Stanza
pytext
Stanza | pytext | |
---|---|---|
8 | - | |
7,337 | 6,354 | |
0.4% | - | |
9.7 | 7.8 | |
3 days ago | over 2 years ago | |
Python | Python | |
GNU General Public License v3.0 or later | BSD 3-clause "New" or "Revised" License |
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Stanza
- Down and Out in the Magic Kingdom
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Parts of speech tagged for German
I use Python's spacy library: https://spacy.io/models/de or stanza: https://stanfordnlp.github.io/stanza/ each with their respective language models.
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Off the shelf sentence parsers?
stanza has a constituency parser. There's a model compatible with the dev branch with an accuracy of 95.8 on PTB, using Roberta as a bottom layer, so it's pretty decent at this point. (The currently released model is not as accurate, but it's easy to get the better model to you.) There's also Tregex as a Java addon which can very easily search for a noun phrase highest up in the tree: NP !>> NP will search for a noun phrase which is not dominated by any higher up noun phrase.
- The Spacy NER model for Spanish is terrible
- Spacy vs NLTK for Spanish Language Statistical Tasks
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Stanza not tokenising sentences as expected
I am using Stanza to tokenise the sentences:
- Stanza β A Python NLP Package for Many Human Languages
pytext
We haven't tracked posts mentioning pytext yet.
Tracking mentions began in Dec 2020.
What are some alternatives?
spaCy - π« Industrial-strength Natural Language Processing (NLP) in Python
stanfordnlp - [Deprecated] This library has been renamed to "Stanza". Latest development at: https://github.com/stanfordnlp/stanza
NLTK - NLTK Source
PyTorch-NLP - Basic Utilities for PyTorch Natural Language Processing (NLP)
Jieba - η»ε·΄δΈζεθ―
BERT-NER - Pytorch-Named-Entity-Recognition-with-BERT
TextBlob - Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.
flair - A very simple framework for state-of-the-art Natural Language Processing (NLP)
polyglot - Multilingual text (NLP) processing toolkit
Pattern - Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.