Triple

T37490963
Position Surface form Disambiguated ID Type / Status
Subject Jean-Pierre Bemba E931684 entity
Predicate stillConvictedOf P6201 FINISHED
Object offences against the administration of justice in a separate ICC 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: offences against the administration of justice in a separate ICC case | Statement: [Jean-Pierre Bemba, stillConvictedOf, offences against the administration of justice in a separate ICC case]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: stillConvictedOf
Context triple: [Jean-Pierre Bemba, stillConvictedOf, offences against the administration of justice in a separate ICC case]
  • A. convictedOf chosen
    Indicates that a person or entity has been found guilty of committing a specified offense or crime through a formal legal process.
  • B. convictedIndividual
    Indicates that an individual has been found guilty of a crime or offense through a formal legal process and has received a conviction.
  • C. someMembersConvictedOf
    Indicates that within a group or organization, at least one member has been found guilty of a crime or offense through a formal legal or disciplinary process.
  • D. hasHadCriminalConviction
    Indicates that an entity has previously been found guilty of a criminal offense through a legal process.
  • E. numberOfConvictions
    Indicates the count of times an entity has been formally found guilty of an offense.
  • 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_69f76ec457a4819094eeb3aed9baac11 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fba68077788190b311e027435fcf87 completed May 6, 2026, 8:37 p.m.
PD Predicate disambiguation batch_69fba34c65ac8190b298f0f00d1dcc0e completed May 6, 2026, 8:23 p.m.
Created at: May 3, 2026, 4:17 p.m.