Triple
T15332185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loen valley |
E366561
|
entity |
| Predicate | hasNearbyTown |
P3883
|
FINISHED |
| Object | Stryn |
E375474
|
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: Stryn | Statement: [Loen valley, hasNearbyTown, Stryn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stryn Context triple: [Loen valley, hasNearbyTown, Stryn]
-
A.
Stryn
chosen
Stryn is a municipality in Vestland county, Norway, known for its dramatic fjord and mountain landscapes, glaciers, and popular outdoor tourism activities.
-
B.
Sørreisa
Sørreisa is a small coastal municipality and village area in northern Norway known for its fjords and rural Arctic landscape.
-
C.
Vennesla
Vennesla is a municipality in Agder county in southern Norway, known for its industrial heritage and scenic river valley setting.
-
D.
Nissedal
Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
-
E.
Sørenga
Sørenga is a modern waterfront neighborhood in Oslo, Norway, known for its residential developments, seaside promenade, and popular public seawater pool and beach.
- 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_69d85a121520819093dcce999fdefe1a |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e0268608190947a58f559a67717 |
completed | April 16, 2026, 1:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff82e1b698819098930596327340d7 |
completed | May 9, 2026, 6:54 p.m. |
Created at: April 10, 2026, 3:17 a.m.