Triple

T14951073
Position Surface form Disambiguated ID Type / Status
Subject Weimarer Land E372793 entity
Predicate bordersWith P224 FINISHED
Object Saalfeld-Rudolstadt E873650 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: Saalfeld-Rudolstadt | Statement: [Weimarer Land, bordersWith, Saalfeld-Rudolstadt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saalfeld-Rudolstadt
Context triple: [Weimarer Land, bordersWith, Saalfeld-Rudolstadt]
  • A. Saalfeld
    Saalfeld is a town in the German state of Thuringia, known for its historic old town and former significance as a regional railway and industrial center.
  • B. Rudolstadt
    Rudolstadt is a historic town in the German state of Thuringia, known for its picturesque old town, Heidecksburg Castle, and cultural festivals.
  • C. Sondershausen
    Sondershausen is a small town in the German state of Thuringia, known for its historic castle, former role as a princely residence, and long tradition of mining and music.
  • D. Saalfeld-Rudolstadt district chosen
    Saalfeld-Rudolstadt district is an administrative district in the state of Thuringia, Germany, known for its historic towns and location in the Thuringian Forest region.
  • E. Harzgerode
    Harzgerode is a small historic town in the eastern Harz Mountains of central Germany, known for its mining heritage and surrounding forested landscapes.
  • 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_69d85cca979481908747d2a81eba1cea completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded690f2e08190ad9dad6dc05a164a completed April 15, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffc3aeb59c8190a39ccb4df7815ed0 completed May 9, 2026, 11:30 p.m.
Created at: April 10, 2026, 2:39 a.m.