Triple

T2256677
Position Surface form Disambiguated ID Type / Status
Subject K. Balaji E49742 entity
Predicate primaryCinema P36764 FINISHED
Object Tamil cinema E39755 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: Tamil cinema | Statement: [K. Balaji, primaryCinema, Tamil cinema]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tamil cinema
Context triple: [K. Balaji, primaryCinema, Tamil cinema]
  • A. Tamil cinema chosen
    Tamil cinema is the film industry based in the Indian state of Tamil Nadu, primarily producing Tamil-language movies and known for its influential contributions to Indian and global cinema.
  • B. Tollywood
    Tollywood is the Bengali-language film industry based primarily in Kolkata, India, known for its rich artistic and literary cinematic tradition.
  • C. 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.
  • D. 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.
  • 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.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: primaryCinema
Context triple: [K. Balaji, primaryCinema, Tamil cinema]
  • A. primaryTheater
    Indicates that a particular location or region is the main setting or principal area where an event, activity, or operation takes place.
  • B. primaryVenueFor
    Indicates that one entity serves as the main or principal venue or location for events, activities, or operations associated with another entity.
  • C. primaryVenues
    Indicates the main or most important venues associated with or used by a given entity.
  • D. primaryServes
    Indicates that one entity’s main or principal function is to serve, support, or provide service to another entity.
  • E. filmSettingTheater
    Indicates that a film’s setting or key scenes take place in a theater (such as a cinema or playhouse).
  • F. None of above. chosen

Provenance (5 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_69a88aaa9250819095e127d0d77e8a32 completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc1570dc88190bb2b17ed4c25dbb5 completed March 7, 2026, 6:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae71c69f088190a38254a8a3670124 completed March 9, 2026, 7:07 a.m.
PD Predicate disambiguation batch_69abbdb34c148190b51e99f540f97204 completed March 7, 2026, 5:54 a.m.
PDg Predicate description generation batch_69abbe86dbcc81908c72793af8fe2a4d completed March 7, 2026, 5:58 a.m.
Created at: March 4, 2026, 7:47 p.m.