Triple

T16817521
Position Surface form Disambiguated ID Type / Status
Subject Lille-Flandres E408791 entity
Predicate hasTransportConnection P845 FINISHED
Object Lille Metro E114351 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 Metro | Statement: [Lille-Flandres, hasTransportConnection, Lille Metro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lille Metro
Context triple: [Lille-Flandres, hasTransportConnection, Lille Metro]
  • A. Lille Metro chosen
    The Lille Metro is a fully automated light metro system serving the city of Lille and its metropolitan area in northern France.
  • B. Lille tramway
    The Lille tramway is a light rail system serving the Lille metropolitan area in northern France, complementing the city’s metro and bus networks.
  • C. Lyon Metro
    Lyon Metro is the rapid transit system serving the French city of Lyon and its suburbs, known for its rubber-tyred lines and integration with the city’s broader public transport network.
  • D. Marseille metro
    The Marseille metro is the rapid transit system serving the city of Marseille, France, providing underground rail connections across key urban areas.
  • E. Charleroi Metro
    Charleroi Metro is a light rail and pre-metro transit system serving the Belgian city of Charleroi and its suburbs.
  • 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_69d88394566c8190b3dcbdc72935f7fa completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b2e30cf48190a61936ba0a49df24 completed April 18, 2026, 4:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00bb0f863081908e74dc4a7c91e91d completed May 10, 2026, 5:06 p.m.
Created at: April 10, 2026, 5:23 a.m.