Triple
T30102737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muhammad Ali–Ken Norton boxing trilogy |
E765041
|
entity |
| Predicate | totalWinsByKenNorton |
P178066
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Muhammad Ali–Ken Norton boxing trilogy, totalWinsByKenNorton, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalWinsByKenNorton Context triple: [Muhammad Ali–Ken Norton boxing trilogy, totalWinsByKenNorton, 1]
-
A.
winsByKO
Indicates that one competitor defeats another by knocking them out, ending the contest immediately.
-
B.
numberOfKnockouts
Indicates the total count of times an entity has defeated opponents by knockout.
-
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.
professionalRecordKOs
Indicates the number of times an entity has won by knockout (KOs) in its professional record.
-
E.
numberOfFightsWithSugarRayRobinson
Indicates the number of times an entity has fought in matches against Sugar Ray Robinson.
- 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_69f22474e4288190b5f895fe3974aa92 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f707f7959881908f037f0d6b1d0c36 |
completed | May 3, 2026, 8:31 a.m. |
| PD | Predicate disambiguation | batch_69f700fc274c8190a128593dc7c7abd0 |
completed | May 3, 2026, 8:02 a.m. |
| PDg | Predicate description generation | batch_69f707f380388190954b79d52a321921 |
completed | May 3, 2026, 8:31 a.m. |
Created at: April 29, 2026, 7:08 p.m.