Triple

T33219014
Position Surface form Disambiguated ID Type / Status
Subject Ross Bannick E850366 entity
Predicate evidenceHandling P176217 FINISHED
Object uses legal knowledge to conceal crimes 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: uses legal knowledge to conceal crimes | Statement: [Ross Bannick, evidenceHandling, uses legal knowledge to conceal crimes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: evidenceHandling
Context triple: [Ross Bannick, evidenceHandling, uses legal knowledge to conceal crimes]
  • A. evidenceTypeHandled
    Indicates that an entity is responsible for processing or managing a particular type or category of evidence.
  • B. evidenceAtIssue
    Indicates that a particular piece of evidence is directly contested, disputed, or central to the disagreement or decision in a case or situation.
  • C. appliesRulesOfEvidence
    Indicates that one party enforces or follows established rules of evidence in relation to another party or proceeding.
  • D. hasProcessEvidence
    Indicates that there is supporting evidence for a process or procedure associated with the subject in relation to the object.
  • E. providesEvidenceFor
    Indicates that one entity serves as support, justification, or proof for the validity or truth of another entity.
  • 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_69f3496083dc8190b229bb6932dc548b completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6dd3cc0648190a275812d6711275a completed May 3, 2026, 5:29 a.m.
PD Predicate disambiguation batch_69f6d82eaee081908f06a71546315aea completed May 3, 2026, 5:07 a.m.
PDg Predicate description generation batch_69f6dd3b335481909e24d4eb5b0269f9 completed May 3, 2026, 5:29 a.m.
Created at: May 1, 2026, 1:30 a.m.