Triple

T7122535
Position Surface form Disambiguated ID Type / Status
Subject Language Movement of 1952 E165980 entity
Predicate martyr P74972 FINISHED
Object Shafiur E171736 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: Shafiur | Statement: [Language Movement of 1952, martyr, Shafiur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shafiur
Context triple: [Language Movement of 1952, martyr, Shafiur]
  • A. Jasimuddin
    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. Shafiur Rahman chosen
    Shafiur Rahman was a Bengali activist who became one of the early martyrs of the 1952 Language Movement in what was then East Bengal (now Bangladesh), symbolizing the struggle for recognition of the Bengali language.
  • D. 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.
  • E. Naimul Karim
    Naimul Karim is one of the children of Jawed Karim, the computer scientist and co-founder of YouTube.
  • 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_69c6888350588190870cd552b427a1cd completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e7759a048190815689298befa8d7 completed March 27, 2026, 8:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7a32e8098819090b88fc920416f6b completed March 28, 2026, 9:45 a.m.
Created at: March 27, 2026, 2:44 p.m.