Triple
T25996752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benny Paret |
E646505
|
entity |
| Predicate | numberOfBoutsWithEmileGriffith |
P193044
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Benny Paret, numberOfBoutsWithEmileGriffith, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfBoutsWithEmileGriffith Context triple: [Benny Paret, numberOfBoutsWithEmileGriffith, 3]
-
A.
numberOfFightsWithSugarRayRobinson
Indicates the number of times an entity has fought in matches against Sugar Ray Robinson.
-
B.
numberOfFightsWithArturoGatti
Indicates the number of separate fights an entity has had against Arturo Gatti.
-
C.
fightNumberForFrazier
Indicates the specific fight number or sequence position of a bout involving Frazier within a series of fights.
-
D.
roundsFought
Indicates the number of rounds in which the related entities have engaged in a fight or combat.
-
E.
numberOfProfessionalFights
Indicates the total count of professional-level fights associated with an entity (such as a person or competitor).
- 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_69e77e88cb8481908da31d4a00661f55 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69fd37b695c88190855801626f91c4cd |
completed | May 8, 2026, 1:09 a.m. |
| PD | Predicate disambiguation | batch_69fd374cccf08190a230e87164af5938 |
completed | May 8, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69fd37b45b4481908b947b52fbcb7ade |
completed | May 8, 2026, 1:09 a.m. |
Created at: April 22, 2026, 8:58 a.m.