Triple
T4776471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tony Boselli |
E106059
|
entity |
| Predicate | careerEndReason |
P15987
|
FINISHED |
| Object | injuries |
—
|
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: injuries | Statement: [Tony Boselli, careerEndReason, injuries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: careerEndReason Context triple: [Tony Boselli, careerEndReason, injuries]
-
A.
typeOfOccupationEnded
Indicates that a particular type of occupation or job role has come to an end for an entity.
-
B.
reasonForLeaving
chosen
Indicates the cause, motivation, or circumstance that led an entity to depart or discontinue an association, position, or place.
-
C.
collegeCareerEnd
Indicates the point or event at which an individual's college-level athletic or academic career concludes.
-
D.
hadOccupationStatusUntil
Indicates that an entity held a particular occupational status up to, but not necessarily beyond, a specified point in time.
-
E.
careerStatus
Indicates the current stage, position, or condition of an entity within its professional or occupational life.
- 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_69bd43f3074c8190937e7b0a457fe9f1 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd69237f80819090713ed62653fb75 |
completed | March 20, 2026, 3:34 p.m. |
| PD | Predicate disambiguation | batch_69bd622be1388190ab5511b589c878c0 |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:21 p.m.