Triple
T14122472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oswald the Lucky Rabbit |
E339937
|
entity |
| Predicate | hasRelative |
P367
|
FINISHED |
| Object |
Gus Goose
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.
|
E1081248
|
NE FINISHED |
How this triple was built (4 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: [Oswald the Lucky Rabbit, hasRelative, Gus Goose]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gus Goose Context triple: [Oswald the Lucky Rabbit, hasRelative, Gus Goose]
-
A.
Wawa Goose
Wawa Goose is a large roadside steel goose statue in Wawa, Ontario, serving as one of Canada's most famous highway landmarks.
-
B.
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."
-
C.
Gus
Gus is a 1976 Disney sports comedy film about a football team that gains an unlikely advantage from a field-goal-kicking mule.
-
D.
Gus
Gus is a character from T. S. Eliot's "Old Possum's Book of Practical Cats," depicted as an elderly, once-famous theater cat reflecting nostalgically on his past glory.
-
E.
Gus
Gus is the affectionate nickname of Burton "Gus" Guster, the loyal and often cautious best friend and business partner in the TV series "Psych."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Gus Goose Triple: [Oswald the Lucky Rabbit, hasRelative, Gus Goose]
Generated description
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.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gus Goose Target entity description: 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.
-
A.
Wawa Goose
Wawa Goose is a large roadside steel goose statue in Wawa, Ontario, serving as one of Canada's most famous highway landmarks.
-
B.
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."
-
C.
Gus
Gus is a character in the 1951 American drama film "Journey into Light," which follows a troubled minister seeking redemption in Los Angeles.
-
D.
Gus
Gus is the affectionate nickname of Burton "Gus" Guster, the loyal and often cautious best friend and business partner in the TV series "Psych."
-
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. chosen
Provenance (5 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_69d81c6a95b481909e39111e0c1f31ee |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de6095548881908a9e66adccca92d2 |
completed | April 14, 2026, 3:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdf07feb48190b7519204b4f789b4 |
completed | May 7, 2026, 6:50 p.m. |
| NEDg | Description generation | batch_69fce0f2dcc48190952ea89af5c809d7 |
completed | May 7, 2026, 6:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fce1792ae48190a9379abff92f0f9e |
completed | May 7, 2026, 7:01 p.m. |
Created at: April 9, 2026, 10:22 p.m.