Triple

T17616908
Position Surface form Disambiguated ID Type / Status
Subject Kőszeg E429106 entity
Predicate hasTwinTown P919 FINISHED
Object Güssing 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: Güssing | Statement: [Kőszeg, hasTwinTown, Güssing]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Güssing
Context triple: [Kőszeg, hasTwinTown, Güssing]
  • A. Güssing District chosen
    Güssing District is an administrative district in the Austrian state of Burgenland, known for its rural landscape and pioneering renewable energy initiatives.
  • B. Vöcklabruck
    Vöcklabruck is a small historic town in Upper Austria known as a regional center near the Attersee lake and the foothills of the Alps.
  • C. Sankt Veit an der Glan
    Sankt Veit an der Glan is a historic town in the Austrian state of Carinthia, known for its medieval architecture and role as a former ducal residence.
  • D. Leoben
    Leoben is a historic industrial and university city in the Austrian state of Styria, known especially for its steel industry and mining university.
  • E. Strobl
    Strobl is a picturesque Austrian lakeside town in the Salzkammergut region, known for its scenic setting on the shores of Wolfgangsee and its popular holiday and outdoor recreation opportunities.
  • 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_69d889e1c6148190ba76241e74688f8b completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46d33a2b081908deecee773c333af completed April 19, 2026, 5:50 a.m.
Created at: April 10, 2026, 5:51 a.m.