Triple

T16183278
Position Surface form Disambiguated ID Type / Status
Subject Qayamat Se Qayamat Tak E392737 entity
Predicate editor P1954 FINISHED
Object Zafar Sultan
Zafar Sultan is a film editor best known for his work on the influential Hindi romantic drama "Qayamat Se Qayamat Tak."
E1209004 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: Zafar Sultan | Statement: [Qayamat Se Qayamat Tak, editor, Zafar Sultan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zafar Sultan
Context triple: [Qayamat Se Qayamat Tak, editor, Zafar Sultan]
  • A. Gul Hayat Begum
    Gul Hayat Begum was the wife of prominent Sindhi nationalist leader and intellectual G. M. Syed.
  • B. Shahzadi Khanam
    Shahzadi Khanam was a Mughal-era noblewoman best known as the daughter of the Bengal Nawab Alivardi Khan.
  • C. Khanum Sultan Begum
    Khanum Sultan Begum was a Mughal princess, known as one of the daughters of the emperor Akbar the Great.
  • D. Fatima Sultan Agha
    Fatima Sultan Agha was a Timurid noblewoman known as the consort of Umar Sheikh Mirza II and a member of the wider Timurid royal household.
  • E. Salima Sultan Begum
    Salima Sultan Begum was a Mughal empress and influential consort in the court of Emperor Akbar, known for her political acumen and high status within the imperial harem.
  • 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: Zafar Sultan
Triple: [Qayamat Se Qayamat Tak, editor, Zafar Sultan]
Generated description
Zafar Sultan is a film editor best known for his work on the influential Hindi romantic drama "Qayamat Se Qayamat Tak."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Zafar Sultan
Target entity description: Zafar Sultan is a film editor best known for his work on the influential Hindi romantic drama "Qayamat Se Qayamat Tak."
  • A. Gul Hayat Begum
    Gul Hayat Begum was the wife of prominent Sindhi nationalist leader and intellectual G. M. Syed.
  • B. Shahzadi Khanam
    Shahzadi Khanam was a Mughal-era noblewoman best known as the daughter of the Bengal Nawab Alivardi Khan.
  • C. Khanum Sultan Begum
    Khanum Sultan Begum was a Mughal princess, known as one of the daughters of the emperor Akbar the Great.
  • D. Fatima Sultan Agha
    Fatima Sultan Agha was a Timurid noblewoman known as the consort of Umar Sheikh Mirza II and a member of the wider Timurid royal household.
  • E. Salima Sultan Begum
    Salima Sultan Begum was a Mughal empress and influential consort in the court of Emperor Akbar, known for her political acumen and high status within the imperial harem.
  • 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_69d87f1e49ac8190a311b54d32990576 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e2205ef39081908da383abdebc2ccc completed April 17, 2026, 11:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a002d9c35248190a5540a692503c989 completed May 10, 2026, 7:02 a.m.
NEDg Description generation batch_6a002ec2fd948190878af958d0b90ce6 completed May 10, 2026, 7:07 a.m.
NED2 Entity disambiguation (via description) batch_6a00312a4fc48190b6bd6ad9db71bb4d completed May 10, 2026, 7:18 a.m.
Created at: April 10, 2026, 5:02 a.m.