Triple

T15977004
Position Surface form Disambiguated ID Type / Status
Subject Eskişehir Air Base E387473 entity
Predicate hasCityServed P3936 FINISHED
Object Eskişehir E344696 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: Eskişehir | Statement: [Eskişehir Air Base, hasCityServed, Eskişehir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eskişehir
Context triple: [Eskişehir Air Base, hasCityServed, Eskişehir]
  • A. Eskişehir chosen
    Eskişehir is a major university and industrial city in northwestern Turkey, known for its vibrant student life, modern urban design, and rich cultural heritage.
  • B. Kayseri
    Kayseri is a historic city in central Turkey, known for its Seljuk and Ottoman architectural heritage and its role as a major commercial and cultural center in Anatolia.
  • C. Konya
    Konya is a major city in central Anatolia known for its rich Seljuk heritage and as the home of the Sufi mystic Rumi and the Whirling Dervishes.
  • D. Bursa
    Bursa is a major city in northwestern Turkey known historically as the first capital of the Ottoman Empire and today as an important industrial and cultural center.
  • E. 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.
  • 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_69d86da94ccc819083d187f5dc6a123e completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1575166d081909c5275c235c8ce0f completed April 16, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a008a1f8d648190b9c6280b875a17e4 completed May 10, 2026, 1:37 p.m.
Created at: April 10, 2026, 4:54 a.m.