Triple
T2321300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Askim |
E51185
|
entity |
| Predicate | locatedOn |
P40
|
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: [Askim, locatedOn, Glomma river]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Glomma river Context triple: [Askim, locatedOn, 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.
Sognefjord
Sognefjord is Norway’s longest and deepest fjord, renowned for its dramatic cliffs, glacial landscapes, and scenic coastal villages.
-
D.
Lysakerelva
Lysakerelva is a river in the Oslo area of Norway that forms part of the boundary between the municipalities of Oslo and Bærum and is known for its waterfalls, hiking paths, and historical industrial sites.
-
E.
Nordre Ål
Nordre Ål is a residential district in the town of Lillehammer in Innlandet county, Norway.
- 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_69a88b074b908190ae983dbca7757d88 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc6337e948190bb4860f7045914e1 |
completed | March 7, 2026, 6:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae896911908190b53954dbf854cc18 |
completed | March 9, 2026, 8:48 a.m. |
Created at: March 4, 2026, 7:49 p.m.