Triple
T7587722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ovanåker Municipality |
E179657
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Ovanåker
Ovanåker is a locality in Gävleborg County, Sweden, known as one of the principal settlements within Ovanåker Municipality.
|
E679245
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Ovanåker | Statement: [Ovanåker Municipality, containsSettlement, Ovanåker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ovanåker Context triple: [Ovanåker Municipality, containsSettlement, Ovanåker]
-
A.
Vingåker
Vingåker is a small locality in Södermanland County, Sweden, known as the hometown of former Swedish Prime Minister Göran Persson.
-
B.
Jädraås
Jädraås is a small village in central Sweden known for its forested surroundings and historic narrow-gauge railway.
-
C.
Hovsjö
Hovsjö is a residential district in the city of Södertälje, Sweden, known for its large-scale housing estates and diverse population.
-
D.
Korsnäs
Korsnäs is a small coastal municipality in western Finland known for its Swedish-speaking majority and traditional Ostrobothnian rural culture.
-
E.
Bollnäs
Bollnäs is a small Swedish town known for its scenic lakeside setting, traditional wooden architecture, and strong bandy sports culture.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ovanåker Triple: [Ovanåker Municipality, containsSettlement, Ovanåker]
Generated description
Ovanåker is a locality in Gävleborg County, Sweden, known as one of the principal settlements within Ovanåker Municipality.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ovanåker Target entity description: Ovanåker is a locality in Gävleborg County, Sweden, known as one of the principal settlements within Ovanåker Municipality.
-
A.
Vingåker
Vingåker is a small locality in Södermanland County, Sweden, known as the hometown of former Swedish Prime Minister Göran Persson.
-
B.
Jädraås
Jädraås is a small village in central Sweden known for its forested surroundings and historic narrow-gauge railway.
-
C.
Hovsjö
Hovsjö is a residential district in the city of Södertälje, Sweden, known for its large-scale housing estates and diverse population.
-
D.
Korsnäs
Korsnäs is a small coastal municipality in western Finland known for its Swedish-speaking majority and traditional Ostrobothnian rural culture.
-
E.
Bollnäs
Bollnäs is a small Swedish town known for its scenic lakeside setting, traditional wooden architecture, and strong bandy sports culture.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c69f335248819093c1006f30513708 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f99875908190b09584cf13ea1e08 |
completed | March 27, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c89a957e2881909c7592f673bea26f |
completed | March 29, 2026, 3:20 a.m. |
| NEDg | Description generation | batch_69c89b5b42dc8190972569b510d2efcd |
completed | March 29, 2026, 3:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c89c56d9688190bd14badc319f9c44 |
completed | March 29, 2026, 3:28 a.m. |
Created at: March 27, 2026, 3:52 p.m.