Triple

T6493359
Position Surface form Disambiguated ID Type / Status
Subject Goose Hollow E148094 entity
Predicate servedBy P82 FINISHED
Object MAX Blue Line E21652 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 Blue Line | Statement: [Goose Hollow, servedBy, MAX Blue Line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MAX Blue Line
Context triple: [Goose Hollow, servedBy, MAX Blue Line]
  • A. MAX Blue Line chosen
    MAX Blue Line is a light rail service in the Portland, Oregon metropolitan area that connects downtown Portland with eastern and western suburbs as part of the region’s MAX Light Rail system.
  • B. Blue Line
    The Blue Line is one of the main lines of the Lisbon Metro system, serving key central and northern areas of Portugal’s capital city.
  • C. Blue Line
    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.
  • D. Blue Line
    Blue Line is a light rail line in the Los Angeles Metro Rail system that connects downtown Los Angeles with Long Beach and was the system’s inaugural route.
  • E. Blue Line
    The Blue Line is a primary light rail route of the San Diego Trolley system, running through key corridors of the San Diego metropolitan area.
  • 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_69c009088f3081909cd467b05919de30 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c06ab6abbc8190a4971ad5a654b0cd completed March 22, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c653bf5c30819083e4e5484b2bd8cc completed March 27, 2026, 9:54 a.m.
Created at: March 22, 2026, 4:53 p.m.