Triple

T7816072
Position Surface form Disambiguated ID Type / Status
Subject Sharmila Tagore E181009 entity
Predicate birthName P65 FINISHED
Object Begum Ayesha Sultana
Begum Ayesha Sultana is the birth name of Sharmila Tagore, a celebrated Indian film actress known for her work in both Hindi and Bengali cinema.
 E705546 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: Begum Ayesha Sultana | Statement: [Sharmila Tagore, birthName, Begum Ayesha Sultana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Begum Ayesha Sultana
Context triple: [Sharmila Tagore, birthName, Begum Ayesha Sultana]
  • A. Lutfunnisa Begum
    Lutfunnisa Begum was a consort of Siraj ud-Daulah, the last independent Nawab of Bengal in the mid-18th century.
  • B. Qudsia Begum
    Qudsia Begum was a Mughal royal consort and influential matriarch best known as the mother of Emperor Akbar II.
  • C. Dildar Begum
    Dildar Begum was a consort of the Mughal emperor Babur and the mother of his son Hindal Mirza.
  • D. Rifa’at Begum
    Rifa’at Begum was the wife of Iskander Mirza, the first President of Pakistan, and thus served as Pakistan’s First Lady during his tenure.
  • E. Mahlara Begum
    Mahlara Begum was a consort of the Mughal emperor Akbar II during the late Mughal period in India.
  • 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: Begum Ayesha Sultana
Triple: [Sharmila Tagore, birthName, Begum Ayesha Sultana]
Generated description
Begum Ayesha Sultana is the birth name of Sharmila Tagore, a celebrated Indian film actress known for her work in both Hindi and Bengali cinema.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Begum Ayesha Sultana
Target entity description: Begum Ayesha Sultana is the birth name of Sharmila Tagore, a celebrated Indian film actress known for her work in both Hindi and Bengali cinema.
  • A. Lutfunnisa Begum
    Lutfunnisa Begum was a consort of Siraj ud-Daulah, the last independent Nawab of Bengal in the mid-18th century.
  • B. Qudsia Begum
    Qudsia Begum was a Mughal royal consort and influential matriarch best known as the mother of Emperor Akbar II.
  • C. Dildar Begum
    Dildar Begum was a consort of the Mughal emperor Babur and the mother of his son Hindal Mirza.
  • D. Rifa’at Begum
    Rifa’at Begum was the wife of Iskander Mirza, the first President of Pakistan, and thus served as Pakistan’s First Lady during his tenure.
  • E. Mahlara Begum
    Mahlara Begum was a consort of the Mughal emperor Akbar II during the late Mughal period in India.
  • 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_69ca828153f48190bdb27ac46f8e0745 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69caf96d1f088190a1d005ffb019afe9 completed March 30, 2026, 10:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69cbded6d1a881909d9816fcd8a55e49 completed March 31, 2026, 2:48 p.m.
NEDg Description generation batch_69cc46bca04481908852425c214a4e34 completed March 31, 2026, 10:12 p.m.
NED2 Entity disambiguation (via description) batch_69cc49129e188190aaebd6a1188788d9 completed March 31, 2026, 10:22 p.m.
Created at: March 30, 2026, 4:39 p.m.