Triple
T15769310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sugar Beach (Kihei, Maui) |
E382308
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Kihei |
E80823
|
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: Kihei | Statement: [Sugar Beach (Kihei, Maui), locatedIn, Kihei]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kihei Context triple: [Sugar Beach (Kihei, Maui), locatedIn, Kihei]
-
A.
Kihei
chosen
Kihei is a coastal town on the southwest shore of Maui, Hawaii, known for its sunny weather, beaches, and resort and residential communities.
-
B.
Kapalua
Kapalua is a resort community on the northwest coast of Maui, Hawaii, known for its luxury accommodations, golf courses, and scenic beaches.
-
C.
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.
-
D.
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.
-
E.
Kailua-Kona
Kailua-Kona is a coastal town on the west side of Hawaii's Big Island known for its sunny beaches, historic sites, coffee farms, and role as a major tourist and commercial 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_69d86da09a10819082fe9797b23e4664 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e051962fe08190a6201dd48196a9ee |
completed | April 16, 2026, 3:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01673979608190905afae3071413c0 |
completed | May 11, 2026, 5:20 a.m. |
Created at: April 10, 2026, 4:47 a.m.