changes

PLOD-filtered.py

@@ -0,0 +1,136 @@
+import os
+
+import datasets
+
+
+logger = datasets.logging.get_logger(__name__)
+
+
+_CITATION = """
+"""
+
+_DESCRIPTION = """
+This is the dataset repository for PLOD Dataset accepted to be published at LREC 2022.
+The dataset can help build sequence labelling models for the task Abbreviation Detection.
+"""
+
+_TRAINING_FILE = "./data/PLOS-train70-filtered-pos_bio.json"
+_DEV_FILE = "./data/PLOS-val15-filtered-pos_bio.json"
+_TEST_FILE = "./data/PLOS-test15-filtered-pos_bio.json"
+
+
+class PLODfilteredConfig(datasets.BuilderConfig):
+    """BuilderConfig for Conll2003"""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig forConll2003.
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(PLODfilteredConfig, self).__init__(**kwargs)
+
+
+class PLODfilteredConfig(datasets.GeneratorBasedBuilder):
+    """PLOD Filtered dataset."""
+
+    BUILDER_CONFIGS = [
+        PLODfilteredConfig(name="PLODfiltered", version=datasets.Version("0.0.2"), description="PLOD filtered dataset"),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "tokens": datasets.Sequence(datasets.Value("string")),
+                    "pos_tags": datasets.Sequence(
+                        datasets.features.ClassLabel(
+                            names=[
+                                "ADJ",
+                                "ADP",
+                                "ADV",
+                                "AUX",
+                                "CONJ",
+                                "CCONJ",
+                                "DET",
+                                "INTJ",
+                                "NOUN",
+                                "NUM",
+                                "PART",
+                                "PRON",
+                                "PROPN",
+                                "PUNCT",
+                                "SCONJ",
+                                "SYM",
+                                "VERB",
+                                "X",
+                                "SPACE"
+                            ]
+                        )
+                    ),
+                    "ner_tags": datasets.Sequence(
+                        datasets.features.ClassLabel(
+                            names=[
+                                "B-O",
+                                "B-AC",
+                                "I-AC",
+                                "B-LF",
+                                "I-LF"
+                            ]
+                        )
+                    ),
+                }
+            ),
+            supervised_keys=None,
+            homepage="https://github.com/surrey-nlp/PLOD-AbbreviationDetection",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        data_files = {
+            "train": os.path.join(_TRAINING_FILE),
+            "dev": os.path.join(_DEV_FILE),
+            "test": os.path.join(_TEST_FILE),
+        }
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_files["train"]}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": data_files["dev"]}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": data_files["test"]}),
+        ]
+
+    def _generate_examples(self, filepath):
+        logger.info("⏳ Generating examples from = %s", filepath)
+        with open(filepath, encoding="utf-8") as f:
+            guid = 0
+            tokens = []
+            pos_tags = []
+            ner_tags = []
+            for line in f:
+                if line.startswith("-DOCSTART-") or line == "" or line == "\n":
+                    if tokens:
+                        yield guid, {
+                            "id": str(guid),
+                            "tokens": tokens,
+                            "pos_tags": pos_tags,
+                            "ner_tags": ner_tags,
+                        }
+                        guid += 1
+                        tokens = []
+                        pos_tags = []
+                        ner_tags = []
+                else:
+                    # conll2003 tokens are space separated
+                    splits = line.split(" ")
+                    tokens.append(splits[0])
+                    pos_tags.append(splits[1].strip())
+                    ner_tags.append(splits[2].strip())
+            # last example
+            yield guid, {
+                "id": str(guid),
+                "tokens": tokens,
+                "pos_tags": pos_tags,
+                "ner_tags": ner_tags,
+            }

README.md

@@ -1,3 +1,5 @@
+# PLOD Abbreviation Detection Dataset
+
 ---
 license: cc-by-sa-4.0
 ---