Triple

T19603619
Position Surface form Disambiguated ID Type / Status
Subject Sarayönü E470545 entity
Predicate hasAdministrativeCenter P1474 FINISHED
Object Sarayönü town 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: Sarayönü town | Statement: [Sarayönü, hasAdministrativeCenter, Sarayönü town]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sarayönü town
Context triple: [Sarayönü, hasAdministrativeCenter, Sarayönü town]
  • A. Sarayönü chosen
    Sarayönü is a rural district and town in central Turkey, located within Konya Province and known for its agricultural activities on the Central Anatolian plateau.
  • B. Güzelyurt
    Güzelyurt is a town in the northwestern part of Cyprus, known for its citrus orchards and archaeological sites.
  • C. Güzelyurt
    Güzelyurt is a historic town in Turkey’s Cappadocia region, known for its rock-cut churches, underground cities, and scenic valleys.
  • D. Toprakkale
    Toprakkale is an ancient fortress and archaeological site in eastern Turkey that served as a significant center of the Iron Age Kingdom of Urartu.
  • E. Sivrice
    Sivrice is a small town and district in eastern Turkey known for its location on the shores of Lake Hazar in Elazığ Province.
  • 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_69d8e510024481908415c0d616fa6186 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e64081af6c8190868b73b07c874cd5 completed April 20, 2026, 3:04 p.m.
Created at: April 10, 2026, 1:43 p.m.