Triple
T26655191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joel Casamayor |
E666475
|
entity |
| Predicate | professionalCareer |
P165048
|
FINISHED |
| Object | world champion at super featherweight |
—
|
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: world champion at super featherweight | Statement: [Joel Casamayor, professionalCareer, world champion at super featherweight]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionalCareer Context triple: [Joel Casamayor, professionalCareer, world champion at super featherweight]
-
A.
professionalOutcome
Indicates the resulting professional status, achievement, or consequence that arises from a person’s work-related actions, experiences, or decisions.
-
B.
businessCareer
Indicates a relationship where an entity’s professional life, roles, or progression is specifically within the field of business or commerce.
-
C.
professionalCategory
Indicates the classification of an entity according to its professional field, role, or occupational domain.
-
D.
professionalSector
Indicates the industry or field in which an entity conducts its professional or occupational activities.
-
E.
professional
Indicates that one entity has a formal, occupation-related role, service, or expertise in relation to another entity.
- 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_69ee9cf8c7188190b9b00270a8a89164 |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f65705a3048190a3728b695ba2ae65 |
completed | May 2, 2026, 7:56 p.m. |
| PD | Predicate disambiguation | batch_69f651a731508190bb0c8c2462eba224 |
completed | May 2, 2026, 7:33 p.m. |
| PDg | Predicate description generation | batch_69f6562ef4e4819082ce6abd41b74dc5 |
completed | May 2, 2026, 7:53 p.m. |
Created at: April 27, 2026, 2:34 a.m.