Triple
T18113246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sel |
E433533
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Heidal |
—
|
NE NERFINISHED |
How this triple was built (2 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, containsSettlement, Heidal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Heidal Context triple: [Sel, containsSettlement, Heidal]
-
A.
Heidal
chosen
Heidal is a village in Innlandet county, Norway, known for its traditional wooden architecture and scenic location in the Gudbrandsdalen valley.
-
B.
Nissedal
Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
-
C.
Engerdal
Engerdal is a sparsely populated municipality in Innlandet county, Norway, known for its vast forests, lakes, and proximity to the Swedish border.
-
D.
Verdal
Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
-
E.
Hemsedal
Hemsedal is a Norwegian mountain village and ski resort area renowned for its alpine terrain and winter sports tourism.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b90916008190a1f110bd7ced5473 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddd3fd9c81909bfe95927f7553e3 |
completed | April 19, 2026, 1:51 p.m. |
Created at: April 10, 2026, 10:28 a.m.