Triple
T5291390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ullevaal |
E119748
|
entity |
| Predicate | nearbyFeature |
P2064
|
FINISHED |
| Object | Sogn area |
E363655
|
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: Sogn area | Statement: [Ullevaal, nearbyFeature, Sogn area]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sogn area Context triple: [Ullevaal, nearbyFeature, Sogn area]
-
A.
Sogn region
chosen
The Sogn region is a traditional district in western Norway known for its dramatic fjord landscapes, including the famous Sognefjord, and its rich cultural and historical heritage.
-
B.
Vadheimsfjorden area
The Vadheimsfjorden area is a deep fjord region in western Norway, known as the location of the greatest depths of the Sognefjord.
-
C.
Setesdal region
The Setesdal region is a traditional valley area in southern Norway known for its distinctive folk culture, music, and well-preserved rural landscapes.
-
D.
Kvænangen
Kvænangen is a fjord in northern Norway known for its dramatic coastal scenery, rich marine life, and traditional fishing communities.
-
E.
Vendsyssel
Vendsyssel is a region in northern Denmark forming the northernmost part of the Jutland peninsula, known for its coastal landscapes and rural towns.
- 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_69bd446de5648190b313a90bd96730d2 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd84eccac481908ba3fe28c3908d1d |
completed | March 20, 2026, 5:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf06f066988190a3df7e270df84fdd |
completed | March 21, 2026, 9 p.m. |
Created at: March 20, 2026, 1:52 p.m.