Triple
T3249053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fun and Fancy Free |
E68132
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Donald Duck |
E77751
|
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: Donald Duck | Statement: [Fun and Fancy Free, featuresCharacter, Donald Duck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Donald Duck Context triple: [Fun and Fancy Free, featuresCharacter, Donald Duck]
-
A.
Donald Duck
chosen
Donald Duck is a classic Disney cartoon character, known for his sailor outfit, short temper, and distinctive semi-intelligible voice.
-
B.
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.
-
C.
Daisy Duck
Daisy Duck is a classic Disney cartoon character, typically portrayed as Donald Duck’s sophisticated, strong-willed girlfriend and a close friend of Minnie Mouse.
-
D.
Mickey Mouse
Mickey Mouse is an iconic cartoon character created by Walt Disney, widely recognized as the cheerful mascot of The Walt Disney Company and a symbol of global popular culture.
-
E.
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.
- 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_69ad858e4c708190aa31d486cfee8a6a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaf3fc3c8819080ac95974581ca0e |
completed | March 8, 2026, 5:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2e82f91788190a9b14613eab7a439 |
completed | March 12, 2026, 4:22 p.m. |
Created at: March 8, 2026, 3:09 p.m.