Triple

T8557518
Position Surface form Disambiguated ID Type / Status
Subject Blue Line (DART) E202609 entity
Predicate connectsWith P37 FINISHED
Object Green Line (DART) E51613 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: Green Line (DART) | Statement: [Blue Line (DART), connectsWith, Green Line (DART)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Green Line (DART)
Context triple: [Blue Line (DART), connectsWith, Green Line (DART)]
  • A. DART Green Line chosen
    The DART Green Line is a light rail service in Dallas, Texas, operated by Dallas Area Rapid Transit and running through key corridors including downtown and Fair Park.
  • B. DART Red Line
    The DART Red Line is a light rail service in Dallas, Texas, forming one of the primary routes in the Dallas Area Rapid Transit rail network.
  • C. Green Line
    The Green Line is one of Chicago's elevated rapid transit routes, running primarily along the city's West and South Sides as part of the Chicago "L" system.
  • D. Green Line
    The Green Line is one of the main corridors of the Hyderabad Metro rapid transit system, serving key areas of the city along its north–south axis.
  • E. Green Line
    The Green Line is one of the color-coded rapid transit routes in the Washington Metro system, serving key neighborhoods in Washington, D.C. and parts of Maryland.
  • 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_69ca8326e6c881908ff720d6abaebdc5 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe946d1408190adc7dfb7b2173f9d completed March 31, 2026, 3:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea868de6881908e87270a1fea0e4b completed April 2, 2026, 5:33 p.m.
Created at: March 30, 2026, 6:20 p.m.