Triple

T13556929
Position Surface form Disambiguated ID Type / Status
Subject Ondava E323798 entity
Predicate flowsThrough P225 FINISHED
Object Prešov Region E130151 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: Prešov Region | Statement: [Ondava, flowsThrough, Prešov Region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Prešov Region
Context triple: [Ondava, flowsThrough, Prešov Region]
  • A. Prešov Region chosen
    The Prešov Region is an administrative region in northeastern Slovakia known for its mountainous landscapes, historic towns, and proximity to the High Tatras.
  • B. Trnava Region
    Trnava Region is an administrative region in western Slovakia known for its historic towns, agricultural landscape, and proximity to the capital, Bratislava.
  • C. Košice Region
    Košice Region is an administrative region in eastern Slovakia that includes the city of Košice as its largest urban center.
  • D. Banská Bystrica region
    The Banská Bystrica region is a central Slovak area historically known as a key stronghold and focal point of anti-Nazi resistance during World War II.
  • E. Trenčín Region
    Trenčín Region is an administrative region in western Slovakia known for its historic towns, including the city of Trenčín, and its cultural and economic significance.
  • 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_69d8076830b48190910a902bae5888e2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaff3063c8190bd20149b3f7df352 completed April 12, 2026, 2:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff8752207c81908369bce03b56b25e completed May 9, 2026, 7:13 p.m.
Created at: April 9, 2026, 9:47 p.m.