Triple

T2448909
Position Surface form Disambiguated ID Type / Status
Subject Old Toronto E53654 entity
Predicate servedBy P82 FINISHED
Object UP Express E99224 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: UP Express | Statement: [Old Toronto, servedBy, UP Express]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: UP Express
Context triple: [Old Toronto, servedBy, UP Express]
  • A. UP Express chosen
    UP Express is a dedicated airport rail link in Toronto that provides fast, frequent train service between Union Station downtown and Toronto Pearson International Airport.
  • B. UPS Worldwide Express
    UPS Worldwide Express is a premium international shipping service from UPS that provides fast, time-definite delivery of packages worldwide.
  • C. PAL Express
    PAL Express is a Philippine low-cost regional airline brand operating domestic and select international flights on behalf of Philippine Airlines.
  • D. Channel Express
    Channel Express was a British airline that operated cargo and passenger services before rebranding and evolving into the low-cost carrier Jet2.com.
  • E. HK Express
    HK Express is a Hong Kong-based low-cost airline operating regional flights across Asia.
  • 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_69ab495d227c8190b26ae6548eeb1019 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd0dc7ed88190920afd4817c621c9 completed March 7, 2026, 7:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69aef0c0069c8190bfb9e71aea4774d3 completed March 9, 2026, 4:09 p.m.
Created at: March 6, 2026, 9:43 p.m.