Triple

T9127392
Position Surface form Disambiguated ID Type / Status
Subject Committee for the Prevention of Torture (Russia) E218998 entity
Predicate hasOpposingActor P53524 FINISHED
Object Russian law enforcement agencies — 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: Russian law enforcement agencies | Statement: [Committee for the Prevention of Torture (Russia), hasOpposingActor, Russian law enforcement agencies]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasOpposingActor
Context triple: [Committee for the Prevention of Torture (Russia), hasOpposingActor, Russian law enforcement agencies]
  • A. hasOpposingAgent
    Indicates that an entity is opposed or counteracted by another agent in a given context or interaction.
  • B. hasOpposingSide
    Indicates that one entity possesses or is associated with another entity that lies on the opposite or facing side relative to a reference orientation or boundary.
  • C. hasOpposingFront
    Indicates that one entity’s front side is directly facing or oriented opposite to the front side of another entity.
  • D. hasOpposingForceType
    Indicates that one force is characterized as being of a type that opposes or counteracts another force.
  • E. hasOpposingFaction chosen
    Indicates that one faction stands in opposition or conflict to another faction.
  • 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_69ca83debfc0819095800583e97ab10f completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca8cad9c0819082d61f53865ef0b4 completed April 1, 2026, 5:10 a.m.
PD Predicate disambiguation batch_69cc66003e3c819091e1e42c9cf7c781 completed April 1, 2026, 12:25 a.m.
Created at: March 30, 2026, 7:18 p.m.