Triple

T1041087
Position Surface form Disambiguated ID Type / Status
Subject Colonial Athletic Association E22470 entity
Predicate hasGenderParticipation P15554 FINISHED
Object men's sports 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: men's sports | Statement: [Colonial Athletic Association, hasGenderParticipation, men's sports]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasGenderParticipation
Context triple: [Colonial Athletic Association, hasGenderParticipation, men's sports]
  • A. hasGenderFocus
    Indicates that something is specifically concerned with, oriented toward, or primarily addressing a particular gender or gender-related issues.
  • B. hasGenderSystem
    Indicates that an entity employs or is characterized by a particular system for categorizing gender.
  • C. hasGenderDistinction
    Indicates that a relationship, classification, or linguistic form differentiates entities based on gender categories.
  • D. hasGenderRequirement chosen
    Indicates that a particular role, activity, or context specifies a required or restricted gender for participation or eligibility.
  • E. hasGenderInSomeTraditions
    Indicates that, in at least some cultural, religious, or historical traditions, the subject is regarded as having a specific gender.
  • 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_69a493d91478819094cc01fb65564bc1 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b845fa8c8190a7b69629883b62e2 completed March 1, 2026, 10:05 p.m.
PD Predicate disambiguation batch_69a4b72ba60881908b017ef3b2b9645e completed March 1, 2026, 10:01 p.m.
Created at: March 1, 2026, 7:41 p.m.