Triple

T20821430
Position Surface form Disambiguated ID Type / Status
Subject Szatmár E512580 entity
Predicate hasTwinTown P919 FINISHED
Object Fehérgyarmat 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: Fehérgyarmat | Statement: [Szatmár, hasTwinTown, Fehérgyarmat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fehérgyarmat
Context triple: [Szatmár, hasTwinTown, Fehérgyarmat]
  • A. Fehérgyarmat chosen
    Fehérgyarmat is a small town in eastern Hungary known for its rural character and location near the Ukrainian and Romanian borders.
  • B. Gyulafehérvár
    Gyulafehérvár, known today as Alba Iulia in Romania, is a historic city that served as the political and cultural center of Transylvania for centuries.
  • C. Szentgotthárd
    Szentgotthárd is a small town in western Hungary near the Austrian and Slovenian borders, known for its historic Cistercian abbey and role in the 1664 Battle of Saint Gotthard.
  • D. Zalaegerszeg
    Zalaegerszeg is a city in western Hungary that serves as the administrative center of Zala County and a regional economic and cultural hub.
  • E. Budakeszi
    Budakeszi is a small town in Hungary, located just west of Budapest and known for its surrounding forests and natural recreational areas.
  • 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_69e0b4ce39108190a6e8e5df4f1c8dc5 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c2f7a1548190b6ef3f1cfad37c1c completed April 21, 2026, 12:21 a.m.
Created at: April 16, 2026, 12:41 p.m.