Split data

data_anon/dev.jsonl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e860b89584bd88e27da41139204a05a96f6d64aa06331051d420c307d2822fcc
+size 20379694

data_anon/test.jsonl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:de6ec0c0cc97bb2c15e0fd3d09537807f95046068ea497ec31e7ecd126f43947
+size 33869151

data_anon/train.jsonl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:209755f6dfee89849455b89918babee0e33618c40e65a99e9a8cbd6164394dbd
+size 98259925

echr.py

@@ -0,0 +1,70 @@
+import datasets
+
+_CITATION = """\
+@inproceedings{chalkidis-etal-2019-neural,
+    title = "Neural Legal Judgment Prediction in {E}nglish",
+    author = "Chalkidis, Ilias  and
+      Androutsopoulos, Ion  and
+      Aletras, Nikolaos",
+    booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics",
+    month = jul,
+    year = "2019",
+    address = "Florence, Italy",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/P19-1424",
+    doi = "10.18653/v1/P19-1424",
+    pages = "4317--4323",
+}
+"""
+
+_HOMEPAGE = "https://archive.org/details/ECHR-ACL2019"
+
+ARTICLES = {
+    "2": "Right to life",
+    "3": "Prohibition of torture",
+    "4": "Prohibition of slavery and forced labour",
+    "5": "Right to liberty and security",
+    "6": "Right to a fair trial",
+    "7": "No punishment without law",
+    "8": "Right to respect for private and family life",
+    "9": "Freedom of thought, conscience and religion",
+    "10": "Freedom of expression",
+    "11": "Freedom of assembly and association",
+    "12": "Right to marry",
+    "13": "Right to an effective remedy",
+    "14": "Prohibition of discrimination",
+    "15": "Derogation in time of emergency",
+    "16": "Restrictions on political activity of aliens",
+    "17": "Prohibition of abuse of rights",
+    "18": "Limitation on use of restrictions on rights",
+    "34": "Individual applications",
+    "38": "Examination of the case",
+    "39": "Friendly settlements",
+    "46": "Binding force and execution of judgments",
+    "P1-1": "Protection of property",
+    "P1-2": "Right to education",
+    "P1-3": "Right to free elections",
+    "P3-1": "Right to free elections",
+    "P4-1": "Prohibition of imprisonment for debt",
+    "P4-2": "Freedom of movement",
+    "P4-3": "Prohibition of expulsion of nationals",
+    "P4-4": "Prohibition of collective expulsion of aliens",
+    "P6-1": "Abolition of the death penalty",
+    "P6-2": "Death penalty in time of war",
+    "P6-3": "Prohibition of derogations",
+    "P7-1": "Procedural safeguards relating to expulsion of aliens",
+    "P7-2": "Right of appeal in criminal matters",
+    "P7-3": "Compensation for wrongful conviction",
+    "P7-4": "Right not to be tried or punished twice",
+    "P7-5": "Equality between spouses",
+    "P12-1": "General prohibition of discrimination",
+    "P13-1": "Abolition of the death penalty",
+    "P13-2": "Prohibition of derogations",
+    "P13-3": "Prohibition of reservations",
+}
+
+class Echr(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="non-anon", data_dir="data"),
+        datasets.BuilderConfig(name="anon", data_dir="data_anon"),
+    ]

process.ipynb

@@ -72,9 +72,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "train = pd.read_json(\"train.jsonl\", lines=True, orient=\"records\")\n",
-    "test = pd.read_json(\"test.jsonl\", lines=True, orient=\"records\")\n",
-    "dev = pd.read_json(\"dev.jsonl\", lines=True, orient=\"records\")"
+    "train = pd.read_json(\"data_anon/train.jsonl\", lines=True, orient=\"records\")\n",
+    "test = pd.read_json(\"data_anon/test.jsonl\", lines=True, orient=\"records\")\n",
+    "dev = pd.read_json(\"data_anon/dev.jsonl\", lines=True, orient=\"records\")"
    ]
   },
   {
@@ -85,7 +85,7 @@
    "source": [
     "import re\n",
     "\n",
-    "number = re.compile(\"^[0-9]+\\. \")\n",
+    "number = re.compile(\"^([0-9]+|CARDINAL)\\s?\\. \")\n",
     "train[\"text\"] = train[\"text\"].map(lambda r: [re.sub(number, \"\", line) for line in r])\n",
     "test[\"text\"] = test[\"text\"].map(lambda r: [re.sub(number, \"\", line) for line in r])\n",
     "dev[\"text\"] = dev[\"text\"].map(lambda r: [re.sub(number, \"\", line) for line in r])"