Triple

T19680456
Position Surface form Disambiguated ID Type / Status
Subject Faches-Thumesnil E472569 entity
Predicate sharesBorderWith P224 FINISHED
Object Loos 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: Loos | Statement: [Faches-Thumesnil, sharesBorderWith, Loos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Loos
Context triple: [Faches-Thumesnil, sharesBorderWith, Loos]
  • A. Loos chosen
    Loos is a commune in northern France that forms part of the Lille metropolitan area.
  • B. Lobbes
    Lobbes is a historic municipality in the Walloon region of Belgium, known for its ancient abbey and picturesque rural setting.
  • C. La Hulpe
    La Hulpe is a small, affluent municipality in Walloon Brabant, Belgium, known for its green surroundings and the Château de La Hulpe within the Solvay Regional Estate.
  • D. Breda
    Breda is an Italian industrial company best known for manufacturing railway rolling stock, including trains and trams used in transit systems worldwide.
  • E. Breda
    Breda is a historic city in the southern Netherlands known for its medieval architecture, former status as a military and political center, and vibrant cultural life.
  • 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_69d8e514f2e08190ba70a4449519d218 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e641bf97348190bc31b00ed4ec6cad completed April 20, 2026, 3:09 p.m.
Created at: April 10, 2026, 1:45 p.m.