Triple

T5229107
Position Surface form Disambiguated ID Type / Status
Subject White British E118063 entity
Predicate hasLegalRelevanceIn P62483 FINISHED
Object anti-discrimination law in the United Kingdom 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: anti-discrimination law in the United Kingdom | Statement: [White British, hasLegalRelevanceIn, anti-discrimination law in the United Kingdom]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasLegalRelevanceIn
Context triple: [White British, hasLegalRelevanceIn, anti-discrimination law in the United Kingdom]
  • A. hasLegalSubject
    Indicates that an entity serves as the legal subject (e.g., rights-holder or obligated party) in a legal relationship or context.
  • B. hasLegalEffect
    Indicates that an action, document, or condition produces recognized legal consequences or enforceable rights and obligations.
  • C. hasLegalIssue
    Indicates that an entity is involved in, associated with, or subject to a legal problem, dispute, or proceeding.
  • D. hasLegalForceIn
    Indicates that something (such as a law, regulation, or agreement) is legally valid, binding, and enforceable within a specified jurisdiction or context.
  • E. jurisprudenceDiscussedIn
    Indicates that a topic, issue, or principle of jurisprudence is examined, analyzed, or debated within a particular document, discussion, or source.
  • F. None of above. chosen

Provenance (4 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_69bd4466fb8c819083b806a79414d7e4 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7b0093a88190aba381ba3f761408 completed March 20, 2026, 4:51 p.m.
PD Predicate disambiguation batch_69bd77bf1ef08190bb3487b3f3ee088c completed March 20, 2026, 4:37 p.m.
PDg Predicate description generation batch_69bd7aff0244819085c4799793ed0185 completed March 20, 2026, 4:51 p.m.
Created at: March 20, 2026, 1:48 p.m.