Triple

T21265497
Position Surface form Disambiguated ID Type / Status
Subject Govind Nihalani E524113 entity
Predicate cinematographerFor P90619 FINISHED
Object Manthan 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: Manthan | Statement: [Govind Nihalani, cinematographerFor, Manthan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manthan
Context triple: [Govind Nihalani, cinematographerFor, Manthan]
  • A. Manthan chosen
    Manthan is a landmark 1976 Indian film directed by Shyam Benegal that dramatizes the origins of India’s rural milk cooperative movement, inspired by the White Revolution.
  • B. Naman
    Naman is an endangered Oceanic language spoken by a small community in Vanuatu.
  • C. Namanve
    Namanve is an industrial and commercial area in central Uganda known for hosting the Kampala Industrial and Business Park and various manufacturing facilities.
  • D. Mandarmani
    Mandarmani is a seaside resort village in West Bengal, India, known for its long, drivable beach and growing popularity as a quieter alternative to busier coastal destinations.
  • E. Manjai Kunda
    Manjai Kunda is a residential neighborhood within the urban area of Serekunda in The Gambia.
  • 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_69e0b5156d7881909bd4f83676590715 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e735ebe09081909f74301e91b4d3d7 completed April 21, 2026, 8:31 a.m.
Created at: April 16, 2026, 4 p.m.