Triple

T7816143
Position Surface form Disambiguated ID Type / Status
Subject Jaya Bhaduri E181010 entity
Predicate child P120 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: [Jaya Bhaduri, child, Abhishek Bachchan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Abhishek Bachchan
Context triple: [Jaya Bhaduri, child, 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. Ranbir Kapoor
    Ranbir Kapoor is a prominent Indian film actor and producer known for his leading roles in contemporary Hindi cinema.
  • D. Sanjay Kapoor
    Sanjay Kapoor is an Indian film and television actor and producer known for his work in Hindi cinema since the 1990s.
  • E. Shahid Kapoor
    Shahid Kapoor is a popular Indian film actor known for his versatile performances in Hindi cinema, including acclaimed roles in films like "Jab We Met," "Haider," and "Kabir Singh."
  • 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_69ca828153f48190bdb27ac46f8e0745 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69caf96d1f088190a1d005ffb019afe9 completed March 30, 2026, 10:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69cb1488a2e48190924f44b46f925d87 completed March 31, 2026, 12:25 a.m.
Created at: March 30, 2026, 4:39 p.m.