Triple

T19707519
Position Surface form Disambiguated ID Type / Status
Subject Home Rule for India E473254 entity
Predicate hasLeader P981 FINISHED
Object S. N. Banerjee 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: S. N. Banerjee | Statement: [Home Rule for India, hasLeader, S. N. Banerjee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: S. N. Banerjee
Context triple: [Home Rule for India, hasLeader, S. N. Banerjee]
  • A. S. N. Bannerjee chosen
    S. N. Bannerjee was a prominent Indian nationalist leader and educator who played a key role in the early Indian National Congress and the broader struggle against British colonial rule.
  • B. S K Banerjee
    S. K. Banerjee is a distinguished scholar associated with the Delhi School of Economics, recognized for significant contributions to economic research and education in India.
  • C. Asit K. Biswas
    Asit K. Biswas is a renowned water resources expert and academic known for his pioneering work in global water management and policy.
  • 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. Surajit Chaudhuri
    Surajit Chaudhuri is a prominent computer scientist known for his influential research in database systems and data management, particularly in query optimization and data analytics.
  • 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_69d8e516dd048190a0b6c93ea3e71f58 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e642bb5cd4819090e4c62bd74c4324 completed April 20, 2026, 3:14 p.m.
Created at: April 10, 2026, 1:46 p.m.