Triple
T18132126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seljordsvatnet |
E434038
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Seljord |
—
|
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: Seljord | Statement: [Seljordsvatnet, locatedIn, Seljord]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seljord Context triple: [Seljordsvatnet, locatedIn, Seljord]
-
A.
Seljord
chosen
Seljord is a small Norwegian town known for its scenic lake, traditional cultural events, and the local legend of the Seljord Lake serpent.
-
B.
Selje
Selje is a small coastal village and former municipality in western Norway, known for its scenic fjord landscape and the historic Selja Monastery ruins.
-
C.
Suldal
Suldal is a large rural municipality in southwestern Norway known for its fjords, mountains, and hydroelectric power production.
-
D.
Nissedal
Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
-
E.
Ottosdal
Ottosdal is a small agricultural town in South Africa’s North West province, known for its grain farming and rural character.
- 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_69d8b909e8cc81908df4cc2b8ea6d11f |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddf2c68881909dfbe59df15ddccc |
completed | April 19, 2026, 1:51 p.m. |
Created at: April 10, 2026, 10:29 a.m.