Triple
T20659118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tinnelva |
E507708
|
entity |
| Predicate | flowsFrom |
P17870
|
FINISHED |
| Object | Tinnsjå |
—
|
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: Tinnsjå | Statement: [Tinnelva, flowsFrom, Tinnsjå]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tinnsjå Context triple: [Tinnelva, flowsFrom, Tinnsjå]
-
A.
Tinnsjå
chosen
Tinnsjå is a deep, mountainous lake in Telemark, Norway, known for its dramatic scenery and historical significance, including its role in World War II.
-
B.
Glåma
Glåma is the longest and largest river in Norway, flowing through eastern parts of the country before emptying into the Oslofjord.
-
C.
Sørreisa
Sørreisa is a small coastal municipality and village area in northern Norway known for its fjords and rural Arctic landscape.
-
D.
Verdalsøra
Verdalsøra is a small town in Trøndelag county, Norway, known for its riverside setting and role as a local commercial and service hub.
-
E.
Stryn
Stryn is a municipality in Vestland county, Norway, known for its dramatic fjord and mountain landscapes, glaciers, and popular outdoor tourism activities.
- 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_69e0b4bf58c081908e52a4500e03ff83 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b2eff7a88190be0bdea227616e02 |
completed | April 20, 2026, 11:12 p.m. |
Created at: April 16, 2026, 11:43 a.m.