Triple

T9418112
Position Surface form Disambiguated ID Type / Status
Subject Žilina Region E227080 entity
Predicate contains P35 FINISHED
Object city of Žilina E218081 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: city of Žilina | Statement: [Žilina Region, contains, city of Žilina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Žilina
Context triple: [Žilina Region, contains, city of Žilina]
  • A. Žilina chosen
    Žilina is a city in northwestern Slovakia that serves as an important industrial and transportation hub, particularly for rail connections in the region.
  • B. Liptovské Sliače
    Liptovské Sliače is a village in the Liptov region of northern Slovakia, known for its traditional architecture and scenic mountainous surroundings.
  • C. 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.
  • D. Žilina District
    Žilina District is an administrative district in northwestern Slovakia centered on the city of Žilina and known for its role as a regional economic and transportation hub.
  • E. Zlín
    Zlín is a city in the Czech Republic known for its modernist architecture and historical association with the Baťa shoe company.
  • 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_69ca84359e7c819091148ba4b670e436 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd68cd1e3481909abcb715e2398120 completed April 1, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69d11029d3348190baf0dba766c4e960 completed April 4, 2026, 1:20 p.m.
Created at: March 30, 2026, 7:48 p.m.