Triple

T17503461
Position Surface form Disambiguated ID Type / Status
Subject Hoheneggelsen E426250 entity
Predicate roadAccessVia P9041 FINISHED
Object Bundesstraße 1 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: Bundesstraße 1 | Statement: [Hoheneggelsen, roadAccessVia, Bundesstraße 1]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bundesstraße 1
Context triple: [Hoheneggelsen, roadAccessVia, Bundesstraße 1]
  • A. Bundesstraße 1 chosen
    Bundesstraße 1 is a major German federal highway that runs east–west across the country, connecting several important cities and historical routes.
  • B. Bundesstraße 10
    Bundesstraße 10 is a major federal highway in southern Germany that runs east–west and connects several important cities in the states of Baden-Württemberg and Rhineland-Palatinate.
  • C. Bundesstraße 11
    Bundesstraße 11 is a major federal highway in southern Germany that runs through Bavaria, connecting Munich with the Bavarian Forest region near the Czech border.
  • D. Bundesstraße 2
    Bundesstraße 2 is a major German federal highway running in a north–south direction and connecting several important cities and regions.
  • E. Bundesstraße 15
    Bundesstraße 15 is a German federal highway in Bavaria that runs north–south, connecting several towns and regions, including the area around Tirschenreuth.
  • 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_69d889dd9164819087b1dc3c9240c870 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e45213a0e88190ac183d87ec088e86 completed April 19, 2026, 3:54 a.m.
Created at: April 10, 2026, 5:48 a.m.