Update README.md

README.md

@@ -42,13 +42,14 @@ tags:
 - knowledge-graph
 pretty_name: CoNLL-2025 NER Dataset
 size_categories:
-- 100K<n<1M
+- 10K<n<100K
 task_categories:
 - token-classification
 ---
 
 ![Banner](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgQCDz3ZEB5_uZjHkWhalOavBmWdYYZUlDOfCl8S70_SrQgcg946ydgmtmNaQmfO0knYV4GCAbWveZruwBgUyqKYcVrKY2R7Ief3ZxVIoYhllw-W8LKPA06IYlGQASl_ahxeW8PM5MVGXpht17YBqwAKo5suSrQA4EB4EY6cnS65Bp1hLKwJXAyZN8kycY/s16000/1.jpg)
 
+
 # 🌍 CoNLL 2025 NER Dataset — Unlocking Entity Recognition in Text
 
 [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
@@ -60,9 +61,7 @@ task_categories:
 
 This **6.38 MB** dataset is lightweight, developer-friendly, and ideal for advancing **natural language processing (NLP)**, **information extraction**, and **text mining**. Whether you're building chatbots 🤖, analyzing news articles 📰, or structuring data for AI 🛠️, this dataset is your key to unlocking structured insights from text.
 
-> **Note**: The dataset link (`https://huggingface.co/datasets/boltuix/conll2025-ner`) is a placeholder. Please replace it with the correct Hugging Face or repository URL once available.
-
-**[Download Now](#download-instructions)** 🚀
+**[Download Now](https://huggingface.co/datasets/boltuix/conll2025-ner)** 🚀
 
 ## Table of Contents 📋
 - [What is NER?](#what-is-ner) ❓
@@ -137,6 +136,9 @@ NER powers applications by extracting structured data from unstructured text, en
 
 ---
 
+
+![Banner](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEihnG3bV5G-X9KgB-HKAykQNMtjCAePR-_VhZHoqeEqPMkglnMFfq6ASvRva0mCSau8-HrsCSGeOantUTUtr9CMkryfz0kny7WDswq0-xEbE6dFZnEBaMtxxJTEuTdNHvsD2A4p04kBAPbGt4AZcDGV2wlnsFrAeJV86I0FsO71pW8cuSz8abQgyiJU2-M/s16000/2.jpg)
+
 ## NER Tags & Purposes 🏷️
 
 The dataset uses the **BIO tagging scheme**:
@@ -148,51 +150,52 @@ Below is a table of the 36 NER tags with their purposes and emojis for visual ap
 
