Triple

T20459033
Position Surface form Disambiguated ID Type / Status
Subject Hangelsberg E501872 entity
Predicate roadAccess P385 FINISHED
Object Bundesstraße 5 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 5 | Statement: [Hangelsberg, roadAccess, Bundesstraße 5]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bundesstraße 5
Context triple: [Hangelsberg, roadAccess, Bundesstraße 5]
  • A. Bundesstraße 5 chosen
    Bundesstraße 5 is a major German federal highway that runs north–south through several states, connecting key cities such as Husum, Hamburg, and Frankfurt (Oder).
  • B. Bundesstraße 50
    Bundesstraße 50 is a German federal highway in Rhineland-Palatinate that serves as an important east–west route across the Hunsrück region.
  • C. Bundesstraße 55
    Bundesstraße 55 is a federal highway in Germany that runs through North Rhine-Westphalia and Hesse, linking several towns and regions in a north–south direction.
  • D. Bundesstraße 59
    Bundesstraße 59 is a German federal highway in North Rhine-Westphalia that connects several towns and cities, serving as an important regional traffic route.
  • E. Bundesstraße 9
    Bundesstraße 9 is a major German federal highway running along the western part of the country, connecting numerous cities and towns near the Rhine.
  • 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_69e0b4ad4940819098cf2ff6413574e5 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e696a4652c8190acf79fa2e285e436 completed April 20, 2026, 9:12 p.m.
Created at: April 16, 2026, 11:33 a.m.