Triple

T7175446
Position Surface form Disambiguated ID Type / Status
Subject Sakarya E167306 entity
Predicate nearbyCity P350 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: [Sakarya, nearbyCity, Bilecik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bilecik
Context triple: [Sakarya, nearbyCity, 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_69c68889a2748190a316c5e65360361a completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e88ec6a8819083cbc3f4c39b8c79 completed March 27, 2026, 8:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7db0401f481909cc09c2b8c23cd24 completed March 28, 2026, 1:43 p.m.
Created at: March 27, 2026, 2:48 p.m.