Triple

T13413112
Position Surface form Disambiguated ID Type / Status
Subject US Open wheelchair doubles E320139 entity
Predicate ruleAdaptation P24476 FINISHED
Object two-bounce rule for wheelchair tennis 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: two-bounce rule for wheelchair tennis | Statement: [US Open wheelchair doubles, ruleAdaptation, two-bounce rule for wheelchair tennis]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: ruleAdaptation
Context triple: [US Open wheelchair doubles, ruleAdaptation, two-bounce rule for wheelchair tennis]
  • A. typicalRuleModification chosen
    Indicates a change made to a standard or default rule, adjusting how that rule normally applies or operates.
  • B. plannedAdaptation
    Indicates that an adaptation or modification has been intentionally designed or scheduled to occur in response to certain conditions or goals.
  • C. billAdaptation
    Indicates that a bill or legislative proposal has been modified or adjusted, typically in response to feedback, new information, or changing conditions.
  • D. mayAdapt
    Indicates that one entity is permitted or allowed to modify, adjust, or alter another entity.
  • E. isAdaptation
    Indicates that one work is derived from, based on, or reinterprets the content of another work.
  • 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_69d806b943cc8190b6af624d385d7e12 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaeb556948190af008c88e5bbf051 completed April 12, 2026, 2:39 p.m.
PD Predicate disambiguation batch_69d9a0355de48190bb3fb96912e20df3 completed April 11, 2026, 1:13 a.m.
Created at: April 9, 2026, 9:35 p.m.