Triple

T12410841
Position Surface form Disambiguated ID Type / Status
Subject Nevşehir E296508 entity
Predicate hasTransport P1298 FINISHED
Object Nevşehir Kapadokya Airport E294558 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 Kapadokya Airport | Statement: [Nevşehir, hasTransport, Nevşehir Kapadokya Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nevşehir Kapadokya Airport
Context triple: [Nevşehir, hasTransport, Nevşehir Kapadokya Airport]
  • A. Nevşehir Kapadokya Airport chosen
    Nevşehir Kapadokya Airport is a regional airport in central Turkey that serves as a primary air gateway for tourists visiting the Cappadocia region.
  • B. Konya Airport
    Konya Airport is a combined civil and military airport serving the city of Konya in central Turkey.
  • C. Kayseri Erkilet Airport
    Kayseri Erkilet Airport is a regional and international airport in central Turkey that serves as a major air gateway for travelers visiting the Cappadocia region.
  • D. Sivas Nuri Demirağ Airport
    Sivas Nuri Demirağ Airport is a public airport serving the city and province of Sivas in central Turkey, providing domestic and limited international air connections.
  • E. Oğuzeli Airport
    Oğuzeli Airport is the main public airport serving the city and province of Gaziantep in southeastern Turkey.
  • 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_69d6ad9f464c81909db36d7e96e34b9e completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d4b86c88190afba0de15b34eee9 completed April 10, 2026, 7:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f671852f588190924ded1c0a360b47 completed May 2, 2026, 9:49 p.m.
Created at: April 8, 2026, 9:55 p.m.