Triple
T1029249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jason Varitek |
E22211
|
entity |
| Predicate | postPlayingRole |
P24180
|
FINISHED |
| Object | coach |
—
|
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: coach | Statement: [Jason Varitek, postPlayingRole, coach]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: postPlayingRole Context triple: [Jason Varitek, postPlayingRole, coach]
-
A.
playedRoleIn
Indicates that an entity performed or assumed a specific role or character within a particular event, production, or context.
-
B.
playedKeyRoleIn
Indicates that an entity had a major, influential, or decisive impact on the occurrence, outcome, or success of another entity or event.
-
C.
plannedRole
Indicates that an entity is expected or intended to assume a particular role or function in a planned or future context.
-
D.
actingRoleType
Indicates the specific type or category of role an entity performs when acting in a particular capacity or function.
-
E.
dramaticRole
Indicates that one entity serves as a character or part played by another entity within a dramatic or theatrical work.
- 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_69a493d848848190aed4011b34b2e8d3 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b95d35888190a20593a278175df7 |
completed | March 1, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69a4b7276180819085c6b23501a6a6e0 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b95bb5908190ad1d5f5e0d8f664d |
completed | March 1, 2026, 10:10 p.m. |
Created at: March 1, 2026, 7:41 p.m.