Triple

T28923981
Position Surface form Disambiguated ID Type / Status
Subject Dr. Edward Armstrong E733593 entity
Predicate hasAllegedCrime P83746 FINISHED
Object causing the death of a patient through drunkenness 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: causing the death of a patient through drunkenness | Statement: [Dr. Edward Armstrong, hasAllegedCrime, causing the death of a patient through drunkenness]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasAllegedCrime
Context triple: [Dr. Edward Armstrong, hasAllegedCrime, causing the death of a patient through drunkenness]
  • A. hasAllegationsOf chosen
    Indicates that one entity is accused or suspected of engaging in certain actions, behaviors, or misconduct, but without implying that these accusations are proven.
  • B. hasCrimeElement
    Indicates that a situation, action, or entity involves or contains a component that is legally recognized as part of a crime.
  • C. hasAllegedDetail
    Indicates that an entity is associated with a detail or piece of information that is claimed or reported but not confirmed as factual.
  • D. hasCriminalElement
    Indicates that the subject involves, contains, or is associated with an illegal or criminal component, activity, or characteristic.
  • E. hasCriminalProcedureBasedOn
    Indicates that one legal system’s criminal procedure is derived from, modeled on, or fundamentally influenced by another specified source or framework.
  • 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_69f05b0a5cc0819094828367ae204b70 completed April 28, 2026, 7 a.m.
NER Named-entity recognition batch_69f71422adac8190a5ceb32dcf820833 completed May 3, 2026, 9:23 a.m.
PD Predicate disambiguation batch_69f712764d2c819081b64b27e5de4a13 completed May 3, 2026, 9:16 a.m.
Created at: April 28, 2026, 8:22 a.m.