Triple

T20466328
Position Surface form Disambiguated ID Type / Status
Subject Hallwang E502057 entity
Predicate hasBorderWith P224 FINISHED
Object Eugendorf 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: Eugendorf | Statement: [Hallwang, hasBorderWith, Eugendorf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eugendorf
Context triple: [Hallwang, hasBorderWith, Eugendorf]
  • A. Eugendorf chosen
    Eugendorf is a market town in the Austrian state of Salzburg, known for its proximity to the city of Salzburg and its location in the scenic Salzkammergut region.
  • B. Gneixendorf
    Gneixendorf is a village and cadastral community that forms part of the city of Krems an der Donau in Lower Austria.
  • C. Althüttendorf
    Althüttendorf is a small rural municipality in the Barnim district of Brandenburg in northeastern Germany.
  • D. Biendorf
    Biendorf is a small municipality in northern Germany notable as the birthplace of German Field Marshal Helmuth von Moltke the Younger.
  • E. Kaiserebersdorf
    Kaiserebersdorf is a neighborhood in Vienna, Austria, located within the district of Simmering and known for its mix of residential areas and industrial facilities.
  • 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_69e0b4ae5f1081908768b0c9a3a0bf38 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e696aa0794819082c9989b1f7e9f37 completed April 20, 2026, 9:12 p.m.
Created at: April 16, 2026, 11:33 a.m.