Triple

T3679741
Position Surface form Disambiguated ID Type / Status
Subject Trenčín E78081 entity
Predicate locatedIn P40 FINISHED
Object Trenčín Region E346735 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: Trenčín Region | Statement: [Trenčín, locatedIn, Trenčín Region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Trenčín Region
Context triple: [Trenčín, locatedIn, Trenčín Region]
  • A. Trenčín Region chosen
    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.
  • B. Žilina Region
    Žilina Region is an administrative region in northern Slovakia known for its mountainous landscapes, cultural heritage, and important industrial and transport centers.
  • C. Trnava Region
    Trnava Region is an administrative region in western Slovakia known for its historic towns, agricultural landscape, and proximity to the capital, Bratislava.
  • D. Prešov Region
    The Prešov Region is an administrative region in northeastern Slovakia known for its mountainous landscapes, historic towns, and proximity to the High Tatras.
  • E. Košice Region
    Košice Region is an administrative region in eastern Slovakia that includes the city of Košice as its largest urban center.
  • 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_69ad85e18c1c8190be8aafb227f39f48 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc49039308190b33082e2b58aa5cf completed March 8, 2026, 6:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4c3ae61908190beefd0df317b5eca completed March 14, 2026, 2:10 a.m.
Created at: March 8, 2026, 3:25 p.m.