 | Tag Name        | Purpose                                                                 | Emoji |
 |------------------|--------------------------------------------------------------------------|--------|
-| B-CARDINAL       | Beginning of a cardinal number (e.g., "1000")                           | 🔢     |
-| B-DATE           | Beginning of a date (e.g., "January")                                   | 🗓️     |
-| B-EVENT          | Beginning of an event (e.g., "Olympics")                                | 🎉     |
-| B-FAC            | Beginning of a facility (e.g., "Eiffel Tower")                          | 🏛️     |
-| B-GPE            | Beginning of a geopolitical entity (e.g., "Tokyo")                      | 🌍     |
-| B-LANGUAGE       | Beginning of a language (e.g., "Spanish")                               | 🗣️     |
-| B-LAW            | Beginning of a law or legal document (e.g., "Constitution")             | 📜     |
-| B-LOC            | Beginning of a non-GPE location (e.g., "Pacific Ocean")                 | 🗺️     |
-| B-MONEY          | Beginning of a monetary value (e.g., "$100")                            | 💸     |
-| B-NORP           | Beginning of a nationality/religious/political group (e.g., "Democrat") | 🏳️     |
-| B-ORDINAL        | Beginning of an ordinal number (e.g., "first")                          | 🥇     |
-| B-ORG            | Beginning of an organization (e.g., "Microsoft")                        | 🏢     |
-| B-PERCENT        | Beginning of a percentage (e.g., "50%")                                 | 📊     |
-| B-PERSON         | Beginning of a person’s name (e.g., "Elon Musk")                        | 👤     |
-| B-PRODUCT        | Beginning of a product (e.g., "iPhone")                                 | 📱     |
-| B-QUANTITY       | Beginning of a quantity (e.g., "two liters")                            | ⚖️     |
-| B-TIME           | Beginning of a time (e.g., "noon")                                      | ⏰     |
-| B-WORK_OF_ART    | Beginning of a work of art (e.g., "Mona Lisa")                          | 🎨     |
-| I-CARDINAL       | Inside of a cardinal number (e.g., "000" in "1000")                     | 🔢     |
-| I-DATE           | Inside of a date (e.g., "2025" in "January 2025")                       | 🗓️     |
-| I-EVENT          | Inside of an event name                                                 | 🎉     |
-| I-FAC            | Inside of a facility name                                               | 🏛️     |
-| I-GPE            | Inside of a geopolitical entity                                         | 🌍     |
-| I-LANGUAGE       | Inside of a language name                                               | 🗣️     |
-| I-LAW            | Inside of a legal document title                                        | 📜     |
-| I-LOC            | Inside of a location                                                    | 🗺️     |
-| I-MONEY          | Inside of a monetary value                                              | 💸     |
-| I-NORP           | Inside of a NORP entity                                                 | 🏳️     |
-| I-ORDINAL        | Inside of an ordinal number                                             | 🥇     |
-| I-ORG            | Inside of an organization name                                          | 🏢     |
-| I-PERCENT        | Inside of a percentage                                                  | 📊     |
-| I-PERSON         | Inside of a person’s name                                               | 👤     |
-| I-PRODUCT        | Inside of a product name                                                | 📱     |
-| I-QUANTITY       | Inside of a quantity                                                    | ⚖️     |
-| I-TIME           | Inside of a time phrase                                                 | ⏰     |
-| I-WORK_OF_ART    | Inside of a work of art title                                           | 🎨     |
-| O                | Outside of any named entity (e.g., "the", "is")                         | 🚫     |
+| B-CARDINAL        | Beginning of a cardinal number (e.g., "1000")                           | 🔢     |
+| B-DATE            | Beginning of a date (e.g., "January")                                   | 🗓️     |
+| B-EVENT           | Beginning of an event (e.g., "Olympics")                                | 🎉     |
+| B-FAC             | Beginning of a facility (e.g., "Eiffel Tower")                          | 🏛️     |
+| B-GPE             | Beginning of a geopolitical entity (e.g., "Tokyo")                      | 🌍     |
+| B-LANGUAGE        | Beginning of a language (e.g., "Spanish")                               | 🗣️     |
+| B-LAW             | Beginning of a law or legal document (e.g., "Constitution")             | 📜     |
+| B-LOC             | Beginning of a non-GPE location (e.g., "Pacific Ocean")                 | 🗺️     |
+| B-MONEY           | Beginning of a monetary value (e.g., "$100")                            | 💸     |
+| B-NORP            | Beginning of a nationality/religious/political group (e.g., "Democrat") | 🏳️     |
+| B-ORDINAL         | Beginning of an ordinal number (e.g., "first")                          | 🥇     |
+| B-ORG             | Beginning of an organization (e.g., "Microsoft")                        | 🏢     |
+| B-PERCENT         | Beginning of a percentage (e.g., "50%")                                 | 📊     |
+| B-PERSON          | Beginning of a person’s name (e.g., "Elon Musk")                        | 👤     |
+| B-PRODUCT         | Beginning of a product (e.g., "iPhone")                                 | 📱     |
+| B-QUANTITY        | Beginning of a quantity (e.g., "two liters")                            | ⚖️     |
+| B-TIME            | Beginning of a time (e.g., "noon")                                      | ⏰     |
+| B-WORK_OF_ART     | Beginning of a work of art (e.g., "Mona Lisa")                          | 🎨     |
+| I-CARDINAL        | Inside of a cardinal number (e.g., "000" in "1000")                     | 🔢     |
+| I-DATE            | Inside of a date (e.g., "2025" in "January 2025")                       | 🗓️     |
+| I-EVENT           | Inside of an event name                                                 | 🎉     |
+| I-FAC             | Inside of a facility name                                               | 🏛️     |
+| I-GPE             | Inside of a geopolitical entity                                         | 🌍     |
+| I-LANGUAGE        | Inside of a language name                                               | 🗣️     |
+| I-LAW             | Inside of a legal document title                                        | 📜     |
+| I-LOC             | Inside of a location                                                    | 🗺️     |
+| I-MONEY           | Inside of a monetary value                                              | 💸     |
+| I-NORP            | Inside of a NORP entity                                                 | 🏳️     |
+| I-ORDINAL         | Inside of an ordinal number                                             | 🥇     |
+| I-ORG             | Inside of an organization name                                          | 🏢     |
+| I-PERCENT         | Inside of a percentage                                                  | 📊     |
+| I-PERSON          | Inside of a person’s name                                               | 👤     |
+| I-PRODUCT         | Inside of a product name                                                | 📱     |
+| I-QUANTITY        | Inside of a quantity                                                    | ⚖️     |
+| I-TIME            | Inside of a time phrase                                                 | ⏰     |
+| I-WORK_OF_ART     | Inside of a work of art title                                           | 🎨     |
+| O                 | Outside of any named entity (e.g., "the", "is")                         | 🚫     |
+
+---
 
