Triple
T13768644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tjeldsund |
E330816
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object | Ofoten |
E322908
|
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: Ofoten | Statement: [Tjeldsund, region, Ofoten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ofoten Context triple: [Tjeldsund, region, Ofoten]
-
A.
Ofoten
chosen
Ofoten is a district in Nordland county in northern Norway, known for its fjords, mountains, and the port town of Narvik.
-
B.
Notodden
Notodden is a town and municipality in Vestfold og Telemark county, Norway, known for its industrial heritage and annual blues festival.
-
C.
Naustdal
Naustdal is a small coastal village and former municipality in Vestland county, western Norway, known for its fjord landscape and salmon-rich Nausta River.
-
D.
Trysil
Trysil is a Norwegian municipality renowned for its large alpine ski resort and extensive outdoor recreation opportunities.
-
E.
Raufoss
Raufoss is an industrial town in Norway known for its manufacturing sector, particularly in defense and automotive components.
- 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_69d81c583b0081909e408a17db517a21 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0233ecc48190b934f085d2501eb1 |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c6fe88348190aa9803f7d6d67023 |
completed | May 3, 2026, 10:06 p.m. |
Created at: April 9, 2026, 10:10 p.m.