Triple

T1954151
Position Surface form Disambiguated ID Type / Status
Subject Vienna/Fairfax–GMU station E42225 entity
Predicate partOfNetwork P840 FINISHED
Object Metrorail E56829 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: Metrorail | Statement: [Vienna/Fairfax–GMU station, partOfNetwork, Metrorail]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Metrorail
Context triple: [Vienna/Fairfax–GMU station, partOfNetwork, Metrorail]
  • A. Metrorail
    Metrorail is Miami-Dade County’s elevated rapid transit system that connects key neighborhoods, suburbs, and downtown Miami.
  • B. Metrorail chosen
    Metrorail is the rapid transit system serving the Washington, D.C. metropolitan area, operated by the Washington Metropolitan Area Transit Authority (WMATA).
  • C. Metro Rail
    Metro Rail is the urban rapid transit rail system serving Los Angeles County, providing light rail and subway services across the region.
  • D. METRORail Red Line
    The METRORail Red Line is a light rail line in Houston, Texas, running through key central areas including downtown and the Museum District.
  • E. METRO light rail
    METRO light rail is a rapid transit system serving the Minneapolis–Saint Paul metropolitan area with multiple color-designated lines connecting key urban, suburban, and airport destinations.
  • 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_69a8870eea088190a38781990812a9bc completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb351c148819080173c09876e814a completed March 7, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69adfbc8146c819084d3dc3b16efb123 completed March 8, 2026, 10:44 p.m.
Created at: March 4, 2026, 7:36 p.m.