Triple
T20610803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DMP PICA200 |
E506440
|
entity |
| Predicate | roleInNintendo3DS |
P140755
|
FINISHED |
| Object | main 3D graphics accelerator |
—
|
LITERAL 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: main 3D graphics accelerator | Statement: [DMP PICA200, roleInNintendo3DS, main 3D graphics accelerator]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInNintendo3DS Context triple: [DMP PICA200, roleInNintendo3DS, main 3D graphics accelerator]
-
A.
roleInDonkeyKongCountry3
Indicates the specific role or function an entity has within the game Donkey Kong Country 3.
-
B.
roleInSuperMarioLand
Indicates the specific function or part an entity plays within the context of the game Super Mario Land.
-
C.
roleInDonkeyKongCountry
Indicates the specific role or function an entity has within the context of Donkey Kong Country.
-
D.
roleInDonkeyKong64
Indicates the role or function an entity has within the context of the game Donkey Kong 64.
-
E.
roleInPikmin3
Indicates the specific function, part, or involvement an entity has within the context of the game Pikmin 3.
- F. None of above. chosen
Provenance (4 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_69e0b4bb2b4081908fa4a72444120f35 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6aad6f53481908fb242947dda7028 |
completed | April 20, 2026, 10:38 p.m. |
| PD | Predicate disambiguation | batch_69e5a00c43308190b7ea58d559257e07 |
completed | April 20, 2026, 3:39 a.m. |
| PDg | Predicate description generation | batch_69e5a6a9f3f88190b961db9aca36f7da |
completed | April 20, 2026, 4:08 a.m. |
Created at: April 16, 2026, 11:41 a.m.