Triple
T13483378
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zora Folley |
E318429
|
entity |
| Predicate | resultAgainstMuhammadAli |
P110574
|
FINISHED |
| Object | lost by knockout |
—
|
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: lost by knockout | Statement: [Zora Folley, resultAgainstMuhammadAli, lost by knockout]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: resultAgainstMuhammadAli Context triple: [Zora Folley, resultAgainstMuhammadAli, lost by knockout]
-
A.
purseMuhammadAli
Indicates the amount of prize money or financial compensation associated with Muhammad Ali in a particular bout or contractual context.
-
B.
MuhammadAliPreFightName
Indicates that the given name is the name Muhammad Ali used before he adopted the name "Muhammad Ali" (i.e., his pre-fight or earlier personal name).
-
C.
numberOfFightsWithSugarRayRobinson
Indicates the number of times an entity has fought in matches against Sugar Ray Robinson.
-
D.
wonChampionshipAgainst
Indicates that one competitor secured a championship title by defeating another specific opponent.
-
E.
formerBoxer
Indicates that a person previously worked or competed as a boxer but no longer does so.
- 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_69d806b6bfec819089222715b2e86c8e |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf3868ec8190a6a1803018d4f2d8 |
completed | April 12, 2026, 2:42 p.m. |
| PD | Predicate disambiguation | batch_69dbae06061881909a6a6032e0507587 |
completed | April 12, 2026, 2:36 p.m. |
| PDg | Predicate description generation | batch_69dbaecc98cc8190829f5be759c4f1e3 |
completed | April 12, 2026, 2:40 p.m. |
Created at: April 9, 2026, 9:42 p.m.