Triple
T15382522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donkey Kong Country |
E367837
|
entity |
| Predicate | animalBuddy |
P116764
|
FINISHED |
| Object |
Winky
Winky is a large green frog companion in the Donkey Kong Country series who helps players reach high places and defeat enemies with powerful jumps.
|
E1153837
|
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: Winky | Statement: [Donkey Kong Country, animalBuddy, Winky]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Winky Context triple: [Donkey Kong Country, animalBuddy, Winky]
-
A.
Winky
Winky is a house-elf from the Harry Potter series, known for her loyalty, tragic fall from grace, and eventual employment at Hogwarts.
-
B.
Mrs. Wix
Mrs. Wix is a morally rigid, impoverished governess who serves as a key guardian and moral counterpoint in Henry James’s novel "What Maisie Knew."
-
C.
Martha May Whovier
Martha May Whovier is a glamorous and kind-hearted resident of Whoville who serves as the Grinch’s love interest in the 2000 live-action adaptation of How the Grinch Stole Christmas.
-
D.
Mimmy
Mimmy is an alternative spelling of the name Mimi, often used as a given name or nickname.
-
E.
Mopsy
Mopsy is one of Peter Rabbit’s well-behaved sister rabbits in Beatrix Potter’s classic children’s stories.
- 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: Winky Triple: [Donkey Kong Country, animalBuddy, Winky]
Generated description
Winky is a large green frog companion in the Donkey Kong Country series who helps players reach high places and defeat enemies with powerful jumps.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Winky Target entity description: Winky is a large green frog companion in the Donkey Kong Country series who helps players reach high places and defeat enemies with powerful jumps.
-
A.
Winky
Winky is a house-elf from the Harry Potter series, known for her loyalty, tragic fall from grace, and eventual employment at Hogwarts.
-
B.
Mrs. Wix
Mrs. Wix is a morally rigid, impoverished governess who serves as a key guardian and moral counterpoint in Henry James’s novel "What Maisie Knew."
-
C.
Martha May Whovier
Martha May Whovier is a glamorous and kind-hearted resident of Whoville who serves as the Grinch’s love interest in the 2000 live-action adaptation of How the Grinch Stole Christmas.
-
D.
Mimmy
Mimmy is an alternative spelling of the name Mimi, often used as a given name or nickname.
-
E.
Mopsy
Mopsy is one of Peter Rabbit’s well-behaved sister rabbits in Beatrix Potter’s classic children’s stories.
- 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_69d85a1551a08190ba2caea7cd51c639 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e61928c81908852c355d537ed9c |
completed | April 16, 2026, 1:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff0b5bc43c81908ffdb7819e3660d9 |
completed | May 9, 2026, 10:24 a.m. |
| NEDg | Description generation | batch_69ff0c1171d4819099e0d0e1411059b2 |
completed | May 9, 2026, 10:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff10a360f8819098c8c9700b062478 |
completed | May 9, 2026, 10:46 a.m. |
Created at: April 10, 2026, 3:19 a.m.