Triple

T22295064
Position Surface form Disambiguated ID Type / Status
Subject European route E31 E551095 entity
Predicate passesThrough P225 FINISHED
Object Wesel 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: Wesel | Statement: [European route E31, passesThrough, Wesel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wesel
Context triple: [European route E31, passesThrough, Wesel]
  • A. Wesel chosen
    Wesel is a historic city in western Germany, located on the Rhine River in the state of North Rhine-Westphalia.
  • B. Viersen
    Viersen is a town in western Germany’s North Rhine-Westphalia, known for its proximity to Mönchengladbach and its role as a local administrative and cultural center.
  • C. Erftstadt
    Erftstadt is a town in the Rhein-Erft district of North Rhine-Westphalia, Germany, located southwest of Cologne and known for its mix of historic villages and suburban residential areas.
  • D. Merzig
    Merzig is a town in the Saarland region of western Germany, near the borders with France and Luxembourg.
  • E. City of Wesel
    The City of Wesel is a historic German town on the Lower Rhine that became an important Reformation and trading center in the early modern period.
  • 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_69e11e45fb848190a1b2ae21296e3a5f completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f1560f06008190b58e71f7c1bd46f7 completed April 29, 2026, 12:51 a.m.
Created at: April 16, 2026, 8:41 p.m.