Triple

T11535389
Position Surface form Disambiguated ID Type / Status
Subject Randhir Kapoor E273533 entity
Predicate fieldOfWork P3 FINISHED
Object Hindi cinema E31769 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: Hindi cinema | Statement: [Randhir Kapoor, fieldOfWork, Hindi cinema]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hindi cinema
Context triple: [Randhir Kapoor, fieldOfWork, Hindi cinema]
  • A. Bollywood cinema chosen
    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.
  • B. 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.
  • C. Kollywood
    Kollywood is the Tamil-language film industry based in Chennai, India, known for its prolific output of commercial and artistic cinema.
  • D. Pollywood
    Pollywood is the regional film industry based in the Indian state of Punjab, producing Punjabi-language movies and entertainment content.
  • E. Nollywood
    Nollywood is Nigeria’s prolific film industry, renowned as one of the largest movie producers in the world and a major cultural force across Africa.
  • 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_69d6aae3fbec8190a14632a5df2538b6 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8839b4bb48190b748ec4119f36c11 completed April 10, 2026, 4:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69e6858af0d081909078d5862ec3d469 completed April 20, 2026, 7:59 p.m.
Created at: April 8, 2026, 9:37 p.m.