Triple

T2094752
Position Surface form Disambiguated ID Type / Status
Subject Fejér County E32753 entity
Predicate containsTown P847 FINISHED
Object Martonvásár E238552 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: Martonvásár | Statement: [Fejér County, containsTown, Martonvásár]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Martonvásár
Context triple: [Fejér County, containsTown, Martonvásár]
  • A. Sátoraljaújhely
    Sátoraljaújhely is a historic town in northeastern Hungary near the Slovak border, known for its wine region, cultural heritage, and scenic Zemplén Mountains setting.
  • B. Pusztaszabolcs chosen
    Pusztaszabolcs is a small town in central Hungary known for its role as a local railway junction and residential community within Fejér County.
  • C. Tatabánya
    Tatabánya is an industrial city in northwestern Hungary known for its mining heritage and role as a regional economic center.
  • D. Dunaújváros
    Dunaújváros is an industrial city in central Hungary known for its steel production and post-war socialist urban planning.
  • E. Keszthely
    Keszthely is a historic town in western Hungary known for its lakeside resort atmosphere, cultural heritage, and proximity to Lake Balaton.
  • 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_69a885eba0708190999696a45cbec816 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abba99ddc48190bb2097b56efb7aca completed March 7, 2026, 5:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae5d8928048190ab9ef79dde8ad4e0 completed March 9, 2026, 5:41 a.m.
Created at: March 4, 2026, 7:43 p.m.