Triple
T6303265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keahiakawelo |
E141306
|
entity |
| Predicate | hasNearbySettlement |
P4647
|
FINISHED |
| Object | Lānaʻi City |
E26082
|
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: Lānaʻi City | Statement: [Keahiakawelo, hasNearbySettlement, Lānaʻi City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lānaʻi City Context triple: [Keahiakawelo, hasNearbySettlement, Lānaʻi City]
-
A.
Hāna
Hāna is a small, remote town on the eastern coast of Maui, Hawaii, known for its lush landscapes, scenic coastal views, and the famously winding Road to Hāna.
-
B.
Lānaʻi
chosen
Lānaʻi is one of the smaller inhabited Hawaiian Islands, known for its quiet, rural character and luxury resort tourism.
-
C.
Wailea
Wailea is a luxury resort community on the south shore of Maui, Hawaii, known for its upscale hotels, golf courses, and beautiful beaches.
-
D.
Pāʻia
Pāʻia is a small, laid-back town on Maui’s north shore in Hawaii, known for its surf culture, bohemian vibe, and proximity to popular windsurfing and kitesurfing beaches.
-
E.
Wailuku
Wailuku is a historic town on the Hawaiian island of Maui that serves as the county seat and a cultural and administrative 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_69c008cf0ad4819095def81e2bd42f9f |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0645e150881908b49a07914dcbfd8 |
completed | March 22, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c5e43e085081908546fa120a43bf84 |
completed | March 27, 2026, 1:58 a.m. |
Created at: March 22, 2026, 4:27 p.m.