Triple

T20282757
Position Surface form Disambiguated ID Type / Status
Subject Ashfaq Ulla Khan E503191 entity
Predicate givenName P17 FINISHED
Object Ashfaq E500075 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: Ashfaq | Statement: [Ashfaq Ulla Khan, givenName, Ashfaq]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ashfaq
Context triple: [Ashfaq Ulla Khan, givenName, Ashfaq]
  • A. Ashfaq chosen
    Ashfaq is the given name of Ashfaqulla Khan, an Indian freedom fighter and revolutionary associated with the Hindustan Republican Association during the struggle against British rule.
  • B. Asif
    Asif is a common male given name used in South Asian and Middle Eastern cultures, notably borne by Pakistani politician Asif Ali Zardari.
  • C. Farooq
    Farooq is a common male given name of Arabic origin, widely used in Muslim communities across South Asia and the Middle East.
  • D. Faysal
    Faysal is a male given name of Arabic origin, commonly used in the Middle East and among Arabic-speaking communities.
  • 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_69e0b4b0e79c8190bd61f22ef1329fa8 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6768f86448190842389a98b93a918 completed April 20, 2026, 6:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a085a27ba5081908af4f2cdc3a2040f completed May 16, 2026, 11:51 a.m.
Created at: April 16, 2026, 10:40 a.m.