Triple

T10400973
Position Surface form Disambiguated ID Type / Status
Subject Line 5 Eglinton E245144 entity
Predicate connectsWith P37 FINISHED
Object Line 3 Scarborough E46848 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: Line 3 Scarborough | Statement: [Line 5 Eglinton, connectsWith, Line 3 Scarborough]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Line 3 Scarborough
Context triple: [Line 5 Eglinton, connectsWith, Line 3 Scarborough]
  • A. Line 3 Scarborough chosen
    Line 3 Scarborough was a former light metro line of the Toronto subway system that served the Scarborough district in Toronto, Ontario, Canada.
  • B. Line 3A
    Line 3A is a planned rapid transit route of the Ho Chi Minh City Metro intended to serve as part of the city’s future urban rail network.
  • C. Metro Line 3
    Metro Line 3 is a major Mexico City Metro route that runs north–south across the city, connecting key residential and commercial areas including the Gustavo A. Madero borough.
  • D. RTA Waterfront Line
    The RTA Waterfront Line is a light rail line in Cleveland, Ohio, that connects downtown with the city's waterfront attractions and nearby neighborhoods.
  • E. Line 3–Red
    Line 3–Red is one of the busiest and most important lines of the São Paulo Metro, running east–west across the city and connecting key residential and commercial areas.
  • 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_69d381b5116081908d85227bab6d3c0c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9e2f11c8190b30695cba2975544 completed April 7, 2026, 11:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7fbd13c888190b3a79a9aacb5291e completed April 9, 2026, 7:19 p.m.
Created at: April 6, 2026, 12:07 p.m.