Triple

T23224270
Position Surface form Disambiguated ID Type / Status
Subject Bengali popular culture E580976 entity
Predicate hasKeyFigure P810 FINISHED
Object Jasimuddin 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: Jasimuddin | Statement: [Bengali popular culture, hasKeyFigure, Jasimuddin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jasimuddin
Context triple: [Bengali popular culture, hasKeyFigure, Jasimuddin]
  • A. Jasimuddin chosen
    Jasimuddin was a renowned Bengali poet and folklorist celebrated for his vivid depictions of rural Bengal and its people.
  • B. Khaliquzzaman
    Khaliquzzaman was a prominent South Asian Muslim politician and leader active during the Indian independence movement and the early years of Pakistan.
  • C. Jahangir Mohammed
    Jahangir Mohammed is a technology entrepreneur best known as the founder of Jasper Technologies, a leading platform for managing Internet of Things (IoT) services.
  • D. Faysal
    Faysal is a male given name of Arabic origin, commonly used in the Middle East and among Arabic-speaking communities.
  • E. Abdul Khalek
    Abdul Khalek is the given name of Abdul Khalek Hassouna, an Egyptian diplomat who served as Secretary-General of the Arab League.
  • 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_69e246043c48819089bae72c9a9c306c completed April 17, 2026, 2:39 p.m.
NER Named-entity recognition batch_69f1922b4a348190ae570a869e30059f completed April 29, 2026, 5:07 a.m.
Created at: April 17, 2026, 4:08 p.m.