Triple
T15800276
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | N739PA |
E383078
|
entity |
| Predicate | registrationStatusAfterAccident |
P120116
|
FINISHED |
| Object | cancelled |
—
|
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: cancelled | Statement: [N739PA, registrationStatusAfterAccident, cancelled]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: registrationStatusAfterAccident Context triple: [N739PA, registrationStatusAfterAccident, cancelled]
-
A.
hasAccidentAt
Indicates that an accident involving a subject occurs at a specific location or time.
-
B.
involvedInAccident
Indicates that an entity participated in, was affected by, or was otherwise a party to a specific accident or collision event.
-
C.
resultOfAccident
Indicates that something exists or occurs as a consequence or outcome of an accident.
-
D.
residenceAfterAccident
Indicates that an entity’s place of residence following an accident is a specified location.
-
E.
hasModeOfTransportInAccident
Indicates that a specific mode of transport was involved in an accident associated with the given entity.
- 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_69d86da16e188190b89af699f1ed0bfe |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4e135b08190b736e77bac5e2bff |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e0053b847c8190945726c3ddac21cc |
completed | April 15, 2026, 9:38 p.m. |
| PDg | Predicate description generation | batch_69e00e48d49c819081afccb02f9cf18b |
completed | April 15, 2026, 10:16 p.m. |
Created at: April 10, 2026, 4:48 a.m.