Triple

T6743370
Position Surface form Disambiguated ID Type / Status
Subject Green Line at North Station E154145 entity
Predicate locatedIn P40 FINISHED
Object North Station E2878 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: North Station | Statement: [Green Line at North Station, locatedIn, North Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: North Station
Context triple: [Green Line at North Station, locatedIn, North Station]
  • A. North Station chosen
    North Station is a major transportation hub in Boston, Massachusetts, serving as a key commuter rail, subway, and intercity bus terminal integrated with the TD Garden arena.
  • B. Airport North Station
    Airport North Station is a Guangzhou Metro station serving the northern area of Guangzhou Baiyun International Airport.
  • C. Airport North Station
    Airport North Station is a metro station in Shenzhen that serves the Shenzhen Bao’an International Airport area, providing urban rail access for air travelers and airport staff.
  • D. South Station
    South Station is Boston’s major intercity rail and bus terminal and a key MBTA subway hub in the city’s downtown.
  • E. Back Bay station
    Back Bay station is a major transportation hub in Boston, Massachusetts, serving MBTA commuter rail, Amtrak, and subway lines in the Back Bay neighborhood.
  • 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_69c6880d84d8819095d19de2295f26ac completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d1b3b1448190a94b4b64f01af14a completed March 27, 2026, 6:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69c70b11b828819084d5a21dde5f1f5b completed March 27, 2026, 10:56 p.m.
Created at: March 27, 2026, 2:10 p.m.