Triple

T15028498
Position Surface form Disambiguated ID Type / Status
Subject Arnhem–Winterswijk railway E378277 entity
Predicate serves P98 FINISHED
Object Wehl E1052107 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: Wehl | Statement: [Arnhem–Winterswijk railway, serves, Wehl]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wehl
Context triple: [Arnhem–Winterswijk railway, serves, Wehl]
  • A. Wehl chosen
    Wehl is a village in the Dutch province of Gelderland that formerly existed as an independent municipality before being incorporated into the nearby city of Doetinchem.
  • B. Wolfach
    Wolfach is a small town in the Black Forest region of Baden-Württemberg, Germany, known for its traditional glassmaking and picturesque setting along the Kinzig River.
  • C. Wehlen
    Wehlen is a wine-growing village on the Moselle River in Germany, renowned for its steep slate vineyards and high-quality Riesling wines.
  • D. Rheydt
    Rheydt is a district of the German city of Mönchengladbach in North Rhine-Westphalia, historically an independent town in the Rhineland.
  • E. Gernsbach
    Gernsbach is a historic town in southwestern Germany’s Black Forest region, known for its medieval old town and picturesque setting along the Murg River.
  • 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_69ded7e0e8c88190ac6f5786b4d4040f completed April 15, 2026, 12:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffcf0743288190b3bec8c48b5c7893 completed May 10, 2026, 12:19 a.m.
Created at: April 10, 2026, 2:58 a.m.