Triple

T8020408
Position Surface form Disambiguated ID Type / Status
Subject Thuringian Basin E186725 entity
Predicate borderedBy P224 FINISHED
Object Kyffhäuser Hills E398897 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: Kyffhäuser Hills | Statement: [Thuringian Basin, borderedBy, Kyffhäuser Hills]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kyffhäuser Hills
Context triple: [Thuringian Basin, borderedBy, Kyffhäuser Hills]
  • A. Kyffhäuser hills chosen
    The Kyffhäuser hills are a low mountain range in central Germany known for the Kyffhäuser Monument and their association with the Barbarossa legend.
  • B. Rhön
    Rhön is a low mountain range in central Germany known for its volcanic landscape, open plateaus, and designation as a UNESCO Biosphere Reserve.
  • C. Hagen Mountains
    The Hagen Mountains are a rugged limestone mountain range in the Northern Limestone Alps of Austria, forming part of the Berchtesgaden Alps near the Salzach River.
  • D. Vogelsberg
    Vogelsberg is a large volcanic mountain range in the German state of Hesse, known for its forested highlands and rural landscapes.
  • E. Hardtberg
    Hardtberg is a borough of the German city of Bonn, located in the western part of the city and comprising several residential and administrative districts.
  • 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_69ca82ac7fc081909b1398cf025423af completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3e8d90488190b57d1e748e272061 completed March 31, 2026, 3:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccbe3243348190bd4e9073e5460386 completed April 1, 2026, 6:41 a.m.
Created at: March 30, 2026, 5:20 p.m.