Triple
T33929150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IBF bantamweight title |
E869836
|
entity |
| Predicate | hasTitleBelt |
P100156
|
FINISHED |
| Object | IBF bantamweight championship belt |
—
|
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: IBF bantamweight championship belt | Statement: [IBF bantamweight title, hasTitleBelt, IBF bantamweight championship belt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTitleBelt Context triple: [IBF bantamweight title, hasTitleBelt, IBF bantamweight championship belt]
-
A.
hasPhysicalBelt
Indicates that one entity possesses or is equipped with a physical belt as an item or feature.
-
B.
beltType
chosen
Indicates the specific kind or category of belt associated with an entity.
-
C.
usesBeltSystem
Indicates that a subject employs a structured belt-ranking system (e.g., colored belts) to denote levels of skill, progress, or status.
-
D.
hasCommuterBelt
Indicates that one area functions as the commuter belt for another, meaning people regularly travel from the first area to the second for work or daily activities.
-
E.
hasHadMultipleBeltDesigns
Indicates that an entity has undergone more than one distinct belt design over time.
- 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_69f3499a59788190bff762a891471b31 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fd6f9d600c8190acf495b7fc632e4b |
completed | May 8, 2026, 5:07 a.m. |
| PD | Predicate disambiguation | batch_69fd6e98a2948190a9f78c415ad23b8c |
completed | May 8, 2026, 5:03 a.m. |
Created at: May 1, 2026, 1:49 a.m.