Triple

T5987945
Position Surface form Disambiguated ID Type / Status
Subject Rügen Bridge E133274 entity
Predicate carries P1393 FINISHED
Object Bundesstraße 96n E318592 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: Bundesstraße 96n | Statement: [Rügen Bridge, carries, Bundesstraße 96n]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bundesstraße 96n
Context triple: [Rügen Bridge, carries, Bundesstraße 96n]
  • A. Bundesstraße 96 chosen
    Bundesstraße 96 is a major German federal highway running in a north–south direction, notably connecting Berlin with the Baltic Sea island of Rügen.
  • B. Bundesstraße 297
    Bundesstraße 297 is a German federal road in the state of Baden-Württemberg that connects several towns and cities, including Göppingen, and serves as an important regional transport route.
  • C. Bundesstraße 8
    Bundesstraße 8 is a major German federal highway running east–west through several states and connecting numerous towns and cities.
  • D. Bundesstraße 202
    Bundesstraße 202 is a federal highway in northern Germany that connects several towns and regions in the state of Schleswig-Holstein.
  • E. Bundesstraße
    A Bundesstraße is a major federal highway in Germany that connects cities and regions and is ranked below the Autobahn in the national road network.
  • 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_69c0087010d081908bb8142342d63330 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04dc51d948190bacf4c40a73e91b2 completed March 22, 2026, 8:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c10854969c8190b9be249f26ad2f47 completed March 23, 2026, 9:31 a.m.
Created at: March 22, 2026, 4:04 p.m.