Triple

T11795984
Position Surface form Disambiguated ID Type / Status
Subject Nitra Region E280506 entity
Predicate hasCity P316 FINISHED
Object Topoľčany E111622 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: Topoľčany | Statement: [Nitra Region, hasCity, Topoľčany]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Topoľčany
Context triple: [Nitra Region, hasCity, Topoľčany]
  • A. Topoľčany chosen
    Topoľčany is a town in western Slovakia known as the birthplace of several notable Slovak ice hockey players, including Miroslav Šatan.
  • B. Považská Bystrica
    Považská Bystrica is a town in northwestern Slovakia known as an industrial center situated in a valley surrounded by the Strážov Mountains.
  • C. Banská Belá
    Banská Belá is a historic village in central Slovakia known for its long-standing association with the region’s mining industry.
  • D. Liptovský Hrádok
    Liptovský Hrádok is a small Slovak town in the Liptov region, known for its historic castle complex and location near the Tatra Mountains.
  • E. Trenčín
    Trenčín is a historic city in western Slovakia known for its medieval castle overlooking the Váh River and its role as a regional cultural and economic 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_69d6ab258b808190b1735835c841e3a4 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a5a1cda0819092d66a82fd882786 completed April 10, 2026, 7:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7304bc684819083ca999f283b0cb3 completed May 3, 2026, 11:23 a.m.
Created at: April 8, 2026, 9:42 p.m.