Triple
T16784343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Homi Jehangir Bhabha |
E407931
|
entity |
| Predicate | aircraftAccident |
P124619
|
FINISHED |
| Object | Air India Flight 101 crash |
—
|
LITERAL 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: Air India Flight 101 crash | Statement: [Homi Jehangir Bhabha, aircraftAccident, Air India Flight 101 crash]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftAccident Context triple: [Homi Jehangir Bhabha, aircraftAccident, Air India Flight 101 crash]
-
A.
missionAccident
Indicates that an accident or unintended harmful event occurred during the course of a mission or operation.
-
B.
aircraftAccidentYear
Indicates the calendar year in which an aircraft accident occurred.
-
C.
aircraftImpact
Indicates that an aircraft collides with or crashes into a target or surface, causing an impact event.
-
D.
accidentAirport
Indicates the airport at which an accident involving the subject entity occurred.
-
E.
aircraftInvolvedInDeath
Indicates that an aircraft played a direct role in causing or contributing to a person's death.
- F. None of above. chosen
Provenance (4 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_69d8839270588190886720d9519bbf8f |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b21996cc81909deb88545af7079f |
completed | April 18, 2026, 4:32 p.m. |
| PD | Predicate disambiguation | batch_69e319cf691c819083e39225f5777ef0 |
completed | April 18, 2026, 5:42 a.m. |
| PDg | Predicate description generation | batch_69e326bac94481908c082117553320f8 |
completed | April 18, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:22 a.m.