Triple

T23048005
Position Surface form Disambiguated ID Type / Status
Subject Dinnyés E573929 entity
Predicate partOf P40 FINISHED
Object Gárdony (town) NE NERFINISHED

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: Gárdony (town) | Statement: [Dinnyés, partOf, Gárdony (town)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gárdony (town)
Context triple: [Dinnyés, partOf, Gárdony (town)]
  • A. Gárdony chosen
    Gárdony is a Hungarian town and popular resort area on the southern shore of Lake Velence, known for its beaches, thermal waters, and recreational tourism.
  • B. Nyíradony
    Nyíradony is a small town in eastern Hungary, located in Hajdú-Bihar County near Debrecen.
  • C. Püspökladány
    Püspökladány is a town in eastern Hungary known for its location on the Great Hungarian Plain and its role as a local agricultural and transport hub.
  • D. Gyöngyös
    Gyöngyös is a historic town in northern Hungary known as a gateway to the Mátra mountain range and its surrounding wine-producing region.
  • E. Zalaszántó
    Zalaszántó is a village in western Hungary known for its scenic rural setting near Lake Balaton and its large Buddhist stupa, one of the biggest in Europe.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245b9c11481909d06c872214d21af completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1867a206c81909ff923cbf56f7787 completed April 29, 2026, 4:18 a.m.
Created at: April 17, 2026, 3:54 p.m.