Triple

T8134410
Position Surface form Disambiguated ID Type / Status
Subject Green Line (DART) E189932 entity
Predicate hasStation P35 FINISHED
Object Bachman station E310572 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: Bachman station | Statement: [Green Line (DART), hasStation, Bachman station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bachman station
Context triple: [Green Line (DART), hasStation, Bachman station]
  • A. Bachman station chosen
    Bachman station is a public transit stop in Dallas, Texas, served by DART’s Green Line light rail system.
  • B. Briarwood station
    Briarwood station is a New York City Subway station in Queens serving the IND Queens Boulevard Line.
  • C. Maplewood station
    Maplewood station is a commuter rail stop on NJ Transit's Morris & Essex Lines serving the suburban community of Maplewood, New Jersey.
  • D. Albertson station
    Albertson station is a Long Island Rail Road commuter rail stop located in the hamlet of Albertson, New York.
  • E. Meadow Woods station
    Meadow Woods station is a commuter rail stop in the Orlando, Florida area served by the SunRail regional rail system.
  • 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_69ca82bcb4848190a9a9d036ad768642 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb43bbae608190bdc1afe6f0ab83ae completed March 31, 2026, 3:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd679a353c8190abe30eb7db13c072 completed April 1, 2026, 6:44 p.m.
Created at: March 30, 2026, 5:35 p.m.