Triple

T11289350
Position Surface form Disambiguated ID Type / Status
Subject Ekta Kapoor E267282 entity
Predicate notableWork P4 FINISHED
Object Udta Punjab E904757 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: Udta Punjab | Statement: [Ekta Kapoor, notableWork, Udta Punjab]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Udta Punjab
Context triple: [Ekta Kapoor, notableWork, Udta Punjab]
  • A. Udta Punjab chosen
    Udta Punjab is a 2016 Indian crime drama film that explores the drug abuse crisis in the state of Punjab through the intersecting lives of several characters.
  • B. Kaithi
    Kaithi is a 2019 Tamil-language action thriller film centered on an ex-convict’s overnight mission to save poisoned police officers while evading ruthless criminals.
  • C. Kaithi
    Kaithi is a historical Brahmic script from northern India that was used to write several Indo-Aryan languages, including Bhojpuri, Magahi, and Maithili.
  • D. Laal Singh Chaddha
    Laal Singh Chaddha is a 2022 Indian Hindi-language comedy-drama film, an official adaptation of the Hollywood classic Forrest Gump, starring Aamir Khan and Kareena Kapoor Khan.
  • E. Bajrangi Bhaijaan
    Bajrangi Bhaijaan is a 2015 Indian Hindi-language drama film starring Salman Khan that follows a devout man's journey to reunite a mute Pakistani girl with her family across the border.
  • 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_69d6aac993a08190a6f36445ebaf9a43 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e98875a08190b8509fe55e49d52d completed April 9, 2026, 6:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4f49badc88190a3195e919900f0c3 completed April 19, 2026, 3:28 p.m.
Created at: April 8, 2026, 9:32 p.m.