Triple

T1345181
Position Surface form Disambiguated ID Type / Status
Subject Montreal Impact E28553 entity
Predicate chairman P377 FINISHED
Object Joey Saputo E153460 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: Joey Saputo | Statement: [Montreal Impact, chairman, Joey Saputo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joey Saputo
Context triple: [Montreal Impact, chairman, Joey Saputo]
  • A. Joey Saputo chosen
    Joey Saputo is a Canadian businessman and sports executive best known as the founding president and long-time owner of Montreal’s professional soccer club.
  • B. Joey Newman
    Joey Newman is an American composer and conductor known for his work on television scores and themes, including contributions to major sports broadcasts.
  • C. Joey Luft
    Joey Luft is an American television producer and occasional actor best known as the son of legendary entertainer Judy Garland and producer Sidney Luft.
  • D. Nathan Phillips
    Nathan Phillips was a prominent Canadian politician who served as the reform-minded mayor of Toronto in the 1950s and early 1960s.
  • E. TJ Holowaychuk
    TJ Holowaychuk is a prolific open-source software engineer best known for creating the popular Node.js web framework Express.js and numerous other developer tools and libraries.
  • 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_69a49854eb3481908c7d56b2e449a290 completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c23d696c8190bb688274280cb680 completed March 1, 2026, 10:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69acce68225081909d995cd7ae5f2224 completed March 8, 2026, 1:18 a.m.
Created at: March 1, 2026, 7:56 p.m.