Japanese ner

flair/datasets/__init__.py

@@ -21,6 +21,7 @@
 from .sequence_labeling import EUROPARL_NER_GERMAN
 from .sequence_labeling import GERMEVAL_14
 from .sequence_labeling import INSPEC
+from .sequence_labeling import JAPANESE_NER
 from .sequence_labeling import LER_GERMAN
 from .sequence_labeling import MIT_MOVIE_NER_SIMPLE
 from .sequence_labeling import MIT_MOVIE_NER_COMPLEX

flair/datasets/sequence_labeling.py

@@ -666,6 +666,84 @@ def __init__(
             **corpusargs,
         )
 
+class JAPANESE_NER(ColumnCorpus):
+    def __init__(
+            self,
+            base_path: Union[str, Path] = None,
+            tag_to_bioes: str = "ner",
+            in_memory: bool = True,
+            **corpusargs,
+    ):
+        """
+        Initialize the Hironsan/IOB2 corpus for Japanese. The first time you call this constructor it will automatically
+        download the dataset.
+        :param base_path: Default is None, meaning that corpus gets auto-downloaded and loaded. You can override this
+        to point to a different folder but typically this should not be necessary.
+        :param tag_to_bioes: NER by default.
+        :param in_memory: If True, keeps dataset in memory giving speedups in training.
+        """
+        if type(base_path) == str:
+            base_path: Path = Path(base_path)
+
+        # column format
+        columns = {0: 'text', 1: 'ner'}
+
+        # this dataset name
+        dataset_name = self.__class__.__name__.lower()
+
+        # default dataset folder is the cache root
+        if not base_path:
+            base_path = Path(flair.cache_root) / "datasets"
+        data_folder = base_path / dataset_name
+
+        # download data from github if necessary (hironsan.txt, ja.wikipedia.conll)
+        IOB2_path = "https://raw.githubusercontent.com/Hironsan/IOB2Corpus/master/"
+
+        # download files if not present locally
+        cached_path(f"{IOB2_path}hironsan.txt", data_folder / 'raw')
+        cached_path(f"{IOB2_path}ja.wikipedia.conll", data_folder / 'raw')
+
+        # we need to modify the original files by adding new lines after after the end of each sentence
+        train_data_file = data_folder / 'train.txt'
+        if not train_data_file.is_file():
+            self.__prepare_jap_wikinews_corpus(data_folder / 'raw' / "hironsan.txt", data_folder / 'train.txt')
+            self.__prepare_jap_wikipedia_corpus(data_folder / 'raw' / "ja.wikipedia.conll", data_folder / 'train.txt')
+
+        super(JAPANESE_NER, self).__init__(
+            data_folder,
+            columns,
+            train_file='train.txt',
+            tag_to_bioes=tag_to_bioes,
+            in_memory=in_memory,
+            **corpusargs,
+        )
+
+    @staticmethod
+    def __prepare_jap_wikipedia_corpus(file_in: Union[str, Path], file_out: Union[str, Path]):
+        with open(file_in, 'r') as f:
+            lines = f.readlines()
+        with open(file_out, 'a') as f:
+            for line in lines:
+                if (line[0] == "。"):
+                    f.write(line)
+                    f.write("\n")
+                elif (line[0] == "\n"):
+                    continue
+                else:
+                    f.write(line)
+
+    @staticmethod
+    def __prepare_jap_wikinews_corpus(file_in: Union[str, Path], file_out: Union[str, Path]):
+        with open(file_in, 'r') as f:
+            lines = f.readlines()
+        with open(file_out, 'a') as f:
+            for line in lines:
+                sp_line = line.split("\t")
+                if (sp_line[0] == "\n"):
+                    f.write("\n")
+                else:
+                    f.write(sp_line[0] + "\t" + sp_line[len(sp_line) - 1])
+
 class STACKOVERFLOW_NER(ColumnCorpus):
     def __init__(
             self,
@@ -3737,4 +3815,4 @@ def _fill_curr_comment(self, fix_flag: bool):
             except StopIteration: # When the end of the comments.tsv file is reached
                 self.curr_row = next_row
                 self.stop_iter = True if not fix_flag else False
-                break
+                break

resources/docs/TUTORIAL_6_CORPUS.md

@@ -173,6 +173,7 @@ data the first time you call the corresponding constructor ID. The following dat
 | 'CONLL_03_SPANISH' | Spanish  |  [CoNLL-03](https://www.clips.uantwerpen.be/conll2002/ner/) 4-class NER |
 | 'DANE' | Danish | [DaNE dataset](https://github.com/alexandrainst/danlp/blob/master/docs/datasets.md#danish-dependency-treebank) | 
 | 'EUROPARL_NER_GERMAN' | German | [German Europarl dataset](https://nlpado.de/~sebastian/software/ner_german.shtml) NER in German EU parliament speeches | 
+| 'JAPANESE_NER' | Japanese | [https://github.com/Hironsan/IOB2Corpus] Japanese NER dataset automatically generated from Wikipedia |
 | 'LER_GERMAN' | German | [Legal Entity Recognition](https://github.com/elenanereiss/Legal-Entity-Recognition) NER in German Legal Documents | 
 | 'MIT_MOVIE_NER_SIMPLE' | English  |  [NER dataset for movie reviews](https://groups.csail.mit.edu/sls/downloads/movie/) - simple NER |
 | 'MIT_MOVIE_NER_COMPLEX' | English  |  [NER dataset for movie reviews](https://groups.csail.mit.edu/sls/downloads/movie/) - complex NER |