Triple

T8565340
Position Surface form Disambiguated ID Type / Status
Subject Baashha E202787 entity
Predicate storyBy P1955 FINISHED
Object Suresh Krissna E758783 NE 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: Suresh Krissna | Statement: [Baashha, storyBy, Suresh Krissna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Suresh Krissna
Context triple: [Baashha, storyBy, Suresh Krissna]
  • A. Suresh Krissna chosen
    Suresh Krissna is an Indian film director best known for his successful Tamil and Telugu commercial films, including major hits with superstar Rajinikanth.
  • B. Himanshu Rai
    Himanshu Rai was a prominent Indian actor and pioneering film producer-director, best known for co-founding Bombay Talkies and helping shape early Indian cinema.
  • C. Paresh Rawal
    Paresh Rawal is a renowned Indian actor and comedian celebrated for his versatile performances in Hindi cinema and theatre.
  • D. Akshay Tandon
    Akshay Tandon is an Indian businessman and sports executive best known for his ownership and leadership role with Indian Super League football club FC Goa.
  • E. Amrish Puri
    Amrish Puri was a renowned Indian actor best known for his powerful villainous roles in Hindi cinema and for playing the iconic antagonist Mola Ram in the film "Indiana Jones and the Temple of Doom."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69ca8327b0a881908606ff860713964d completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe9d2331881909d92ddde90f580e9 completed March 31, 2026, 3:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf9ffe17e481908516d2f526d60684 completed April 3, 2026, 11:09 a.m.
Created at: March 30, 2026, 6:20 p.m.