A fast implementation of RuSH (Rule-based sentence Segmenter using Hashing).
Project description
py4jrush
py4jrush is the python interface to RuSH(https://github.com/jianlins/RuSH) (Ru le-based sentence S egmenter using H ashing), which is originally developed using Java. This version is implemented through py4j, compared with the original PyRuSH.
RuSH is an efficient, reliable, and easy adaptable rule-based sentence segmentation solution. It is specifically designed to handle the telegraphic written text in clinical note. It leverages a nested hash table to execute simultaneous rule processing, which reduces the impact of the rule-base growth on execution time and eliminates the effect of rule order on accuracy.
If you wish to cite RuSH in a publication, please use:
Jianlin Shi ; Danielle Mowery ; Kristina M. Doing-Harris ; John F. Hurdle.RuSH: a Rule-based Segmentation Tool Using Hashing for Extremely Accurate Sentence Segmentation of Clinical Text. AMIA Annu Symp Proc. 2016: 1587.
The full text can be found here.
Installation
When you run pip install py4jrush, the installer will automatically check for Java JDK 8. If JDK 8 is not found, it will use the install-jdk Python package to download and install JDK 8 for you. No manual Java setup is required.
pip install py4jrush
How to use
A standalone RuSH class is available to be directly used in your code. From 1.0.4, pyRush adopt spaCy 3.x api to initiate an component.
from py4jrush import RuSH
input_str = "The patient was admitted on 03/26/08\n and was started on IV antibiotics elevation" +\
", was also counseled to minimizing the cigarette smoking. The patient had edema\n\n" +\
"\n of his bilateral lower extremities. The hospital consult was also obtained to " +\
"address edema issue question was related to his liver hepatitis C. Hospital consult" +\
" was obtained. This included an ultrasound of his abdomen, which showed just mild " +\
"cirrhosis. "
rush = RuSH('../conf/rush_rules.tsv')
sentences=rush.segToSentenceSpans(input_str)
for sentence in sentences:
print("Sentence({0}-{1}):\t>{2}<".format(sentence.begin, sentence.end, input_str[sentence.begin:sentence.end]))
Spacy Componentized py4jrush
Start from version 1.0.3, py4jrush adds Spacy compatible Sentencizer component: PyRuSHSentencizer.
from py4jrush import PyRuSHSentencizer
from spacy.lang.en import English
nlp = English()
nlp.add_pipe("medspacy_py4jrush")
doc = nlp("This is a sentence. This is another sentence.")
print('\n'.join([str(s) for s in doc.sents]))
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