French Adjectives Transformation #249
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The pytest succeed when I try to run it locally, it shouldn't fail in the build : |
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Hi @Louanes1, I'm one of the assigned reviewers for your transformation. Below is my general review, see comments for more specific feedback.
Correctness: Failed the build with an AssertionError. I saw the comment regarding passing the unit test locally. Maybe see if your local version is up-to-date? Otherwise, I'm also unsure why it failed.
Interface: Looks good.
Applicable Tasks & Keywords: Task types have been added, missing keywords.
Specificity: The task is specific to text classification, generation, and tagging.
Novelty: This transformation is not implemented in NL-Augmenter already.
Adding New Libraries: All added to requirements, only nltk's version has not been specified.
Description: Readme looks good.
Data and code source: None. Should add a sentence stating it was fully created by author (or cite relevant sources).
Paraphrasers and Data Augmenters: N/A
Test Cases: 3 examples added, 5 recommended.
Evaluating Robustness: Evaluation has not been provided.
Languages other than English: French.
Decent Programming Practise: No docstrings, consider adding some.
If anything needs clarification, please let me know. Otherwise, thanks for the contribution!
| This perturbation would benefit all tasks which have a sentence/paragraph/document as input like text classification, text generation, etc. that requires synthetic data augmentation / diversification. | ||
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| ## What are the limitation of this transformation ? | ||
| This tool does not take the general context into account, sometimes, the ouput will not match the general sense of te sentence. |
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misspelling: *the
If possible, the results of the evaluate.py test should be added to the Readme as well.
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| This transformation change some words with synonyms according to if their POS tag is a ADJ for simple french sentences. It requires Spacy_lefff (an extention of spacy for french POS and lemmatizing) and nltk package with the open multilingual wordnet dictionary. | ||
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| Authors : Lisa Barthe and Louanes Hamla from Fablab by Inetum in Paris |
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Emails should be added to the authors, please.
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It is recommended to include at least 5 examples here.
| from spacy_lefff import LefffLemmatizer, POSTagger | ||
| from spacy.language import Language | ||
| from nltk.corpus import wordnet | ||
| import nltk |
| TaskType.TEXT_TAGGING, | ||
| ] | ||
| languages = ["fr"] | ||
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Relavent keywords should also be added.
| fr-core-news-md @ https://github.com/explosion/spacy-models/releases/download/fr_core_news_md-3.0.0/fr_core_news_md-3.0.0-py3-none-any.whl | ||
| spacy-lefff==0.4.0 | ||
| textblob_fr==0.2.0 | ||
| nltk |
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Should nltk's version be specified as well?
| perturbed_texts = synonym_transformation( | ||
| sentence | ||
| ) | ||
| print("perturbed text inside of class",perturbed_texts) |
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May want to delete this print line.
No description provided.