Triple
T35673388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeremy Stephens |
E1030784
|
entity |
| Predicate | hasCareerType |
P55498
|
FINISHED |
| Object | combat sports career |
—
|
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: combat sports career | Statement: [Jeremy Stephens, hasCareerType, combat sports career]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCareerType Context triple: [Jeremy Stephens, hasCareerType, combat sports career]
-
A.
hasCareerFunction
Indicates that an entity performs, is associated with, or is responsible for a specific career-related role or function.
-
B.
hasCareerService
Indicates that an entity provides or is associated with a career-related support or advisory service for another entity.
-
C.
hasCareerStage
Indicates the specific phase or stage of a person's or entity's professional or occupational progression.
-
D.
hasCareerScope
Indicates that an entity’s career, role, or profession extends over, is relevant to, or is defined within a particular domain, field, or scope.
-
E.
careerType
chosen
Indicates the kind or category of professional occupation or career path associated with an 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_69f76e0acfc0819082c8495c2210ce73 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff9d9cb4f8819083682be3c483b599 |
completed | May 9, 2026, 8:48 p.m. |
| PD | Predicate disambiguation | batch_69ff9c38bf9c8190bbb85b32f3ae3d2e |
completed | May 9, 2026, 8:42 p.m. |
Created at: May 3, 2026, 4:05 p.m.