Triple
T15693603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bømlafjord Tunnel |
E380397
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Stord |
—
|
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: Stord | Statement: [Bømlafjord Tunnel, locatedNear, Stord]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stord Context triple: [Bømlafjord Tunnel, locatedNear, Stord]
-
A.
Stord
chosen
Stord is a large island and municipality in Vestland county, western Norway, known for its industrial activity and location along major fjords and shipping routes.
-
B.
Sandefjord
Sandefjord is a coastal town and municipality in southern Norway known for its maritime heritage, whaling history, and popular seaside attractions.
-
C.
Knarvik
Knarvik is a village in Vestland county, Norway, known as a local commercial and service hub just north of Bergen.
-
D.
Melbu
Melbu is a small coastal village and fishing community in Hadsel Municipality in Nordland county, Norway.
-
E.
Lyngdal
Lyngdal is a coastal town and municipality in southern Norway known for its beaches, fjords, and 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_69d86d99e860819094b6957cde470f2c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f4f5a888190bd3681bcb9bbc02f |
completed | April 16, 2026, 2:54 a.m. |
Created at: April 10, 2026, 4:44 a.m.