Triple
T26743879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Antonio Margarito |
E674339
|
entity |
| Predicate | titleFightWeightClass |
P180209
|
FINISHED |
| Object | light middleweight |
—
|
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: light middleweight | Statement: [Antonio Margarito, titleFightWeightClass, light middleweight]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleFightWeightClass Context triple: [Antonio Margarito, titleFightWeightClass, light middleweight]
-
A.
weightClass
Indicates the categorical grouping of an entity based on its weight range or mass classification.
-
B.
firstBoutWeightClass
Indicates the weight class in which an entity (such as a fighter) competed in their first recorded bout.
-
C.
weightClassAlternativeName
Indicates that one weight class is referred to by an alternative name or label.
-
D.
launchWeightClass
Indicates the weight category or class into which a launch (typically of a vehicle, payload, or mission) is classified based on its mass.
-
E.
fourthBoutWeightClass
Indicates the weight class category assigned to the fourth bout in a sequence of matches or fights.
- 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_69eecda63a3881908095c47900692e65 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f739a638748190808e7a2930dce16e |
completed | May 3, 2026, 12:03 p.m. |
| PD | Predicate disambiguation | batch_69f732f2dc6c8190a4e86da98cc5eb05 |
completed | May 3, 2026, 11:35 a.m. |
| PDg | Predicate description generation | batch_69f739a58b3c81908abc2b8738a65678 |
completed | May 3, 2026, 12:03 p.m. |
Created at: April 27, 2026, 3:50 a.m.