|
from pathlib import Path |
|
from typing import List |
|
|
|
import datasets |
|
|
|
from nusacrowd.utils import schemas |
|
from nusacrowd.utils.configs import NusantaraConfig |
|
from nusacrowd.utils.constants import Tasks |
|
|
|
_CITATION = """\ |
|
@inproceedings{van-der-goot-etal-2020-cross, |
|
title={From Masked-Language Modeling to Translation: Non-{E}nglish Auxiliary Tasks Improve Zero-shot Spoken Language Understanding}, |
|
author={van der Goot, Rob and Sharaf, Ibrahim and Imankulova, Aizhan and {\"U}st{\"u}n, Ahmet and Stepanovic, Marija and Ramponi, Alan and Khairunnisa, Siti Oryza and Komachi, Mamoru and Plank, Barbara}, |
|
booktitle = "Proceedings of the 2021 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)", |
|
year = "2021", |
|
address = "Mexico City, Mexico", |
|
publisher = "Association for Computational Linguistics" |
|
} |
|
""" |
|
_DATASETNAME = "xsid" |
|
_DESCRIPTION = """\ |
|
XSID is a new benchmark for cross-lingual (X) Slot and Intent Detection in 13 languages from 6 language families, including a very low-resource dialect. |
|
""" |
|
_HOMEPAGE = "https://bitbucket.org/robvanderg/xsid/src/master/" |
|
_LANGUAGES = ["ind"] |
|
_LICENSE = "CC-BY-SA 4.0" |
|
_LOCAL = False |
|
_URLS = { |
|
_DATASETNAME: "https://bitbucket.org/robvanderg/xsid/get/04ce1e6c8c28.zip", |
|
} |
|
_SUPPORTED_TASKS = [Tasks.INTENT_CLASSIFICATION, Tasks.POS_TAGGING] |
|
_SOURCE_VERSION = "0.3.0" |
|
_NUSANTARA_VERSION = "1.0.0" |
|
|
|
INTENT_LIST = [ |
|
"AddToPlaylist", |
|
"BookRestaurant", |
|
"PlayMusic", |
|
"RateBook", |
|
"SearchCreativeWork", |
|
"SearchScreeningEvent", |
|
"alarm/cancel_alarm", |
|
"alarm/modify_alarm", |
|
"alarm/set_alarm", |
|
"alarm/show_alarms", |
|
"alarm/snooze_alarm", |
|
"alarm/time_left_on_alarm", |
|
"reminder/cancel_reminder", |
|
"reminder/set_reminder", |
|
"reminder/show_reminders", |
|
"weather/checkSunrise", |
|
"weather/checkSunset", |
|
"weather/find" |
|
] |
|
|
|
TAG_LIST = [ |
|
"B-album", |
|
"B-artist", |
|
"B-best_rating", |
|
"B-condition_description", |
|
"B-condition_temperature", |
|
"B-cuisine", |
|
"B-datetime", |
|
"B-ecurring_datetime", |
|
"B-entity_name", |
|
"B-facility", |
|
"B-genre", |
|
"B-location", |
|
"B-movie_name", |
|
"B-movie_type", |
|
"B-music_item", |
|
"B-object_location_type", |
|
"B-object_name", |
|
"B-object_part_of_series_type", |
|
"B-object_select", |
|
"B-object_type", |
|
"B-party_size_description", |
|
"B-party_size_number", |
|
"B-playlist", |
|
"B-rating_unit", |
|
"B-rating_value", |
|
"B-recurring_datetime", |
|
"B-reference", |
|
"B-reminder/todo", |
|
"B-restaurant_name", |
|
"B-restaurant_type", |
|
"B-served_dish", |
|
"B-service", |
|
"B-sort", |
|
"B-track", |
|
"B-weather/attribute", |
|
"I-album", |
|
"I-artist", |
|
"I-best_rating", |
|
"I-condition_description", |
|
"I-condition_temperature", |
|
"I-cuisine", |
|
"I-datetime", |
|
"I-ecurring_datetime", |
|
"I-entity_name", |
|
"I-facility", |
|
"I-genre", |
|
"I-location", |
|
"I-movie_name", |
|
"I-movie_type", |
|
"I-music_item", |
|
"I-object_location_type", |
|
"I-object_name", |
|
"I-object_part_of_series_type", |
|
"I-object_select", |
|
"I-object_type", |
|
"I-party_size_description", |
|
"I-party_size_number", |
|
"I-playlist", |
|
"I-rating_unit", |
|
"I-rating_value", |
|
"I-recurring_datetime", |
|
"I-reference", |
|
"I-reminder/todo", |
|
"I-restaurant_name", |
|
"I-restaurant_type", |
|
"I-served_dish", |
|
"I-service", |
|
"I-sort", |
|
"I-track", |
|
"I-weather/attribute", |
|
"O", |
|
"Orecurring_datetime" |
|
] |
|
|
|
class XSID(datasets.GeneratorBasedBuilder): |
|
"""xSID datasets contains datasets to detect the intent from the text""" |
|
|
|
BUILDER_CONFIGS = [ |
|
NusantaraConfig( |
|
name="xsid_source", |
|
version=datasets.Version(_SOURCE_VERSION), |
|
description="xSID source schema", |
|
schema="source", |
|
subset_id="xsid", |
|
), |
|
NusantaraConfig( |
|
name="xsid_nusantara_text", |
|
