Triple

T20618872
Position Surface form Disambiguated ID Type / Status
Subject Sweet Country E506644 entity
Predicate starring P1507 FINISHED
Object Matt Day NE NERFINISHED

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: Matt Day | Statement: [Sweet Country, starring, Matt Day]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matt Day
Context triple: [Sweet Country, starring, Matt Day]
  • A. Matt Day chosen
    Matt Day is an Australian actor known for his work in film and television, including prominent roles in both drama and comedy.
  • B. Joe Daley
    Joe Daley is a former Canadian professional ice hockey goaltender best known for starring with the Winnipeg Jets in the World Hockey Association during the 1970s.
  • C. Ryan Dusick
    Ryan Dusick is an American musician best known as the original drummer and a founding member of the pop rock band Maroon 5.
  • D. Matt Harpring
    Matt Harpring is a former American professional basketball player and standout small forward best known for his collegiate career at Georgia Tech and his NBA tenure with teams including the Utah Jazz.
  • E. Austin Kellogg
    Austin Kellogg is a person notable enough to be recognized as a bearer of the Kellogg surname, though specific widely known achievements or roles are not clearly documented.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4bc90988190ac360aaf645efc1d completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6abdf9d7c8190969247a4ae55b781 completed April 20, 2026, 10:42 p.m.
Created at: April 16, 2026, 11:41 a.m.