Triple

T9005011
Position Surface form Disambiguated ID Type / Status
Subject Kufstein E215120 entity
Predicate hasTwinTown P919 FINISHED
Object Sélestat E57547 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: Sélestat | Statement: [Kufstein, hasTwinTown, Sélestat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sélestat
Context triple: [Kufstein, hasTwinTown, Sélestat]
  • A. Sélestat chosen
    Sélestat is a historic town in the Alsace region of northeastern France, known for its well-preserved medieval architecture and cultural heritage.
  • B. Wissembourg
    Wissembourg is a historic town in northeastern France’s Alsace region, known for its well-preserved medieval architecture and proximity to the German border.
  • C. Kaysersberg
    Kaysersberg is a picturesque medieval town in France’s Alsace region, renowned for its half-timbered houses, hillside vineyards, and well-preserved historic charm.
  • D. Molsheim
    Molsheim is a historic town in northeastern France’s Grand Est region, known for its medieval architecture and as the birthplace of the Bugatti automobile brand.
  • E. Lörrach
    Lörrach is a town in southwest Germany’s Baden-Württemberg state, near the borders with Switzerland and France, known for its proximity to Basel and its role as a regional economic and cultural 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_69ca83a12d648190b1e4fe11e8a31890 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc695afa34819086cf6fcce2997b5f completed April 1, 2026, 12:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfdb9a11948190a43f60d0df71b1af completed April 3, 2026, 3:24 p.m.
Created at: March 30, 2026, 7:05 p.m.