Triple

T9245570
Position Surface form Disambiguated ID Type / Status
Subject Trisha E222184 entity
Predicate debutInCinema P87765 FINISHED
Object Tamil film industry 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 film industry | Statement: [Trisha, debutInCinema, Tamil film industry]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tamil film industry
Context triple: [Trisha, debutInCinema, Tamil film industry]
  • 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. Pollywood
    Pollywood is the regional film industry based in the Indian state of Punjab, producing Punjabi-language movies and entertainment content.
  • C. Tollywood film industry
    The Tollywood film industry is the segment of Indian cinema that produces movies in the Telugu language, primarily based in Hyderabad.
  • D. Kollywood
    Kollywood is the Tamil-language film industry based in Chennai, India, known for its prolific output of commercial and artistic cinema.
  • 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.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: debutInCinema
Context triple: [Trisha, debutInCinema, Tamil film industry]
  • A. filmDebut
    Indicates the first film in which an entity (typically a person) appeared or participated, marking their initial entry into film work.
  • B. soundFilmDebutDate
    Indicates the date on which an entity first appeared in a sound film.
  • C. madeProfessionalDebutIn
    Indicates the time or event in which an individual first performed or appeared in a professional capacity within a given field or organization.
  • D. firstFeatureFilmRelease
    Indicates the date or event of an entity’s debut feature-length film being publicly released.
  • E. screenDebutInMajorRoleFor
    Indicates that one entity made their first significant on-screen appearance (major role) in a particular production or work.
  • 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_69ca841d2b18819089f9faf5b2c2aec0 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd03efaa748190973916bd790f6e3a completed April 1, 2026, 11:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69d121f7a61081908801cdc965f65c3a completed April 4, 2026, 2:36 p.m.
PD Predicate disambiguation batch_69cc7a4765648190aa9445c4a22dc471 completed April 1, 2026, 1:52 a.m.
PDg Predicate description generation batch_69cc95597be081908ece2491dd2f0f74 completed April 1, 2026, 3:47 a.m.
Created at: March 30, 2026, 7:30 p.m.