Upload _logicnlg.py

_logicnlg.py

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+#!/usr/bin/env python3
+
+"""
+The script used to load the dataset from the original source.
+"""
+
+import json
+import datasets
+import glob
+import os
+
+_CITATION = """\
+@inproceedings{chen2020logical,
+  title={Logical Natural Language Generation from Open-Domain Tables},
+  author={Chen, Wenhu and Chen, Jianshu and Su, Yu and Chen, Zhiyu and Wang, William Yang},
+  booktitle={Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics},
+  pages={7929--7942},
+  year={2020}
+}
+"""
+_DESCRIPTION = """\
+LogicNLG is a dataset for natural language generation from open-domain tables. 
+LogicNLG is based on TabFact (Chen et al., 2019), which is a table-based fact-checking dataset with rich logical inferences in the annotated statements.
+"""
+
+_URL = "https://github.com/wenhuchen/LogicNLG"
+_LICENSE = "MIT"
+
+class LogicNLG(datasets.GeneratorBasedBuilder):
+    VERSION = "1.0.0"
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features({
+                'table': datasets.Value(dtype='large_string'),
+                "ref": datasets.Value(dtype='string'),
+                "linked_columns": datasets.Value(dtype='string'),
+                "title": datasets.Value(dtype='string'),
+                "template": datasets.Value(dtype='string'),
+                "table_id": datasets.Value(dtype='string'),
+            }),
+            supervised_keys=None,
+            homepage="https://wenhuchen.github.io/logicnlg.github.io/",
+            citation=_CITATION,
+            license=_LICENSE,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": "data", "split" : "train"}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": "data", "split" : "dev"}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": "data", "split" : "test"}),
+        ]
+
+    def _generate_examples(self, filepath, split):
+        filename = split if split != "dev" else "val"
+        data = []
+
+        with open(os.path.join(filepath, f"{filename}_lm.json")) as f:
+            j = json.load(f)
+
+        for i, (table_id, examples) in enumerate(j.items()):
+            table = []
+            with open(os.path.join(filepath, "all_csv", table_id)) as f:
+                for line in f.readlines():
+                    table.append(line.rstrip("\n").split("#"))
+
+            for example in examples:
+                data.append({
+                    "table": table,
+                    "ref": example[0],
+                    "linked_columns": example[1],
+                    "title": example[2],
+                    "template": example[3],
+                    "table_id": table_id,
+                })
+        for example_idx, entry in enumerate(data):
+            yield example_idx, {key: str(value) for key, value in entry.items()}
+
+
+if __name__ == '__main__':
+    dataset = datasets.load_dataset(__file__)
+    dataset.push_to_hub("kasnerz/logicnlg")