Triple
T24541064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drew Bledsoe |
E607091
|
entity |
| Predicate | injuryLedToStartingOpportunityFor |
P156659
|
FINISHED |
| Object | Tom Brady |
—
|
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: Tom Brady | Statement: [Drew Bledsoe, injuryLedToStartingOpportunityFor, Tom Brady]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: injuryLedToStartingOpportunityFor Context triple: [Drew Bledsoe, injuryLedToStartingOpportunityFor, Tom Brady]
-
A.
injuryEndedCareer
Indicates that an injury caused the permanent end of an entity’s professional career.
-
B.
injuredIn
Indicates that an entity sustained an injury as a result of a specified event, situation, or action.
-
C.
causeOfInjury
Indicates that one entity is the source or reason that another entity sustained an injury.
-
D.
injuryYear
Indicates the year in which an injury occurred or was recorded for the entity.
-
E.
injuryPlotPoint
Indicates that an event in the narrative involves a character being injured, serving as a significant plot development or turning point.
- 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_69e2c4c9bf94819082d05da6f5c29907 |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6b0ca8081908d931aec560eae56 |
completed | April 30, 2026, 12:47 a.m. |
| PDg | Predicate description generation | batch_69f2b8b8bc5881908df49c0b07110246 |
completed | April 30, 2026, 2:04 a.m. |
Created at: April 18, 2026, 2:26 a.m.