Triple
T13808331
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sel municipality |
E331816
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Heidal
Heidal is a village in Innlandet county, Norway, known for its traditional wooden architecture and scenic location in the Gudbrandsdalen valley.
|
E1096211
|
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: Heidal | Statement: [Sel municipality, containsSettlement, Heidal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Heidal Context triple: [Sel municipality, containsSettlement, Heidal]
-
A.
Nissedal
Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
-
B.
Engerdal
Engerdal is a sparsely populated municipality in Innlandet county, Norway, known for its vast forests, lakes, and proximity to the Swedish border.
-
C.
Verdal
Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
-
D.
Hemsedal
Hemsedal is a Norwegian mountain village and ski resort area renowned for its alpine terrain and winter sports tourism.
-
E.
Ottosdal
Ottosdal is a small agricultural town in South Africa’s North West province, known for its grain farming and rural character.
- 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: Heidal Triple: [Sel municipality, containsSettlement, Heidal]
Generated description
Heidal is a village in Innlandet county, Norway, known for its traditional wooden architecture and scenic location in the Gudbrandsdalen valley.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Heidal Target entity description: Heidal is a village in Innlandet county, Norway, known for its traditional wooden architecture and scenic location in the Gudbrandsdalen valley.
-
A.
Nissedal
Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
-
B.
Engerdal
Engerdal is a sparsely populated municipality in Innlandet county, Norway, known for its vast forests, lakes, and proximity to the Swedish border.
-
C.
Verdal
Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
-
D.
Hemsedal
Hemsedal is a Norwegian mountain village and ski resort area renowned for its alpine terrain and winter sports tourism.
-
E.
Ottosdal
Ottosdal is a small agricultural town in South Africa’s North West province, known for its grain farming and rural character.
- 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_69d81c59f8808190a851bc56afdc55e9 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de026eae8481908b8880635e6a9152 |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd4c20e45c8190968a5d88a2b3fe37 |
completed | May 8, 2026, 2:36 a.m. |
| NEDg | Description generation | batch_69fd5067188c81908328426b8bafb6dc |
completed | May 8, 2026, 2:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd511fe3d48190af66cb10abeb7499 |
completed | May 8, 2026, 2:57 a.m. |
Created at: April 9, 2026, 10:12 p.m.