Triple

T10660573
Position Surface form Disambiguated ID Type / Status
Subject Hasnat Khan E251212 entity
Predicate givenName P17 FINISHED
Object Hasnat E251212 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: Hasnat | Statement: [Hasnat Khan, givenName, Hasnat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hasnat
Context triple: [Hasnat Khan, givenName, Hasnat]
  • A. Hasnat Khan chosen
    Hasnat Khan is a British-Pakistani heart surgeon best known for his romantic relationship with Diana, Princess of Wales.
  • B. Nasir
    Nasir is a creative work associated with Wyoming Sessions, likely a music release or recording project.
  • C. Thadiq
    Thadiq is a town in central Saudi Arabia known for its traditional architecture and location within the Riyadh administrative region.
  • D. Kashif
    Kashif was an American R&B singer, songwriter, and producer known for his influential 1980s work that helped shape the post-disco and urban contemporary sound.
  • E. Zafar
    Zafar was an important ancient South Arabian city that served as the political and cultural center of the Himyarite Kingdom in what is now Yemen.
  • 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_69d6aa5b0d2881909584b20efc5877f0 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6e017f97c8190b22765a6f1e6719d completed April 8, 2026, 11:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69d9885dc17881909df20abedd9da5e3 completed April 10, 2026, 11:31 p.m.
Created at: April 8, 2026, 9:07 p.m.