Triple

T20417580
Position Surface form Disambiguated ID Type / Status
Subject Shaadi No. 1 E500751 entity
Predicate distributor P1951 FINISHED
Object Pooja Entertainment 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: Pooja Entertainment | Statement: [Shaadi No. 1, distributor, Pooja Entertainment]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pooja Entertainment
Context triple: [Shaadi No. 1, distributor, Pooja Entertainment]
  • A. Pooja Entertainment chosen
    Pooja Entertainment is an Indian film production company known for backing a range of Bollywood movies across genres.
  • B. Balaji Telefilms
    Balaji Telefilms is a major Indian television and film production company known for creating numerous popular Hindi soap operas and entertainment content.
  • C. Reliance Entertainment
    Reliance Entertainment is an Indian film and media production company known for financing and distributing a wide range of Bollywood and international movies.
  • D. Suresh Productions
    Suresh Productions is a prominent Indian film production company based in Hyderabad, widely known for producing numerous successful Telugu-language films.
  • E. Bakshi Productions
    Bakshi Productions is an animation studio founded by director Ralph Bakshi, known for producing his distinctive and often experimental animated 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_69e0b4a935588190b9446a99b37ced44 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e67a44ecf48190ba5a3872af500dc8 completed April 20, 2026, 7:11 p.m.
Created at: April 16, 2026, 11:30 a.m.