Triple

T12739182
Position Surface form Disambiguated ID Type / Status
Subject İzmir ESHOT bus network E304442 entity
Predicate serviceAreaIncludes P82 FINISHED
Object Dikili E696147 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: Dikili | Statement: [İzmir ESHOT bus network, serviceAreaIncludes, Dikili]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dikili
Context triple: [İzmir ESHOT bus network, serviceAreaIncludes, Dikili]
  • A. Dikili chosen
    Dikili is a coastal town and district in western Turkey known for its beaches, thermal springs, and proximity to the Aegean Sea.
  • B. Kocaali
    Kocaali is a coastal town and district in northwestern Turkey, situated along the Black Sea in Sakarya Province.
  • C. Dikwa
    Dikwa is a historic town in northeastern Nigeria that once served as a key political and administrative center of the Borno Empire.
  • D. Halkapınar
    Halkapınar is a small rural district and municipality in central Turkey’s Konya Province, known for its agricultural character and proximity to the Taurus Mountains.
  • E. Halkapınar
    Halkapınar is a major transport hub and urban area in İzmir, Turkey, known for its extensive rail and tram connections.
  • 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_69f67c8ff57c8190a935b5c9f4bb5aa3 completed May 2, 2026, 10:37 p.m.
Created at: April 9, 2026, 5:26 p.m.