Triple

T2103889
Position Surface form Disambiguated ID Type / Status
Subject Washington Metro Green Line E37149 entity
Predicate hasStation P35 FINISHED
Object Waterfront station E71536 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: Waterfront station | Statement: [Washington Metro Green Line, hasStation, Waterfront station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Waterfront station
Context triple: [Washington Metro Green Line, hasStation, Waterfront station]
  • A. Waterfront station chosen
    Waterfront station is a Washington Metro rapid transit stop in Southwest Washington, D.C., serving the Green Line and the surrounding waterfront neighborhood.
  • B. Riverside station
    Riverside station is a major Massachusetts Bay Transportation Authority light rail station and park-and-ride hub located in Newton, Massachusetts.
  • C. Bayside station
    Bayside station is a Long Island Rail Road commuter rail stop in the Bayside neighborhood of Queens, New York City.
  • D. Reservoir station
    Reservoir station is a light rail stop on Boston’s MBTA Green Line that serves the D branch near Cleveland Circle in Brookline.
  • E. Bridgeport station
    Bridgeport station is a SEPTA rapid transit stop in Bridgeport, Pennsylvania, serving passengers on the Norristown High Speed Line.
  • 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_69a8861828948190924aa30c08806b3a completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abbabf7cdc81909636dff34badc1c5 completed March 7, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae3069f78c819092a6d9d903e4df13 completed March 9, 2026, 2:28 a.m.
Created at: March 4, 2026, 7:43 p.m.