Triple

T7780204
Position Surface form Disambiguated ID Type / Status
Subject Gauthier E221494 entity
Predicate hasCognate P2525 FINISHED
Object Walter E32053 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: Walter | Statement: [Gauthier, hasCognate, Walter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Walter
Context triple: [Gauthier, hasCognate, Walter]
  • A. Walter chosen
    Walter is a masculine given name of Germanic origin that has been widely used in English-speaking countries.
  • B. Wilbert
    Wilbert is the given first name of American character actor Bill Cobbs, known for his numerous supporting roles in film and television.
  • C. Wally Fay
    Wally Fay is a supporting character in the 1945 film noir "Mildred Pierce," known as a somewhat sleazy businessman entangled in the story’s web of betrayal and murder.
  • D. Walter Nelson
    Walter Nelson was an attorney who served on the defense team in the landmark Ossian Sweet murder trial, which challenged racial injustice in 1920s Detroit.
  • E. Basil Wolverton
    Basil Wolverton was an American cartoonist and comic book artist renowned for his grotesque, highly detailed, and surreal illustration style, particularly in humor and science fiction comics.
  • 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_69ca83ebbef881909ac47f789145fef7 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69caa4d6cf9881909f5220437db13cc7 completed March 30, 2026, 4:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69cb137f224881908731d47547584a8e completed March 31, 2026, 12:21 a.m.
Created at: March 30, 2026, 4:20 p.m.