Triple

T23224342
Position Surface form Disambiguated ID Type / Status
Subject Bengali popular culture E580976 entity
Predicate hasKeyFigure P810 FINISHED
Object Bidya Sinha Saha Mim
Bidya Sinha Saha Mim is a prominent Bangladeshi actress and model known for her leading roles in Bengali films and television dramas.
E1578629 NE FINISHED

How this triple was built (4 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: Bidya Sinha Saha Mim | Statement: [Bengali popular culture, hasKeyFigure, Bidya Sinha Saha Mim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bidya Sinha Saha Mim
Context triple: [Bengali popular culture, hasKeyFigure, Bidya Sinha Saha Mim]
  • A. Dibaratrir Kabya
    Dibaratrir Kabya is a renowned Bengali novel celebrated for its psychological depth and social realism.
  • B. Swagata Biday
    Swagata Biday is a notable literary work by prominent Bengali writer and poet Buddhadeva Bose.
  • C. Odia Panjika
    Odia Panjika is the traditional Hindu almanac used in the Indian state of Odisha to determine religious festivals, auspicious timings, and regional observances.
  • D. Rupasi Bangla
    Rupasi Bangla is a celebrated Bengali poetry collection by Jibanananda Das, renowned for its lyrical evocation of the natural beauty and cultural soul of Bengal.
  • E. Tillotama Shome
    Tillotama Shome is an acclaimed Indian actress known for her nuanced performances in independent and mainstream films across multiple languages.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Bidya Sinha Saha Mim
Triple: [Bengali popular culture, hasKeyFigure, Bidya Sinha Saha Mim]
Generated description
Bidya Sinha Saha Mim is a prominent Bangladeshi actress and model known for her leading roles in Bengali films and television dramas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Bidya Sinha Saha Mim
Target entity description: Bidya Sinha Saha Mim is a prominent Bangladeshi actress and model known for her leading roles in Bengali films and television dramas.
  • A. Dibaratrir Kabya
    Dibaratrir Kabya is a renowned Bengali novel celebrated for its psychological depth and social realism.
  • B. Swagata Biday
    Swagata Biday is a notable literary work by prominent Bengali writer and poet Buddhadeva Bose.
  • C. Odia Panjika
    Odia Panjika is the traditional Hindu almanac used in the Indian state of Odisha to determine religious festivals, auspicious timings, and regional observances.
  • D. Rupasi Bangla
    Rupasi Bangla is a celebrated Bengali poetry collection by Jibanananda Das, renowned for its lyrical evocation of the natural beauty and cultural soul of Bengal.
  • E. Tillotama Shome
    Tillotama Shome is an acclaimed Indian actress known for her nuanced performances in independent and mainstream films across multiple languages.
  • F. None of above. chosen

Provenance (5 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.
NED1 Entity disambiguation (via context triple) batch_6a0c3f51c9ec81909d8838c7e1d47468 completed May 19, 2026, 10:45 a.m.
NEDg Description generation batch_6a0c43740a7c81909e9af7a9974a5700 completed May 19, 2026, 11:03 a.m.
NED2 Entity disambiguation (via description) batch_6a0c44d05c748190a5f4ab5f76dfcaab completed May 19, 2026, 11:09 a.m.
Created at: April 17, 2026, 4:08 p.m.