Triple

T2103898
Position Surface form Disambiguated ID Type / Status
Subject Washington Metro Green Line E37149 entity
Predicate connectsWith P37 FINISHED
Object Yellow Line E14071 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: Yellow Line | Statement: [Washington Metro Green Line, connectsWith, Yellow Line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yellow Line
Context triple: [Washington Metro Green Line, connectsWith, Yellow Line]
  • A. Yellow Line chosen
    The Yellow Line is one of the color-coded rapid transit routes in the Washington Metro system, running primarily in a north–south direction and serving key areas in Washington, D.C. and Northern Virginia.
  • B. Yellow Line
    The Yellow Line is one of the primary passenger rail routes of the Tyne and Wear Metro rapid transit system serving the Newcastle upon Tyne area in North East England.
  • C. Yellow Line
    The Yellow Line is one of the main lines of the Lisbon Metro system, connecting key residential and commercial areas of Portugal’s capital.
  • D. Yellow Line
    Yellow Line is one of the major rapid transit corridors of the Delhi Metro network, connecting key areas across Delhi and its neighboring regions.
  • E. Yellow Line
    The Yellow Line is a designated route within the Baltimore Light Rail system that serves as one of its primary color-coded service lines.
  • 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_69af175e79d881909390ae71cceb6db2 completed March 9, 2026, 6:54 p.m.
Created at: March 4, 2026, 7:43 p.m.