Triple

T22225404
Position Surface form Disambiguated ID Type / Status
Subject The Treaty E549324 entity
Predicate hasCastMember P2308 FINISHED
Object Tom Jordan 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: Tom Jordan | Statement: [The Treaty, hasCastMember, Tom Jordan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tom Jordan
Context triple: [The Treaty, hasCastMember, Tom Jordan]
  • A. Tom Jordan chosen
    Tom Jordan is the central protagonist of the 1962 political thriller film "Guns of Darkness," around whom the story’s tense escape and survival plot revolves.
  • B. Bob Jordan
    Bob Jordan is an American business executive best known as the Chief Executive Officer of Southwest Airlines.
  • C. Mike Winters
    Mike Winters is a former Major League Baseball umpire who worked in the National League and MLB for several decades, including numerous postseason and All-Star Game assignments.
  • D. Jack Jordan
    Jack Jordan is a fictional character in DC Comics, best known as the father of Green Lantern Hal Jordan and a test pilot whose death profoundly shapes his son's heroic path.
  • E. Jack Deerson
    Jack Deerson is a cinematographer best known for his work on the 1971 road movie "Two-Lane Blacktop."
  • 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_69e11e403d6481909a94d0aaf157f6ef completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f12b93e2208190aee70ffd82962ea0 completed April 28, 2026, 9:50 p.m.
Created at: April 16, 2026, 8:37 p.m.