Triple

T15040495
Position Surface form Disambiguated ID Type / Status
Subject Centralbron E378586 entity
Predicate partOf P40 FINISHED
Object European route E4 E118533 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: European route E4 | Statement: [Centralbron, partOf, European route E4]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: European route E4
Context triple: [Centralbron, partOf, European route E4]
  • A. European route E4 chosen
    European route E4 is a major north–south European highway running through Sweden, connecting key cities from Helsingborg in the south to Tornio at the Finnish border.
  • B. European route E45
    European route E45 is a major north–south trans-European highway running from northern Scandinavia through central Europe to southern Italy.
  • C. European route E46
    European route E46 is an international E-road corridor in Western Europe that connects cities in France, Belgium, and Germany as part of the trans-European road network.
  • D. European route E42
    European route E42 is a major west–east European highway running from France through Belgium and Germany, forming part of the international E-road network.
  • E. European route E41
    European route E41 is a major north–south European highway running through Germany and Switzerland, linking cities such as Dortmund, Kassel, Würzburg, Nuremberg, and Zurich.
  • 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_69d85cd46b2c819090d054c27787f677 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded82e79a481908ddb9609af8c4407 completed April 15, 2026, 12:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69febfd954548190b3f7c60d95403f3e completed May 9, 2026, 5:02 a.m.
Created at: April 10, 2026, 3 a.m.