Triple

T168107
Position Surface form Disambiguated ID Type / Status
Subject Amartya Sen E3058 entity
Predicate languageSpoken P151 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: [Amartya Sen, languageSpoken, Bengali]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bengali
Context triple: [Amartya Sen, languageSpoken, 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. Hindi
    Hindi is an Indo-Aryan language widely spoken across northern and central India and used in government, education, media, and popular culture.
  • C. Maithili
    Maithili is an Indo-Aryan language spoken primarily in the eastern Indian state of Bihar and neighboring regions, with a rich literary tradition and official recognition in India.
  • D. Sindhi
    Sindhi is an Indo-Aryan language spoken primarily in Pakistan and India, known for its rich literary tradition and distinct script variants.
  • E. Kannada
    Kannada is a major Dravidian language predominantly spoken in the Indian state of Karnataka and surrounding regions, with a rich literary tradition spanning over a millennium.
  • 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_69a2524ce1e48190ab066bf72859f474 completed Feb. 28, 2026, 2:26 a.m.
NER Named-entity recognition batch_69a258b58efc8190959c86f73d67b744 completed Feb. 28, 2026, 2:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2e0f8bf748190b2752f250a63d8e3 completed Feb. 28, 2026, 12:35 p.m.
Created at: Feb. 28, 2026, 2:34 a.m.