Triple

T34851907
Position Surface form Disambiguated ID Type / Status
Subject New York club kids E1004619 entity
Predicate legalAssociation P70474 FINISHED
Object Angel Melendez murder case 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: Angel Melendez murder case | Statement: [New York club kids, legalAssociation, Angel Melendez murder case]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: legalAssociation
Context triple: [New York club kids, legalAssociation, Angel Melendez murder case]
  • A. legalRepresentation
    Indicates that one entity formally acts on behalf of another in legal matters, such as providing counsel, advocacy, or defense within a legal system.
  • B. legalMatters
    Indicates that one entity is involved with, concerned about, or responsible for legal issues, processes, or obligations related to another entity or context.
  • C. legalCodeFocus
    Indicates that something is specifically concerned with, centered on, or primarily addressing a particular legal code or body of law.
  • D. legalParties chosen
    Indicates that the related entities are formally recognized participants in a legal relationship, case, contract, or proceeding.
  • E. legalBackground
    Indicates that an entity has education, training, or experience related to law or the legal profession.
  • 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_69f76dba76f0819090643cba102c41ec completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69ff7ae5d088819089aa3b6360b6b749 completed May 9, 2026, 6:20 p.m.
PD Predicate disambiguation batch_69ff7a4df6488190bf60d675b36b1d6d completed May 9, 2026, 6:17 p.m.
Created at: May 3, 2026, 4 p.m.