Triple

T5461798
Position Surface form Disambiguated ID Type / Status
Subject Indian cinema E122609 entity
Predicate language P15 FINISHED
Object Bengali E5055 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: Bengali | Statement: [Indian cinema, language, Bengali]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bengali
Context triple: [Indian cinema, language, Bengali]
  • A. Bengali chosen
    Bengali is an Indo-Aryan language spoken primarily in the Bengal region of South Asia and serving as the official and most widely used language of Bangladesh and the Indian state of West Bengal.
  • B. Bangladeshi
    Bangladeshi refers to a person or attribute associated with Bangladesh, particularly its people, nationality, or cultural heritage.
  • C. Bhojpuri
    Bhojpuri is an Indo-Aryan language spoken primarily in eastern Uttar Pradesh, western Bihar, and parts of Nepal, with a rich folk culture and a large diaspora community.
  • D. Hindi
    Hindi is an Indo-Aryan language widely spoken across northern and central India and used in government, education, media, and popular culture.
  • E. Assamese
    Assamese is an Eastern Indo-Aryan language primarily spoken in the Indian state of Assam and recognized as one of the official languages of India.
  • 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_69bd4643f16081908d7f29e08096115a completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd9201dbfc8190bea22d6ecbc25b3e completed March 20, 2026, 6:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf414ebd288190ae90593232ff2db9 completed March 22, 2026, 1:09 a.m.
Created at: March 20, 2026, 2:08 p.m.