Triple
T15666774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gladstone Gander |
E377206
|
entity |
| Predicate | relativeOf |
P367
|
FINISHED |
| Object | Gus Goose |
E1081248
|
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: Gus Goose | Statement: [Gladstone Gander, relativeOf, Gus Goose]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gus Goose Context triple: [Gladstone Gander, relativeOf, Gus Goose]
-
A.
Gus Goose
chosen
Gus Goose is a Disney cartoon character best known as Donald Duck’s lazy, gluttonous cousin who frequently appears in comedic stories set in Duckburg.
-
B.
Wawa Goose
Wawa Goose is a large roadside steel goose statue in Wawa, Ontario, serving as one of Canada's most famous highway landmarks.
-
C.
Gus-Gus
Gus-Gus is the lovable, chubby little mouse from Disney’s Cinderella known for his clumsiness, big heart, and comic relief.
-
D.
Gus
Gus is the given name of American filmmaker Gus Van Sant, known for directing independent and mainstream films such as "Good Will Hunting" and "Milk."
-
E.
Gus
Gus is a 1976 Disney sports comedy film about a football team that gains an unlikely advantage from a field-goal-kicking mule.
- 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_69d85cd2e28481909d4e975bee20872f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f1151548190a14607e762686cb1 |
completed | April 16, 2026, 2:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff6ed8d9188190a68035d2508b117d |
completed | May 9, 2026, 5:28 p.m. |
Created at: April 10, 2026, 4:16 a.m.