Add two untitled config; Update README

README.md

@@ -1,3 +1,120 @@
 ---
-license: mit
+annotations_creators:
+- machine-generated
+language_creators:
+- found
+language:
+- en
+license:
+- mit
+multilinguality:
+- monolingual
+size_categories:
+- 100K<n<1M
+source_datasets:
+- original
+task_categories:
+- text-classification
+task_ids:
+- text-segmentation
+- topic-shift-detection
+- semantic-chunking
+pretty_name: Wiki-727K
+tags:
+- text segmentation
+- document segmentation
+- topic segmentation
+- topic shift detection
+- semantic chunking
+- chunking
+- nlp
+- wikipedia
+dataset_info:
+- config_name: default
+  features:
+  - name: id
+    dtype: string
+  - name: sent_ids
+    sequence: string
+  - name: sentences
+    sequence: string
+  - name: levels
+    sequence: uint8
+  - name: titles_mask
+    sequence: uint8
+  - name: labels
+    sequence:
+      class_label:
+        names:
+          '0': neg
+          '1': pos
+  splits:
+  - name: train
+    num_bytes: 5260132718
+    num_examples: 582160
+  - name: validation
+    num_bytes: 658387335
+    num_examples: 72354
+  - name: test
+    num_bytes: 672558301
+    num_examples: 73232
+  download_size: 1569504207
+  dataset_size: 6591078354
+- config_name: titled
+  features:
+  - name: id
+    dtype: string
+  - name: sent_ids
+    sequence: string
+  - name: sentences
+    sequence: string
+  - name: titles_mask
+    sequence: uint8
+  - name: levels
+    sequence: uint8
+  - name: labels
+    sequence:
+      class_label:
+        names:
+          '0': neg
+          '1': pos
+  splits:
+  - name: train
+    num_bytes: 4754764877
+    num_examples: 582160
+  - name: validation
+    num_bytes: 595209014
+    num_examples: 72354
+  - name: test
+    num_bytes: 608033007
+    num_examples: 73232
+  download_size: 1569504207
+  dataset_size: 5958006898
+- config_name: untitled
+  features:
+  - name: id
+    dtype: string
+  - name: sent_ids
+    sequence: string
+  - name: sentences
+    sequence: string
+  - name: labels
+    sequence:
+      class_label:
+        names:
+          '0': neg
+          '1': pos
+  splits:
+  - name: train
+    num_bytes: 4565834833
+    num_examples: 582160
+  - name: validation
+    num_bytes: 571636978
+    num_examples: 72354
+  - name: test
+    num_bytes: 583978545
+    num_examples: 73232
+  download_size: 1569504207
+  dataset_size: 5721450356
 ---
+# Dataset Card for Wiki-727K Dataset

preprocess_util.py

@@ -58,29 +58,34 @@ def _parse_article(text: str, id: str, drop_titles: bool = False, hier_titles: b
 
         # Add the title as a single sentence
         if not drop_titles and non_empty(title_str):
-            doc_sent_ids.append(f'{doc_id}_sec{sec_idx}_title')
+            # doc_sent_ids.append(f'{doc_id}_sec{sec_idx}_title')
+            doc_sent_ids.append(f'{sec_idx}')
             doc_sentences.append(title_str)
-            doc_levels.append(level)
             doc_titles_mask.append(1)
+            doc_levels.append(level)
             doc_labels.append(0)
 
         # Add the sentences
         for sent_idx, sent in enumerate(sentences):
-            doc_sent_ids.append(f'{doc_id}_sec{sec_idx}_sent{sent_idx}')
+            doc_sent_ids.append(f'{sec_idx}_{sent_idx}')
             doc_sentences.append(sent)
-            doc_levels.append(level)
             doc_titles_mask.append(0)
+            doc_levels.append(level)
             doc_labels.append(1 if sent_idx == len(sentences) - 1 else 0)
 
     out = {
         'id': doc_id, 
         'sent_ids': doc_sent_ids, 
         'sentences': doc_sentences, 
-        'levels': doc_levels, 
         'titles_mask': doc_titles_mask, 
+        'levels': doc_levels, 
         'labels': doc_labels
     }
     
+    if drop_titles:
+        out.pop('titles_mask')
+        out.pop('levels')
+    
     return out
 
 

wiki727k.py

@@ -17,8 +17,8 @@ Wiki-727k dataset loading script responsible for downloading and extracting raw
 See https://github.com/koomri/text-segmentation for more information.
 
