Triple

T17892392
Position Surface form Disambiguated ID Type / Status
Subject Hatun E447353 entity
Predicate partiallyReplacedBy P101 FINISHED
Object Hanım
Hanım is a Turkish honorific title traditionally used to address or refer to women with respect and courtesy.
E1294054 NE FINISHED

How this triple was built (4 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: [Hatun, partiallyReplacedBy, Hanım]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hanım
Context triple: [Hatun, partiallyReplacedBy, Hanım]
  • A. 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.
  • B. Hekimhan
    Hekimhan is a town and district in Malatya Province in eastern Turkey.
  • C. Hamida
    Hamida is a central, ambitious young woman in Naguib Mahfouz’s novel "Midaq Alley," whose desire to escape poverty and traditional constraints drives much of the story’s conflict.
  • D. Müşfika Kadın
    Müşfika Kadın was one of the consorts of Ottoman Sultan Abdul Hamid II and a member of the late Ottoman imperial harem.
  • E. Peyveste Hanım
    Peyveste Hanım was one of the consorts of Ottoman Sultan Abdul Hamid II and a member of the late Ottoman imperial harem.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Hanım
Triple: [Hatun, partiallyReplacedBy, Hanım]
Generated description
Hanım is a Turkish honorific title traditionally used to address or refer to women with respect and courtesy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Hanım
Target entity description: Hanım is a Turkish honorific title traditionally used to address or refer to women with respect and courtesy.
  • A. 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.
  • B. Hekimhan
    Hekimhan is a town and district in Malatya Province in eastern Turkey.
  • C. Hamida
    Hamida is a central, ambitious young woman in Naguib Mahfouz’s novel "Midaq Alley," whose desire to escape poverty and traditional constraints drives much of the story’s conflict.
  • D. Müşfika Kadın
    Müşfika Kadın was one of the consorts of Ottoman Sultan Abdul Hamid II and a member of the late Ottoman imperial harem.
  • E. Peyveste Hanım
    Peyveste Hanım was one of the consorts of Ottoman Sultan Abdul Hamid II and a member of the late Ottoman imperial harem.
  • F. None of above. chosen

Provenance (5 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_69d8b9f59bd48190a6fc925a855b8bac completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e49d7a855c8190b20bdbf6dcd4fd47 completed April 19, 2026, 9:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0313e10c40819089cb912a020b32de completed May 12, 2026, 11:49 a.m.
NEDg Description generation batch_6a031528abac8190b5257eff1647b6b3 completed May 12, 2026, 11:55 a.m.
NED2 Entity disambiguation (via description) batch_6a03164881ec8190a783b095f3cf47b3 completed May 12, 2026, noon
Created at: April 10, 2026, 10:19 a.m.