Triple

T16090533
Position Surface form Disambiguated ID Type / Status
Subject Sarat Chandra Bose E390347 entity
Predicate child P120 FINISHED
Object Subrata Bose
Subrata Bose was an Indian politician and parliamentarian, known for his role in West Bengal politics and as a member of the prominent Bose family.
E1195203 NE FINISHED

How this triple was built (4 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: Subrata Bose | Statement: [Sarat Chandra Bose, child, Subrata Bose]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Subrata Bose
Context triple: [Sarat Chandra Bose, child, Subrata Bose]
  • A. Subrata Mitra
    Subrata Mitra was an acclaimed Indian cinematographer best known for his pioneering visual work on Satyajit Ray’s films, which helped define the look of parallel cinema.
  • B. Subrata Roy
    Subrata Roy is an Indian businessman best known as the founder and chairman of the Sahara India Pariwar conglomerate.
  • C. Subrata Saha
    Subrata Saha is a notable individual distinguished enough to be specifically recognized as a prominent bearer of the surname Saha.
  • D. 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.
  • E. 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.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Subrata Bose
Triple: [Sarat Chandra Bose, child, Subrata Bose]
Generated description
Subrata Bose was an Indian politician and parliamentarian, known for his role in West Bengal politics and as a member of the prominent Bose family.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Subrata Bose
Target entity description: Subrata Bose was an Indian politician and parliamentarian, known for his role in West Bengal politics and as a member of the prominent Bose family.
  • A. Subrata Mitra
    Subrata Mitra was an acclaimed Indian cinematographer best known for his pioneering visual work on Satyajit Ray’s films, which helped define the look of parallel cinema.
  • B. Subrata Roy
    Subrata Roy is an Indian businessman best known as the founder and chairman of the Sahara India Pariwar conglomerate.
  • C. Subrata Saha
    Subrata Saha is a notable individual distinguished enough to be specifically recognized as a prominent bearer of the surname Saha.
  • D. 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.
  • E. 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.
  • F. None of above. chosen

Provenance (5 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_69d87f198bc48190a8b7e53ca15b7ead completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e184522b2c8190986daae6cb2d9db4 completed April 17, 2026, 12:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffeb934b448190a486401ac6c01065 completed May 10, 2026, 2:21 a.m.
NEDg Description generation batch_69ffefb0225881909982c384a5beb50a completed May 10, 2026, 2:38 a.m.
NED2 Entity disambiguation (via description) batch_69fff01e1b808190931fff3e91939b82 completed May 10, 2026, 2:40 a.m.
Created at: April 10, 2026, 4:59 a.m.