Triple

T17473178
Position Surface form Disambiguated ID Type / Status
Subject Kars Province E425470 entity
Predicate bordersProvince P224 FINISHED
Object Ardahan Province 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: Ardahan Province | Statement: [Kars Province, bordersProvince, Ardahan Province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ardahan Province
Context triple: [Kars Province, bordersProvince, Ardahan Province]
  • A. Ardahan chosen
    Ardahan is a town in northeastern Turkey that serves as the capital of Ardahan Province near the border with Georgia.
  • B. Kastamonu Province
    Kastamonu Province is a historically rich, mountainous region in northern Turkey, known for its traditional architecture, forests, and cultural heritage.
  • C. Tokat Province
    Tokat Province is a region in north-central Turkey known for its rich history dating back to ancient Pontus, its agricultural production, and its well-preserved Ottoman-era architecture.
  • D. Trabzon Province
    Trabzon Province is a coastal region in northeastern Turkey along the Black Sea, known for its mountainous landscapes, rich history, and the city of Trabzon as its capital.
  • E. Giresun Province
    Giresun Province is a coastal province in northeastern Turkey along the Black Sea, known for its lush green landscapes and extensive hazelnut production.
  • 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_69d889dbc2e88190b18ea6115e819258 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e451b990848190b2e8510d67e94b79 completed April 19, 2026, 3:53 a.m.
Created at: April 10, 2026, 5:47 a.m.