Triple

T14680865
Position Surface form Disambiguated ID Type / Status
Subject Mondercange E344778 entity
Predicate hasNeighbouringCommune P33892 FINISHED
Object Roeser E1056589 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: Roeser | Statement: [Mondercange, hasNeighbouringCommune, Roeser]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Roeser
Context triple: [Mondercange, hasNeighbouringCommune, Roeser]
  • A. Roeser chosen
    Roeser is a commune and small town in southern Luxembourg, situated just south of Luxembourg City in the country’s Minett region.
  • B. Roderesch
    Roderesch is a small village in the municipality of Noordenveld in the province of Drenthe in the northeastern Netherlands.
  • C. Rutishauser
    Rutishauser is a Swiss surname most notably associated with Heinz Rutishauser, a pioneering mathematician and computer scientist in the field of numerical analysis and early programming languages.
  • D. Riedesel
    Riedesel is a German surname historically associated with noble families and notable figures such as military officers and diplomats.
  • E. Röthlein
    Röthlein is a small municipality in the Schweinfurt district of Bavaria, Germany.
  • 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_69d822e34b348190ada4d1cdb6c7c226 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb5692284819090f775be8e478522 completed April 14, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fde180ff0c8190a8b7c7804e36c3f8 completed May 8, 2026, 1:13 p.m.
Created at: April 10, 2026, 1:28 a.m.