Triple

T22102907
Position Surface form Disambiguated ID Type / Status
Subject Ram Lakhan E546213 entity
Predicate castMember P1668 FINISHED
Object Anil Kapoor 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: Anil Kapoor | Statement: [Ram Lakhan, castMember, Anil Kapoor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anil Kapoor
Context triple: [Ram Lakhan, castMember, Anil Kapoor]
  • A. Anil Kapoor chosen
    Anil Kapoor is a veteran Indian actor and producer known for his work in Hindi cinema and international films, recognized for his energetic screen presence and roles in movies like "Mr. India," "Dil Dhadakne Do," and the series "24."
  • B. Anupam Kher
    Anupam Kher is an acclaimed Indian actor known for his extensive work in Hindi cinema and notable roles in international films.
  • C. Rishi Kapoor
    Rishi Kapoor was a prominent Indian film actor and director, best known for his romantic lead roles in Hindi cinema from the 1970s onward and as a member of the influential Kapoor film family.
  • D. Sameer Saran
    Sameer Saran is an Indian businessman best known as the husband of actress Rinke Khanna, daughter of Bollywood stars Rajesh Khanna and Dimple Kapadia.
  • E. Randeep Hooda
    Randeep Hooda is an Indian film actor known for his intense performances in Hindi cinema across critically acclaimed and commercially successful films.
  • 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_69e11e378dc08190896d6a51597afd5a completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f129175a7881909549883f23c53dca completed April 28, 2026, 9:39 p.m.
Created at: April 16, 2026, 8:30 p.m.