Triple

T16273574
Position Surface form Disambiguated ID Type / Status
Subject Yenişehir E395064 entity
Predicate servedBy P82 FINISHED
Object Bursa Yenişehir Airport E85308 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: Bursa Yenişehir Airport | Statement: [Yenişehir, servedBy, Bursa Yenişehir Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bursa Yenişehir Airport
Context triple: [Yenişehir, servedBy, Bursa Yenişehir Airport]
  • A. Bursa Yenişehir Airport chosen
    Bursa Yenişehir Airport is a regional airport in Turkey serving the city of Bursa with domestic and limited international flights.
  • B. 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.
  • 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. Konya Airport
    Konya Airport is a combined civil and military airport serving the city of Konya in central Turkey.
  • E. Samsun-Çarşamba Airport
    Samsun-Çarşamba Airport is a regional public airport serving the city of Samsun and its surrounding area on Turkey’s Black Sea coast.
  • 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_69d87f221d8081909b0b2063e7528ba2 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2460b22d88190bdc7cf509cf74198 completed April 17, 2026, 2:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0017c0ef4c8190b44ac84f71b2ed41 completed May 10, 2026, 5:29 a.m.
Created at: April 10, 2026, 5:05 a.m.