Triple

T34280711
Position Surface form Disambiguated ID Type / Status
Subject New York E879581 entity
Predicate hadStateJudge P178739 FINISHED
Object Samuel Nelson NE NERFINISHED

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: Samuel Nelson | Statement: [New York, hadStateJudge, Samuel Nelson]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hadStateJudge
Context triple: [New York, hadStateJudge, Samuel Nelson]
  • A. hasJudge
    Indicates that a legal case, proceeding, or decision is presided over or decided by a particular judge.
  • B. hasJudgeFrom
    Indicates that an entity has a judge whose origin, affiliation, or source is from a specified place or organization.
  • C. hasJudges
    Indicates that one entity serves as a judge or panel of judges for another entity, such as an event, competition, or legal case.
  • D. hadJudicialCounterpart
    Indicates that one legal or judicial entity corresponded to, or was matched by, another entity serving an equivalent judicial role or function.
  • E. hadStateFrom
    Indicates that an entity possessed or was in a particular state starting from a specified point in time.
  • 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_69f349b5f6648190b9420d94a4cd16e0 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f713bfdc148190a249a7874320bab8 completed May 3, 2026, 9:22 a.m.
PD Predicate disambiguation batch_69f7127884388190884f23d181a65d19 completed May 3, 2026, 9:16 a.m.
PDg Predicate description generation batch_69f7135fa2988190a20a94cfe616d754 completed May 3, 2026, 9:20 a.m.
Created at: May 1, 2026, 1:57 a.m.