Triple

T22196999
Position Surface form Disambiguated ID Type / Status
Subject Lou Duva E548574 entity
Predicate trained P3665 FINISHED
Object Michael Moorer 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: Michael Moorer | Statement: [Lou Duva, trained, Michael Moorer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Moorer
Context triple: [Lou Duva, trained, Michael Moorer]
  • A. Michael Moorer chosen
    Michael Moorer is an American former professional boxer and multiple-time world champion who notably lost the heavyweight title to an aging George Foreman in a famous 1994 upset.
  • B. Mark Moseley
    Mark Moseley is an American voice actor and impressionist known for frequently dubbing or soundalike performances for major film stars in animated features and other media.
  • C. Matthew Moore
    Matthew Moore is an American professional football quarterback known for his NFL career with teams such as the Carolina Panthers and Miami Dolphins.
  • D. Sean Moore
    Sean Moore is the drummer and a founding member of the Welsh alternative rock band Manic Street Preachers.
  • E. Sean Moore
    Sean Moore is a writer known for his work on the film "Tsunami."
  • 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_69e11e3ecc7c8190b5f94cd8f42e9d37 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f12ae7c72081909b7817d66391bef4 completed April 28, 2026, 9:47 p.m.
Created at: April 16, 2026, 8:35 p.m.