Triple

T25511513
Position Surface form Disambiguated ID Type / Status
Subject Nicole Bonnet E639392 entity
Predicate relationshipToCrime P46944 FINISHED
Object reluctant participant in theft 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: reluctant participant in theft | Statement: [Nicole Bonnet, relationshipToCrime, reluctant participant in theft]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: relationshipToCrime
Context triple: [Nicole Bonnet, relationshipToCrime, reluctant participant in theft]
  • A. hasRelationshipToPerpetrator
    Indicates that an entity has a specified type of relationship or connection to the perpetrator of an act or event.
  • B. suspectRelationshipToVictim
    Indicates that one entity is believed or alleged to have a potentially involved or connected role in relation to a victim.
  • C. isRelatedCriminalMatterOf
    Indicates that one legal case or issue is connected to, arises from, or is otherwise associated with another in a criminal context.
  • D. roleInCrime chosen
    Indicates the specific function, responsibility, or participation an entity has within the commission of a particular crime.
  • E. victimRelation
    Indicates that one entity is the victim or target of harm, wrongdoing, or an adverse action caused by another entity.
  • 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_69e75dbd09308190b6b5f0afdc12ec6d completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69fbc36ce1f88190a7fa1656b714e107 completed May 6, 2026, 10:40 p.m.
PD Predicate disambiguation batch_69fbbd13595c81908719f52c3d37a7e8 completed May 6, 2026, 10:13 p.m.
Created at: April 21, 2026, 2:49 p.m.