Triple

T9853821
Position Surface form Disambiguated ID Type / Status
Subject West Hollywood E239534 entity
Predicate hasAntiDiscriminationOrdinances P28758 FINISHED
Object yes 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: yes | Statement: [West Hollywood, hasAntiDiscriminationOrdinances, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasAntiDiscriminationOrdinances
Context triple: [West Hollywood, hasAntiDiscriminationOrdinances, yes]
  • A. discriminatoryLaw
    Indicates that a law treats individuals or groups differently in a way that is biased, unfair, or based on protected characteristics such as race, gender, or religion.
  • B. discriminationStatus
    Indicates whether an entity is subject to, engaged in, or affected by discriminatory treatment based on protected or distinguishing characteristics.
  • C. hasLocalOrdinances
    Indicates that a governing body or jurisdiction has established and enacted specific local ordinances or regulations.
  • D. prohibitsDiscriminationBasis chosen
    Indicates that an entity forbids discriminatory treatment based on specified characteristics or grounds.
  • E. includedMinorityProtectionClausesFor
    Indicates that one party incorporated specific clauses or provisions into an agreement to safeguard the rights or interests of a minority group associated with the other party.
  • 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_69ca84e4fdc08190a624425bcef98665 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb376d32c819089381cf6ed83629d completed April 2, 2026, 12:08 a.m.
PD Predicate disambiguation batch_69cd03e57cac8190914bb5ae608a6e0e completed April 1, 2026, 11:39 a.m.
Created at: March 30, 2026, 8:34 p.m.