Triple
T36794884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aires Flight 8250 |
E909155
|
entity |
| Predicate | aircraftBreakup |
P158004
|
FINISHED |
| Object | fuselage broke into pieces |
—
|
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: fuselage broke into pieces | Statement: [Aires Flight 8250, aircraftBreakup, fuselage broke into pieces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftBreakup Context triple: [Aires Flight 8250, aircraftBreakup, fuselage broke into pieces]
-
A.
aircraftAccident
Indicates that an event involves an aircraft experiencing an accident, such as a crash, collision, or serious malfunction during operation.
-
B.
missionAccident
Indicates that an accident or unintended harmful event occurred during the course of a mission or operation.
-
C.
fuselageBreakup
chosen
Indicates that an aircraft’s fuselage has structurally broken apart, either in flight or during an accident sequence.
-
D.
airCrashDate
Indicates the date on which an air crash (aviation accident) occurred.
-
E.
aircraftInvolvedInDeath
Indicates that an aircraft played a direct role in causing or contributing to a person's 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_69f76e7b98888190899b6478a82ad6ae |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7ca93bd0481909d6eee9e950001a1 |
completed | May 3, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69f7c89b528c8190bf80b230fc7c7108 |
completed | May 3, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:12 p.m.