Triple

T3501660
Position Surface form Disambiguated ID Type / Status
Subject State/Lake station E73981 entity
Predicate servedByLine P1293 FINISHED
Object Green Line E17058 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 | Statement: [State/Lake station, servedByLine, Green Line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Green Line
Context triple: [State/Lake station, servedByLine, Green Line]
  • A. Green Line chosen
    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.
  • B. Green Line
    The Green Line is one of the color-coded routes of the Tyne and Wear Metro rapid transit system serving the Newcastle upon Tyne area in northeast England.
  • C. Green Line
    The Green Line is one of the main rapid transit routes of the Dubai Metro, serving key districts along Dubai Creek and connecting important commercial and residential areas.
  • D. Green Line
    The Green Line is one of the major corridors of the Delhi Metro network, serving western parts of Delhi and connecting key residential and industrial areas to the rest of the city.
  • E. Green Line
    The Green Line is one of the main rapid transit corridors of the Chennai Metro system in Chennai, India, connecting key areas of the city via elevated and underground stations.
  • 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_69ad85cdb6e48190a335d412b9194ed8 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbbd5fbe8819091b61fa8df355f0c completed March 8, 2026, 6:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdacbe49ac81908f014539a1147a4f completed March 20, 2026, 8:23 p.m.
Created at: March 8, 2026, 3:18 p.m.