Triple

T11704024
Position Surface form Disambiguated ID Type / Status
Subject Zemplín E278195 entity
Predicate wineTypeProduced P2082 FINISHED
Object Tokaj E234399 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: Tokaj | Statement: [Zemplín, wineTypeProduced, Tokaj]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tokaj
Context triple: [Zemplín, wineTypeProduced, Tokaj]
  • A. Tokaj chosen
    Tokaj is a historic town in northeastern Hungary renowned worldwide for its Tokaji wine region and sweet dessert wines.
  • B. Sopron wine region
    Sopron wine region is a historic Hungarian wine-producing area near the Austrian border, known especially for its Kékfrankos (Blaufränkisch) red wines.
  • C. Szekszárd wine region
    Szekszárd wine region is a historic Hungarian wine-producing area renowned for its high-quality red wines, particularly blends based on Kadarka and Kékfrankos.
  • D. Villány
    Villány is a small town in southern Hungary renowned as one of the country’s premier wine regions, especially famous for its red wines.
  • E. Kalocsa
    Kalocsa is a historic town in southern Hungary known as an important Roman Catholic archiepiscopal center and for its traditional paprika production and folk art.
  • 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_69d6aaff2ce88190b4a1e4b341ad5377 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a49b1080819096593733ee48a187 completed April 10, 2026, 7:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef83525ae081909ee6f3fbb5d37dd7 completed April 27, 2026, 3:40 p.m.
Created at: April 8, 2026, 9:40 p.m.