e-MGs
pke
| e-MGs | pke | |
|---|---|---|
| 2 | 3 | |
| 6 | 1,531 | |
| - | - | |
| 4.8 | 3.1 | |
| 3 months ago | 10 months ago | |
| Python | Python | |
| MIT License | GNU General Public License v3.0 only |
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e-MGs
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Is it possible to adapt a parser to a SOV language?
I don't have code of my own, the parser is taken from here https://github.com/cristianochesi/e-MGs but according to my advisor I should be able to adapt the parser to a SOV (subject-object-verb) language without touching the code.
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Forest package output is all messy
Sorry for my late reply, but this is the parser I'm running https://github.com/cristianochesi/e-MGs
pke
- Question on easing comprehension
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[P] Building model to extract keywords from legal documents
Look into rake, pke, phrasemachine, pyate, keybert.
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Best approach for automatic key word extraction
There are lots of off-the-shelf tools for this. Look into: - https://github.com/boudinfl/pke - https://github.com/kevinlu1248/pyate - https://github.com/zelandiya/RAKE-tutorial - https://github.com/slanglab/phrasemachine - https://github.com/MaartenGr/KeyBERT/
What are some alternatives?
KeyBERT - Minimal keyword extraction with BERT
rake-nltk - Python implementation of the Rapid Automatic Keyword Extraction algorithm using NLTK.
yake - Single-document unsupervised keyword extraction
pytextrank - Python implementation of TextRank algorithms ("textgraphs") for phrase extraction
pyate - PYthon Automated Term Extraction
textstat - :memo: python package to calculate readability statistics of a text object - paragraphs, sentences, articles.
phrasemachine - Quickly extract multi-word phrases from a corpus
news-fetch - A Python Package which helps to scrape all news details from any news websites
EasyOCR - Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.
retext-readability - plugin to check readability
kefir - 🥛turkic morphology project