Triple
T625650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maui |
E15811
|
entity |
| Predicate | hasCulturalRegion |
P1968
|
FINISHED |
| Object | Hana |
E100137
|
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: Hana | Statement: [Maui, hasCulturalRegion, Hana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hana Context triple: [Maui, hasCulturalRegion, Hana]
-
A.
Hana
chosen
Hana is a small, remote town on the eastern coast of Maui, Hawaii, known for its lush landscapes, waterfalls, and the scenic Road to Hana.
-
B.
Hana
Hana is a compassionate Canadian army nurse in Michael Ondaatje's novel "The English Patient," who cares for a badly burned man in an abandoned Italian villa during World War II.
-
C.
Haya
Haya is a feminine given name of Arabic origin, commonly used in the Middle East and among Arabic-speaking communities.
-
D.
Minna
Minna is a major city and administrative center in north-central Nigeria, known as the capital of Niger State and a regional hub for trade and transportation.
-
E.
Michiko
Michiko is the former Empress of Japan and the wife of Emperor Emeritus Akihito, known for being the first commoner to marry into the Japanese imperial family.
- 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_69a4935c131c8190a5378c6bf101e8cc |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49e574444819087999404f3e3ffd9 |
completed | March 1, 2026, 8:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7a3a48ac88190bea34fc7df8b503e |
completed | March 4, 2026, 3:14 a.m. |
Created at: March 1, 2026, 7:35 p.m.