script name changed

coarsewsd_20.py

@@ -0,0 +1,86 @@
+
+# @title Gold cwsd20 temp
+import json
+import datasets
+
+
+_CITATION = """\
+@misc{loureiro2021analysis,
+      title={Analysis and Evaluation of Language Models for Word Sense Disambiguation}, 
+      author={Daniel Loureiro and Kiamehr Rezaee and Mohammad Taher Pilehvar and Jose Camacho-Collados},
+      year={2021},
+      eprint={2008.11608},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+"""
+
+_DESCRIPTION = """\
+The CoarseWSD-20 dataset is a coarse-grained sense disambiguation built from Wikipedia 
+(nouns only) targetting 2 to 5 senses of 20 ambiguous words. It was specifically designed 
+to provide an ideal setting for evaluating WSD models (e.g. no senses in test sets missing 
+from training), both quantitavely and qualitatively.
+"""
+
+path = "/content/CoarseWSD-20/data/apple/train.data.txt"
+
+
+
+class CWSD20(datasets.GeneratorBasedBuilder):
+    """TODO(WiCTSV): Short description of my dataset."""
+
+    # TODO(WiCTSV): Set up version.
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+        # TODO(WiCTSV): Specifies the datasets.DatasetInfo object
+        return datasets.DatasetInfo(
+            # This is the description that will appear on the datasets page.
+            description=_DESCRIPTION,
+            # datasets.features.FeatureConnectors
+            features=datasets.Features(
+                {
+                    "idx": datasets.Value("int32"),
+                    "sentence": datasets.Value("string"),
+                    # "idx": datasets.Value("int32"),
+                    # "word": datasets.Value("string"),
+                    # "start1": datasets.Value("int32"),
+                    # "start2": datasets.Value("int32"),
+                    # "end1": datasets.Value("int32"),
+                    # "end2": datasets.Value("int32"),
+                    # "label": datasets.Value("int32")
+                }
+            ),
+            # If there's a common (input, target) tuple from the features,
+            # specify them here. They'll be used if as_supervised=True in
+            # builder.as_dataset.
+            supervised_keys=None,
+            # Homepage of the dataset for documentation
+            homepage="https://github.com/google-research-datasets/boolean-questions",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        # TODO(WiCTSV): Downloads the data and defines the splits
+        # dl_manager is a datasets.download.DownloadManager that can be used to
+        # download and extract URLs
+        # urls_to_download = _URLS
+        dl = path
+
+        return [datasets.SplitGenerator(name=datasets.Split.TRAIN, 
+                gen_kwargs={"ex": dl})]
+
+    def _generate_examples(self, ex):
+      """Yields examples."""
+      with open(ex, encoding="utf-8") as exf:
+          for id_, exi in enumerate(exf):
+            example = {}
+            # 'word', 'sentence1', 'sentence2', 'start1', 'start2', 'end1', 'end2', 'idx', 'label'
+            parts = exi.split("\t")
+            idx = parts[0]
+            sent = parts[1]
+            example["sentence"] = sent
+            example["idx"] = idx
+            
+            yield id_, example