Triple
T13441205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Napili |
E320364
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Lahaina |
E80373
|
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: Lahaina | Statement: [Napili, near, Lahaina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lahaina Context triple: [Napili, near, Lahaina]
-
A.
Lahaina
chosen
Lahaina is a historic coastal town on the Hawaiian island of Maui, formerly a whaling hub and royal capital, now known for its tourism and cultural significance.
-
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.
Līhuʻe
Līhuʻe is the principal town and administrative center of Kauai County on the Hawaiian island of Kauai.
-
D.
Kalaheo
Kalaheo is a small residential community on the island of Kauai in Hawaii, known for its hillside neighborhoods, coffee farms, and views over the island’s south shore.
-
E.
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.
- 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_69d80761e6cc8190a90c844589998ecc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaee704ac8190b4c7f4e0d3a88494 |
completed | April 12, 2026, 2:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff8752207c81908369bce03b56b25e |
completed | May 9, 2026, 7:13 p.m. |
Created at: April 9, 2026, 9:40 p.m.