Triple
T195056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul Pierce |
E3799
|
entity |
| Predicate | postRetirementOccupation |
P2374
|
FINISHED |
| Object | basketball analyst |
—
|
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: basketball analyst | Statement: [Paul Pierce, postRetirementOccupation, basketball analyst]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: postRetirementOccupation Context triple: [Paul Pierce, postRetirementOccupation, basketball analyst]
-
A.
retired
Indicates that an entity has permanently stopped working in their former occupation or role, typically after reaching a certain age or service duration.
-
B.
retiredFrom
Indicates that an entity has permanently stopped working for or being active in a specified organization, role, or activity.
-
C.
subjectOccupation
chosen
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
D.
hadOccupationStatusUntil
Indicates that an entity held a particular occupational status up to, but not necessarily beyond, a specified point in time.
-
E.
sponsorOccupation
Indicates that one entity serves as the occupation or professional role of a sponsor associated with another entity.
- 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_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a25969425081908e178db8ba4631c2 |
completed | Feb. 28, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69a25677da14819094cd02868fd30c83 |
completed | Feb. 28, 2026, 2:44 a.m. |
Created at: Feb. 28, 2026, 2:41 a.m.