Triple

T15030160
Position Surface form Disambiguated ID Type / Status
Subject T-bana E378321 entity
Predicate hasLine P35 FINISHED
Object Red line E378957 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: Red line | Statement: [T-bana, hasLine, Red line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Red line
Context triple: [T-bana, hasLine, Red line]
  • A. Red line chosen
    The Red line is one of the main color-coded routes of the Stockholm metro system, serving numerous central and suburban stations across the city.
  • B. Red Line
    The Red Line is a regional express bus route operated under the SolanoExpress system, providing intercity transit service in Solano County and surrounding areas.
  • C. Red Line
    Red Line is a major rapid transit route in the Washington Metro system, running through key areas of Washington, D.C., and its Maryland suburbs.
  • D. Red Line
    The Red Line is a major rapid transit route in Chicago that runs north–south through the city, serving as one of the busiest lines in its subway and elevated rail system.
  • E. Red Line
    The Red Line is a rapid transit route in the Greater Cleveland Regional Transit Authority system that connects Cleveland Hopkins International Airport with downtown and eastern suburbs.
  • 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_69d85cd46b2c819090d054c27787f677 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded7e2416081908dfba48d7f7b4a84 completed April 15, 2026, 12:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69fea5b4d58481908afbc89263e07b50 completed May 9, 2026, 3:10 a.m.
Created at: April 10, 2026, 2:59 a.m.