Triple

T6637243
Position Surface form Disambiguated ID Type / Status
Subject commuter rail R2 Nord E150487 entity
Predicate hasSymbol P129 FINISHED
Object R2N
R2N is the symbol used to designate the R2 Nord commuter rail line in the Barcelona suburban railway network.
 E599013 NE FINISHED

How this triple was built (4 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: R2N | Statement: [commuter rail R2 Nord, hasSymbol, R2N]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: R2N
Context triple: [commuter rail R2 Nord, hasSymbol, R2N]
  • A. R2
    R2 is the MBTA station code used to identify Ashmont station on Boston's Red Line transit system.
  • B. 2RN
    2RN is the transmission and network services company responsible for operating Ireland’s national digital terrestrial television and radio infrastructure.
  • C. R29
    R29 is the internal station code used by the New York City Subway system to identify the 7th Avenue station on the BMT Brighton Line.
  • D. RNR
    RNR is the abbreviation for the Royal Naval Reserve, the volunteer reserve force of the United Kingdom’s Royal Navy.
  • E. R5
    R5 is a government office building in Oslo that forms part of Norway’s central Regjeringskvartalet complex.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: R2N
Triple: [commuter rail R2 Nord, hasSymbol, R2N]
Generated description
R2N is the symbol used to designate the R2 Nord commuter rail line in the Barcelona suburban railway network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: R2N
Target entity description: R2N is the symbol used to designate the R2 Nord commuter rail line in the Barcelona suburban railway network.
  • A. R2
    R2 is the MBTA station code used to identify Ashmont station on Boston's Red Line transit system.
  • B. 2RN
    2RN is the transmission and network services company responsible for operating Ireland’s national digital terrestrial television and radio infrastructure.
  • C. R29
    R29 is the internal station code used by the New York City Subway system to identify the 7th Avenue station on the BMT Brighton Line.
  • D. RNR
    RNR is the abbreviation for the Royal Naval Reserve, the volunteer reserve force of the United Kingdom’s Royal Navy.
  • E. R5
    R5 is the U.S. Forest Service’s Pacific Southwest Region, which oversees national forests primarily in California and parts of neighboring areas.
  • F. None of above. chosen

Provenance (5 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_69c687f0ceb08190bf40807bfc605fa5 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6afcf439c8190b9334b34774da821 completed March 27, 2026, 4:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cbf71874819080cc89b6740b1567 completed March 27, 2026, 6:27 p.m.
NEDg Description generation batch_69c6cd0bb0e48190ae51fde4b4631f65 completed March 27, 2026, 6:31 p.m.
NED2 Entity disambiguation (via description) batch_69c6cd90b9208190b4c5bf44db073314 completed March 27, 2026, 6:33 p.m.
Created at: March 27, 2026, 1:59 p.m.