Triple
T25617953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sugar Ray Robinson |
E642208
|
entity |
| Predicate | professionalWinsByKnockout |
P41311
|
FINISHED |
| Object | 108 |
—
|
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: 108 | Statement: [Sugar Ray Robinson, professionalWinsByKnockout, 108]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionalWinsByKnockout Context triple: [Sugar Ray Robinson, professionalWinsByKnockout, 108]
-
A.
winsByKO
Indicates that one competitor defeats another by knocking them out, ending the contest immediately.
-
B.
professionalRecordKOs
chosen
Indicates the number of times an entity has won by knockout (KOs) in its professional record.
-
C.
numberOfKnockouts
Indicates the total count of times an entity has defeated opponents by knockout.
-
D.
careerWins
Indicates the total number of wins an individual or entity has accumulated over the course of their entire career.
-
E.
totalTKOs
Indicates the total number of times an entity has won or caused a technical knockout (TKO) in a given context or record.
- 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_69e77e7a96748190b10f2699041e4e43 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5f9e8734c8190a214685b1647abe1 |
completed | May 2, 2026, 1:19 p.m. |
| PD | Predicate disambiguation | batch_69f4807f8680819098a524158d049c63 |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 5:01 p.m.