Datasets:
Add texts/texts_fixed.csv: corrected Polish and English beside the originals
Browse files- texts/README.md +35 -0
- texts/texts_fixed.csv +0 -0
texts/README.md
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# Corrected texts
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`texts_fixed.csv` holds the Polish and English text of the 29,928 dataset pairs (the keys in
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`splits/split_*_ms.csv` and `splits/split_*_filtered.csv`), each in two versions:
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- `pl`, `en`: the texts as first published. All results in the CrocoSign paper use `en` as the reference.
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- `pl_fixed`, `en_fixed`: corrected versions. `fixed` is 1 when either text differs from the original.
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The original files in `translations/` and `splits/` are unchanged.
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What was corrected (2026-10-31):
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- Polish, 211 pairs: typos and missing diacritics (`ze` for `że`, `Pam` for `Pan`), and cut-off word
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fragments, removed while keeping the signer's self-correction (`słoik z kot... żabą` becomes `słoik z żabą`).
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- English, 1,440 pairs (4.8%): meaning errors of the machine translation. Most are systematic: `migać`
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rendered as "blink" or "flash" instead of "sign", `wskazówka` (clock hand) as "pointer" or "clue",
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`kosz` (basket) as "garbage can", `kula` (ball) as "bullet", `smarkacz` (brat) as "snot" or "greaser", `Pan` as
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"The Lord", `drezyna` (draisine) as "dreidel", and `akurat` left untranslated. Others follow from a
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Polish typo, such as "the stove" for `Piec`, a typo of `Pies` (dog).
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In all, 1,547 pairs have `fixed` = 1 (211 with a Polish change, 1,440 with an English change; some have
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both). The English corrections were made against `pl_fixed`.
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How we found them: a dictionary scan (hunspell, Morfeusz 2) and a language model that read every Polish
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sentence and then every Polish-English pair and proposed corrections. We approved the Polish list and
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spot-checked the English one (25 random flags, all real errors), and checked recall on the systematic terms
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above; the cases the model missed there (40, mostly `migać`) and 5 clock times were corrected by hand.
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Other errors that the model did not flag remain. The Polish keeps the signers' colloquial
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wording, and forms such as `na dworzu` are left as they are.
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```python
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import pandas as pd
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texts = pd.read_csv("texts/texts_fixed.csv").set_index("key")
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target = texts["en_fixed"] # or texts["en"] to reproduce the paper
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```
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texts/texts_fixed.csv
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