Update sent_ids to ids; Update README

README.md

@@ -32,7 +32,7 @@ dataset_info:
   features:
   - name: id
     dtype: string
-  - name: sent_ids
+  - name: ids
     sequence: string
   - name: sentences
     sequence: string
@@ -45,7 +45,7 @@ dataset_info:
       class_label:
         names:
           '0': semantic-continuity
-          '1': semantic-break
+          '1': semantic-shift
   splits:
   - name: train
     num_bytes: 4754764877
@@ -59,4 +59,38 @@ dataset_info:
   download_size: 1569504207
   dataset_size: 5958006898
 ---
-# Dataset Card for Wiki-727K Dataset
+# Dataset Card for Wiki-727K Dataset
+
+Wiki-727K is a large dataset for text segmentation, automatically extracted and labeled from Wikipedia. It is designed as a sentence-level sequence labeling task for identifying semantic or topic shift in documents.
+
+## Dataset Overview
+
+- **Train**: 582k
+- **Validation**: 72k
+- **Test**: 73k
+
+## Features
+
+- **id (string):** Document ID.
+- **ids (sequence of string):** Sentence IDs for each document.
+- **sentences (sequence of string):** Sentences in each document.
+- **titles_mask (sequence of uint8):** Mask indicating if a sentence is a title (optional).
+- **levels (sequence of uint8):** Hierarchical level of each sentence (optional).
+- **labels (sequence of class):** Binary labels: `semantic-continuity` or `semantic-shift`.
+
+## Usage
+
+The dataset can be loaded using the HuggingFace `datasets` library:
+
+```python
+from datasets import load_dataset
+
+titled_dataset = load_dataset('saeedabc/wiki727k', num_proc=8, trust_remote_code=True)
+
+untitled_dataset = load_dataset('saeedabc/wiki727k', drop_titles=True, num_proc=8, trust_remote_code=True)
+
+```
+
+## Dataset Details
+
+- **Homepage**: [Wiki-727K GitHub](https://github.com/koomri/text-segmentation)

preprocess_util.py

@@ -25,7 +25,7 @@ def _parse_article(text: str, id: str, drop_titles: bool = False, prepend_title_
 
     ### Parse the sections into sentences
     doc_id = id
-    doc_sent_ids = []
+    doc_ids = []
     doc_sentences = []
     doc_levels = []
     doc_titles_mask = []
@@ -58,8 +58,8 @@ def _parse_article(text: str, id: str, drop_titles: bool = False, prepend_title_
 
         # 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'{sec_idx}')
+            # doc_ids.append(f'{doc_id}_sec{sec_idx}_title')
+            doc_ids.append(f'{sec_idx}')
             doc_sentences.append(title_str)
             doc_titles_mask.append(1)
             doc_levels.append(level)
@@ -67,7 +67,7 @@ def _parse_article(text: str, id: str, drop_titles: bool = False, prepend_title_
 
         # Add the sentences
         for sent_idx, sent in enumerate(sentences):
-            doc_sent_ids.append(f'{sec_idx}_{sent_idx}')
+            doc_ids.append(f'{sec_idx}_{sent_idx}')
             doc_sentences.append(sent)
             doc_titles_mask.append(0)
             doc_levels.append(level)
@@ -75,7 +75,7 @@ def _parse_article(text: str, id: str, drop_titles: bool = False, prepend_title_
 
     out = {
         'id': doc_id, 
-        'sent_ids': doc_sent_ids, 
+        'ids': doc_ids, 
         'sentences': doc_sentences, 
         'titles_mask': doc_titles_mask, 
         'levels': doc_levels, 

wiki727k.py

@@ -18,7 +18,7 @@ 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)
+    >>> dataset = load_dataset('saeedabc/wiki727k', num_proc=8, trust_remote_code=True)
 """
 
 
@@ -121,7 +121,7 @@ class Wiki727k(datasets.GeneratorBasedBuilder):
         features = datasets.Features(
             {
                 "id": datasets.Value("string"),         # document id --> [doc0, doc1, ...]
-                "sent_ids": datasets.Sequence(          # document sentence ids --> [[doc0_sent0, doc0_sent1, ...], ...]
+                "ids": datasets.Sequence(               # document sentence ids --> [[doc0_sent0, doc0_sent1, ...], ...]
                     datasets.Value("string")
                 ),
                 "sentences": datasets.Sequence(
@@ -134,7 +134,7 @@ class Wiki727k(datasets.GeneratorBasedBuilder):
                     datasets.Value("uint8")
                 ),
                 "labels": datasets.Sequence(
-                    datasets.ClassLabel(num_classes=2, names=['semantic-continuity', 'semantic-break'])
+                    datasets.ClassLabel(num_classes=2, names=['semantic-continuity', 'semantic-shift'])
                 ),
             }
         )