Triple

T14358516
Position Surface form Disambiguated ID Type / Status
Subject Michael Ealy E356034 entity
Predicate spouse P13 FINISHED
Object Khatira Rafiqzada E356043 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: Khatira Rafiqzada | Statement: [Michael Ealy, spouse, Khatira Rafiqzada]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Khatira Rafiqzada
Context triple: [Michael Ealy, spouse, Khatira Rafiqzada]
  • A. Khatira Rafiqzada chosen
    Khatira Rafiqzada is an American former actress and musician who is publicly known as the wife of actor Michael Ealy.
  • B. Sakhi Hassan Chowrangi
    Sakhi Hassan Chowrangi is a prominent traffic intersection and landmark area in Karachi, Pakistan, known for its commercial activity and proximity to the Sakhi Hassan neighborhood.
  • C. Nilofer Khan
    Nilofer Khan is an Indian academic and administrator who became the first woman to serve as Vice-Chancellor of the University of Kashmir.
  • D. Gulmancema
    Gulmancema is a Gur language spoken primarily by the Gurma people in parts of Burkina Faso and neighboring West African countries.
  • E. Intizar Hussain
    Intizar Hussain was a prominent Pakistani writer and critic renowned for his Urdu short stories and novels that blend tradition, memory, and modernist narrative techniques.
  • 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_69d82790a7e08190877e2d349b2e8d8e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8f52ca7881908704eef20228aed3 completed April 14, 2026, 7:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c48dd408190ac45ad4ca6f610c3 completed May 8, 2026, 2:36 a.m.
Created at: April 10, 2026, 1:15 a.m.