Triple

T10125675
Position Surface form Disambiguated ID Type / Status
Subject Ghare Baire (1984 film) E226207 entity
Predicate leadActor P1507 FINISHED
Object Victor Banerjee E349131 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: Victor Banerjee | Statement: [Ghare Baire (1984 film), leadActor, Victor Banerjee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Victor Banerjee
Context triple: [Ghare Baire (1984 film), leadActor, Victor Banerjee]
  • A. Victor Banerjee chosen
    Victor Banerjee is an Indian actor known for his acclaimed performances in both Indian and international cinema, including major roles in films by directors such as David Lean and Satyajit Ray.
  • B. Ash Mukherjee
    Ash Mukherjee is a character in the British television drama series "It's a Sin," which explores the lives of young gay men during the 1980s AIDS crisis in London.
  • C. Sanjit Bhattacharya
    Sanjit Bhattacharya is a British actor known for his work in film and television and for being married to writer-comedian Meera Syal.
  • D. Sarbajit Banerjee
    Sarbajit Banerjee is a chemist known for his research in materials chemistry, particularly on phase transitions and electronic properties of transition metal oxides.
  • E. Sanjay Banerji
    Sanjay Banerji is an economist and academic recognized for his scholarly contributions associated with the Delhi School of Economics.
  • 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_69ca843057b48190a86730167f5d6b98 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cdd2ed85b4819097dfe89e044e1a90 completed April 2, 2026, 2:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2cc5cb62081908f4725de14916c11 completed April 5, 2026, 8:55 p.m.
Created at: March 30, 2026, 9:05 p.m.