Triple
T18950849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EBR-I |
E463643
|
entity |
| Predicate | safetyIncidentType |
P1788
|
FINISHED |
| Object | power excursion accident |
—
|
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: power excursion accident | Statement: [EBR-I, safetyIncidentType, power excursion accident]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyIncidentType Context triple: [EBR-I, safetyIncidentType, power excursion accident]
-
A.
accidentType
chosen
Indicates the specific category or kind of accident associated with an event or incident.
-
B.
hazardType
Indicates the specific kind or category of hazard associated with an entity or situation.
-
C.
notableIncidentType
Indicates the specific category or kind of significant event or incident associated with an entity.
-
D.
situationType
Indicates the general kind or category of situation, event, or circumstance that a given instance represents.
-
E.
safetyCategory
Indicates the classification of something according to its level or type of safety.
- 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_69d8dcffc278819086792a4ebfddfafa |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d542b238819089ccd2df279a2f7f |
completed | April 20, 2026, 7:26 a.m. |
| PD | Predicate disambiguation | batch_69e4a2efec5c8190840704016bf547a1 |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, noon