Initial config

itacola.py

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+import csv
+import sys
+
+import datasets
+from typing import List
+
+csv.field_size_limit(sys.maxsize)
+
+
+_CITATION = """\
+@inproceedings{trotta-etal-2021-itacola,
+    author = {Trotta, Daniela and Guarasci, Raffaele and Leonardelli, Elisa and Tonelli, Sara},
+    title = {Monolingual and Cross-Lingual Acceptability Judgments with the Italian {CoLA} corpus},
+    journal = {Arxiv preprint},
+    year = {2021},
+}
+"""
+
+_DESCRIPTION = """\
+The Italian Corpus of Linguistic Acceptability includes almost 10k sentences taken from 
+linguistic literature with a binary annotation made by the original authors themselves. 
+The work is inspired by the English Corpus of Linguistic Acceptability (CoLA) by Warstadt et al.
+Part of the dataset has been manually annotated to highlight 9 linguistic phenomena.
+"""
+
+_HOMEPAGE = "https://github.com/dhfbk/ItaCoLA-dataset"
+
+_LICENSE = "None"
+
+_SPLITS = ["train", "test"]
+
+
+class ItaColaConfig(datasets.BuilderConfig):
+    """BuilderConfig for ItaCoLA."""
+
+    def __init__(
+        self,
+        features,
+        data_url,
+        **kwargs,
+    ):
+        """
+        Args:
+        features: `list[string]`, list of the features that will appear in the
+            feature dict. Should not include "label".
+        data_url: `string`, url to download the zip file from.
+        **kwargs: keyword arguments forwarded to super.
+        """
+        super().__init__(version=datasets.Version("1.0.0"), **kwargs)
+        self.data_url = data_url
+        self.features = features
+
+
+class ItaCola(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.0.0")
+
+    BUILDER_CONFIGS = [
+        ItaColaConfig(
+            name="scores",
+            features=["unique_id", "source", "acceptability", "sentence"],
+            data_url="https://raw.githubusercontent.com/dhfbk/ItaCoLA-dataset/main/ItaCoLA_dataset.tsv"
+        ),
+        ItaColaConfig(
+            name="phenomena",
+            features=[
+                "unique_id",
+                "source",
+                "acceptability",
+                "sentence",
+                "cleft_construction",
+                "copular_construction",
+                "subject_verb_agreement",
+                "wh_islands_violations",
+                "simple",
+                "question",
+                "auxiliary",
+                "bind",
+                "indefinite_pronouns",
+            ],
+            data_url="https://github.com/dhfbk/ItaCoLA-dataset/raw/main/ItaCoLA_dataset_phenomenon.tsv"
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = "scores"
+
+    def _info(self):
+        features = {feature: datasets.Value("int32") for feature in self.config.features}
+        features["source"] = datasets.Value("string")
+        features["sentence"] = datasets.Value("string")
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(features),
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        data_file = dl_manager.download_and_extract(self.config.data_url)
+        if self.config.name == "scores":
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TRAIN,
+                    gen_kwargs={
+                        "filepath": data_file,
+                        "split": "train",
+                        "features": self.config.features,
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name=datasets.Split.TEST,
+                    gen_kwargs={
+                        "filepath": data_file,
+                        "split": "test",
+                        "features": self.config.features,
+                    },
+                ),
+            ]
+        else:
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TRAIN,
+                    gen_kwargs={
+                        "filepath": data_file,
+                        "split": "train",
+                        "features": self.config.features,
+                    },
+                ),
+            ]
+    
+    def _generate_examples(self, filepath: str, split: str, features: List[str]):
+        """Yields examples as (key, example) tuples."""
+        with open(filepath, encoding="utf8") as f:
+            for id_, row in f:
+                if id_ == 0:
+                    continue
+                ex_split = None
+                fields = row.strip().split("\t")
+                if len(fields) > 5:
+                    fields, ex_split = fields[:-1], fields[-1]
+                    if ex_split.strip() != split:
+                        continue
+                yield id_, {
+                    k:v.strip() for k,v in zip(features, fields)
+                }