Triple

T7434783
Position Surface form Disambiguated ID Type / Status
Subject Gyor-Moson-Sopron County E171584 entity
Predicate hasBorderTown P847 FINISHED
Object Mosonmagyaróvár E663578 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: Mosonmagyaróvár | Statement: [Gyor-Moson-Sopron County, hasBorderTown, Mosonmagyaróvár]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mosonmagyaróvár
Context triple: [Gyor-Moson-Sopron County, hasBorderTown, Mosonmagyaróvár]
  • A. Mosonmagyaróvár chosen
    Mosonmagyaróvár is a historic town in northwestern Hungary near the Austrian and Slovak borders, known for its thermal baths and strategic location as a regional transport hub.
  • B. Csákvár
    Csákvár is a small town in central Hungary known for its rural character and location within the Transdanubian region.
  • C. Mosonszentmiklós
    Mosonszentmiklós is a village in northwestern Hungary, notable as the birthplace of renowned conductor Arthur Nikisch.
  • D. Sárvár
    Sárvár is a historic town in western Hungary known for its medieval Nádasdy Castle and thermal spa culture.
  • E. Nagyvázsony
    Nagyvázsony is a village in Veszprém County, Hungary, known for its historic Kinizsi Castle and traditional rural character.
  • 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_69c68a64228c8190affaec2a8127ce7b completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f328cf6081908bea065639fd3620 completed March 27, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8278670bc819095bdbcc0837b6716 completed March 28, 2026, 7:09 p.m.
Created at: March 27, 2026, 3:13 p.m.