBomPart) | bom part 8 L275 4377274 (prodi:bom-part-8-L275-4377274) |
| bom 8 (prodi:bom-8) | has BOM Part (pv:hasBomPart) | bom part 8 L781 7008508 (prodi:bom-part-8-L781-7008508) |
| bom 8 (prodi:bom-8) | has BOM Part (pv:hasBomPart) | bom part 8 W232 7656495 (prodi:bom-part-8-W232-7656495) |
| bom 8 (prodi:bom-8) | has BOM Part (pv:hasBomPart) | bom part 8 Z322 3336300 (prodi:bom-part-8-Z322-3336300) |

[Tool] Stopped generation process