version=datasets.Version(_NUSANTARA_VERSION), |
|
description="xSID Nusantara intent classification schema", |
|
schema="nusantara_text", |
|
subset_id="xsid", |
|
), |
|
NusantaraConfig( |
|
name="xsid_nusantara_seq_label", |
|
version=datasets.Version(_NUSANTARA_VERSION), |
|
description="xSID Nusantara pos tagging schema", |
|
schema="nusantara_seq_label", |
|
subset_id="xsid", |
|
), |
|
] |
|
|
|
DEFAULT_CONFIG_NAME = "xsid_source" |
|
|
|
def _info(self) -> datasets.DatasetInfo: |
|
if self.config.schema == "source": |
|
features = datasets.Features( |
|
{ |
|
"id": datasets.Value("string"), |
|
"text": datasets.Value("string"), |
|
"text-en": datasets.Value("string"), |
|
"intent": datasets.Value("string"), |
|
"tokens": datasets.Sequence(datasets.Value("string")), |
|
} |
|
) |
|
elif self.config.schema == "nusantara_text": |
|
features = schemas.text_features(label_names=INTENT_LIST) |
|
elif self.config.schema == "nusantara_seq_label": |
|
features = schemas.seq_label_features(label_names=TAG_LIST) |
|
else: |
|
raise ValueError(f"Invalid config schema: {self.config.schema}") |
|
|
|
return datasets.DatasetInfo( |
|
description=_DESCRIPTION, |
|
features=features, |
|
homepage=_HOMEPAGE, |
|
license=_LICENSE, |
|
citation=_CITATION, |
|
) |
|
|
|
def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]: |
|
urls = _URLS[_DATASETNAME] |
|
base_path = Path(dl_manager.download_and_extract(urls)) / "robvanderg-xsid-04ce1e6c8c28" / "data" / "xSID-0.3" |
|
data_files = { |
|
"train": base_path / "id.projectedTrain.conll", |
|
"test": base_path / "id.test.conll", |
|
"validation": base_path / "id.valid.conll" |
|
} |
|
|
|
return [ |
|
datasets.SplitGenerator( |
|
name=datasets.Split.TRAIN, |
|
gen_kwargs={"filepath": data_files["train"]}, |
|
), |
|
datasets.SplitGenerator( |
|
name=datasets.Split.TEST, |
|
gen_kwargs={"filepath": data_files["test"]}, |
|
), |
|
datasets.SplitGenerator( |
|
name=datasets.Split.VALIDATION, |
|
gen_kwargs={"filepath": data_files["validation"]}, |
|
), |
|
] |
|
|
|
def _generate_examples(self, filepath: Path): |
|
print('filepath', filepath) |
|
if self.config.name == "xsid_source": |
|
with open(filepath, "r") as file: |
|
data = file.read().strip("\n").split("\n\n") |
|
|
|
i = 0 |
|
for sample in data: |
|
id = "" |
|
tokens = [] |
|
for row_sample in sample.split("\n"): |
|
s = row_sample.split(": ") |
|
if s[0] == "# id": |
|
id = s[1] |
|
elif s[0] == "# text-en": |
|
text_en = s[1] |
|
elif s[0] == "# text": |
|
text = s[1] |
|
elif s[0] == "# intent": |
|
intent = s[1] |
|
else: |
|
tokens.append(s[0]) |
|
|
|
if id == "": |
|
id = i |
|
i = i + 1 |
|
|
|
ex = { |
|
"id": id, |
|
"text": text, |
|
"text-en": text_en, |
|
"intent": intent, |
|
"tokens": tokens |
|
} |
|
yield id, ex |
|
|
|
elif self.config.name == "xsid_nusantara_text": |
|
with open(filepath, "r") as file: |
|
data = file.read().strip("\n").split("\n\n") |
|
|
|
i = 0 |
|
for sample in data: |
|
id = "" |
|
for row_sample in sample.split("\n"): |
|
s = row_sample.split(": ") |
|
if s[0] == "# id": |
|
id = s[1] |
|
elif s[0] == "# text": |
|
text = s[1] |
|
elif s[0] == "# intent": |
|
intent = s[1] |
|
|
|
if id == "": |
|
id = i |
|
i = i + 1 |
|
|
|
ex = { |
|
"id": id, |
|
"text": text, |
|
"label": intent |
|
} |
|
yield id, ex |
|
|
|
elif self.config.name == "xsid_nusantara_seq_label": |
|
with open(filepath, "r") as file: |
|
data = file.read().strip("\n").split("\n\n") |
|
|
|
i = 0 |
|
for sample in data: |
|
id = "" |
|
tokens = [] |
|
labels = [] |
|
for row_sample in sample.split("\n"): |
|
s = row_sample.split(": ") |
|
if s[0] == "# id": |
|
id = s[1] |
|
elif len(s) == 1: |
|
tokens.append(s[0].split("\t")[1]) |
|
labels.append(s[0].split("\t")[3]) |
|
|
|
if id == "": |
|
id = i |
|
i = i + 1 |
|
|
|
ex = { |
|
"id": id, |
|
"tokens": tokens, |
|
"labels": labels |
|
} |
|
yield id, ex |
|
|
|
else: |
|
raise ValueError(f"Invalid config: {self.config.name}") |
|
|