Triple
T3623413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colin Clive |
E76779
|
entity |
| Predicate | causeOfCareerChange |
P11376
|
FINISHED |
| Object | knee injury |
—
|
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: knee injury | Statement: [Colin Clive, causeOfCareerChange, knee injury]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causeOfCareerChange Context triple: [Colin Clive, causeOfCareerChange, knee injury]
-
A.
careerImpact
chosen
Indicates how one entity influences or changes another entity’s professional trajectory, opportunities, or outcomes.
-
B.
managedCareerOf
Indicates that one entity was responsible for overseeing, directing, or handling the professional career of another entity.
-
C.
reasonForLeaving
Indicates the cause, motivation, or circumstance that led an entity to depart or discontinue an association, position, or place.
-
D.
careerStart
Indicates the point in time when an entity begins its professional career or main occupational activity.
-
E.
businessCareer
Indicates a relationship where an entity’s professional life, roles, or progression is specifically within the field of business or commerce.
- 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_69ad85dae2fc81908d1ceadbc6af0089 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc2bc79008190abe6900adcbda8de |
completed | March 8, 2026, 6:41 p.m. |
| PD | Predicate disambiguation | batch_69adb8410a5881909c94818d7060b2b0 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:23 p.m.