Triple
T6928444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kauai County |
E160370
|
entity |
| Predicate | hasIsland |
P970
|
FINISHED |
| Object | Niihau |
E654649
|
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: Niihau | Statement: [Kauai County, hasIsland, Niihau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Niihau Context triple: [Kauai County, hasIsland, Niihau]
-
A.
Niihau
chosen
Niihau is a privately owned, sparsely populated Hawaiian island known for its restricted access, preservation of traditional Native Hawaiian culture, and nickname “the Forbidden Isle.”
-
B.
Kaluahi
Kaluahi is a town located in the Madhubani district of the Indian state of Bihar.
-
C.
Nānākuli
Nānākuli is a coastal community on the leeward side of Oʻahu in Hawaii, known for its strong Native Hawaiian presence and scenic beaches.
-
D.
Holualoa
Holualoa is a small, historic coffee-farming village located on the slopes above Kailua-Kona on the Big Island of Hawaii.
-
E.
Kailua-Kona
Kailua-Kona is a coastal town on the west side of Hawaii's Big Island known for its sunny beaches, historic sites, coffee farms, and role as a major tourist and commercial center.
- 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_69c6884d350081908d8a970e4d40ad78 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6da1de28881908579bc198e74203e |
completed | March 27, 2026, 7:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7eeb79b9c819084738c207aa5c62d |
completed | March 28, 2026, 3:07 p.m. |
Created at: March 27, 2026, 2:27 p.m.