Triple

T19699985
Position Surface form Disambiguated ID Type / Status
Subject Peyveste Hanım E473064 entity
Predicate nobleTitle P914 FINISHED
Object Hanım 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: Hanım | Statement: [Peyveste Hanım, nobleTitle, Hanım]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hanım
Context triple: [Peyveste Hanım, nobleTitle, Hanım]
  • A. Hanım chosen
    Hanım is a Turkish honorific title traditionally used to address or refer to women with respect and courtesy.
  • B. Mihrengiz Kadın
    Mihrengiz Kadın was one of the consorts of Ottoman Sultan Mehmed V Reşad and a member of the late Ottoman imperial harem.
  • C. Kadın
    Kadın is an Ottoman imperial title historically given to the official consorts of the sultans, ranking below the valide sultan but above most other women in the harem hierarchy.
  • D. Hüsnümah Kadın
    Hüsnümah Kadın was one of the consorts of Ottoman Sultan Murad V, belonging to the imperial harem during the late 19th century.
  • E. Hümaşah Kadın
    Hümaşah Kadın was a consort of Ottoman Sultan Abdul Hamid I and a member of the imperial harem during the late 18th century.
  • 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_69d8e515bef88190bc30781aea50537a completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e642b4e01081908f857f219d5d7a24 completed April 20, 2026, 3:13 p.m.
Created at: April 10, 2026, 1:46 p.m.