Triple

T10847453
Position Surface form Disambiguated ID Type / Status
Subject Transilien Line N E256049 entity
Predicate connectsWith P37 FINISHED
Object RER Line B E10905 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: RER Line B | Statement: [Transilien Line N, connectsWith, RER Line B]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: RER Line B
Context triple: [Transilien Line N, connectsWith, RER Line B]
  • A. RER B line chosen
    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.
  • B. RER Line C
    RER Line C is a major commuter rail line in the Paris RER network, running along the Seine and serving numerous suburbs and key destinations in the Île-de-France region.
  • C. RER line E
    RER line E is a Paris regional express railway line connecting central Paris with eastern suburbs such as Gagny.
  • D. RER line D
    RER line D is one of the main lines of the Paris RER suburban rail network, running north–south through central Paris and serving numerous suburbs across the Île-de-France region.
  • E. RER NG
    RER NG is a new-generation double-deck electric multiple unit train designed for Île-de-France’s RER network, offering higher capacity, improved accessibility, and enhanced passenger comfort.
  • 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_69d6aa81a5d08190aa86689061d1ddd2 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d75113bc188190ac78df0c51d95de6 completed April 9, 2026, 7:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69dff7cc0d648190afb0ce80bac7f3dc completed April 15, 2026, 8:40 p.m.
Created at: April 8, 2026, 9:20 p.m.