Triple
T20287189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rocco Francis Marchegiano |
E509915
|
entity |
| Predicate | boxingRecordKnockouts |
P27027
|
FINISHED |
| Object | 43 |
—
|
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: 43 | Statement: [Rocco Francis Marchegiano, boxingRecordKnockouts, 43]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: boxingRecordKnockouts Context triple: [Rocco Francis Marchegiano, boxingRecordKnockouts, 43]
-
A.
professionalRecordKOs
Indicates the number of times an entity has won by knockout (KOs) in its professional record.
-
B.
winsByKO
Indicates that one competitor defeats another by knocking them out, ending the contest immediately.
-
C.
totalTKOs
Indicates the total number of times an entity has won or caused a technical knockout (TKO) in a given context or record.
-
D.
boxingRecordSummary
Indicates the summarized outcome or performance record of an entity in boxing matches, such as total wins, losses, and related statistics.
-
E.
numberOfKnockouts
chosen
Indicates the total count of times an entity has defeated opponents by knockout.
- 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_69e0b4c652388190b782cad965e5a098 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e676931fe08190b278d829a745701f |
completed | April 20, 2026, 6:55 p.m. |
| PD | Predicate disambiguation | batch_69e55b1e5e1c8190ba8a5544b1db9e1d |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 16, 2026, 11:07 a.m.