Triple
T18126135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tysfjord municipality |
E433879
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Drag |
—
|
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: Drag | Statement: [Tysfjord municipality, hasSettlement, Drag]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Drag Context triple: [Tysfjord municipality, hasSettlement, Drag]
-
A.
Drag
chosen
Drag is a small coastal village in Nordland county, Norway, known for its scenic fjord-side location and proximity to the Tysfjord.
-
B.
Drag
Drag is a 1997 studio album by k.d. lang featuring smoky, lounge-influenced covers themed around addiction and dependency.
-
C.
Drag-On
Drag-On is an American rapper best known for his work with DMX and the Ruff Ryders collective in the late 1990s and early 2000s.
-
D.
The Drag
The Drag is a narrow, winding canyon-like district in Orgrimmar that serves as a central thoroughfare connecting several of the city's major quarters.
-
E.
Grab
Grab is a Southeast Asian super-app company best known for its ride-hailing, food delivery, and digital payments services.
- 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_69e4ddee1efc8190b04324b98de5c9d0 |
completed | April 19, 2026, 1:51 p.m. |
Created at: April 10, 2026, 10:29 a.m.