Triple

T13786611
Position Surface form Disambiguated ID Type / Status
Subject John Walter I E331273 entity
Predicate familyName P18 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: [John Walter I, familyName, Walter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Walter
Context triple: [John Walter I, familyName, Walter]
  • A. Walter chosen
    Walter is a masculine given name of Germanic origin that has been widely used in English-speaking countries.
  • B. Walter
    Walter is a grumpy, sharp-tongued old-man puppet character featured in Jeff Dunham’s stand-up comedy acts.
  • C. Walter Haut
    Walter Haut was a former U.S. Army Air Force public information officer best known for issuing the 1947 Roswell UFO press release and later co-founding the International UFO Museum and Research Center.
  • D. Wilbert
    Wilbert is the given first name of American character actor Bill Cobbs, known for his numerous supporting roles in film and television.
  • E. 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.
  • 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_69d81c58feb08190a77bca8bf7d6d20f completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de0249e4f88190a80316394940627d completed April 14, 2026, 9 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b07d872c81908f912263d8f7c80d completed May 3, 2026, 8:30 p.m.
Created at: April 9, 2026, 10:11 p.m.