Triple
T38687676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evander Holyfield vs. Bert Cooper |
E949163
|
entity |
| Predicate | originalOpponent |
P84463
|
FINISHED |
| Object | Francesco Damiani |
—
|
NE NERFINISHED |
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: Francesco Damiani | Statement: [Evander Holyfield vs. Bert Cooper, originalOpponent, Francesco Damiani]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalOpponent Context triple: [Evander Holyfield vs. Bert Cooper, originalOpponent, Francesco Damiani]
-
A.
opponentInCase
Indicates that two parties are on opposing sides in the same legal case or proceeding.
-
B.
secondaryOpponent
Indicates that an entity serves as an additional or backup opponent to a primary one in a given context or interaction.
-
C.
laterOpponent
chosen
Indicates that one entity becomes the opponent of another at a later time or stage, following an earlier phase or matchup.
-
D.
associatedOpponent
Indicates that one entity is recognized or designated as an opponent or adversary associated with another entity in a given context.
-
E.
regularOpponent
Indicates that two entities frequently compete against each other as recurring opponents in some contest or competitive context.
- 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_69f76efe16148190befd5dd59c3dfeaa |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a2026248190b894436a578d79ac |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:33 p.m.