Triple

T5128980
Position Surface form Disambiguated ID Type / Status
Subject Suchitra Sen E115648 entity
Predicate notableWork P4 FINISHED
Object Mamta
Mamta is a classic 1966 Hindi drama film starring Suchitra Sen, known for its emotional story of sacrifice and maternal love.
 E498191 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: Mamta | Statement: [Suchitra Sen, notableWork, Mamta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mamta
Context triple: [Suchitra Sen, notableWork, Mamta]
  • A. Bhagirathi Sapre
    Bhagirathi Sapre was the mother of Rani Lakshmibai, the famed warrior queen of Jhansi who became a symbol of resistance during the Indian Rebellion of 1857.
  • B. Vandana
    Vandana is the first name of Vandana Shiva, an Indian scholar, environmental activist, and advocate of ecofeminism and sustainable agriculture.
  • C. Vishakha
    Vishakha is a celebrated Marathi poetry collection by Vishnu Vaman Shirwadkar (Kusumagraj), renowned for its lyrical depth and humanistic themes.
  • D. Vishakha
    Vishakha is one of the principal gopis in Hindu devotional tradition, revered as a close companion and intimate devotee of Lord Krishna and Radha.
  • E. Kumudavathi
    Kumudavathi is a river in the Indian state of Karnataka that serves as a tributary of the Arkavathi River.
  • 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: Mamta
Triple: [Suchitra Sen, notableWork, Mamta]
Generated description
Mamta is a classic 1966 Hindi drama film starring Suchitra Sen, known for its emotional story of sacrifice and maternal love.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mamta
Target entity description: Mamta is a classic 1966 Hindi drama film starring Suchitra Sen, known for its emotional story of sacrifice and maternal love.
  • A. Bhagirathi Sapre
    Bhagirathi Sapre was the mother of Rani Lakshmibai, the famed warrior queen of Jhansi who became a symbol of resistance during the Indian Rebellion of 1857.
  • B. Vandana
    Vandana is the first name of Vandana Shiva, an Indian scholar, environmental activist, and advocate of ecofeminism and sustainable agriculture.
  • C. Vishakha
    Vishakha is a celebrated Marathi poetry collection by Vishnu Vaman Shirwadkar (Kusumagraj), renowned for its lyrical depth and humanistic themes.
  • D. Vishakha
    Vishakha is one of the principal gopis in Hindu devotional tradition, revered as a close companion and intimate devotee of Lord Krishna and Radha.
  • E. Kumudavathi
    Kumudavathi is a river in the Indian state of Karnataka that serves as a tributary of the Arkavathi River.
  • 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_69bd444426bc819099ccd23f141e22aa completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd7825facc8190b2a6c17216290b5c completed March 20, 2026, 4:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69becfd90a848190a1c78063a437cf3c completed March 21, 2026, 5:05 p.m.
NEDg Description generation batch_69bed21a34f881908c3ef34c0971e7b5 completed March 21, 2026, 5:15 p.m.
NED2 Entity disambiguation (via description) batch_69bed2819f408190adc04c438706bfff completed March 21, 2026, 5:16 p.m.
Created at: March 20, 2026, 1:42 p.m.