Triple

T21406469
Position Surface form Disambiguated ID Type / Status
Subject Midaq Alley E528047 entity
Predicate hasCharacter P2308 FINISHED
Object Hussain Kirsha 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: Hussain Kirsha | Statement: [Midaq Alley, hasCharacter, Hussain Kirsha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hussain Kirsha
Context triple: [Midaq Alley, hasCharacter, Hussain Kirsha]
  • A. Hussain Kirsha chosen
    Hussain Kirsha is a character in Naguib Mahfouz’s novel "Midaq Alley," known as the son of a café owner whose ambitions and moral compromises reflect the social changes in mid-20th-century Cairo.
  • B. Talat Hussain
    Talat Hussain was a prominent Pakistani actor and voice artist known for his work in film, television, and radio in Pakistan and abroad.
  • C. Ilyas Khoja
    Ilyas Khoja was a 14th-century khan of Moghulistan, a Chagatai Mongol successor state in Central Asia.
  • D. Abdul Hayee
    Abdul Hayee, better known by his pen name Sahir Ludhianvi, was a renowned Indian Urdu poet and celebrated Bollywood lyricist noted for his socially conscious and emotionally powerful verse.
  • E. Nasir Hussain
    Nasir Hussain was a prominent Indian film producer, director, and screenwriter known for shaping Hindi cinema with popular musical and romantic films from the 1960s to the 1980s.
  • 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_69e0b520ee3c8190abddbee7e37e834c completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8b1b08fdc81909b3ba01add5f6484 completed April 22, 2026, 11:32 a.m.
Created at: April 16, 2026, 5:31 p.m.