Triple
T35805406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Batista vs Triple H |
E1035089
|
entity |
| Predicate | turningPointForCareer |
P11376
|
FINISHED |
| Object | Batista main-event push |
—
|
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: Batista main-event push | Statement: [Batista vs Triple H, turningPointForCareer, Batista main-event push]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: turningPointForCareer Context triple: [Batista vs Triple H, turningPointForCareer, Batista main-event push]
-
A.
placeInCareer
Indicates the specific role, position, or stage an entity occupies within a person’s professional career.
-
B.
careerImpact
chosen
Indicates how one entity influences or changes another entity’s professional trajectory, opportunities, or outcomes.
-
C.
settingOfCareer
Indicates the primary environment, context, or domain in which a person’s career takes place or is situated.
-
D.
managedCareerOf
Indicates that one entity was responsible for overseeing, directing, or handling the professional career of another entity.
-
E.
careerDevelopment
Indicates a relationship where one entity supports, influences, or engages in the growth, progression, or improvement of another entity’s professional path or skills.
- 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_69f76e169bd081909f16cd8c9ee7870c |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7aa699d68819081ed363931894ab3 |
completed | May 3, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69f7a8d219f8819081dc4ce3c83ca0cb |
completed | May 3, 2026, 7:58 p.m. |
Created at: May 3, 2026, 4:06 p.m.