Dontopedia

COCO

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-16.)

COCO has 10 facts recorded in Dontopedia across 4 references, with 1 live disagreement.

10 facts·7 predicates·4 sources·1 in dispute

Mostly:task(3), standard computer vision benchmark(1), provides mean field(1)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (6)

Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.

trainedWithDataTrained With Data(2)

containsDatasetContains Dataset(1)

embodiesImagePriorEmbodies Image Prior(1)

referencesDatasetReferences Dataset(1)

representsDatasetMeanRepresents Dataset Mean(1)

Other facts (9)

The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.

9 facts
PredicateValueRef
Taskobject detection[4]
Tasksegmentation[4]
Taskcaptioning[4]
Standard Computer Vision Benchmarknull[1]
Provides Mean Fieldtrue[2]
Has Quantity566000[3]
Rdf:typeDataset[4]
Full TitleCommon Objects in Context[4]
Num Classes80[4]

Timeline

Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.

standardComputerVisionBenchmarkblah/watt-activation/part-244
null
providesMeanFieldblah/watt-activation/part-253
true
labelblah/watt-activation/250
COCO
hasQuantityblah/watt-activation/250
566000
typelme/3665dde5-ce93-4293-bb71-6b4ca696ba94
ex:Dataset
fullTitlelme/3665dde5-ce93-4293-bb71-6b4ca696ba94
Common Objects in Context
tasklme/3665dde5-ce93-4293-bb71-6b4ca696ba94
object detection
tasklme/3665dde5-ce93-4293-bb71-6b4ca696ba94
segmentation
tasklme/3665dde5-ce93-4293-bb71-6b4ca696ba94
captioning
numClasseslme/3665dde5-ce93-4293-bb71-6b4ca696ba94
80

References (4)

4 references
  1. [1]Part 2441 fact
    ctx:discord/blah/watt-activation/part-244
  2. [2]Part 2531 fact
    ctx:discord/blah/watt-activation/part-253
  3. [3]2502 facts
    ctx:discord/blah/watt-activation/250
    • full textwatt-activation-250
      text/plain3 KBdoc:agent/watt-activation-250/2966119d-31a8-473f-864c-78e91ddcd89d
      Show excerpt
      [2026-03-12 12:56] xenonfun: ⏺ All done. Here's the summary: Inference Results (multimodal_v3_e2_packed/best, 21.1M params) ``` Text generation — 363 tok/s, phase metrics: blk r K beta 0 0.5159 0.1605
  4. ctx:claims/lme/3665dde5-ce93-4293-bb71-6b4ca696ba94
    • full textbeam-chunk
      text/plain19 KBdoc:beam/3665dde5-ce93-4293-bb71-6b4ca696ba94
      Show excerpt
      [Session date: 2023/08/20 (Sun) 06:56] User: I'm looking to improve my skills in machine learning and artificial intelligence. Can you recommend some online courses or resources that can help me with that? By the way, I've already taken som

See also

Keep researching

Missing something or suspicious of what's here? Kick off a research session — a Claude agent will investigate, cite its sources, and file new facts into a dedicated context you can review before accepting into the shared view.