Triple

T20081078
Position Surface form Disambiguated ID Type / Status
Subject Modern School, New Delhi E500000 entity
Predicate alumni P51 FINISHED
Object Gulzar NE NERFINISHED

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: Gulzar | Statement: [Modern School, New Delhi, alumni, Gulzar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gulzar
Context triple: [Modern School, New Delhi, alumni, Gulzar]
  • A. Gulzar chosen
    Gulzar is a renowned Indian poet, lyricist, and filmmaker celebrated for his evocative Urdu and Hindi writings and influential contributions to Indian cinema and music.
  • B. Javed Akhtar
    Javed Akhtar is a renowned Indian poet, lyricist, and screenwriter known for his influential work in Hindi cinema and outspoken advocacy of secularism and rational thought.
  • C. Shailendra
    Shailendra was a celebrated Indian poet and film lyricist, renowned for his evocative and timeless songs in classic Hindi cinema.
  • D. Sahir Ludhianvi
    Sahir Ludhianvi was a renowned Indian Urdu poet and Hindi film lyricist known for his progressive, socially conscious verse and iconic songs in classic Bollywood cinema.
  • E. Naushad
    Naushad was a legendary Indian film music director and composer renowned for his classical-based scores in Hindi cinema’s golden era.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da627770948190997f486f9a2e370f completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66557c19c8190b511857490bbd423 completed April 20, 2026, 5:41 p.m.
Created at: April 11, 2026, 3:41 p.m.