 Usage:
-    from datasets import load_dataset
-    dataset = load_dataset('saeedabc/wiki727k', trust_remote_code=True, num_proc=8)
+    >>> from datasets import load_dataset
+    >>> dataset = load_dataset('saeedabc/wiki727k', trust_remote_code=True, num_proc=8)
 """
 
 
@@ -76,7 +76,7 @@ _URL = "https://www.dropbox.com/sh/k3jh0fjbyr0gw0a/AACKW_gsxUf282QqrfH3yD10a/wik
 class Wiki727k(datasets.GeneratorBasedBuilder):
     """Wiki727k dataset formulated as a sentence-level sequence labelling task for text segmentation."""
 
-    VERSION = datasets.Version("1.1.0")
+    VERSION = datasets.Version("1.0.0")
 
     # This is an example of a dataset with multiple configurations.
     # If you don't want/need to define several sub-sets in your dataset,
@@ -88,11 +88,12 @@ class Wiki727k(datasets.GeneratorBasedBuilder):
 
     # You will be able to load one or the other configurations in the following list with
     # data = datasets.load_dataset('name', 'config1')
-    # BUILDER_CONFIGS = [
-    #     datasets.BuilderConfig(name="default", version=VERSION, description=""),
-    # ]
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="titled", version=VERSION, description="Article titles are kept alongside regular sentences in `sentences` attribute, but differentiated with positive values (i.e. 1 as opposed to 0) in `titles_mask` attribute. (Default configuration with all attributes)"),
+        datasets.BuilderConfig(name="untitled", version=VERSION, description="Article titles are droped, therefore `sentences` attribute consists of only regular sentences, and `titles_mask` attribute is not present. (Alternative configuration ready for Document Segmentation task)"),
+    ]
 
-    # DEFAULT_CONFIG_NAME = "default"  # It's not mandatory to have a default configuration. Just use one if it make sense.
+    DEFAULT_CONFIG_NAME = "titled"  # It's not mandatory to have a default configuration. Just use one if it make sense.
 
     def _info(self):
         # TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset
@@ -107,10 +108,10 @@ class Wiki727k(datasets.GeneratorBasedBuilder):
                 "sentences": datasets.Sequence(
                     datasets.Value("string")
                 ),
-                "levels": datasets.Sequence(
+                "titles_mask": datasets.Sequence(
                     datasets.Value("uint8")
                 ),
-                "titles_mask": datasets.Sequence(
+                "levels": datasets.Sequence(
                     datasets.Value("uint8")
                 ),
                 "labels": datasets.Sequence(
@@ -118,6 +119,10 @@ class Wiki727k(datasets.GeneratorBasedBuilder):
                 ),
             }
         )
+        
+        if self.config.name == "untitled":
+            features.pop("titles_mask")
+            features.pop("levels")
 
         return datasets.DatasetInfo(
             # This is the description that will appear on the datasets page.
@@ -164,8 +169,9 @@ class Wiki727k(datasets.GeneratorBasedBuilder):
     # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
     def _generate_examples(self, filepaths: list, split: str):            
         for filepath in filepaths:
-            kwargs = dict(drop_titles=False, hier_titles=False)
-            for doc in parse_split_files(filepath, **kwargs):
+            for doc in parse_split_files(filepath, 
+                                         drop_titles=(self.config.name == "untitled"), 
+                                         hier_titles=False):
                 yield doc['id'], doc
                 
                 
@@ -175,4 +181,5 @@ if __name__ == '__main__':
     # Make sure to set num_proc to more than 1 to speed up the loading process
     # Sharding is already enabled by the loading script
     dataset = load_dataset('saeedabc/wiki727k', trust_remote_code=True, num_proc=8)
-    print(dataset)
+    print(dataset)
+    print(dataset['train'][0])