Triple

T16183612
Position Surface form Disambiguated ID Type / Status
Subject Taare Zameen Par E392743 entity
Predicate castMember P1668 FINISHED
Object Vipin Sharma E1012012 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: Vipin Sharma | Statement: [Taare Zameen Par, castMember, Vipin Sharma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vipin Sharma
Context triple: [Taare Zameen Par, castMember, Vipin Sharma]
  • A. Vipin Sharma chosen
    Vipin Sharma is an Indian actor known for his character roles in Hindi cinema and streaming projects, including a prominent part in the action thriller film "Monkey Man."
  • B. Vipin Kumar
    Vipin Kumar is a prominent computer scientist known for his influential research in data mining and high-performance computing, particularly in applications to climate and earth sciences.
  • C. Vijay Maurya
    Vijay Maurya is an Indian actor, writer, and director known for his work in Hindi cinema and web series.
  • D. Dinesh Gupta
    Dinesh Gupta was an Indian revolutionary freedom fighter known for his role in the anti-colonial struggle against British rule in Bengal.
  • E. Sunil Gulati
    Sunil Gulati is an American soccer executive best known for serving as president of the U.S. Soccer Federation and playing a key role in the growth and governance of the sport in the United States.
  • 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_69d87f1e49ac8190a311b54d32990576 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e2205fc080819097858f36253fef7c completed April 17, 2026, 11:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a003548837c819091695a91f88bd0bc completed May 10, 2026, 7:35 a.m.
Created at: April 10, 2026, 5:02 a.m.