Triple

T12739188
Position Surface form Disambiguated ID Type / Status
Subject İzmir ESHOT bus network E304442 entity
Predicate serviceAreaIncludes P82 FINISHED
Object Kınık E696152 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: Kınık | Statement: [İzmir ESHOT bus network, serviceAreaIncludes, Kınık]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kınık
Context triple: [İzmir ESHOT bus network, serviceAreaIncludes, Kınık]
  • A. Kınık chosen
    Kınık is a town and district in western Turkey known for its agricultural activities and location within İzmir Province.
  • B. Kırcaali
    Kırcaali (Kardzhali) is a city in southern Bulgaria known as a regional center in the Eastern Rhodope Mountains with a significant historical Turkish population.
  • C. Malkara
    Malkara is a town and district in Turkey’s European region of Thrace, known for its agricultural economy and location within Tekirdağ Province.
  • D. Kurukdere
    Kurukdere is a locality in present-day eastern Turkey known primarily as the site of a significant battle during the Crimean War between Russian and Ottoman forces.
  • E. Büyükerşen
    Büyükerşen is a Turkish surname most prominently associated with Yılmaz Büyükerşen, a well-known academic and long-serving mayor of Eskişehir.
  • 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_69d7bdf1426c8190a4402e1c4cdec33a completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9646cfcac81909283dca987755c0e completed April 10, 2026, 8:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69f68eb388488190a30866e9a7a0bc41 completed May 2, 2026, 11:54 p.m.
Created at: April 9, 2026, 5:26 p.m.