Triple

T16766005
Position Surface form Disambiguated ID Type / Status
Subject Fertő-Hanság National Park E407463 entity
Predicate mainSettlementNearby P13187 FINISHED
Object Sopron E99815 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: Sopron | Statement: [Fertő-Hanság National Park, mainSettlementNearby, Sopron]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sopron
Context triple: [Fertő-Hanság National Park, mainSettlementNearby, Sopron]
  • A. Sopron chosen
    Sopron is a historic city in western Hungary near the Austrian border, known for its well-preserved medieval old town and wine-making traditions.
  • B. Veszprém
    Veszprém is a historic city in western Hungary known for its medieval castle district and role as a regional cultural and administrative center.
  • C. Kaposvár
    Kaposvár is a city in southwestern Hungary that serves as the administrative and cultural center of Somogy County.
  • D. Szekszárd
    Szekszárd is a historic Hungarian town renowned as one of the country’s leading red wine regions and the administrative center of Tolna County.
  • E. Gödöllő
    Gödöllő is a Hungarian town near Budapest best known for its historic Royal Palace, one of the largest Baroque palaces in Hungary.
  • 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_69d8839174188190909f190097207065 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3b0330d6081908ce99f14c70b90f2 completed April 18, 2026, 4:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0180bf3d308190b4965d57fe327a52 completed May 11, 2026, 7:09 a.m.
Created at: April 10, 2026, 5:21 a.m.