Triple

T14938425
Position Surface form Disambiguated ID Type / Status
Subject Colmar-Berg E372457 entity
Predicate hasNeighbouringCommune P33892 FINISHED
Object Mersch E1080586 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: Mersch | Statement: [Colmar-Berg, hasNeighbouringCommune, Mersch]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mersch
Context triple: [Colmar-Berg, hasNeighbouringCommune, Mersch]
  • A. Mersch chosen
    Mersch is a commune and town in central Luxembourg known as a regional hub situated at the confluence of several rivers and important transport routes.
  • B. Bütgenbach
    Bütgenbach is a municipality in eastern Belgium’s German-speaking Community, known for its scenic lake, outdoor recreation, and proximity to the strategic Elsenborn Ridge.
  • C. Mechernich
    Mechernich is a small town in the Eifel region of North Rhine-Westphalia, Germany, known for its rural landscape and cultural landmarks such as the Bruder Klaus Field Chapel.
  • D. Dallenwil
    Dallenwil is a Swiss municipality known for its alpine setting and outdoor recreation opportunities in the canton of Nidwalden.
  • E. Erkelenz
    Erkelenz is a historic town in western Germany, known for its medieval origins and role as a regional administrative and cultural center.
  • 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_69d85cc9da0c81908d583ca3f63a3908 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded64904d88190b6b4140da8e8199d completed April 15, 2026, 12:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe968d71dc81909b76551f9cd9ebab completed May 9, 2026, 2:06 a.m.
Created at: April 10, 2026, 2:38 a.m.