Update README.md

README Structure in titles.

README.md

@@ -1,11 +1,11 @@
-# How to use
+# 1. How to use
 
 How to load this dataset directly with the datasets library:
 
 `>>> from datasets import load_dataset`   
 `>>> dataset = load_dataset("mammut-corpus-venezuela")`  
 
-# Dataset Summary
+# 2. Dataset Summary
 
 **mammut-corpus-venezuela** is a dataset for Spanish language modeling. This dataset comprises a large number of Venezuelan and Latin-American Spanish texts, manually selected and collected in 2021. The data was collected by a process of web scraping from different portals, downloading of Telegram group chats' history, and selecting of Venezuelan and Latin-American Spanish corpus available online. The texts come from Venezuelan Spanish speakers, subtitlers, journalists, politicians, doctors, writers, and online sellers. Social biases may be present, and a percentage of the texts may be fake or contain misleading or offensive language.
 
@@ -13,29 +13,28 @@ Each record in the dataset contains the author of the text (anonymized for conve
 
 The dataset counts with a train split and a test split.
 
-# Supported Tasks and Leaderboards
+# 3. Supported Tasks and Leaderboards
 
 This dataset can be used for language modeling.
 
-# Languages
+# 4. Languages
 
 The dataset contains Venezuelan and Latin-American Spanish.
 
-# Dataset Structure
+# 5. Dataset Structure
 
-## Data Instances
+## 5.1 Data Instances
 
 An example from the dataset:
-{
-    "AUTHOR":“author in title”,
-    “TITLE”:“Luis Alberto Buttó: Hecho en socialismo”
-    "SENTENCE":“Históricamente, siempre fue así.”,
-    "DATE":“2021-07-04 07:18:46.918253”,    
-    "SOURCE":"la patilla",
-    “TOKENS”:“4”
-    “TYPE”:“opinion/news”
-}
-
+  
+  
+    "AUTHOR":"author in title",     
+    "TITLE":"Luis Alberto Buttó: Hecho en socialismo",         
+    "SENTENCE":"Históricamente, siempre fue así.",
+    "DATE":"2021-07-04 07:18:46.918253",      
+    "SOURCE":"la patilla",      
+    "TOKENS":"4",      
+    "TYPE":"opinion/news",   
 
 
 The average word token count are provided below:
@@ -46,7 +45,7 @@ Train
 Test
 4,876,739
 
-## Data Fields
+## 5.2 Data Fields
 
 The data have several fields:
 AUTHOR: author of the text. It is anonymized for conversation authors.
@@ -57,12 +56,12 @@ TITLE: title of the text from which SENTENCE originates.
 TOKENS: number of tokens (excluding punctuation marks) of SENTENCE.
 TYPE: linguistic register of the text.
 
-## Data Splits
+## 5.3 Data Splits
 
 Size of downloaded dataset files:
 Size of the generated dataset:
 Total amount of disk used:
-The mammut-corpus-ve dataset has 2 splits: train and test. Below are the statistics:
+The mammut-corpus-venezuela dataset has 2 splits: train and test. Below are the statistics:
 
 
 Dataset Split
@@ -72,15 +71,15 @@ Train
 Test
 157,011
 
-# Dataset Creation
+# 6. Dataset Creation
 
-## Curation Rationale
+## 6.1 Curation Rationale
 
-The purpose of the mammut-corpus-ve dataset is language modeling. It can be used for pre-training a model from scratch or for fine-tuning on another pre-trained model.
+The purpose of the mammut-corpus-venezuela dataset is language modeling. It can be used for pre-training a model from scratch or for fine-tuning on another pre-trained model.
 
-## Source Data
+## 6.2 Source Data
 
-### Initial Data Collection and Normalization
+### 6.2.1 Initial Data Collection and Normalization
 
 The data consists of opinion articles and text messages. It was collected by a process of web scraping from different portals, downloading of Telegram group chats’ history and selecting of Venezuelan and Latin-American Spanish corpus available online.
 
@@ -88,55 +87,55 @@ The text from the web scraping process was separated in sentences and was automa
 
 An arrow parquet file was created.
 
-Text sources: El Estímulo (website), cinco8 (website), csm_1990 (oral speaking corpus), “El atajo más largo” (blog), El Pitazo (website), La Patilla (website), Venezuelan movies subtitles, Preseea Mérida (oral speaking corpus), Prodavinci (website), Runrunes (website), and Telegram group chats.
+Text sources: El Estímulo (website), cinco8 (website), csm_1990 (oral speaking corpus), "El atajo más largo" (blog), El Pitazo (website), La Patilla (website), Venezuelan movies subtitles, Preseea Mérida (oral speaking corpus), Prodavinci (website), Runrunes (website), and Telegram group chats.
 
-### Who are the source language producers?
+### 6.2.2 Who are the source language producers?
 
 The texts come from Venezuelan Spanish speakers, subtitlers, journalists, politicians, doctors, writers, and online sellers.
 
-## Annotations
+## 6.3 Annotations
 
-### Annotation process
+### 6.3.1 Annotation process
 
 At the moment the dataset does not contain any additional annotations.
 
-### Who are the annotators?
+### 6.3.2 Who are the annotators?
 
 Not applicable.
 
-## Personal and Sensitive Information
+## 6.4 Personal and Sensitive Information
 
 The data is partially anonymized. Also, there are messages from Telegram selling chats, some percentage of these messages may be fake or contain misleading or offensive language.
 
-# Considerations for Using the Data
+# 7. Considerations for Using the Data
 
-## Social Impact of Dataset
+## 7. 1Social Impact of Dataset
 
 The purpose of this dataset is to help the development of language modeling models (pre-training or fine-tuning) in Venezuelan Spanish.
 
-## Discussion of Biases
+## 7.2 Discussion of Biases
 
 Most of the content comes from political, economical and sociological opinion articles. Social biases may be present.
 
-## Other Known Limitations
+## 7.3 Other Known Limitations
 (If applicable, description of the other limitations in the data.)
 
 Not applicable.
 
-# Additional Information
+# 8. Additional Information
 
-## Dataset Curators
+## 8.1 Dataset Curators
 
 The data was originally collected by Lino Urdaneta and Miguel Riveros from Mammut.io.
 
-## Licensing Information
+## 8.2 Licensing Information
 
 Not applicable.
 
-## Citation Information
+## 8.3 Citation Information
 
 Not applicable.
 
-## Contributions
+## 8.4 Contributions
 
 Not applicable.