Triple

T17700447
Position Surface form Disambiguated ID Type / Status
Subject LTAN E441283 entity
Predicate identifies P310 FINISHED
Object Konya Airport NE NERFINISHED

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: Konya Airport | Statement: [LTAN, identifies, Konya Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Konya Airport
Context triple: [LTAN, identifies, Konya Airport]
  • A. Konya Airport chosen
    Konya Airport is a combined civil and military airport serving the city of Konya in central Turkey.
  • B. 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.
  • C. Nevşehir Kapadokya Airport
    Nevşehir Kapadokya Airport is a regional airport in central Turkey that serves as a primary air gateway for tourists 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. Bursa Yenişehir Airport
    Bursa Yenişehir Airport is a regional airport in Turkey serving the city of Bursa with domestic and limited international flights.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9ea20b48190ace88bb46b01e6a9 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4715ae1fc81908438a1bba970c6ec completed April 19, 2026, 6:08 a.m.
Created at: April 10, 2026, 10:04 a.m.