Triple

T22292349
Position Surface form Disambiguated ID Type / Status
Subject Fandry E551028 entity
Predicate writer P1360 FINISHED
Object Nagraj Manjule 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: Nagraj Manjule | Statement: [Fandry, writer, Nagraj Manjule]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nagraj Manjule
Context triple: [Fandry, writer, Nagraj Manjule]
  • A. Nagraj Manjule chosen
    Nagraj Manjule is an acclaimed Indian filmmaker and screenwriter known for his socially conscious, award-winning Marathi films such as "Fandry" and "Sairat."
  • B. Madhur Bhandarkar
    Madhur Bhandarkar is a National Award–winning Indian film director known for his hard-hitting, realistic portrayals of urban society in Hindi cinema.
  • C. Amit Masurkar
    Amit Masurkar is an Indian film director and screenwriter best known for critically acclaimed Hindi films like "Sulemani Keeda" and the political satire "Newton."
  • D. Tigmanshu Dhulia
    Tigmanshu Dhulia is an Indian filmmaker, screenwriter, and actor known for his gritty storytelling in films like "Paan Singh Tomar" and his influential work in Hindi cinema.
  • E. Prakash Jha
    Prakash Jha is an Indian film producer, director, and screenwriter best known for his politically charged and socially relevant Hindi films such as "Gangaajal," "Raajneeti," and "Aarakshan."
  • 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_69e11e45fb848190a1b2ae21296e3a5f completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f1560d1ec48190ab86f158c94b677b completed April 29, 2026, 12:51 a.m.
Created at: April 16, 2026, 8:41 p.m.