Triple
T5003093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Max Baer Sr. |
E112419
|
entity |
| Predicate | numberOfProfessionalFights |
P61426
|
FINISHED |
| Object | 84 |
—
|
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: 84 | Statement: [Max Baer Sr., numberOfProfessionalFights, 84]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfProfessionalFights Context triple: [Max Baer Sr., numberOfProfessionalFights, 84]
-
A.
totalFights
Indicates the total number of fights that have occurred involving the specified entities or within the specified context.
-
B.
isWorldChampionshipFight
Indicates that a given fight is officially recognized as a world championship bout for a title in its sport.
-
C.
fightNumberForFrazier
Indicates the specific fight number or sequence position of a bout involving Frazier within a series of fights.
-
D.
professionalRecordDraws
Indicates the number of times a professional competitor’s official matches have ended in a draw.
-
E.
numberOfTitleDefenses
Indicates the number of times an entity has successfully defended a previously won title or championship.
- 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_69bd4433d0b08190877e83959ef40d81 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7472a1dc8190942f568a81fdd961 |
completed | March 20, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69bd714aee2481908fb0dd5fa2daf3a1 |
completed | March 20, 2026, 4:09 p.m. |
| PDg | Predicate description generation | batch_69bd74713fc88190916c2b04cd2e677e |
completed | March 20, 2026, 4:23 p.m. |
Created at: March 20, 2026, 1:35 p.m.