def METHOD_NAME(self, sentences):
    """
    Applies the tag method over a list of sentences. This method will return a
    list of dictionaries. Every dictionary will contain a word with its
    calculated annotations/tags.
    """
    encoding = self._encoding
    if not path.isfile(self.executable(self._path)):
        raise LookupError(
            "Senna executable expected at %s but not found"
            % self.executable(self._path)
        )
    # Build the senna command to run the tagger
    _senna_cmd = [
        self.executable(self._path),
        "-path",
        self._path,
        "-usrtokens",
        "-iobtags",
    ]
    _senna_cmd.extend(["-" + op for op in self.operations])
    # Serialize the actual sentences to a temporary string
    _input = "\n".join(" ".join(x) for x in sentences) + "\n"
    if isinstance(_input, str) and encoding:
        _input = _input.encode(encoding)
    # Run the tagger and get the output
    p = Popen(_senna_cmd, stdin=PIPE, stdout=PIPE, stderr=PIPE)
    (stdout, stderr) = p.communicate(input=_input)
    senna_output = stdout
    # Check the return code.
    if p.returncode != 0:
        raise RuntimeError("Senna command failed! Details: %s" % stderr)
    if encoding:
        senna_output = stdout.decode(encoding)
    # Output the tagged sentences
    map_ = self._map()
    tagged_sentences = [[]]
    sentence_index = 0
    token_index = 0
    for tagged_word in senna_output.strip().split("\n"):
        if not tagged_word:
            tagged_sentences.append([])
            sentence_index += 1
            token_index = 0
            continue
        tags = tagged_word.split("\t")
        result = {}
        for tag in map_:
            result[tag] = tags[map_[tag]].strip()
        try:
            result["word"] = sentences[sentence_index][token_index]
        except IndexError as e:
            raise IndexError(
                "Misalignment error occurred at sentence number %d. Possible reason"
                " is that the sentence size exceeded the maximum size. Check the "
                "documentation of Senna class for more information."
                % sentence_index
            ) from e
        tagged_sentences[-1].append(result)
        token_index += 1
    return tagged_sentences