Triple

T6214136
Position Surface form Disambiguated ID Type / Status
Subject Shreya Ghoshal E138941 entity
Predicate performedIn P795 FINISHED
Object Punjabi cinema E22094 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: Punjabi cinema | Statement: [Shreya Ghoshal, performedIn, Punjabi cinema]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Punjabi cinema
Context triple: [Shreya Ghoshal, performedIn, Punjabi cinema]
  • A. Punjabi cinema chosen
    Punjabi cinema is the film industry that produces motion pictures in the Punjabi language, primarily based in the Punjab regions of India and Pakistan.
  • B. Pakistani cinema
    Pakistani cinema is the film industry of Pakistan, encompassing movies produced in various regional languages and known for its evolving storytelling, music, and cultural influence across South Asia.
  • C. Bollywood cinema
    Bollywood cinema is the mainstream Hindi-language film industry based in Mumbai, India, known for its song-and-dance musicals, melodrama, and massive cultural influence across South Asia and the global Indian diaspora.
  • D. Pollywood
    Pollywood is the regional film industry based in the Indian state of Punjab, producing Punjabi-language movies and entertainment content.
  • E. Indian cinema
    Indian cinema is the diverse and prolific film industry of India, encompassing multiple regional and language-based film sectors and producing some of the world's highest-volume and most influential movies.
  • 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_69c008ada364819096c9e92c74d639b5 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0629fd3c08190a121097c188417c4 completed March 22, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69c16f61ed708190a034136cc270e9d0 completed March 23, 2026, 4:50 p.m.
Created at: March 22, 2026, 4:21 p.m.