Triple
T12042878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Play It to the Bone |
E286706
|
entity |
| Predicate | hasBoxingAsSport |
P102913
|
FINISHED |
| Object | boxing |
—
|
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: boxing | Statement: [Play It to the Bone, hasBoxingAsSport, boxing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBoxingAsSport Context triple: [Play It to the Bone, hasBoxingAsSport, boxing]
-
A.
hasBoxerCharacter
Indicates that an entity includes or features a character who is a boxer.
-
B.
hasNotableBoxer
Indicates that an entity is associated with or characterized by a boxer who is considered notable or distinguished.
-
C.
wasOlympicBoxerFor
Indicates that a person competed as a boxer representing a particular country or team in the Olympic Games.
-
D.
boxingStable
Indicates that one entity is a boxing stable (training/management camp) to which the other entity (typically a boxer) is affiliated or belongs.
-
E.
introducedSport
Indicates that an entity caused a particular sport to be brought into use, practice, or awareness within a specific context or place.
- 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_69d6ab4780948190bdb9f7620c2ac27e |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902bac9e08190aa1a99c835f29542 |
completed | April 10, 2026, 2:01 p.m. |
| PDg | Predicate description generation | batch_69d91006e14081909838412df082f794 |
completed | April 10, 2026, 2:58 p.m. |
Created at: April 8, 2026, 9:47 p.m.