Triple

T19939149
Position Surface form Disambiguated ID Type / Status
Subject Bischofswerda E479256 entity
Predicate nearestMotorway P25934 FINISHED
Object A4 motorway — 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: A4 motorway | Statement: [Bischofswerda, nearestMotorway, A4 motorway]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: A4 motorway
Context triple: [Bischofswerda, nearestMotorway, A4 motorway]
  • A. A4 motorway
    The A4 motorway is a major Dutch highway that connects key cities including Amsterdam, The Hague, and Rotterdam, forming part of the European route network.
  • B. A4 motorway
    The A4 motorway is a major Italian highway running across northern Italy, connecting key cities such as Turin, Milan, Verona, Vicenza, and Venice.
  • C. A4 motorway
    The A4 motorway is a major French highway connecting Paris to the eastern regions of France and onward toward Germany, serving as a key commuter and long-distance route.
  • D. A4 motorway
    The A4 motorway is a major Swiss highway that connects the Zurich region with central and northern parts of the country, facilitating both local and international transit.
  • E. A4 motorway chosen
    The A4 motorway is a major German autobahn running east–west across central Germany, connecting cities such as Aachen, Cologne, Erfurt, Jena, and Dresden.
  • 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_69d8e522a17c819095165d4d24939fd8 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65a19d77c819088bce99c94568d0d completed April 20, 2026, 4:53 p.m.
Created at: April 10, 2026, 1:53 p.m.