Triple

T11102838
Position Surface form Disambiguated ID Type / Status
Subject Boney Kapoor E262553 entity
Predicate industry P71 FINISHED
Object South Indian film industry E800354 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: South Indian film industry | Statement: [Boney Kapoor, industry, South Indian film industry]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: South Indian film industry
Context triple: [Boney Kapoor, industry, South Indian film industry]
  • A. South Indian cinema chosen
    South Indian cinema is the collective film industry of the southern states of India, encompassing Tamil, Telugu, Malayalam, and Kannada films known for their distinctive storytelling, music, and star-driven productions.
  • B. Mollywood
    Mollywood is the Malayalam-language film industry based in the Indian state of Kerala, known for its content-driven cinema and strong storytelling traditions.
  • C. Pollywood
    Pollywood is the regional film industry based in the Indian state of Punjab, producing Punjabi-language movies and entertainment content.
  • D. 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.
  • E. Tollywood
    Tollywood is the Bengali-language film industry based primarily in Kolkata, India, known for its rich artistic and literary cinematic tradition.
  • 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_69d6aa9a40d88190a373e2c7e48285db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79a2c30a481908c45020c37caebe4 completed April 9, 2026, 12:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3e7ff368c8190ab01b7538ad83826 completed April 18, 2026, 8:22 p.m.
Created at: April 8, 2026, 9:27 p.m.