Triple

T3215547
Position Surface form Disambiguated ID Type / Status
Subject Antony E67385 entity
Predicate railNetwork P522 FINISHED
Object Réseau Express Régional (RER) E68667 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: Réseau Express Régional (RER) | Statement: [Antony, railNetwork, Réseau Express Régional (RER)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Réseau Express Régional (RER)
Context triple: [Antony, railNetwork, Réseau Express Régional (RER)]
  • A. RER network chosen
    The RER network is a rapid transit system of express suburban trains serving Paris and its surrounding metropolitan area, integrating both urban and regional rail services.
  • B. RER A
    RER A is one of the main lines of the Paris regional express network, carrying large volumes of commuters and travelers between central Paris and its suburbs.
  • C. RER B line
    The RER B line is a major Paris regional express railway line that connects central Paris with key northern and southern suburbs, including Charles de Gaulle Airport.
  • D. RER D
    RER D is one of the main lines of the Paris regional express network (RER), connecting northern and southern suburbs through central Paris.
  • E. RER line E
    RER line E is a Paris regional express railway line connecting central Paris with eastern suburbs such as Gagny.
  • 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_69ad858ac36c81909962589cd277d6e2 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adab085a408190af9fb40acca31a5f completed March 8, 2026, 4:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69b533595bb88190814ea2ebe3495525 completed March 14, 2026, 10:07 a.m.
Created at: March 8, 2026, 3:07 p.m.