Triple

T15853646
Position Surface form Disambiguated ID Type / Status
Subject Métropole Européenne de Lille E384400 entity
Predicate containsAdministrativeTerritorialEntity P747 FINISHED
Object Lomme E472572 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: Lomme | Statement: [Métropole Européenne de Lille, containsAdministrativeTerritorialEntity, Lomme]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lomme
Context triple: [Métropole Européenne de Lille, containsAdministrativeTerritorialEntity, Lomme]
  • A. Lomme chosen
    Lomme is a suburban district and former commune that now forms part of the metropolitan area of Lille in northern France.
  • B. Lomma
    Lomma is a coastal municipality in southern Sweden known for its beaches and proximity to the city of Malmö.
  • C. Lönnbohm
    Lönnbohm is the original family name of the renowned Finnish poet and journalist Eino Leino.
  • D. Tammela
    Tammela is a rural municipality in southern Finland known for its forests, lakes, and national parks such as Torronsuo and Liesjärvi.
  • E. Löningen
    Löningen is a small town and municipality in Lower Saxony, Germany, known for its rural character and location within the Cloppenburg district.
  • 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_69d86da422088190aac39e32e6c68429 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e14cae96648190884a85f68b6e9fe1 completed April 16, 2026, 8:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffa14977408190815ef02cc54075cc completed May 9, 2026, 9:04 p.m.
Created at: April 10, 2026, 4:50 a.m.