Triple

T17023945
Position Surface form Disambiguated ID Type / Status
Subject TGV services E413016 entity
Predicate majorHub P2958 FINISHED
Object Marseille Saint-Charles E323196 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: Marseille Saint-Charles | Statement: [TGV services, majorHub, Marseille Saint-Charles]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marseille Saint-Charles
Context triple: [TGV services, majorHub, Marseille Saint-Charles]
  • A. Marseille-Saint-Charles station chosen
    Marseille-Saint-Charles station is the main railway terminus in Marseille, France, serving as a major national and regional transport hub.
  • B. Montpellier Sud de France station
    Montpellier Sud de France station is a modern high-speed railway station serving the city of Montpellier in southern France, primarily on the TGV network.
  • C. Lyon-Perrache station
    Lyon-Perrache station is one of Lyon’s main railway hubs, serving regional, national, and international train connections in southeastern France.
  • D. Nîmes station
    Nîmes station is a major railway hub in southern France that connects the city of Nîmes to regional and high-speed national rail networks.
  • E. Vanves–Malakoff station
    Vanves–Malakoff station is a suburban railway station in the southwestern Paris metropolitan area serving local commuter traffic on the Transilien network.
  • 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_69d886cc4170819093deddc7b8b4b6a7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d5d2abbc81908943becf5f539fc6 completed April 18, 2026, 7:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a012334c3b48190b125ab926450c45b completed May 11, 2026, 12:30 a.m.
Created at: April 10, 2026, 5:33 a.m.