Triple

T20604359
Position Surface form Disambiguated ID Type / Status
Subject Ashby station E506263 entity
Predicate servedByLine P1293 FINISHED
Object Green Line 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: Green Line | Statement: [Ashby station, servedByLine, Green Line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Green Line
Context triple: [Ashby station, servedByLine, Green Line]
  • A. Green Line
    The Green Line is the oldest and busiest line of the Athens Metro, running primarily at ground level and connecting key northern and southern suburbs through central Athens.
  • B. Green Line
    The Green Line is one of Chicago's elevated rapid transit routes, running primarily along the city's West and South Sides as part of the Chicago "L" system.
  • C. Green Line
    The Green Line is one of the main rapid transit routes of the Dubai Metro, serving key districts along Dubai Creek and connecting important commercial and residential areas.
  • D. Green Line
    Green Line is a hybrid-oriented trim level of the Saturn Aura midsize sedan designed to offer improved fuel efficiency and lower emissions.
  • E. Green Line
    The Green Line is a light rail service route within the San Diego Trolley system that connects key destinations across the San Diego metropolitan area.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

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_69e0b4bb2b4081908fa4a72444120f35 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6aa233e1881908749d2f29c2946e4 completed April 20, 2026, 10:35 p.m.
Created at: April 16, 2026, 11:41 a.m.