Triple

T22571394
Position Surface form Disambiguated ID Type / Status
Subject Japanese Deaf community E558081 entity
Predicate hasLegalConcerns P71081 FINISHED
Object recognition of sign language in law 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: recognition of sign language in law | Statement: [Japanese Deaf community, hasLegalConcerns, recognition of sign language in law]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasLegalConcerns
Context triple: [Japanese Deaf community, hasLegalConcerns, recognition of sign language in law]
  • A. hasLegalIssue
    Indicates that an entity is involved in, associated with, or subject to a legal problem, dispute, or proceeding.
  • B. hasLegalRelevanceIn
    Indicates that something is legally significant, applicable, or has consequences within a specified legal context, case, or jurisdiction.
  • C. mainLegalIssue
    Indicates the primary legal question or dispute that is central to a case or legal matter.
  • D. hasLegalSubject
    Indicates that an entity serves as the legal subject (e.g., rights-holder or obligated party) in a legal relationship or context.
  • E. legalMatters chosen
    Indicates that one entity is involved with, concerned about, or responsible for legal issues, processes, or obligations related to another entity or context.
  • 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_69e11e5ae4ac8190b1f503457603d969 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15fae1ed881909430769a0015c39c completed April 29, 2026, 1:32 a.m.
PD Predicate disambiguation batch_69ee626e6bb08190ada4dd8b48cc0c43 completed April 26, 2026, 7:07 p.m.
Created at: April 16, 2026, 8:52 p.m.