Triple

T11040095
Position Surface form Disambiguated ID Type / Status
Subject Walter B. Pitkin Jr. E260989 entity
Predicate hasGivenName P17 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: [Walter B. Pitkin Jr., hasGivenName, Walter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Walter
Context triple: [Walter B. Pitkin Jr., hasGivenName, 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_69d6aa979bdc8190bf0e79104cc098c1 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d797ff519481909ebc2515b3d241de completed April 9, 2026, 12:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3a9d61b548190949f0dfbcb782064 completed April 18, 2026, 3:57 p.m.
Created at: April 8, 2026, 9:26 p.m.