Triple
T27546575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Island Express Helicopters |
E695377
|
entity |
| Predicate | accidentNotableVictim |
P19083
|
FINISHED |
| Object | Gianna Bryant |
—
|
NE NERFINISHED |
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: Gianna Bryant | Statement: [Island Express Helicopters, accidentNotableVictim, Gianna Bryant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: accidentNotableVictim Context triple: [Island Express Helicopters, accidentNotableVictim, Gianna Bryant]
-
A.
notableVictim
Indicates that the subject is a person or entity who is notably recognized as a victim of the object (such as an event, crime, or harmful action).
-
B.
notablePersonKilledThere
Indicates that a notable or famous person was killed at the referenced location.
-
C.
notableVictims
chosen
Indicates that the object is a person or group who is especially well-known or significant as a victim of the subject.
-
D.
notableAccidentYear
Indicates the year in which a notable accident involving the subject occurred.
-
E.
fatalAccident
Indicates that an accident resulted in at least one death.
- F. None of above.
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_69ef5386c3e08190bfe33aa326e1f72b |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69f6359e3d3c81909814e2f0a7fb0ea9 |
completed | May 2, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f631871c888190bf29466fe4254e51 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 1:33 p.m.