Triple

T11240857
Position Surface form Disambiguated ID Type / Status
Subject Sonam Kapoor E266068 entity
Predicate father P120 FINISHED
Object Anil Kapoor E243955 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: Anil Kapoor | Statement: [Sonam Kapoor, father, Anil Kapoor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anil Kapoor
Context triple: [Sonam Kapoor, father, 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. Randeep Hooda
    Randeep Hooda is an Indian film actor known for his intense performances in Hindi cinema across critically acclaimed and commercially successful films.
  • E. Gulshan Grover
    Gulshan Grover is an Indian film actor, popularly known as Bollywood’s “Bad Man” for his numerous villainous roles across Hindi cinema.
  • 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_69d6aac656d48190b275efaa7d6074ee completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e919eaf48190a1457851cfc56afb completed April 9, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69e8a68e4404819096c5023c7eca4b6a completed April 22, 2026, 10:44 a.m.
Created at: April 8, 2026, 9:30 p.m.