Triple

T10213334
Position Surface form Disambiguated ID Type / Status
Subject Guru (2007 film) E242382 entity
Predicate leadActor P1507 FINISHED
Object Abhishek Bachchan E673482 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: Abhishek Bachchan | Statement: [Guru (2007 film), leadActor, Abhishek Bachchan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Abhishek Bachchan
Context triple: [Guru (2007 film), leadActor, Abhishek Bachchan]
  • A. Abhishek Bachchan chosen
    Abhishek Bachchan is an Indian film actor and producer known for his work in Bollywood across a range of commercial and critically acclaimed movies.
  • B. Rajat Kapoor
    Rajat Kapoor is an Indian actor, writer, and filmmaker known for his work in independent cinema and acclaimed films such as "Bheja Fry," "Mithya," and "Ankhon Dekhi."
  • C. Vikrant Kapoor
    Vikrant Kapoor is the central male protagonist in the 1999 Bollywood musical romance film "Taal," portrayed by actor Akshaye Khanna.
  • D. Ranbir Kapoor
    Ranbir Kapoor is a prominent Indian film actor and producer known for his leading roles in contemporary Hindi cinema.
  • E. Sonu Sood
    Sonu Sood is an Indian actor and film producer known for his roles in Hindi, Telugu, and other regional films, as well as for his extensive humanitarian and philanthropic work.
  • 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_69d381ae26c48190985abd0e25ee5d04 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d3aa24efc081909714d98943543283 completed April 6, 2026, 12:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d71c77f65c8190862fde1c2fae045b completed April 9, 2026, 3:26 a.m.
Created at: April 6, 2026, 11:03 a.m.