Metadata-Version: 2.1
Name: spacy_annotator
Version: 1.1
Summary: SpaCy annotator for Named Entity Recognition (NER) using ipywidgets.
Home-page: https://github.com/ieriii/spacy-annotator
Author: Enrico Alemani
Author-email: enrico.alemani@hey.com
License: MIT
Download-URL: https://github.com/ieriii/spacy-annotator/archive/v_01.tar.gz
Description: # spacy-annotator
        spaCy annotator for Named Entity Recognition (NER) using ipywidgets.
        The annotator allows users to quickly assign custom labels to one or more entities in the text.   
        
        **Features**:
        * The annotator supports pandas dataframe (see `pandas_annotations.py`): it adds annotations in a separate 'annotation' column of the dataframe;
        * If a spacy model is passed into the annotator, the model is used to identify entities in text.   
        This trick of pre-labelling the example using the current best model available allows for accelerated labelling - also known as of noisy pre-labelling;
        * The annotations adhere to spaCy format and are ready to serve as input to spaCy NER model.   
        No additional code required!
        
        **Note**: not using pandas dataframe? No problem. You can always label entities from text stored in a simple python list (see `list_annotations.py`).
        
        Blog post: [medium/enrico.alemani/spacy-annotator](https://medium.com/@enrico.alemani/how-to-create-training-data-for-spacy-ner-models-using-ipywidgets-c4aa71bf61a2)
        
        ## Example code - pandas annotations
        ```python
        import pandas as pd
        import re
        from spacy_annotator.pandas_annotations import annotate as pd_annotate
        
        # Data
        df = pd.DataFrame.from_dict({'full_text' : ['New York is lovely but Milan is amazing!']})
        
        # Annotations
        pd_dd = pd_annotate(df,
                    col_text = 'full_text',     # Column in pandas dataframe containing text to be labelled
                    labels = ['GPE', 'PERSON'], # List of labels
                    sample_size=1,              # Size of the sample to be labelled
                    delimiter='~',              # Delimiter to separate entities in GUI
                    model = None,               # spaCy model for noisy pre-labelling
                    regex_flags=re.IGNORECASE   # One (or more) regex flags to be applied when searching for entities in text
                    )
        
        # Example output
        pd_dd['annotations'][0]
        ```
        
        ## Preview
        ![spacy-annotator demo](demo/spacy-annotator_demo.gif)
        
        ## Contributing
        1. Fork the repo on GitHub;
        2. Clone the project to your own machine;
        3. Commit changes to your own branch; and
        4. Push your work back up to your own fork;
        5. Submit a Pull request so that I can review your changes.
        
        ## Version
        ipywidgets: 7.5.1   
        re: 2.2.1   
        spacy: 2.2.4
        
        ## References
        spacy-annotator is based on [spaCy](https://spacy.io/) and [pigeon](https://github.com/agermanidis/pigeon).   
        Many thanks to them for making their awesome libraries publicly available.
        
Keywords: spacy,NER,NLP
Platform: UNKNOWN
Description-Content-Type: text/markdown
