Triple

T19120039
Position Surface form Disambiguated ID Type / Status
Subject Autobahn A59 E468016 entity
Predicate passesThrough P225 FINISHED
Object Dinslaken 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: Dinslaken | Statement: [Autobahn A59, passesThrough, Dinslaken]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dinslaken
Context triple: [Autobahn A59, passesThrough, Dinslaken]
  • A. Dinslaken chosen
    Dinslaken is a town in western Germany’s North Rhine-Westphalia region, known for its industrial heritage and proximity to the Ruhr area.
  • B. Tennstädt
    Tennstädt is a small town in the Thuringia region of central Germany.
  • C. Fricktal
    Fricktal is a region in northwestern Switzerland known for its rural landscapes, vineyards, and location along the Rhine near the German border.
  • D. Gallneukirchen
    Gallneukirchen is a small Austrian town in Upper Austria known for its local community life and regional cultural traditions.
  • E. Baltschieder
    Baltschieder is a small Swiss municipality in the canton of Valais, located in the Upper Valais region of the Alps.
  • 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_69d8dd06a26481908039e2a1bae8c597 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e3c810808190a88d5c7859e7c650 completed April 20, 2026, 8:28 a.m.
Created at: April 10, 2026, 12:05 p.m.