37K multi-turn conversations dataset
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-10.)
37K multi-turn conversations dataset has 12 facts recorded in Dontopedia across 2 references, with 1 live disagreement.
Mostly:sourced from(2), conversation count(1), dataset size(1)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (1)
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.
discussesDiscusses(1)
- Message 5
ex:message-5
Other facts (11)
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.
| Predicate | Value | Ref |
|---|---|---|
| Sourced From | Dailydialog | [1] |
| Sourced From | Soda | [1] |
| Conversation Count | 37000 | [1] |
| Dataset Size | 24MB | [1] |
| Format Description | one conversation per line with / turn markers | [1] |
| Rdf:type | Dataset Specification | [2] |
| Sample Count | 10000 | [2] |
| Feature Count | 10 | [2] |
| Target Distribution | binary | [2] |
| Has Feature Dimensionality | 10 | [2] |
| Has Sample Size | 10000 | [2] |
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.
References (2)
ctx:discord/blah/vidya/7- full textvidya-7text/plain3 KB
doc:agent/vidya-7/06ef0b6b-8c5c-46b4-a7b7-96e33a18cb2dShow excerpt
[2026-02-22 22:34] ajaxdavis: hell yeah! [2026-02-22 22:35] ajaxdavis: so you had to train base model and then do RL with chat messages training set after for the chatty behavior? [2026-02-22 22:36] rolandnsharp7643: nah, there is no RL at …
ctx:claims/beam/015c5023-ca31-419e-93cf-0713ac674694- full textbeam-chunktext/plain1 KB
doc:beam/015c5023-ca31-419e-93cf-0713ac674694Show excerpt
- **Early Stopping**: Implement early stopping to halt training if the validation loss does not improve over a certain number of epochs. ### 9. **Model Complexity** - **Simplify the Model**: If the model is too complex, it might over…
See also
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