Metadata-Version: 2.1
Name: lexsub
Version: 1.1.1
Summary: State of the art Lexical Substitution in Context
Home-page: https://github.com/anishacharya/LexSub
Author: Anish Acharya
Author-email: anishacharya@utexas.edu
License: UNKNOWN
Description: ## Setup 
        ``` 
        pip3 install lexsub
        Release: https://pypi.org/project/lexsub/   
        ```
        
        ## Background
        The Lexical Substitution task involves selecting and ranking lexical paraphrases for a target word in a given sentential context. In the task, annotators and systems find an alternative substitute word or phrase for a target word in context.
        The task involves both finding the synonyms and disambiguating the context.
        To give an example:
        ```
        Context: The wine was too strong to drink.
        Target Word: strong
        
        Predicted Candidates (Ranked): 
        powerful 
        potent 
        warm
        hot 
        solid 
        hard 
        ```
        
        *Powerful* and *potent* are much better replacements as indicated by 
        the score next to them as well. Whereas, all are viable 
        replacement candidates given the context from a language modeling
        perspective.   
        Now notice two important things that is interesting: 
        * Not all synonyms fit in the context.  
        (direct lexical substitutions aka synonyms won’t always work)
        * Not all words that fit in the context preserve the meaning 
        of the sentence. (LM score doesn’t always correlate)  
        
        ## Datasets: 
        A. *Lexical Substitution*:
        * [SEMEVAL-2007](http://www.dianamccarthy.co.uk/task10index.html)
        * [Coinco](https://www.ims.uni-stuttgart.de/en/research/resources/corpora/coinco/)
        
        B. *Word Sense Disambiguation:*
        * [WIC](https://pilehvar.github.io/wic/)
        * [WSD](http://lcl.uniroma1.it/wsdeval/home)
        
        
        ## References: 
        1. [SOTA-BERT](https://www.aclweb.org/anthology/P19-1328.pdf)
        2. [Pre-BERT-SOTA,Melamud](https://www.aclweb.org/anthology/N16-1131.pdf) 
        3. [PIC- Katrin](https://u.cs.biu.ac.il/~melamuo/publications/melamud_vsm15.pdf)
        4. [SemBERT, AAAI 2020](https://arxiv.org/pdf/1909.02209.pdf)
        5. [LIBERT](https://arxiv.org/pdf/1909.02339.pdf) 
        6. [Morgifier LSTM, ICLR 2020](https://arxiv.org/pdf/1909.01792.pdf)
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
