Triple

T9238031
Position Surface form Disambiguated ID Type / Status
Subject Office Christmas Party E221984 entity
Predicate mainCharacter P1183 FINISHED
Object Josh Parker E314077 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: Josh Parker | Statement: [Office Christmas Party, mainCharacter, Josh Parker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Josh Parker
Context triple: [Office Christmas Party, mainCharacter, Josh Parker]
  • A. Scott Oake
    Scott Oake is a Canadian sportscaster best known for his long-running work as a rinkside reporter and host on national hockey broadcasts.
  • B. Jonathan Tucker
    Jonathan Tucker is an American actor known for his intense, character-driven roles in film and television, including prominent performances in series like "Kingdom," "Westworld," and "City on a Hill."
  • C. Leo Parker
    Leo Parker was an American baritone saxophonist known for his work in the bebop and hard bop jazz scenes of the 1940s and 1950s.
  • D. Nicholas Woodeson
    Nicholas Woodeson is a British character actor known for his work in film, television, and theatre, including roles in productions such as "Skyfall," "Rome," and "The Death of Stalin."
  • E. Ethan Embry chosen
    Ethan Embry is an American actor known for his roles in 1990s films such as "Empire Records," "Can't Hardly Wait," and various television series.
  • 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_69ca83ee26cc81909ac624e190597d6d completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccf09f9e908190801fe114c5e63984 completed April 1, 2026, 10:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1bca05c608190935af17d94c567d6 completed April 5, 2026, 1:36 a.m.
Created at: March 30, 2026, 7:30 p.m.