Triple

T4586682
Position Surface form Disambiguated ID Type / Status
Subject Malhun Hatun E103383 entity
Predicate residence P75 FINISHED
Object Söğüt E120912 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: Söğüt | Statement: [Malhun Hatun, residence, Söğüt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Söğüt
Context triple: [Malhun Hatun, residence, Söğüt]
  • A. Söğüt chosen
    Söğüt is a historic town in northwestern Turkey renowned as the early center of the Ottoman beylik and the birthplace of the Ottoman Empire.
  • B. Menemen
    Menemen is a district and town in İzmir Province, Turkey, known for its agricultural production and as part of the greater İzmir metropolitan area.
  • C. Karabük
    Karabük is an industrial city in northern Turkey best known for its historic iron and steel industry and its proximity to the UNESCO-listed Ottoman town of Safranbolu.
  • D. Doğanhisar
    Doğanhisar is a rural district and town in central Turkey known for its agricultural economy and location within the Konya region.
  • E. Boğazköy
    Boğazköy is an important archaeological site in central Turkey best known as the location of Hattusa, the former capital of the Hittite Empire.
  • 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_69bd43dccaf08190aa89e9991a289719 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5906a43c81908fb11bf8f94be122 completed March 20, 2026, 2:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69be5c76788c8190b6b9dfe008957222 completed March 21, 2026, 8:53 a.m.
Created at: March 20, 2026, 1:10 p.m.