Triple
T2594392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thrilla in Manila |
E58193
|
entity |
| Predicate | fightNumberForFrazier |
P40098
|
FINISHED |
| Object | third fight vs Muhammad Ali |
—
|
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: third fight vs Muhammad Ali | Statement: [Thrilla in Manila, fightNumberForFrazier, third fight vs Muhammad Ali]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fightNumberForFrazier Context triple: [Thrilla in Manila, fightNumberForFrazier, third fight vs Muhammad Ali]
-
A.
totalFights
Indicates the total number of fights that have occurred involving the specified entities or within the specified context.
-
B.
fightingOutOf
Indicates that an individual is competing or representing themselves in a fight or match while being officially associated with a particular location, camp, or organization.
-
C.
facedOpponent
Indicates that one entity directly confronted or competed against another as an opponent in a contest, conflict, or challenge.
-
D.
wonChampionshipAgainst
Indicates that one competitor secured a championship title by defeating another specific opponent.
-
E.
battleOpponent
Indicates that two entities are engaged in or designated as opponents in a battle or combat scenario.
- 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_69ab4ac14040819098b13f4a27d5c8ff |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd427f58c8190af1c1a9724158c96 |
completed | March 7, 2026, 7:30 a.m. |
| PD | Predicate disambiguation | batch_69abd0d344988190a18dd93b13e002e6 |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd2baee308190bdaa41ef1f6bc9cc |
completed | March 7, 2026, 7:24 a.m. |
Created at: March 6, 2026, 9:49 p.m.