Triple

T16527889
Position Surface form Disambiguated ID Type / Status
Subject Kumar Shahani E401486 entity
Predicate directorOf P537 FINISHED
Object Tarang E1218713 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: Tarang | Statement: [Kumar Shahani, directorOf, Tarang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tarang
Context triple: [Kumar Shahani, directorOf, Tarang]
  • A. Tarang chosen
    Tarang is a 1984 Indian art film directed by Kumar Shahani, noted for its experimental narrative style and exploration of class conflict and industrial capitalism.
  • B. Tarang
    Tarang is a prominent musical composition by Indian tabla virtuoso Sandeep Das, showcasing his innovative approach to Indian classical rhythm.
  • C. Vidhaata
    Vidhaata is a 1982 Hindi action drama film directed by Subhash Ghai, known for its star-studded cast, popular music, and commercial success in Indian cinema.
  • D. Raakh
    Raakh is a 1989 Indian neo-noir crime drama film, acclaimed for its gritty storytelling and performances, and regarded as a cult classic in Hindi cinema.
  • E. Tarpeena
    Tarpeena is a small rural town and locality in South Australia, known historically for its timber and forestry industries.
  • 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_69d883838abc8190bc79cb2d41733ce2 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32ed57be481908625d4c5aab0940c completed April 18, 2026, 7:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0067a7616c8190af486bef3331e115 completed May 10, 2026, 11:10 a.m.
Created at: April 10, 2026, 5:14 a.m.