janome
skweak
janome | skweak | |
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2 | 8 | |
828 | 911 | |
- | 0.3% | |
5.2 | 6.2 | |
11 months ago | 7 months ago | |
Python | Python | |
Apache License 2.0 | MIT License |
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janome
- [discussion] Open AI api translations
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[Computer Stuff] What's the best way to split a Japanese sentence into "words"?
I did program stuff like that a bit in Korean and Japanese. So, in short, these tools/libraries are called 'Tokenizers'. I.e. search for "Japanese tokenizer", it will also tell you that MeCab is one of them. There is no good/easy way to split words in Japanese with simple algorithms, so these libraries, that are based on statistics or AI, will be your only choice. There is a good example sentence that shows how futile this would be without those libraries: "すもももももももものうち". From here.
skweak
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Entity Extraction with Predefined List
Thanks for pointing me in the right direction. Seems like there’s a few other approaches with weak supervision: https://github.com/NorskRegnesentral/skweak
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[P] Programmatic: Powerful Weak Labeling
Code for https://arxiv.org/abs/2104.09683 found: https://github.com/NorskRegnesentral/skweak
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Show HN: Programmatic – a REPL for creating labeled data
Hi Raza here, one of the other co-founders.
I know that HN likes to nerd out over technical details so thought I’d share a bit more on how we aggregate the noisy labels to clean them up.
At the moment we use the great Skweak [1] open source library to do this. Skweak uses an HMM to infer the most likely unobserved label given the evidence of the votes from each of the labelling functions.
This whole strategy of first training a label model and then training a neural net was pioneered by Snorkel. We’ve used this approach for now but we actually think there are big opportunities for improvement.
We’re working on an end-to-end approach that de-noises the labelling function and trains the model at the same time. So far we’ve seen improvements on the standard benchmarks [2] and are planning to submit to Neurips.
R
[1]: Skweak package: https://github.com/NorskRegnesentral/skweak
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The hand-picked selection of the best Python libraries released in 2021
skweak.
- Skweak: Weak Supervision for NLP
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Inevitable Manual Work involved in NLP
For more advanced unsupervised labeling, you should check skweak
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How to get Training data for NER?
I'm the main developer behind skweak by the way, happy to hear you're interested in our toolkit :-) We do already have a small list of products (see https://github.com/NorskRegnesentral/skweak/blob/main/data/products.json) extracted from DBPedia and Wikidata, but it may not be exactly the type of products you're looking for.
What are some alternatives?
kanji-data - A JSON kanji dataset with updated JLPT levels and WaniKani information
snorkel - A system for quickly generating training data with weak supervision
tika-python - Tika-Python is a Python binding to the Apache Tika™ REST services allowing Tika to be called natively in the Python community.
argilla - Argilla is a collaboration platform for AI engineers and domain experts that require high-quality outputs, full data ownership, and overall efficiency.
asian-comprehension-worksheet-generator - Create worksheet to learn Asian language (eg. Chinese) and practice reading and writing in grid format. Perfect tool for kid and beginner.
DearPy3D - Dear PyGui 3D Engine (prototyping)
wakaranai - An educational tool for learning hiragana and katakana
snorkel - A system for quickly generating training data with weak supervision [Moved to: https://github.com/snorkel-team/snorkel]
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
AugLy - A data augmentations library for audio, image, text, and video.
languagepod101-scraper - Python scraper for Language Pods such as Japanesepod101.com :japanese_ogre: :japan: :sushi: Compatible with Japanese, Chinese, French, German, Italian, Korean, Portuguese, Russian, Spanish and many more! ✨
Text-Summarization-using-NLP - Text Summarization using NLP to fetch BBC News Article and summarize its text and also it includes custom article Summarization