Triple

T19273663
Position Surface form Disambiguated ID Type / Status
Subject Zubeidaa E481991 entity
Predicate producer P490 FINISHED
Object Zee Telefilms NE NERFINISHED

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: Zee Telefilms | Statement: [Zubeidaa, producer, Zee Telefilms]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zee Telefilms
Context triple: [Zubeidaa, producer, Zee Telefilms]
  • A. Zee Studios chosen
    Zee Studios is a major Indian film production and distribution company known for backing prominent Marathi-language films as well as movies in other regional and Hindi markets.
  • B. Balaji Telefilms
    Balaji Telefilms is a major Indian television and film production company known for creating numerous popular Hindi soap operas and entertainment content.
  • C. Vijay TV
    Vijay TV is a popular Tamil-language television channel in India known for its entertainment shows, reality programs, and serials.
  • D. Mu.ZEE
    Mu.ZEE is a modern and contemporary art museum in Ostend, Belgium, renowned for its extensive collection of Belgian art from the late 19th century to today.
  • E. YRF Television
    YRF Television is the television production and content arm of Indian entertainment company Yash Raj Films, known for creating Hindi-language TV shows and series.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8ce54cc8190998418ff1f66ef28 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fbba7758819081c1c78667c59c5e completed April 20, 2026, 10:11 a.m.
Created at: April 10, 2026, 1:29 p.m.