| """ Slovene corpus for coreference resolution coref149. """ | |
| import os | |
| import xml.etree.ElementTree as ET | |
| import datasets | |
| _CITATION = """\ | |
| @article{coref149, | |
| author={Žitnik, Slavko and Bajec, Marko}, | |
| title={Odkrivanje koreferenčnosti v slovenskem jeziku na označenih besedilih iz coref149}, | |
| journal={Slovenščina 2.0: empirične, aplikativne in interdisciplinarne raziskave}, | |
| number={1}, | |
| volume={6}, | |
| year={2018}, | |
| month={Jun.}, | |
| pages={37–67}, | |
| doi={10.4312/slo2.0.2018.1.37-67} | |
| } | |
| """ | |
| _DESCRIPTION = """\ | |
| Slovene corpus for coreference resolution. Contains manually annotated coreferences. | |
| """ | |
| _HOMEPAGE = "http://hdl.handle.net/11356/1182" | |
| _LICENSE = "Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)" | |
| _URLS = { | |
| "coref149": "https://www.clarin.si/repository/xmlui/bitstream/handle/11356/1182/coref149_v1.0.zip" | |
| } | |
| class Coref149(datasets.GeneratorBasedBuilder): | |
| """Slovene corpus for coreference resolution.""" | |
| VERSION = datasets.Version("1.0.0") | |
| def _info(self): | |
| features = datasets.Features( | |
| { | |
| "id_doc": datasets.Value("string"), | |
| "words": datasets.Sequence(datasets.Sequence(datasets.Value("string"))), | |
| "mentions": [{ | |
| "id_mention": datasets.Value("string"), | |
| "mention_data": { | |
| "idx_sent": datasets.Value("uint32"), | |
| "word_indices": datasets.Sequence(datasets.Value("uint32")), | |
| "global_word_indices": datasets.Sequence(datasets.Value("uint32")) | |
| } | |
| }], | |
| "coref_clusters": datasets.Sequence(datasets.Sequence(datasets.Value("string"))) | |
| } | |
| ) | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=features, | |
| homepage=_HOMEPAGE, | |
| license=_LICENSE, | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| urls = _URLS["coref149"] | |
| data_dir = dl_manager.download_and_extract(urls) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={ | |
| "data_dir": data_dir | |
| } | |
| ) | |
| ] | |
| def _generate_examples(self, data_dir): | |
| TC_NAMESPACE = "{http://www.dspin.de/data/textcorpus}" | |
| all_files = sorted([fname for fname in os.listdir(data_dir) if fname.endswith(".tcf")], | |
| key=lambda _fname: int(_fname.split(".")[-2])) | |
| for idx_file, curr_fname in enumerate(all_files): | |
| curr_doc = ET.parse(os.path.join(data_dir, curr_fname)) | |
| root = curr_doc.getroot() | |
| id_doc = curr_fname.split(os.path.sep)[-1] | |
| token_tags = root.findall(f".//{TC_NAMESPACE}token") | |
| id2tok, id2idx, id2globidx, id2sentidx = {}, {}, {}, {} | |
| for idx_global, token in enumerate(token_tags): | |
| id_token = token.attrib["ID"] | |
| text_token = token.text.strip() | |
| id2tok[id_token] = text_token | |
| id2globidx[id_token] = idx_global | |
| sent_tags = root.findall(f".//{TC_NAMESPACE}sentence") | |
| words = [] | |
| for idx_sent, sent in enumerate(sent_tags): | |
| token_ids = sent.attrib["tokenIDs"].split(" ") | |
| for local_position, _id_tok in enumerate(token_ids): | |
| id2sentidx[_id_tok] = idx_sent | |
| id2idx[_id_tok] = local_position | |
| words.append([id2tok[_id] for _id in token_ids]) | |
| mentions, clusters = [], [] | |
| for ent in root.findall(f".//{TC_NAMESPACE}entity"): | |
| curr_cluster = [] | |
| for ref in ent.findall(f"{TC_NAMESPACE}reference"): | |
| id_mention = f"{id_doc}.{ref.attrib['ID']}" | |
| curr_cluster.append(id_mention) | |
| curr_mention = { | |
| "id_mention": id_mention, | |
| "mention_data": { | |
| "idx_sent": None, | |
| "word_indices": [], | |
| "global_word_indices": [] | |
| } | |
| } | |
| for id_token in ref.attrib['tokenIDs'].split(" "): | |
| curr_mention["mention_data"]["idx_sent"] = id2sentidx[id_token] | |
| curr_mention["mention_data"]["word_indices"].append(id2idx[id_token]) | |
| curr_mention["mention_data"]["global_word_indices"].append(id2globidx[id_token]) | |
| mentions.append(curr_mention) | |
| clusters.append(curr_cluster) | |
| yield idx_file, { | |
| "id_doc": id_doc, | |
| "words": words, | |
| "mentions": mentions, | |
| "coref_clusters": clusters | |
| } | |