Triple
T4351528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hōkūleʻa |
E98036
|
entity |
| Predicate | navalArchitect |
P17956
|
FINISHED |
| Object | Herb Kane |
E433355
|
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: Herb Kane | Statement: [Hōkūleʻa, navalArchitect, Herb Kane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Herb Kane Context triple: [Hōkūleʻa, navalArchitect, Herb Kane]
-
A.
Herb Kane
chosen
Herb Kane was a Native Hawaiian artist, historian, and cultural leader renowned for reviving traditional Polynesian navigation and canoe voyaging.
-
B.
Gerald Hagey
Gerald Hagey was a Canadian academic and administrator best known as the founding president who led the development of the University of Waterloo into a major institution.
-
C.
Ed Shaughnessy
Ed Shaughnessy was an American jazz drummer best known for his long tenure with Doc Severinsen’s band on The Tonight Show Starring Johnny Carson.
-
D.
Ted Cheesman
Ted Cheesman was a film editor best known for his work on classic Hollywood productions, including the 1933 monster film "King Kong."
-
E.
Hugh Kaul
Hugh Kaul was a prominent Birmingham, Alabama businessman and philanthropist known for his significant support of the arts and cultural institutions.
- 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_69b3454965f881908c41190bb22f0e4b |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b351a99788819080b13a20124e49a0 |
completed | March 12, 2026, 11:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5f5d00e20819095114787f95e3858 |
completed | March 14, 2026, 11:57 p.m. |
Created at: March 12, 2026, 11:15 p.m.