Triple
T25255019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pegasus Airlines Flight 8622 |
E633143
|
entity |
| Predicate | aircraftDamage |
P158316
|
FINISHED |
| Object | substantial damage |
—
|
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: substantial damage | Statement: [Pegasus Airlines Flight 8622, aircraftDamage, substantial damage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftDamage Context triple: [Pegasus Airlines Flight 8622, aircraftDamage, substantial damage]
-
A.
aircraftImpact
Indicates that an aircraft collides with or crashes into a target or surface, causing an impact event.
-
B.
aircraftDamagedUS
Indicates that a U.S. aircraft has been damaged, typically as a result of a specific event or action.
-
C.
aircraftLossType
Indicates the manner or category of how an aircraft was lost, such as through damage, destruction, disappearance, or other loss circumstances.
-
D.
aircraftLosses
Indicates the number or occurrence of aircraft that have been destroyed, damaged beyond repair, or otherwise lost.
-
E.
survivingAircraftCount
Indicates the number of aircraft that remain operational or intact after a specified event, condition, or time period.
- 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_69e75a922ad481908f4f1f884583cb42 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f4808f350881908ebf53f883f5e5b0 |
completed | May 1, 2026, 10:29 a.m. |
| PD | Predicate disambiguation | batch_69f45d06d0388190b36ecde92013624a |
completed | May 1, 2026, 7:57 a.m. |
| PDg | Predicate description generation | batch_69f465699c9c8190ac7b4b32b782550c |
completed | May 1, 2026, 8:33 a.m. |
Created at: April 21, 2026, 1:13 p.m.