Triple

T4873848
Position Surface form Disambiguated ID Type / Status
Subject Muszyna E109150 entity
Predicate twinnedWith P1072 FINISHED
Object Sátoraljaújhely E214382 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: Sátoraljaújhely | Statement: [Muszyna, twinnedWith, Sátoraljaújhely]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sátoraljaújhely
Context triple: [Muszyna, twinnedWith, Sátoraljaújhely]
  • A. Sátoraljaújhely chosen
    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. Kaposvár
    Kaposvár is a city in southwestern Hungary that serves as the administrative and cultural center of Somogy County.
  • C. Zalaegerszeg
    Zalaegerszeg is a city in western Hungary that serves as the administrative center of Zala County and a regional economic and cultural hub.
  • D. Hódmezővásárhely
    Hódmezővásárhely is a city in southeastern Hungary known for its agricultural traditions, pottery, and regional cultural heritage.
  • E. Szombathely
    Szombathely is one of Hungary’s oldest cities, known for its Roman heritage and role as a regional cultural and economic center near the Austrian border.
  • 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_69bd440d96a48190b0c87069adef2af1 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6d9fa0b08190ab1fc7ec395dca37 completed March 20, 2026, 3:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69be67f5b51c8190a8114450084d2b13 completed March 21, 2026, 9:42 a.m.
Created at: March 20, 2026, 1:27 p.m.