Triple
T24274709
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WBA light middleweight title |
E605374
|
entity |
| Predicate | knockdownCountRule |
P41948
|
FINISHED |
| Object | WBA rules apply |
—
|
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: WBA rules apply | Statement: [WBA light middleweight title, knockdownCountRule, WBA rules apply]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: knockdownCountRule Context triple: [WBA light middleweight title, knockdownCountRule, WBA rules apply]
-
A.
numberOfKnockdowns
Indicates the count of times an entity has been knocked down during a specified event or interaction.
-
B.
hasKnockoutRule
Indicates that a rule or condition exists specifying when and how a knockout (elimination) occurs in a competitive or game-like setting.
-
C.
dropCount
Indicates the number of times an entity has been dropped or caused to drop something.
-
D.
roundOfKnockdown
Indicates the specific round in which a knockdown event occurs during a fight or match.
-
E.
countingRule
chosen
Indicates the rule or method used to count or quantify items, events, or entities in a given 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_69e2954707dc8190915551eb114cfff6 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28d5da53c8190810f4e7777d112ba |
completed | April 29, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69f1c457a2908190993824395b3c365d |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 18, 2026, 12:07 a.m.