Triple
T4208631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Air France Flight 447 |
E93840
|
entity |
| Predicate | impactOutcome |
P54758
|
FINISHED |
| Object | aircraft destroyed |
—
|
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: aircraft destroyed | Statement: [Air France Flight 447, impactOutcome, aircraft destroyed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOutcome Context triple: [Air France Flight 447, impactOutcome, aircraft destroyed]
-
A.
impactEvent
Indicates that one entity physically strikes or collides with another, producing a resulting effect or change.
-
B.
impactIfCompleted
Indicates the effect or consequence that will occur if the referenced task or action is fully completed.
-
C.
impactBuilding
Indicates that one entity physically collides with or strikes a building, causing an impact event.
-
D.
impactCategory
Indicates the type or domain of effect that one entity or action has on another, classifying the nature of its impact.
-
E.
initialOutcome
Indicates the result or state that first occurs at the beginning of a process, event, or interaction, before any subsequent changes or outcomes.
- 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_69b3451743608190808f41d17ccf2650 |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b34e098da881909a0cc339cc186627 |
completed | March 12, 2026, 11:36 p.m. |
| PD | Predicate disambiguation | batch_69b347efd9b08190bb50f82e4e7fe06d |
completed | March 12, 2026, 11:10 p.m. |
| PDg | Predicate description generation | batch_69b34e04ef1c81908bb34ae1cbfab1e6 |
completed | March 12, 2026, 11:36 p.m. |
Created at: March 12, 2026, 11:03 p.m.