Triple

T3582052
Position Surface form Disambiguated ID Type / Status
Subject Vienna station E75821 entity
Predicate lineServed P6301 FINISHED
Object Orange Line unclear NED1 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: Orange Line | Statement: [Vienna station, lineServed, Orange Line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orange Line
Context triple: [Vienna station, lineServed, Orange Line]
  • A. Orange Line
    The Orange Line is one of the primary rapid transit routes in the Washington Metro system, running east–west through Washington, D.C. and its Virginia and Maryland suburbs.
  • B. Orange Line
    The Orange Line is a major corridor of the Delhi Metro system that connects central Delhi to the Indira Gandhi International Airport and surrounding areas.
  • C. Orange Line
    The Orange Line is a planned corridor of Bengaluru’s Namma Metro system intended to expand rapid transit connectivity across additional parts of the city.
  • D. Orange Line
    The Orange Line is a rapid transit route in Chicago that connects the city's Loop with Midway International Airport as part of the Chicago "L" system.
  • E. Orange Line
    The Orange Line is a light rail route in the Dallas Area Rapid Transit (DART) system serving key destinations including Dallas/Fort Worth International Airport and several northern suburbs.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

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_69ad85d6dc3c8190b491b79b83e25461 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc102cb2881908fa4dc1bf6fa5961 completed March 8, 2026, 6:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5336104a081908c5f07e8b4d22c58 completed March 14, 2026, 10:07 a.m.
Created at: March 8, 2026, 3:21 p.m.