Triple

T14199190
Position Surface form Disambiguated ID Type / Status
Subject Bundesstraße 9 E351918 entity
Predicate hasRouteType P13326 FINISHED
Object Bundesstraße E303466 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 | Statement: [Bundesstraße 9, hasRouteType, Bundesstraße]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bundesstraße
Context triple: [Bundesstraße 9, hasRouteType, Bundesstraße]
  • A. Bundesstraße chosen
    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.
  • B. Bundesstraße 10
    Bundesstraße 10 is a major federal highway in southern Germany that runs east–west and connects several important cities in the states of Baden-Württemberg and Rhineland-Palatinate.
  • C. Bundesstraße 14
    Bundesstraße 14 is a major federal highway in Germany that connects several important cities and regions in the southern part of the country.
  • 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 11
    Bundesstraße 11 is a major federal highway in southern Germany that runs through Bavaria, connecting Munich with the Bavarian Forest region near the Czech border.
  • 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_69d827894ac0819097803e57f3227b23 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61f472548190a1a7edc40526eac3 completed April 14, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4676a2bc8190af239516ddbbf5e3 completed May 8, 2026, 2:12 a.m.
Created at: April 10, 2026, 1:04 a.m.