Triple

T5491973
Position Surface form Disambiguated ID Type / Status
Subject Asian Turkey E123721 entity
Predicate containsCity P294 FINISHED
Object Nevşehir E296508 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: Nevşehir | Statement: [Asian Turkey, containsCity, Nevşehir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nevşehir
Context triple: [Asian Turkey, containsCity, Nevşehir]
  • A. Nevşehir chosen
    Nevşehir is a city in central Turkey that serves as the main urban center and gateway to the historic, cave-dotted region of Cappadocia.
  • B. Kütahya
    Kütahya is a historic city in western Turkey known for its Ottoman-era architecture and traditional ceramic and tile production.
  • C. Çankırı
    Çankırı is a small provincial city in north-central Turkey known for its historical fortifications, salt mines, and location on the Anatolian plateau.
  • D. Aksaray
    Aksaray is a historic city in central Turkey known for its location on the ancient Silk Road and its proximity to the Cappadocia region.
  • 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_69bd464a2d908190869324ce176779c8 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd9280403c8190baaa3f7923449a37 completed March 20, 2026, 6:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d4f458288190ac1d6a8489bbc943 completed March 27, 2026, 7:05 p.m.
Created at: March 20, 2026, 2:10 p.m.