Triple
T5435565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Office of Highway Safety |
E121998
|
entity |
| Predicate | typeOfAccidentsInvestigated |
P11082
|
FINISHED |
| Object | passenger vehicle crashes |
—
|
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: passenger vehicle crashes | Statement: [Office of Highway Safety, typeOfAccidentsInvestigated, passenger vehicle crashes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfAccidentsInvestigated Context triple: [Office of Highway Safety, typeOfAccidentsInvestigated, passenger vehicle crashes]
-
A.
accidentType
Indicates the specific category or kind of accident associated with an event or incident.
-
B.
resultOfAccident
Indicates that something exists or occurs as a consequence or outcome of an accident.
-
C.
investigatedEvent
Indicates that an event was the subject of an investigation or inquiry carried out by some agent.
-
D.
typeOfInvestigation
chosen
Indicates the specific kind or category of investigation being conducted or referred to in the relationship.
-
E.
accident
Indicates an unintended, unforeseen event or mishap occurring, often resulting in damage, injury, or disruption.
- 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_69bd46400768819092925d461c0b8432 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd922f66bc8190b7d47fd68d2fcf2e |
completed | March 20, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69bd919aeb048190b786f814177d6cd9 |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:06 p.m.