Triple

T6491638
Position Surface form Disambiguated ID Type / Status
Subject Rosemont–La Petite-Patrie E148049 entity
Predicate hasMetroLine P17559 FINISHED
Object Blue Line E166089 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: Blue Line | Statement: [Rosemont–La Petite-Patrie, hasMetroLine, Blue Line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Blue Line
Context triple: [Rosemont–La Petite-Patrie, hasMetroLine, Blue Line]
  • A. Blue Line
    The Blue Line is one of the color-coded rapid transit routes in the Washington Metro system, running through key parts of Washington, D.C. and its Virginia suburbs.
  • B. Blue Line
    The Blue Line is one of Boston's MBTA rapid transit routes, running primarily between downtown Boston and the coastal communities of East Boston and Revere.
  • C. Blue Line
    Blue Line is a light rail line in the Los Angeles Metro Rail system that connects downtown Los Angeles with Long Beach and was the system’s inaugural route.
  • D. Blue Line
    The Blue Line is one of the primary heavy-rail transit routes in Atlanta’s MARTA system, running east–west across the metropolitan area and serving key urban and suburban stations.
  • E. Blue Line chosen
    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_69c009088f3081909cd467b05919de30 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c06a9bf9208190b0957eda06ed3d65 completed March 22, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c65fc0d90c8190abf85b591e90e292 completed March 27, 2026, 10:45 a.m.
Created at: March 22, 2026, 4:53 p.m.