Triple

T29614971
Position Surface form Disambiguated ID Type / Status
Subject Avargal E754835 entity
Predicate hasAntagonistActor P116420 FINISHED
Object Rajanikanth NE NERFINISHED

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: Rajanikanth | Statement: [Avargal, hasAntagonistActor, Rajanikanth]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasAntagonistActor
Context triple: [Avargal, hasAntagonistActor, Rajanikanth]
  • A. hasAntagonisticProtagonist
    Indicates that the work features a main character who opposes or undermines the typical heroic or moral expectations of a traditional protagonist.
  • B. antagonistActorRole chosen
    Indicates that an actor plays the role of an antagonist in a given work or context.
  • C. antagonistOf
    Indicates a relationship where one entity actively opposes, conflicts with, or serves as an adversary to another.
  • D. antagonistStatus
    Indicates that an entity holds an opposing or adversarial role, often acting as the main source of conflict relative to another entity or objective.
  • E. hasAntagonistGroup
    Indicates that an entity is opposed or challenged by a specific group acting as its antagonist.
  • 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_69f0ef85f62081909842b59fdf8717e1 completed April 28, 2026, 5:33 p.m.
NER Named-entity recognition batch_69f7221dc9a88190bb8194fcc29c42bc completed May 3, 2026, 10:23 a.m.
PD Predicate disambiguation batch_69f72153a9188190b02adc84e1be4af8 completed May 3, 2026, 10:20 a.m.
Created at: April 28, 2026, 6:31 p.m.