Triple

T22887772
Position Surface form Disambiguated ID Type / Status
Subject Bonn public transport network E567650 entity
Predicate connectsArea P2564 FINISHED
Object Bad Godesberg 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: Bad Godesberg | Statement: [Bonn public transport network, connectsArea, Bad Godesberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bad Godesberg
Context triple: [Bonn public transport network, connectsArea, Bad Godesberg]
  • A. Bad Godesberg chosen
    Bad Godesberg is a district in the city of Bonn, Germany, known for its affluent residential areas, former diplomatic missions, and scenic location along the Rhine River.
  • B. Godesberg
    Godesberg is a historic district in Bonn, Germany, known for its medieval castle ruins and role in regional conflicts such as the Cologne War.
  • C. Bad Driburg
    Bad Driburg is a small spa town in North Rhine-Westphalia, Germany, known for its mineral springs and health resorts.
  • D. Heiligenstadt
    Heiligenstadt is a historic neighborhood in Vienna, Austria, known for its wine taverns and its association with composer Ludwig van Beethoven.
  • E. Bogheim
    Bogheim is a small village in North Rhine-Westphalia, Germany, that forms part of the municipality of Kreuzau in the Düren district.
  • 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_69e2458a92ec81908fc1cd5f6407d2ab completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17fc2adb4819081bce7e6849ba31a completed April 29, 2026, 3:49 a.m.
Created at: April 17, 2026, 3:40 p.m.