Triple
T25466195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stephan Fox |
E638180
|
entity |
| Predicate | hasFormerCareer |
P107616
|
FINISHED |
| Object | professional Muay Thai competition |
—
|
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: professional Muay Thai competition | Statement: [Stephan Fox, hasFormerCareer, professional Muay Thai competition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFormerCareer Context triple: [Stephan Fox, hasFormerCareer, professional Muay Thai competition]
-
A.
hasPastOccupation
chosen
Indicates that an entity previously held a particular job, role, or occupation in the past.
-
B.
characterFormerOccupation
Indicates that a character previously held a specific occupation but no longer does.
-
C.
hasFormerTeam
Indicates that an entity was previously a member of, played for, or was affiliated with a team in the past but is no longer associated with that team.
-
D.
hasCareerStage
Indicates the specific phase or stage of a person's or entity's professional or occupational progression.
-
E.
earlierOccupation
Indicates that one occupation held by an entity occurred before another occupation in that entity’s work history.
- 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_69e75db8bab08190baca80b4a8c315fd |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f65f7731e4819099d5bd3d915ee266 |
completed | May 2, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f65c1f94ac8190bc6fbc7916fc0d82 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 21, 2026, 2:14 p.m.