Triple
T25015684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lawrence Neil Bonnett |
E626122
|
entity |
| Predicate | majorInjuryTrack |
P164772
|
FINISHED |
| Object | Darlington Raceway |
—
|
NE NERFINISHED |
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: Darlington Raceway | Statement: [Lawrence Neil Bonnett, majorInjuryTrack, Darlington Raceway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorInjuryTrack Context triple: [Lawrence Neil Bonnett, majorInjuryTrack, Darlington Raceway]
-
A.
injuredIn
Indicates that an entity sustained an injury as a result of a specified event, situation, or action.
-
B.
injuryPlotPoint
Indicates that an event in the narrative involves a character being injured, serving as a significant plot development or turning point.
-
C.
injuryStatus
Indicates the condition or state of harm, damage, or physical injury affecting an entity.
-
D.
injuryType
Indicates the specific kind or category of injury associated with an entity or event.
-
E.
hasInjuries
Indicates that an entity has sustained one or more physical or bodily injuries.
- 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_69e2ff27755881908490178e83701160 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f650fc44e48190bc0e0a935eac62a6 |
completed | May 2, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69f64cab1f648190a2a9460690d18a37 |
completed | May 2, 2026, 7:12 p.m. |
| PDg | Predicate description generation | batch_69f650c466b881908954e43bfebae8a4 |
completed | May 2, 2026, 7:30 p.m. |
Created at: April 18, 2026, 6:06 a.m.