Triple

T3974705
Position Surface form Disambiguated ID Type / Status
Subject Boston T E85611 entity
Predicate hasLine P35 FINISHED
Object Orange Line E45338 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: [Boston T, hasLine, Orange Line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orange Line
Context triple: [Boston T, hasLine, Orange Line]
  • A. 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.
  • B. 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.
  • C. 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.
  • D. Orange Line chosen
    The Orange Line is a rapid transit route in the Boston metropolitan area that runs north–south through downtown as part of the MBTA subway 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.

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_69aed93908348190a26c8aaf4fab3e86 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef9b511f88190afca12c77481b344 completed March 9, 2026, 4:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69badb16faf88190aa047ba701ff7c0d completed March 18, 2026, 5:04 p.m.
Created at: March 9, 2026, 3:32 p.m.