Triple
T15885078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lærdal |
E385170
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Hemsedal |
E453351
|
NE FINISHED |
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: Hemsedal | Statement: [Lærdal, borderedBy, Hemsedal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hemsedal Context triple: [Lærdal, borderedBy, Hemsedal]
-
A.
Hemsedal
chosen
Hemsedal is a Norwegian mountain village and ski resort area renowned for its alpine terrain and winter sports tourism.
-
B.
Nissedal
Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
-
C.
Heidal
Heidal is a village in Innlandet county, Norway, known for its traditional wooden architecture and scenic location in the Gudbrandsdalen valley.
-
D.
Engerdal
Engerdal is a sparsely populated municipality in Innlandet county, Norway, known for its vast forests, lakes, and proximity to the Swedish border.
-
E.
Valldal
Valldal is a village in western Norway known for its scenic fjord landscape and strawberry farming, situated in the county of Møre og Romsdal.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d86da5b800819083a31be937d738b0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1561997bc8190a40e7d68defbbddd |
completed | April 16, 2026, 9:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0313aa65a481909707b1e7a6d6ce6f |
completed | May 12, 2026, 11:48 a.m. |
Created at: April 10, 2026, 4:51 a.m.