Triple

T12353885
Position Surface form Disambiguated ID Type / Status
Subject Nevşehir Kapadokya Airport E294558 entity
Predicate cityServed P82 FINISHED
Object Göreme E294548 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: Göreme | Statement: [Nevşehir Kapadokya Airport, cityServed, Göreme]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Göreme
Context triple: [Nevşehir Kapadokya Airport, cityServed, Göreme]
  • A. Göreme chosen
    Göreme is a historic town in central Turkey renowned for its unique rock formations, cave dwellings, and rock-cut churches within the Göreme National Park in the Cappadocia region.
  • B. Gölbaşı
    Gölbaşı is a district and suburban area of Ankara in central Turkey, known for its lakes, recreational areas, and proximity to the capital city.
  • C. Gemlik
    Gemlik is a coastal town and district in Bursa Province, northwestern Turkey, known for its port on the Sea of Marmara and its olive production.
  • D. Yüreğir
    Yüreğir is a metropolitan district and municipality of Adana Province in southern Turkey, located on the eastern bank of the Seyhan River and forming part of the city of Adana.
  • E. Suşehri
    Suşehri is a town and district in northeastern Turkey known for its location within Sivas Province and its surrounding mountainous landscape.
  • 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_69f671837a5c81908a7f41ac7e2bef59 completed May 2, 2026, 9:49 p.m.
Created at: April 8, 2026, 9:54 p.m.