Triple

T7660243
Position Surface form Disambiguated ID Type / Status
Subject Tollywood E173485 entity
Predicate hasNotableDirector P4744 FINISHED
Object Tapan Sinha E179098 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: Tapan Sinha | Statement: [Tollywood, hasNotableDirector, Tapan Sinha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tapan Sinha
Context triple: [Tollywood, hasNotableDirector, Tapan Sinha]
  • A. Tapan Sinha chosen
    Tapan Sinha was a renowned Indian film director celebrated for his socially conscious and critically acclaimed works in Bengali cinema.
  • B. Bimal Parekh
    Bimal Parekh is an Indian businessman and co-owner of the Indian Super League football club Mumbai City FC.
  • C. M.S. Sathyu
    M.S. Sathyu is an acclaimed Indian film director best known for his socially conscious and politically charged works, including the landmark film "Garm Hava," which helped define the parallel cinema movement.
  • D. Satyajit Sen
    Satyajit Sen is an individual notable enough to be recognized as a distinguished bearer of the surname Sen.
  • E. Bimal Roy
    Bimal Roy was a renowned Indian film director celebrated for his socially conscious, realist storytelling and classic Hindi films such as "Do Bigha Zamin" and "Bandini."
  • 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_69c69955517c819085bc715b96d304d2 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c701a47a5c8190867e39f552c86787 completed March 27, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c93fa2550481908348b8b4dd23d6df completed March 29, 2026, 3:05 p.m.
Created at: March 27, 2026, 3:59 p.m.