Triple

T6354343
Position Surface form Disambiguated ID Type / Status
Subject Ottoman Beylik E142953 entity
Predicate capital P234 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: [Ottoman Beylik, capital, Söğüt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Söğüt
Context triple: [Ottoman Beylik, capital, 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_69c008d6dcbc8190aa1c2f1fd8916b42 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c067e0cf1081908ee7e83b9dcf740e completed March 22, 2026, 10:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69c70060c7788190aab7ca88615d6e71 completed March 27, 2026, 10:10 p.m.
Created at: March 22, 2026, 4:31 p.m.