Triple

T7271450
Position Surface form Disambiguated ID Type / Status
Subject Noyes station E161113 entity
Predicate line P1293 FINISHED
Object Purple Line E18256 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: Purple Line | Statement: [Noyes station, line, Purple Line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Purple Line
Context triple: [Noyes station, line, Purple Line]
  • A. Purple Line
    The Purple Line is a major rapid transit corridor of Bengaluru’s Namma Metro system, connecting key residential and commercial areas across the city.
  • B. Purple Line chosen
    The Purple Line is a rapid transit route in Chicago's 'L' system that primarily serves the city's northern suburbs and connects them to the North Side of Chicago.
  • C. Purple Line
    The Purple Line is a light rail route in Houston, Texas, that serves as part of the METRORail system, connecting downtown with southeastern neighborhoods and key destinations.
  • D. Blue Line
    The Blue Line is one of the Montreal Metro’s rapid transit lines, running east–west to serve several central and northeastern neighborhoods of the city.
  • E. Blue Line
    The Blue Line is one of the main lines of the Lisbon Metro system, serving key central and northern areas of Portugal’s capital city.
  • 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_69c6885181008190b419040e22939c7c completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eb0a03888190b5aa1da80dd303c5 completed March 27, 2026, 8:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7fa6d84b88190916b1d9ddb0d1d0d completed March 28, 2026, 3:57 p.m.
Created at: March 27, 2026, 2:58 p.m.