Triple
T3701751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Troms |
E80793
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Finnsnes |
E315835
|
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: Finnsnes | Statement: [Troms, containsCity, Finnsnes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Finnsnes Context triple: [Troms, containsCity, Finnsnes]
-
A.
Finnsnes
chosen
Finnsnes is a small coastal town in northern Norway that serves as a commercial and transport hub for the island municipality of Senja.
-
B.
Stryn
Stryn is a municipality in Vestland county, Norway, known for its dramatic fjord and mountain landscapes, glaciers, and popular outdoor tourism activities.
-
C.
Møysalen
Møysalen is a prominent mountain in northern Norway known for its rugged alpine scenery and popular hiking routes.
-
D.
Bekkestua
Bekkestua is a suburban center in Bærum, Norway, functioning as a local commercial and transport hub just west of Oslo.
-
E.
Fagernes
Fagernes is a small town in central Norway that serves as a regional hub and gateway to the mountainous Valdres district.
- 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_69ad8b1793888190a5f70e4b21dc05a1 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adc547c1848190a1ece46c59b7c43d |
completed | March 8, 2026, 6:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5282613d0819085a47d1fffdaa4d5 |
completed | March 14, 2026, 9:19 a.m. |
Created at: March 8, 2026, 3:33 p.m.