Triple

T17533360
Position Surface form Disambiguated ID Type / Status
Subject Red Line (METRORail) E426993 entity
Predicate system P730 FINISHED
Object METRORail NE NERFINISHED

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: [Red Line (METRORail), system, METRORail]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: METRORail
Context triple: [Red Line (METRORail), system, METRORail]
  • A. Metro Rail
    Metro Rail is the light rail rapid transit system serving the Buffalo–Niagara region of New York.
  • B. Metro Rail
    Metro Rail is the urban rapid transit rail system serving Los Angeles County, providing light rail and subway services across the region.
  • C. METRORail light rail chosen
    METRORail light rail is Houston's urban light rail transit system operated by METRO, connecting key destinations throughout the city’s central area.
  • D. Metrorail
    Metrorail is the rapid transit system serving the Washington, D.C. metropolitan area, operated by the Washington Metropolitan Area Transit Authority (WMATA).
  • E. Metrorail
    Metrorail is Miami-Dade County’s elevated rapid transit system that connects key neighborhoods, suburbs, and downtown Miami.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889de677081909b22d2657b1f0292 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4536a0f588190ade91d32308897a0 completed April 19, 2026, 4 a.m.
Created at: April 10, 2026, 5:49 a.m.