chore: import upstream snapshot with attribution

2026-07-13 12:37:51 +08:00
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+## Examples of textcat training data
+
+spacy JSON training files were generated from JSONL with:
+
+```
+python textcatjsonl_to_trainjson.py -m en file.jsonl .
+```
+
+`cooking.json` is an example with mutually-exclusive classes with two labels:
+
+* `baking`
+* `not_baking`
+
+`jigsaw-toxic-comment.json` is an example with multiple labels per instance:
+
+* `insult`
+* `obscene`
+* `severe_toxic`
+* `toxic`
+
+### Data Sources
+
+* `cooking.jsonl`: https://cooking.stackexchange.com. The meta IDs link to the
+  original question as `https://cooking.stackexchange.com/questions/ID`, e.g.,
+  `https://cooking.stackexchange.com/questions/2` for the first instance.
+* `jigsaw-toxic-comment.jsonl`: [Jigsaw Toxic Comments Classification
+  Challenge](https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge)
+
+### Data Licenses
+
+* `cooking.jsonl`: CC BY-SA 4.0 ([`CC_BY-SA-4.0.txt`](CC_BY-SA-4.0.txt))
+* `jigsaw-toxic-comment.jsonl`:
+    * text: CC BY-SA 3.0 ([`CC_BY-SA-3.0.txt`](CC_BY-SA-3.0.txt))
+    * annotation: CC0 ([`CC0.txt`](CC0.txt))