Triple

T1783300
Position Surface form Disambiguated ID Type / Status
Subject Indians E39335 entity
Predicate associatedWithCinema P2830 FINISHED
Object Bollywood E31769 NE FINISHED

How this triple was built (3 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: Bollywood | Statement: [Indians, associatedWithCinema, Bollywood]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bollywood
Context triple: [Indians, associatedWithCinema, Bollywood]
  • 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. 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.
  • C. 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.
  • D. Lollywood
    Lollywood is the Pakistani film industry based in Lahore, historically known for producing Punjabi- and Urdu-language movies.
  • 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.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: associatedWithCinema
Context triple: [Indians, associatedWithCinema, Bollywood]
  • A. appliesToTheater
    Indicates that something is relevant or applicable specifically to a theater or theatrical context.
  • B. servedInTheatre
    Indicates that an individual performed military or service duties within a specific theater of operations or geographic area during a conflict or campaign.
  • C. isAssociatedWith chosen
    Indicates that there exists a connection, relationship, or involvement between two entities without specifying its exact nature.
  • D. hasNumberOfCinemas
    Indicates the quantity of cinemas associated with a given entity.
  • E. servedInTheatres
    Indicates that a film or performance was publicly exhibited in movie theaters or similar cinema venues.
  • F. None of above.

Provenance (4 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_69a88630519c8190a17addd83c4a3ef4 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69ab74dc9d1481908084ef07872a71f8 completed March 7, 2026, 12:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada9a1aa8481908cbcecde85804461 completed March 8, 2026, 4:53 p.m.
PD Predicate disambiguation batch_69aa61cf3ca881908641fd73ce2f7c9d completed March 6, 2026, 5:10 a.m.
Created at: March 4, 2026, 7:31 p.m.