Triple

T2705782
Position Surface form Disambiguated ID Type / Status
Subject Lou Marsh Trophy E59337 entity
Predicate namedForEmployer P22544 FINISHED
Object Toronto Star E59399 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: Toronto Star | Statement: [Lou Marsh Trophy, namedForEmployer, Toronto Star]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toronto Star
Context triple: [Lou Marsh Trophy, namedForEmployer, Toronto Star]
  • A. Toronto Star chosen
    The Toronto Star is a major Canadian daily newspaper based in Toronto, known for its large circulation and progressive, investigative journalism.
  • B. Rogers Media
    Rogers Media is a major Canadian media and communications company that owns and operates television and radio stations, sports media assets, and digital platforms.
  • C. The Canadian Press
    The Canadian Press is a national news agency in Canada that supplies news content to media outlets across the country.
  • D. Chicago Tribune
    The Chicago Tribune is a major American daily newspaper based in Chicago, known for its influential coverage of national and local news since the 19th century.
  • E. National Post
    The National Post is a Canadian English-language daily newspaper known for its national coverage and generally conservative editorial stance.
  • 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_69ab4ac66bc88190b9e4afa5fc843f72 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abda559a908190ad5d92c11a398a03 completed March 7, 2026, 7:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69afb683092c8190859e92acadfb820c completed March 10, 2026, 6:13 a.m.
Created at: March 6, 2026, 9:55 p.m.