Triple

T12325034
Position Surface form Disambiguated ID Type / Status
Subject Salman Khan E293806 entity
Predicate spouse P13 FINISHED
Object Umaima Marvi E293803 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: Umaima Marvi | Statement: [Salman Khan, spouse, Umaima Marvi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Umaima Marvi
Context triple: [Salman Khan, spouse, Umaima Marvi]
  • A. Umaima Marvi chosen
    Umaima Marvi is the wife of educator and Khan Academy founder Sal Khan.
  • B. Lateef Fatima Khan
    Lateef Fatima Khan was the mother of Bollywood superstar Shah Rukh Khan and came from a respected Muslim family with a background in social service and activism.
  • C. Hina Jilani
    Hina Jilani is a prominent Pakistani lawyer and human rights activist known for her pioneering work in women's rights, civil liberties, and international justice.
  • D. Nasira Iqbal
    Nasira Iqbal is a Pakistani jurist and former judge of the Lahore High Court, recognized as one of the country’s prominent female legal figures.
  • E. Fara Sherazi
    Fara Sherazi is a fictional CIA analyst character from the television series "Homeland," portrayed by actress Nazanin Boniadi.
  • 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_69d6ab6ae0dc8190b1522a9c1c55c114 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f4e7e588190b37e2413bc649198 completed April 10, 2026, 6:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63eefad508190be266c776525a7cc completed May 2, 2026, 6:14 p.m.
Created at: April 8, 2026, 9:53 p.m.