def numeric_parse_text(conn, table, word_embeddings_file, word_delimiter=
    '\t', parse_column='first_objects'):
    """
    Parses text data into numeric data using a word-embeddings file

    Parameters
    ----------
    conn : CAS
        Specifies the CAS connection object.
    table: CASTable
        Specifies table containing data to be parsed
    word_embeddings_file : string
        Specifies path to file containing word embeddings
    word_delimiter : string, optional
        Specifies delimiter used in word embeddings file
        Default : '	'
    parse_column : string, optional
        Specifies name of column containing text data to be parsed
        Default : 'first_objects'
    Returns
    -------
    :class:`CASTable`

    """
    conn.upload_file(data=word_embeddings_file, casout=dict(name=
        'word_embeddings', replace=True), importOptions=dict(fileType=
        'delimited', delimiter=word_delimiter, getNames=True, guessRows=2,
        varChars=True))
    conn.tpParse(table=table, docId='_id_', entities='NONE', text=
        parse_column, nounGroups=False, offset=dict(name='pos_output',
        replace=True))
    conn.applyWordVector(casout=dict(name='objects_all_numeric', replace=
        True), modelTable=dict(name='word_embeddings'), table=dict(name=
        'pos_output'))
    conn.altertable('objects_all_numeric', columns=[dict(name='_Document_',
        rename='_id_')])
    objects_numeric = conn.CASTable('objects_all_numeric')
    return objects_numeric
