neo-gate_adapt.py

# Copyright 2024 FBK

# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at

#     http://www.apache.org/licenses/LICENSE-2.0

# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License
import argparse
import json
import pandas as pd
from typing import Dict, List, Tuple


__version__ = '0.1'


def get_tagset_mapping(tagset_filename: str) -> dict:
    """
    Loads a `dict` from the JSON file, which should be organized as a dictionary containing
    tags from Neo-GATE's tagset as keys and the corresponding desired forms as values.

    For an example of a tagset mapping, see the file `schwa.json`.
    For more information, visit https://huggingface.co/datasets/FBK-MT/Neo-GATE.
    """
    with open(tagset_filename, 'r') as tagset_file:
        return json.load(tagset_file)


def get_neogate(neogate_filename: str) -> Tuple[List[str], List[str]]:
    """
    Reads the tagged references and the annotations from the corresponding columns of the NeoGATE
    TSV file.
    """
    neogate = pd.read_csv(neogate_filename, delimiter='\t')
    return neogate['REF-TAGGED'].to_list(), neogate['ANNOTATION'].to_list()


def annotate_with_tags(tagset: Dict[str, str], str_to_annotate: str) -> str:
    """
    Replaces all the tags defined in `tagset` with the corresponding form in `str_to_annotate`.
    """
    for key in tagset:
        str_to_annotate = str_to_annotate.replace(key, tagset[key])
    return str_to_annotate


def main(args):
    tagset = get_tagset_mapping(args.tagset)
    refs, anns = get_neogate(args.neogate)
    assert len(refs) == len(anns), \
        "The number of references does not match the number of annotations."
    with open(f"{args.out}.ann", 'w') as annotations_file, \
         open(f"{args.out}.ref", 'w') as references_file:
        for ann, ref in zip(refs, anns):
            annotations_file.write(annotate_with_tags(tagset, ann))
            annotations_file.write("\n")
            references_file.write(annotate_with_tags(tagset, ref))
            references_file.write("\n")


if __name__ == '__main__':
    """
    This script adapts Neo-GATE's annotations and references to the desired neomorpheme paradigm.
    The script requires a JSON file containing the tagset mapping for the desired paradigm.
    For more information, visit https://huggingface.co/datasets/FBK-MT/Neo-GATE.

    The resulting references will be saved in a `.ref` file, whereas the annotations will be saved
    in a `.ann` file.
    """
    print(f"Neo-GATE adaptation script {__version__}.")
    parser = argparse.ArgumentParser()
    parser.add_argument('--neogate', type=str, default='./Neo-GATE.tsv',
                        help="TSV file containing Neo-GATE.")
    parser.add_argument('--tagset', type=str, required=True,
                        help="JSON file containing tags as keys and the desired forms as values.")
    parser.add_argument('--out', type=str, help="Output file name.", required=True)
    args = parser.parse_args()
    main(args)