Triple

T6110513
Position Surface form Disambiguated ID Type / Status
Subject Aquarium E136225 entity
Predicate servedByLine P1293 FINISHED
Object Blue Line E45844 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: Blue Line | Statement: [Aquarium, servedByLine, Blue Line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Blue Line
Context triple: [Aquarium, servedByLine, Blue Line]
  • A. Blue Line
    The Blue Line is one of the color-coded rapid transit routes in the Washington Metro system, running through key parts of Washington, D.C. and its Virginia suburbs.
  • B. Blue Line chosen
    The Blue Line is one of Boston's MBTA rapid transit routes, running primarily between downtown Boston and the coastal communities of East Boston and Revere.
  • C. Blue Line
    The Blue Line is one of the primary heavy-rail transit routes in Atlanta’s MARTA system, running east–west across the metropolitan area and serving key urban and suburban stations.
  • D. Blue Line
    The Blue Line is one of the major corridors of the Delhi Metro rapid transit system, connecting key residential and commercial areas across Delhi and its neighboring regions.
  • E. Blue Line
    The Blue Line is a light rail route in the Dallas Area Rapid Transit (DART) system serving key neighborhoods and suburbs in the Dallas–Fort Worth metroplex.
  • 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_69c0089ea6f88190b349be53e04b4f5f completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05b84ed088190a12cdb844d743326 completed March 22, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c20d56f234819082d89a755ae5a446 completed March 24, 2026, 4:04 a.m.
Created at: March 22, 2026, 4:13 p.m.