Triple

T11895566
Position Surface form Disambiguated ID Type / Status
Subject Dunajská Streda E283026 entity
Predicate hasTwinTown P919 FINISHED
Object Nagykőrös E883253 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: Nagykőrös | Statement: [Dunajská Streda, hasTwinTown, Nagykőrös]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nagykőrös
Context triple: [Dunajská Streda, hasTwinTown, Nagykőrös]
  • A. Nagykőrös chosen
    Nagykőrös is a historic town in central Hungary known for its agricultural traditions and small-town character.
  • B. Kiskőrös
    Kiskőrös is a small town in southern Hungary known as the birthplace of the national poet Sándor Petőfi and for its wine-producing region.
  • C. Kőszeg
    Kőszeg is a historic Hungarian town near the Austrian border, renowned for its well-preserved medieval architecture and role in defending against Ottoman sieges.
  • D. Nagykálló
    Nagykálló is a town in northeastern Hungary known for its historical architecture and traditional cultural heritage.
  • E. Nagykörút
    Nagykörút is a major semicircular thoroughfare in central Budapest, lined with historic buildings, shops, and public transport routes, and serving as one of the city’s key urban arteries.
  • 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_69d6ab2a90b08190a4e818821cc93e6d completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8dd1286808190949719f54ff49a01 completed April 10, 2026, 11:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69fcb63c80048190be87b41cdd4ac775 completed May 7, 2026, 3:56 p.m.
Created at: April 8, 2026, 9:44 p.m.