NLTK
Stanza
NLTK | Stanza | |
---|---|---|
68 | 8 | |
13,683 | 7,309 | |
0.9% | 0.4% | |
9.3 | 9.6 | |
about 1 month ago | 7 days ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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NLTK
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Create a Question/Answer Chatbot in Python
Using the NTLK Natural Language Toolkit
- NLTK version 3.8.2 is no longer available on PyPI
- Nltk version 3.8.2 is no longer available on PyPI
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350M Tokens Don't Lie: Love and Hate in Hacker News
Is this just using LLM to be cool? How does pure LLM with simple "In the scale between 0-10"" stack up against traditional, battle-tested sentiment analysis tools?
Gemini suggests NLTK and spaCy
https://www.nltk.org/
https://spacy.io/
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Building a local AI smart Home Assistant
alternatively, could we not simply split by common characters such as newlines and periods, to split it within sentences? it would be fragile with special handling required for numbers with decimal points and probably various other edge cases, though.
there are also Python libraries meant for natural language parsing[0] that could do that task for us. I even see examples on stack overflow[1] that simply split text into sentences.
[0]: https://www.nltk.org/
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Sorry if this is a dumb question but is the main idea behind LLMs to output text based on user input?
Check out https://www.nltk.org/ and work through it, it'll give you a foundational understanding of how all this works, but very basically it's just a fancy auto-complete.
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Best Portfolio Projects for Data Science
NLTK Documentation
- Where to start learning NLP ?
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Is there a programmatic way to check if two strings are paraphrased?
If this is True, then you need also Natural Language Toolkit to process the words.
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[CROSS-POST] What programming language should I learn for corpus linguistics?
In that case, you should definitely have a look at Python's nltk library which stands for Natural Language Toolkit. They have a rich corpus collection for all kinds of specialized things like grammars, taggers, chunkers, etc.
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
What are some alternatives?
spaCy - π« Industrial-strength Natural Language Processing (NLP) in Python
TextBlob - Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.
Jieba - η»ε·΄δΈζεθ―
bert - TensorFlow code and pre-trained models for BERT
BERT-NER - Pytorch-Named-Entity-Recognition-with-BERT
polyglot - Multilingual text (NLP) processing toolkit
pytext - A natural language modeling framework based on PyTorch
PyTorch-NLP - Basic Utilities for PyTorch Natural Language Processing (NLP)
flair - A very simple framework for state-of-the-art Natural Language Processing (NLP)