Triple
T5290765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SJ Norge |
E119734
|
entity |
| Predicate | serviceArea |
P82
|
FINISHED |
| Object | Møre og Romsdal |
E114915
|
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: Møre og Romsdal | Statement: [SJ Norge, serviceArea, Møre og Romsdal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Møre og Romsdal Context triple: [SJ Norge, serviceArea, Møre og Romsdal]
-
A.
Møre og Romsdal
chosen
Møre og Romsdal is a coastal county in western Norway known for its dramatic fjords, islands, and mountainous landscapes.
-
B.
Sogn og Fjordane
Sogn og Fjordane was a former county in western Norway known for its dramatic fjords, mountains, and coastal landscapes.
-
C.
Rogaland
Rogaland is a county in southwestern Norway known for its rugged coastline, fjords, and the oil industry centered around the city of Stavanger.
-
D.
Hordaland
Hordaland was a former county in western Norway known for its fjords, coastal landscapes, and the city of Bergen.
-
E.
Trøndelag
Trøndelag is a central region of Norway known for its historic city of Trondheim, coastal landscapes, and strong cultural traditions.
- 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_69bd84eac7b88190900142bd1310c0fd |
completed | March 20, 2026, 5:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bfdeb0d0cc8190a16b8dcff2658bbf |
completed | March 22, 2026, 12:21 p.m. |
Created at: March 20, 2026, 1:52 p.m.