Triple

T12353807
Position Surface form Disambiguated ID Type / Status
Subject Melendiz Mountains E294556 entity
Predicate nearbySettlement P350 FINISHED
Object Aksaray E351172 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: Aksaray | Statement: [Melendiz Mountains, nearbySettlement, Aksaray]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aksaray
Context triple: [Melendiz Mountains, nearbySettlement, Aksaray]
  • A. Aksaray chosen
    Aksaray is a historic city in central Turkey known for its location on the ancient Silk Road and its proximity to the Cappadocia region.
  • B. Amasya
    Amasya is a historic city in northern Turkey, renowned for its Ottoman-era architecture, rock tombs of Pontic kings, and scenic setting along the Yeşilırmak River.
  • C. Kütahya
    Kütahya is a historic city in western Turkey known for its Ottoman-era architecture and traditional ceramic and tile production.
  • 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. 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.
  • 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_69d6ab6ccbec8190b09e2d357aa80064 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f8bc60c8190b0ceb84093e70db4 completed April 10, 2026, 6:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f726570a2481909f417be6e38d283a completed May 3, 2026, 10:41 a.m.
Created at: April 8, 2026, 9:54 p.m.