Triple

T17013973
Position Surface form Disambiguated ID Type / Status
Subject Vas County E412769 entity
Predicate containsTouristAttraction P5121 FINISHED
Object Kőszeg Old Town E429106 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: Kőszeg Old Town | Statement: [Vas County, containsTouristAttraction, Kőszeg Old Town]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kőszeg Old Town
Context triple: [Vas County, containsTouristAttraction, Kőszeg Old Town]
  • A. Kőszeg chosen
    Kőszeg is a historic Hungarian town near the Austrian border, renowned for its well-preserved medieval architecture and role in defending against Ottoman sieges.
  • B. Kiskőrös
    Kiskőrös is a small town in southern Hungary known as the birthplace of the national poet Sándor Petőfi and for its wine-producing region.
  • C. Keszthely
    Keszthely is a historic town in western Hungary known for its lakeside resort atmosphere, cultural heritage, and proximity to Lake Balaton.
  • D. Szécsény
    Szécsény is a historic town in northern Hungary known for its medieval architecture and role as a regional center in Nógrád County.
  • E. Gyöngyös
    Gyöngyös is a historic town in northern Hungary known as a gateway to the Mátra mountain range and its surrounding wine-producing region.
  • 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_69d886cc4170819093deddc7b8b4b6a7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d47e64f081908f43870c7564d0ae completed April 18, 2026, 6:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a011b4990948190861ff81f8fc3e8f2 completed May 10, 2026, 11:56 p.m.
Created at: April 10, 2026, 5:33 a.m.