Triple

T2692473
Position Surface form Disambiguated ID Type / Status
Subject Exhibition Place E58433 entity
Predicate servedBy P82 FINISHED
Object Exhibition GO Station E58159 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: Exhibition GO Station | Statement: [Exhibition Place, servedBy, Exhibition GO Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Exhibition GO Station
Context triple: [Exhibition Place, servedBy, Exhibition GO Station]
  • A. Exhibition GO Station chosen
    Exhibition GO Station is a commuter rail station in Toronto, Ontario, serving GO Transit passengers traveling to and from the Canadian National Exhibition grounds and the surrounding waterfront area.
  • B. Expo 2020 station
    Expo 2020 station is a Dubai Metro station that serves the Expo 2020 site and its surrounding developments in Dubai, United Arab Emirates.
  • C. The Expo
    The Expo is a well-known multipurpose event and exhibition venue in Portland, Oregon, hosting trade shows, conventions, and community events.
  • D. Expo Center station
    Expo Center station is a light rail station in Portland, Oregon, serving as the northern terminus of TriMet’s MAX Yellow Line near the Portland Expo Center.
  • E. Shibuya Depot
    Shibuya Depot is a Tokyo Metro facility in Shibuya used for the storage, inspection, and maintenance of Ginza Line trains.
  • 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_69ab4ac269e481909cb317d79e68b75b completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abda0dd97c81909a60cf200f57c087 completed March 7, 2026, 7:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69afaf6501088190b8fe1ba8de4f6e00 completed March 10, 2026, 5:43 a.m.
Created at: March 6, 2026, 9:54 p.m.