Triple

T22755621
Position Surface form Disambiguated ID Type / Status
Subject Rekha E562834 entity
Predicate notableWork P4 FINISHED
Object Krrish 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: Krrish | Statement: [Rekha, notableWork, Krrish]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Krrish
Context triple: [Rekha, notableWork, Krrish]
  • A. Krrish chosen
    Krrish is a popular Indian superhero film franchise known for its sci-fi action, visual effects, and central masked hero.
  • B. Ghajini
    Ghajini is a 2008 Indian psychological action thriller film, directed by A.R. Murugadoss, known for its amnesia-driven revenge plot and Aamir Khan’s intensely physical performance.
  • C. Kaalpurush
    Kaalpurush is an acclaimed Bengali film by director Buddhadeb Dasgupta that explores memory, time, and human relationships through a poetic, surreal narrative.
  • D. Jawan
    Jawan is a small town in the Aligarh district of Uttar Pradesh, India, known primarily as a local agricultural and market center.
  • E. Jawan
    Jawan is a 2023 Indian action thriller film starring Shah Rukh Khan, known for its high-octane action, social themes, and massive box-office success.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e24551ec7881909a9c924dbea155f6 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f179bd22588190ac724a656194f5b9 completed April 29, 2026, 3:23 a.m.
Created at: April 17, 2026, 3:25 p.m.