Triple

T7130276
Position Surface form Disambiguated ID Type / Status
Subject Lille Europe E166167 entity
Predicate connectedTo P37 FINISHED
Object Lille tramway E491649 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: Lille tramway | Statement: [Lille Europe, connectedTo, Lille tramway]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lille tramway
Context triple: [Lille Europe, connectedTo, Lille tramway]
  • A. Lille tramway chosen
    The Lille tramway is a light rail system serving the Lille metropolitan area in northern France, complementing the city’s metro and bus networks.
  • B. Lille Metro
    The Lille Metro is a fully automated light metro system serving the city of Lille and its metropolitan area in northern France.
  • C. Valenciennes tramway
    The Valenciennes tramway is a modern light rail system serving the city of Valenciennes and its surrounding metropolitan area in northern France.
  • D. Strasbourg tramway
    The Strasbourg tramway is a modern light rail transit system in Strasbourg, France, known for its extensive network, integration with urban renewal, and cross-border service into Germany.
  • E. Tramway de Reims
    Tramway de Reims is the modern light rail tram system serving the city of Reims in northeastern France, providing urban public transportation across the metropolitan area.
  • 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_69c6888350588190870cd552b427a1cd completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e66dc2388190bdec018f1cc6b20a completed March 27, 2026, 8:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7ad8d00848190a5a4b9b64b3426e7 completed March 28, 2026, 10:29 a.m.
Created at: March 27, 2026, 2:44 p.m.