Triple

T18478223
Position Surface form Disambiguated ID Type / Status
Subject Rolandswerth E451487 entity
Predicate locatedOnTransportRoute P2409 FINISHED
Object Bundesstraße 9 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 9 | Statement: [Rolandswerth, locatedOnTransportRoute, Bundesstraße 9]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bundesstraße 9
Context triple: [Rolandswerth, locatedOnTransportRoute, Bundesstraße 9]
  • A. Bundesstraße 9 chosen
    Bundesstraße 9 is a major German federal highway running along the western part of the country, connecting numerous cities and towns near the Rhine.
  • B. Bundesstraße 96
    Bundesstraße 96 is a major German federal highway running in a north–south direction, notably connecting Berlin with the Baltic Sea island of Rügen.
  • C. Bundesstraße 91
    Bundesstraße 91 is a German federal highway in the state of Saxony-Anhalt that connects the town of Weißenfels with other regional centers.
  • D. Bundesstraße 7
    Bundesstraße 7 is a major German federal highway running east–west across several states and connecting numerous cities and regions.
  • E. Bundesstraße 8
    Bundesstraße 8 is a major German federal highway running east–west through several states and connecting numerous towns and cities.
  • 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_69d8d38465a0819099b9b42d2a662ac1 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e53064a7548190b712a14ad0c7a477 completed April 19, 2026, 7:43 p.m.
Created at: April 10, 2026, 11:35 a.m.