Triple

T18682147
Position Surface form Disambiguated ID Type / Status
Subject Ajka E456759 entity
Predicate locatedInRegion P40 FINISHED
Object Western Hungary 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: Western Hungary | Statement: [Ajka, locatedInRegion, Western Hungary]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Western Hungary
Context triple: [Ajka, locatedInRegion, Western Hungary]
  • A. Eastern Hungary
    Eastern Hungary is a geographic region of Hungary that includes major cities such as Debrecen and is known for its plains, cultural heritage, and agricultural significance.
  • B. Northern Hungary
    Northern Hungary is a region of Hungary known for its industrial cities like Miskolc, historic castles, and the Bükk and Mátra mountain ranges.
  • C. Central Hungary
    Central Hungary is a key administrative and economic region of Hungary that includes the capital city, Budapest, and serves as the country’s primary political and commercial hub.
  • D. Southeastern Hungary
    Southeastern Hungary is a largely flat, agricultural region of Hungary known for its rural landscapes, historic towns, and proximity to the Romanian and Serbian borders.
  • E. Western Transdanubia chosen
    Western Transdanubia is a region in western Hungary known for its shared border with Austria, diverse landscapes, and historical towns.
  • 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_69d8d391eb488190ac2e9abf5bf255e4 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e55b2906ec8190ad8db8e3ae6b2945 completed April 19, 2026, 10:46 p.m.
Created at: April 10, 2026, 11:49 a.m.