Triple
T1905189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hāna Highway |
E37784
|
entity |
| Predicate | hasNearbyTown |
P3883
|
FINISHED |
| Object | Paia |
E81493
|
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: [Hāna Highway, hasNearbyTown, Paia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paia Context triple: [Hāna Highway, hasNearbyTown, Paia]
-
A.
Paia
chosen
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.
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.
-
C.
Kahului
Kahului is a major commercial and transportation hub on the island of Maui in Hawaii, known for its harbor, airport, and retail centers.
-
D.
Hilo
Hilo is a major town on the Big Island of Hawaii known for its lush rainforests, waterfalls, and role as a regional cultural and economic center.
-
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_69a8861be7148190a680937ec451a304 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb191b710819091a5b767550fcf61 |
completed | March 7, 2026, 5:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae7edf084881908bb8db8e0348bfc8 |
completed | March 9, 2026, 8:03 a.m. |
Created at: March 4, 2026, 7:35 p.m.