Triple

T4529073
Position Surface form Disambiguated ID Type / Status
Subject Tilikum Crossing E106249 entity
Predicate carries P1393 FINISHED
Object MAX Orange Line E22353 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: MAX Orange Line | Statement: [Tilikum Crossing, carries, MAX Orange Line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MAX Orange Line
Context triple: [Tilikum Crossing, carries, MAX Orange Line]
  • A. MAX Orange Line chosen
    The MAX Orange Line is a light rail service in the Portland, Oregon metropolitan area that connects downtown Portland with the southeast corridor, including Milwaukie.
  • B. 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.
  • C. 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.
  • D. 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.
  • E. 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.
  • 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_69bd43f3d6e08190a91824f833d51bbe completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd5779593081908593537b9239e01b completed March 20, 2026, 2:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69bda45eadd0819093429e14c88a161d completed March 20, 2026, 7:47 p.m.
Created at: March 20, 2026, 1:03 p.m.