Triple

T11704135
Position Surface form Disambiguated ID Type / Status
Subject Felvidék E278196 entity
Predicate hasCulturalRegion P1968 FINISHED
Object Gömör E941852 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: Gömör | Statement: [Felvidék, hasCulturalRegion, Gömör]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gömör
Context triple: [Felvidék, hasCulturalRegion, Gömör]
  • A. Gömör chosen
    Gömör is a historical region in Central Europe, traditionally associated with parts of present-day Slovakia and Hungary, known for its mining heritage and medieval settlements.
  • B. Gyál
    Gyál is a town in central Hungary that functions as a suburban residential area near Budapest within Pest County.
  • C. Somlyó
    Somlyó is a historical locality in the Kingdom of Hungary, best known as the birthplace of Stephen Báthory, who became King of Poland and Grand Duke of Lithuania in the 16th century.
  • D. Sárbogárd
    Sárbogárd is a small town in central Hungary known for its agricultural surroundings and role as a local transport hub within Fejér County.
  • E. Mórahalom
    Mórahalom is a small town in southern Hungary near the Serbian border, known for its thermal spa and role as a local agricultural and tourism center.
  • 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_69d6aaff2ce88190b4a1e4b341ad5377 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a49b1080819096593733ee48a187 completed April 10, 2026, 7:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69f0195739348190b40a378ca227cf85 completed April 28, 2026, 2:20 a.m.
Created at: April 8, 2026, 9:40 p.m.