Triple

T101136
Position Surface form Disambiguated ID Type / Status
Subject MIT Engineers E2041 entity
Predicate genderPolicy P277 FINISHED
Object fields men's teams 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: fields men's teams | Statement: [MIT Engineers, genderPolicy, fields men's teams]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: genderPolicy
Context triple: [MIT Engineers, genderPolicy, fields men's teams]
  • A. hasGenderPolicy chosen
    Indicates that an entity has adopted, implemented, or is governed by a specific policy related to gender issues or gender equality.
  • B. genderCategories
    Indicates the classification of an entity into one or more gender-related categories or identities.
  • C. recruitmentPolicy
    Indicates the rules, criteria, and procedures an organization follows when attracting, selecting, and hiring candidates.
  • D. hasGenderFocus
    Indicates that something is specifically concerned with, oriented toward, or primarily addressing a particular gender or gender-related issues.
  • E. governingPolicy
    Indicates that one entity serves as the authoritative policy or set of rules that directs, constrains, or regulates the behavior, operation, or decisions of another entity.
  • 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_69a24e0a5b7c81908d52da08c60dabc4 completed Feb. 28, 2026, 2:08 a.m.
NER Named-entity recognition batch_69a25760af348190bf402089c240887d completed Feb. 28, 2026, 2:48 a.m.
PD Predicate disambiguation batch_69a2563921f8819087f720b1c803579f completed Feb. 28, 2026, 2:43 a.m.
Created at: Feb. 28, 2026, 2:12 a.m.