Triple

T5462409
Position Surface form Disambiguated ID Type / Status
Subject Indian parallel cinema E122622 entity
Predicate notableFilm P22 FINISHED
Object Ankur E481982 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: Ankur | Statement: [Indian parallel cinema, notableFilm, Ankur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ankur
Context triple: [Indian parallel cinema, notableFilm, Ankur]
  • A. Ankur chosen
    Ankur is a landmark 1974 Indian Hindi-language film directed by Shyam Benegal that helped launch the parallel cinema movement in India.
  • B. Anish
    Anish is a given name most notably associated with Anish Kapoor, the British-Indian sculptor renowned for his large-scale, often reflective and abstract public artworks.
  • C. Vivek
    Vivek is a common Indian male given name, notably borne by entrepreneur and NBA team owner Vivek Ranadivé.
  • D. Nishant
    Nishant is a critically acclaimed 1975 Indian parallel cinema film directed by Shyam Benegal that explores themes of feudal oppression and social injustice in rural India.
  • E. Ankit Bhati
    Ankit Bhati is an Indian entrepreneur best known as the co-founder and former Chief Technology Officer of the ride-hailing company Ola.
  • 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_69bd4643f16081908d7f29e08096115a completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd92033dd08190a90bcae6b9f149d3 completed March 20, 2026, 6:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf414ebd288190ae90593232ff2db9 completed March 22, 2026, 1:09 a.m.
Created at: March 20, 2026, 2:08 p.m.