Triple
T3701505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harstad |
E78588
|
entity |
| Predicate | formerCounty |
P1069
|
FINISHED |
| Object | Troms |
E80793
|
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: Troms | Statement: [Harstad, formerCounty, Troms]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Troms Context triple: [Harstad, formerCounty, Troms]
-
A.
Troms
chosen
Troms was a former county in northern Norway known for its Arctic landscapes, coastal fjords, and the city of Tromsø.
-
B.
Volda
Volda is a municipality in Møre og Romsdal county, Norway, known for its fjord landscape, cultural life, and Volda University College.
-
C.
Tjøme
Tjøme is a scenic island and former municipality in Vestfold, Norway, known for its coastal landscapes, summer cabins, and popular seaside recreation areas.
-
D.
Giske
Giske is a coastal municipality in Møre og Romsdal county, Norway, known for its islands, fishing communities, and proximity to the town of Ålesund.
-
E.
Røst
Røst is a small, remote island and fishing community in northern Norway, known for its dramatic coastal scenery, rich seabird colonies, and traditional cod fisheries.
- 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_69ad85e3b1888190abc983e06968696d |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc547c1848190a1ece46c59b7c43d |
completed | March 8, 2026, 6:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4cdf1b16081909b18af630d0b4817 |
completed | March 14, 2026, 2:54 a.m. |
Created at: March 8, 2026, 3:26 p.m.