Triple
T10086365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Shore of Maui |
E215232
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object | Paia |
E392728
|
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: Paia | Statement: [North Shore of Maui, hasTown, Paia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paia Context triple: [North Shore of Maui, hasTown, Paia]
-
A.
Paia
Paia is a small, laid-back town on Maui’s north shore known for its surf culture, bohemian vibe, and as a gateway to the Road to Hana.
-
B.
Lihue
Lihue is the county seat and main commercial center of the Hawaiian island of Kauai, known for its airport, harbor, and role as a gateway for visitors.
-
C.
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.
-
D.
Haleiwa
Haleiwa is a historic surf town on Oahu’s North Shore in Hawaii, known for its laid-back atmosphere, beaches, and local shops and eateries.
-
E.
Pāʻia
chosen
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.
- 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_69ca83a1eed081908b2e9580f2ebeea7 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd04745b48190a77c422eb76b6660 |
completed | April 2, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2b68b4dbc8190b0ada78fb29feffd |
completed | April 5, 2026, 7:22 p.m. |
Created at: March 30, 2026, 9:01 p.m.