Triple
T3041435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kapalua Airport |
E83138
|
entity |
| Predicate | serves |
P98
|
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: [Kapalua Airport, serves, Lahaina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lahaina Context triple: [Kapalua Airport, serves, 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.
Līhuʻe
Līhuʻe is the principal town and administrative center of Kauai County on the Hawaiian island of Kauai.
-
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.
Kahului
Kahului is a major commercial and transportation hub on the island of Maui in Hawaii, known for its harbor, airport, and retail centers.
-
E.
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.
- 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_69ad8b2298908190a7cb4e9bdbf064d0 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9b5b92088190971bed04e65c5917 |
completed | March 8, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b276d6aaec8190b741e58790c4af23 |
completed | March 12, 2026, 8:18 a.m. |
Created at: March 8, 2026, 3:01 p.m.