Triple
T1518534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mickey Mouse franchise |
E32173
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object |
Goofy
Goofy is a tall, anthropomorphic dog and classic Disney cartoon character known for his clumsiness, distinctive laugh, and good-natured personality.
|
E173090
|
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: Goofy | Statement: [Mickey Mouse franchise, hasCharacter, Goofy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Goofy Context triple: [Mickey Mouse franchise, hasCharacter, Goofy]
-
A.
Mickey
Mickey is a character from the virtual reality co-op shooter game "After the Fall," set in a post-apocalyptic, frozen Los Angeles overrun by monstrous creatures.
-
B.
Daffy
Daffy is the colloquial nickname given to the British World War II Boulton Paul Defiant turret fighter aircraft.
-
C.
Mr. Magoo
Mr. Magoo is a near-sighted, bumbling cartoon character known for getting into comical misadventures due to his poor vision.
-
D.
Pepé Le Pew
Pepé Le Pew is a romantic, overly confident skunk from the Looney Tunes cartoons, best known for his comedic, French-accented pursuit of love.
-
E.
Daffy Duck
Daffy Duck is a classic Looney Tunes cartoon character known for his zany, self-centered antics and comedic rivalry with characters like Bugs Bunny.
- 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: Goofy Triple: [Mickey Mouse franchise, hasCharacter, Goofy]
Generated description
Goofy is a tall, anthropomorphic dog and classic Disney cartoon character known for his clumsiness, distinctive laugh, and good-natured personality.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Goofy Target entity description: Goofy is a tall, anthropomorphic dog and classic Disney cartoon character known for his clumsiness, distinctive laugh, and good-natured personality.
-
A.
Mickey
Mickey is a character from the virtual reality co-op shooter game "After the Fall," set in a post-apocalyptic, frozen Los Angeles overrun by monstrous creatures.
-
B.
Daffy
Daffy is the colloquial nickname given to the British World War II Boulton Paul Defiant turret fighter aircraft.
-
C.
Mr. Magoo
Mr. Magoo is a near-sighted, bumbling cartoon character known for getting into comical misadventures due to his poor vision.
-
D.
Pepé Le Pew
Pepé Le Pew is a romantic, overly confident skunk from the Looney Tunes cartoons, best known for his comedic, French-accented pursuit of love.
-
E.
Daffy Duck
Daffy Duck is a classic Looney Tunes cartoon character known for his zany, self-centered antics and comedic rivalry with characters like Bugs Bunny.
- 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_69a885e8caf88190a5fbb6159ce87786 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a907ed44ac8190953e428c831e24df |
completed | March 5, 2026, 4:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad2346e7b481909c105a969724591d |
completed | March 8, 2026, 7:20 a.m. |
| NEDg | Description generation | batch_69ad23d86d088190bbea03d5d49bc009 |
completed | March 8, 2026, 7:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad2459c38c8190a8c166c2743a8936 |
completed | March 8, 2026, 7:25 a.m. |
Created at: March 4, 2026, 7:26 p.m.