Triple
T27546737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ara Zobayan |
E695382
|
entity |
| Predicate | aircraftTypeFlownInAccident |
P1523
|
FINISHED |
| Object | Sikorsky S-76B |
—
|
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: Sikorsky S-76B | Statement: [Ara Zobayan, aircraftTypeFlownInAccident, Sikorsky S-76B]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftTypeFlownInAccident Context triple: [Ara Zobayan, aircraftTypeFlownInAccident, Sikorsky S-76B]
-
A.
aircraftType
Indicates the specific model or category of aircraft associated with an entity or event.
-
B.
aircraftTypesUsedOn
Indicates the types or models of aircraft that are used on or assigned to a particular route, service, operation, or context.
-
C.
aircraftFlown
chosen
Indicates that an entity (typically a person or organization) operates or pilots a particular aircraft.
-
D.
aircraftInvolvedInDeath
Indicates that an aircraft played a direct role in causing or contributing to a person's death.
-
E.
aircraftTypesOperated
Indicates the types or models of aircraft that an entity (such as an airline or operator) uses or operates.
- 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_69f65a6c900881908f18b61273d7bf8d |
completed | May 2, 2026, 8:11 p.m. |
| PD | Predicate disambiguation | batch_69f659ce58408190ba9e007b4810d4d0 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 27, 2026, 1:33 p.m.