Triple
T12290577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tyson–Holyfield II ear-biting incident |
E292945
|
entity |
| Predicate | hasRuleInfraction |
P32803
|
FINISHED |
| Object | biting opponent |
—
|
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: biting opponent | Statement: [Tyson–Holyfield II ear-biting incident, hasRuleInfraction, biting opponent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRuleInfraction Context triple: [Tyson–Holyfield II ear-biting incident, hasRuleInfraction, biting opponent]
-
A.
hasTransgression
chosen
Indicates that one entity has committed, is responsible for, or is associated with a violation, offense, or wrongdoing in relation to another entity or rule.
-
B.
hasPunishment
Indicates that an entity is subject to a specified penalty, sanction, or adverse consequence as a result of some action, condition, or rule.
-
C.
violationOf
Indicates that one entity breaches, disobeys, or infringes upon a rule, law, agreement, or right associated with another entity.
-
D.
hasReasonForArrest
Indicates that an arrest is associated with a specific reason or cause.
-
E.
hasFirstConviction
Indicates that an entity has received its first legal conviction for an offense.
- 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_69d6ab690ad081908c0ed3870ec82d53 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d9261e1570819084bb4fdb44aa6aea |
completed | April 10, 2026, 4:32 p.m. |
| PD | Predicate disambiguation | batch_69d91c4d9a9c8190aeb7beaf9792d8f0 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:52 p.m.