https://github.com/ikergarcia1996/basic-cyk-parser
Basic CYK-Parser written in python 3
https://github.com/ikergarcia1996/basic-cyk-parser
cyk cyk-algorithm cyk-parser grammar grammar-parser natural-language-processing nlp parser parsing python-3
Last synced: 4 months ago
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Basic CYK-Parser written in python 3
- Host: GitHub
- URL: https://github.com/ikergarcia1996/basic-cyk-parser
- Owner: ikergarcia1996
- License: mit
- Created: 2019-01-11T19:56:57.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2019-01-11T20:34:35.000Z (over 6 years ago)
- Last Synced: 2025-01-10T23:51:55.783Z (4 months ago)
- Topics: cyk, cyk-algorithm, cyk-parser, grammar, grammar-parser, natural-language-processing, nlp, parser, parsing, python-3
- Language: Jupyter Notebook
- Homepage:
- Size: 47.9 KB
- Stars: 9
- Watchers: 5
- Forks: 9
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
This is a basic CYK Parser implemented in Python 3. This parser has been implemented for the "Computational Linguistics: Morphology and Syntax" course of the Language Analysis and Processing Master (http://ixa.si.ehu.es/master/?lang=en).
# Files in the repository
1. CYK_Parser.ipyn: Parser in jupyter notebook format
2. CYK_Parser.ipyn: Parser in .py format
3. example.py: Some examples of use (usage: python3 example.py)
4. example_output.txt: output of the example.py script in txt format
5. example_grammar*.txt: Some example grammars
# Author
```
Iker García Ferrero - ikergarcia1996
```
# Example Of Use
```
# Initialize the grammar and read the rules from a file
g = Grammar('example_grammar1.txt')
# Parse a sentence
g.parse('astronomers saw stars with ears')
# Print the table used for parsing the sentence
g.print_parse_table()
# Get the list of trees generated for the sentence
trees = g.get_trees()
# Get the result of the production rule, VP, S, NP...
p = trees[0].get_type
# Get the left child of the production rule
l = trees[0].get_left
# Get the right child of the production rule
d = trees[0].get_right
```
## Expected output
```
Grammar file readed succesfully. Rules readed:
S --> NP VP
PP --> P NP
VP --> V NP
VP --> VP PP
NP --> NP PP
NP --> astronomers
NP --> ears
NP --> saw
V --> saw
NP --> telescope
NP --> stars
P --> with
Applied Rule: VP[2,2] --> V[1,2] NP[1,3]
Applied Rule: PP[2,4] --> P[1,4] NP[1,5]
Applied Rule: S[3,1] --> NP[1,1] VP[2,2]
Applied Rule: NP[3,3] --> NP[1,3] PP[2,4]
Applied Rule: VP[4,2] --> V[1,2] NP[3,3]
Applied Rule: VP[4,2] --> VP[2,2] PP[2,4]
Applied Rule: S[5,1] --> NP[1,1] VP[4,2]
Applied Rule: S[5,1] --> NP[1,1] VP[4,2]
----------------------------------------
The sentence IS accepted in the language
Number of possible trees: 2
----------------------------------------
----------- ------------ ------ ------ ------
['S', 'S']
[] ['VP', 'VP']
['S'] [] ['NP']
[] ['VP'] [] ['PP']
['NP'] ['NP', 'V'] ['NP'] ['P'] ['NP']
astronomers saw stars with ears
----------- ------------ ------ ------ ------
```
# Example of grammar file
The program assumes that the grammar is a valid context-free grammar in CNF form (https://www.tutorialspoint.com/automata_theory/chomsky_normal_form.htm). Rules must be separated by lines.
```
S -> NP VP
PP -> P NP
VP -> V NP
VP -> VP PP
NP-> NP PP
NP -> astronomers
NP -> ears
NP -> saw
NP-> telescope
NP -> stars
P -> with
V -> saw
```