Triple

T16183370
Position Surface form Disambiguated ID Type / Status
Subject Jo Jeeta Wohi Sikandar E392738 entity
Predicate lyricist P1360 FINISHED
Object Majrooh Sultanpuri E634219 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: Majrooh Sultanpuri | Statement: [Jo Jeeta Wohi Sikandar, lyricist, Majrooh Sultanpuri]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Majrooh Sultanpuri
Context triple: [Jo Jeeta Wohi Sikandar, lyricist, Majrooh Sultanpuri]
  • A. Majrooh Sultanpuri chosen
    Majrooh Sultanpuri was a celebrated Indian Urdu poet and prolific film lyricist whose songs became classics of Hindi cinema from the 1940s onward.
  • B. Gulzar Houz
    Gulzar Houz is a historic fountain and landmark in Hyderabad, India, known for its central location in the old city and its cultural significance.
  • C. Sattar Khan
    Sattar Khan was a prominent Iranian revolutionary leader and national hero who played a key role in defending and advancing the goals of the Persian Constitutional Revolution in the early 20th century.
  • D. Najeeb Khan
    Najeeb Khan is an Indian cinematographer best known for his work on the iconic 1992 coming-of-age sports film "Jo Jeeta Wohi Sikandar."
  • E. Farrukh Dhondy
    Farrukh Dhondy is a British-Indian writer, playwright, and former commissioning editor for Channel 4 known for his works on race, politics, and South Asian history.
  • 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_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_6a006796bed4819085d988d7f2d7afcb completed May 10, 2026, 11:10 a.m.
Created at: April 10, 2026, 5:02 a.m.