Triple

T14059893
Position Surface form Disambiguated ID Type / Status
Subject Eger E338315 entity
Predicate locatedIn P40 FINISHED
Object Northern Hungary E215782 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: Northern Hungary | Statement: [Eger, locatedIn, Northern Hungary]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Northern Hungary
Context triple: [Eger, locatedIn, Northern Hungary]
  • A. Northern Hungary chosen
    Northern Hungary is a region of Hungary known for its industrial cities like Miskolc, historic castles, and the Bükk and Mátra mountain ranges.
  • B. 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.
  • C. northwestern Hungary
    Northwestern Hungary is a geographic region of Hungary that includes parts of Transdanubia and features industrial cities, historical towns, and proximity to both Austria and Slovakia.
  • 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. 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.
  • 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_69d81c67ba6c819091935650dfb3b895 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de5686f51c81908c33143ecbaae83d completed April 14, 2026, 3 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd324133f8819088c0d80a4e8fb5be completed May 8, 2026, 12:45 a.m.
Created at: April 9, 2026, 10:21 p.m.