Triple

T10807357
Position Surface form Disambiguated ID Type / Status
Subject Basu E255002 entity
Predicate hasLanguageForm P6281 FINISHED
Object বসু E254908 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: বসু | Statement: [Basu, hasLanguageForm, বসু]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: বসু
Context triple: [Basu, hasLanguageForm, বসু]
  • A. Basu chosen
    Basu is an Indian surname, particularly common among Bengali communities, that is closely related to and sometimes used as a variant of the surname Bose.
  • B. Bhudev Mukhopadhyay
    Bhudev Mukhopadhyay was a 19th-century Bengali writer, educator, and social thinker known for his contributions to early modern Bengali literature and intellectual life.
  • C. Sailoz Mookherjea
    Sailoz Mookherjea was a prominent Indian modernist painter associated with the Bengal School of Art, known for his lyrical landscapes and expressive use of color.
  • D. Somen Bose
    Somen Bose is an actor known for appearing in the Indian film "Nayak."
  • E. Basu Bhattacharya
    Basu Bhattacharya was an influential Indian filmmaker known for his introspective, realist films that helped shape the parallel cinema movement, particularly through nuanced explorations of middle-class marriage and relationships.
  • 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_69d6aa61c15c8190a1839550c56e75e1 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d733b506488190921e6a1f4168dd9e completed April 9, 2026, 5:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69de8513fe0881909d6833c85aac03a8 completed April 14, 2026, 6:19 p.m.
Created at: April 8, 2026, 9:18 p.m.