Triple
T22419738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wally Buono |
E554213
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Wally |
—
|
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: Wally | Statement: [Wally Buono, givenName, Wally]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wally Context triple: [Wally Buono, givenName, Wally]
-
A.
Wally
Wally is a character featured in the educational children's series "Alphabetical Order," likely serving as a playful figure to help teach letters and literacy concepts.
-
B.
Wally
chosen
Wally is a common English diminutive given name, typically derived from names like Walter or Waldemar.
-
C.
Wally
Wally is a character from the comedy film "The Great Outdoors," known for his role in the movie’s humorous family vacation mishaps.
-
D.
Wally
Wally, better known as Numbuh 4, is a hot-headed, tough but loyal member of the Kids Next Door from the animated series "Codename: Kids Next Door."
-
E.
Wally
Wally is a perpetually lazy, coffee-loving office worker from the "Dilbert" comic strip, known for his extreme apathy and talent for avoiding work.
- 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_69e11e4e6ce8819085a1e06d886bf21c |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1594a58508190b41fd16c8de5f8b4 |
completed | April 29, 2026, 1:05 a.m. |
Created at: April 16, 2026, 8:46 p.m.