Triple

T6354353
Position Surface form Disambiguated ID Type / Status
Subject Ottoman Beylik E142953 entity
Predicate hasPart P35 FINISHED
Object Bilecik E527516 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: Bilecik | Statement: [Ottoman Beylik, hasPart, Bilecik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bilecik
Context triple: [Ottoman Beylik, hasPart, Bilecik]
  • A. Bilecik chosen
    Bilecik is a small city in northwestern Turkey known as the capital of Bilecik Province and for its proximity to the historic town of Söğüt, birthplace of the Ottoman Empire.
  • B. 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.
  • C. Kalecik
    Kalecik is a district and town in central Turkey known for its historic architecture and the locally famous Kalecik Karası grape variety.
  • D. Çankırı
    Çankırı is a small provincial city in north-central Turkey known for its historical fortifications, salt mines, and location on the Anatolian plateau.
  • E. Zonguldak
    Zonguldak is a port city on Turkey’s Black Sea coast known historically for its coal mining industry.
  • 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_69c75101ed10819083d0414fd8b6d86e completed March 28, 2026, 3:54 a.m.
Created at: March 22, 2026, 4:31 p.m.