Triple
T10657627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salvador Sánchez |
E251133
|
entity |
| Predicate | boxingRecordLosses |
P8293
|
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: [Salvador Sánchez, boxingRecordLosses, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: boxingRecordLosses Context triple: [Salvador Sánchez, boxingRecordLosses, 1]
-
A.
boxingRecordSummary
Indicates the summarized outcome or performance record of an entity in boxing matches, such as total wins, losses, and related statistics.
-
B.
professionalRecordKOs
Indicates the number of times an entity has won by knockout (KOs) in its professional record.
-
C.
careerLosses
chosen
Indicates the total number of defeats or losses an entity has accumulated over the course of its entire career.
-
D.
undefeatedInProfessionalBoxing
Indicates that a boxer has never lost any match in their professional boxing career.
-
E.
totalFights
Indicates the total number of fights that have occurred involving the specified entities or within the specified context.
- 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_69d6aa5a4c4881908f39be6efe5981e5 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6e0157dbc81909ef7d61f65b2fd93 |
completed | April 8, 2026, 11:09 p.m. |
| PD | Predicate disambiguation | batch_69d6dd8753108190b799ffa0c760526e |
completed | April 8, 2026, 10:58 p.m. |
Created at: April 8, 2026, 9:07 p.m.