Triple
T22877895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nidelva |
E567375
|
entity |
| Predicate | hasNameInLanguage |
P15
|
FINISHED |
| Object | Nidelva (Norwegian) |
—
|
NE NERFINISHED |
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: Nidelva (Norwegian) | Statement: [Nidelva, hasNameInLanguage, Nidelva (Norwegian)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nidelva (Norwegian) Context triple: [Nidelva, hasNameInLanguage, Nidelva (Norwegian)]
-
A.
Nidelva
chosen
Nidelva is the main river flowing through Trondheim, Norway, known for its scenic bends, historic waterfront buildings, and central role in the city’s landscape.
-
B.
Nissedal
Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
-
C.
Gravdal
Gravdal is a small coastal village on the island of Vestvågøy in Norway’s Lofoten archipelago.
-
D.
Lærdal
Lærdal is a municipality in Vestland county, Norway, known for its dramatic fjord landscapes, historic wooden architecture, and the UNESCO-listed Nærøyfjord area nearby.
-
E.
Eidsvåg
Eidsvåg is a village in Møre og Romsdal county, Norway, known for its fjord-side location and role as a local service and industrial hub.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e24589d8348190b96422d13a678bc1 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17f5966c08190a9ded9b19b166112 |
completed | April 29, 2026, 3:47 a.m. |
Created at: April 17, 2026, 3:39 p.m.