Triple
T4931256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glåmdalen |
E110699
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Glomma River |
E96298
|
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: Glomma River | Statement: [Glåmdalen, namedAfter, Glomma River]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Glomma River Context triple: [Glåmdalen, namedAfter, Glomma River]
-
A.
Glomma
chosen
Glomma is Norway’s longest and largest river, flowing through Eastern Norway before emptying into the Oslofjord.
-
B.
Drammenselva
Drammenselva is a major river in southeastern Norway known for its historical timber floating, hydroelectric power production, and salmon fishing.
-
C.
Moldeelva
Moldeelva is a river flowing through the Norwegian town of Molde, contributing to its landscape and local environment.
-
D.
Børselva
Børselva is a river in northern Norway known for flowing into Porsangerfjorden and for its scenic Arctic landscape and salmon fishing.
-
E.
Sognefjord
Sognefjord is Norway’s longest and deepest fjord, renowned for its dramatic cliffs, glacial landscapes, and scenic coastal villages.
- 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_69bd4415190c8190817bee7ec9f9f944 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd706245e48190a61d573438461c30 |
completed | March 20, 2026, 4:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be77b18b6c8190bbc8d0764f6a03bf |
completed | March 21, 2026, 10:49 a.m. |
Created at: March 20, 2026, 1:30 p.m.