Triple
T3558449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mario Kart: Double Dash!! |
E75275
|
entity |
| Predicate | includesTrack |
P3284
|
FINISHED |
| Object |
Sherbet Land
Sherbet Land is an icy, penguin-filled racetrack set in a snowy wonderland in the Mario Kart series.
|
E370323
|
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: Sherbet Land | Statement: [Mario Kart: Double Dash!!, includesTrack, Sherbet Land]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sherbet Land Context triple: [Mario Kart: Double Dash!!, includesTrack, Sherbet Land]
-
A.
Kiddyland
Kiddyland is a children’s amusement area within Playland Park featuring kid-friendly rides and attractions.
-
B.
Sky Land
Sky Land is a high-altitude, cloud-filled world in Super Mario Bros. 3 known for its vertical level design and airborne challenges.
-
C.
Toyland
Toyland is the colorful, whimsical fantasy world that serves as the primary setting for Enid Blyton’s Noddy stories, inhabited by living toys and playful characters.
-
D.
Sleepy Bay
Sleepy Bay is a small, scenic coastal inlet in Tasmania known for its rugged granite shoreline, clear waters, and picturesque views within Freycinet National Park.
-
E.
Candy Shop
"Candy Shop" is a 2005 hip hop single by 50 Cent featuring Olivia, produced by Scott Storch, known for its seductive lyrics and catchy, club-oriented beat.
- 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: Sherbet Land Triple: [Mario Kart: Double Dash!!, includesTrack, Sherbet Land]
Generated description
Sherbet Land is an icy, penguin-filled racetrack set in a snowy wonderland in the Mario Kart series.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sherbet Land Target entity description: Sherbet Land is an icy, penguin-filled racetrack set in a snowy wonderland in the Mario Kart series.
-
A.
Kiddyland
Kiddyland is a children’s amusement area within Playland Park featuring kid-friendly rides and attractions.
-
B.
Sky Land
Sky Land is a high-altitude, cloud-filled world in Super Mario Bros. 3 known for its vertical level design and airborne challenges.
-
C.
Toyland
Toyland is the colorful, whimsical fantasy world that serves as the primary setting for Enid Blyton’s Noddy stories, inhabited by living toys and playful characters.
-
D.
Sleepy Bay
Sleepy Bay is a small, scenic coastal inlet in Tasmania known for its rugged granite shoreline, clear waters, and picturesque views within Freycinet National Park.
-
E.
Candy Shop
"Candy Shop" is a 2005 hip hop single by 50 Cent featuring Olivia, produced by Scott Storch, known for its seductive lyrics and catchy, club-oriented beat.
- 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_69ad85d45090819086f34fb85d850a1e |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc0881d50819092332491b9527c9d |
completed | March 8, 2026, 6:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b3bb9983f48190bda2749d93c74a8d |
completed | March 13, 2026, 7:24 a.m. |
| NEDg | Description generation | batch_69b3bcae84a48190b085f253773cd14f |
completed | March 13, 2026, 7:28 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b3f90df47c81908855021f68ca7ec8 |
completed | March 13, 2026, 11:46 a.m. |
Created at: March 8, 2026, 3:20 p.m.