 **Example**  
-For `"Microsoft opened in Tokyo on January 2025"`:  
+For `"Microsoft opened in Tokyo on January 2025"`:
+
 - **Tokens**: `["Microsoft", "opened", "in", "Tokyo", "on", "January", "2025"]`  
 - **Tags**: `[B-ORG, O, O, B-GPE, O, B-DATE, I-DATE]`
 
----
-
 ## Installation 🛠️
 
 Install dependencies to work with the dataset:
@@ -209,12 +212,10 @@ pip install datasets pandas pyarrow
 ## Download Instructions 📥
 
 ### Direct Download
-- Access the dataset from the official repository (URL TBD).  
+- Grab the dataset from the [Hugging Face repository](https://huggingface.co/datasets/boltuix/conll2025-ner) 📂.
 - Load it with pandas 🐼, Hugging Face `datasets` 🤗, or your preferred tool.
 
-> **Note**: The dataset link is currently unavailable. Replace `[https://huggingface.co/datasets/boltuix/conll2025-ner]` with the correct URL once available.
-
-**[Start Exploring Dataset](#quickstart-dive-in)** 🚀
+**[Start Exploring Dataset](https://huggingface.co/datasets/boltuix/conll2025-ner)** 🚀
 
 ---
 
@@ -347,7 +348,7 @@ Tokenize further with `transformers` 🤗 or `NeuroNER` for model training.
 
 ## Visualizing NER Tags 📉
 
-The chart below visualizes the estimated distribution of NER tags in the dataset. Since exact tag counts are unavailable, the data is illustrative. Use the provided Python script to compute actual counts and generate a precise visualization.
+Visualize the NER tag distribution to understand entity prevalence. Since exact counts are unavailable, the chart below uses estimated data for demonstration. Replace with actual counts after analysis.
 
 <chartjs>
 {
@@ -368,9 +369,6 @@ The chart below visualizes the estimated distribution of NER tags in the dataset
         "display": true,
         "text": "CoNLL 2025 NER: Tag Distribution (Estimated)",
         "font": { "size": 16 }
-      },
-      "legend": {
-        "display": false
       }
     },
     "scales": {
@@ -387,7 +385,7 @@ The chart below visualizes the estimated distribution of NER tags in the dataset
 }
 </chartjs>
 
-To compute and visualize actual tag counts:
+To compute actual counts:
 
 ```python
 import pandas as pd
@@ -401,21 +399,16 @@ df = pd.read_parquet("conll2025_ner.parquet")
 all_tags = [tag for tags in df["ner_tags"] for tag in tags]
 tag_counts = Counter(all_tags)
 
-# Prepare data for plotting
-labels = list(tag_counts.keys())
-values = list(tag_counts.values())
-
 # Plot
 plt.figure(figsize=(12, 7))
-plt.bar(labels, values, color="#36A2EB")
-plt.title("CoNLL 2025 NER: Tag Distribution", fontsize=16)
-plt.xlabel("NER Tag", fontsize=12)
-plt.ylabel("Count", fontsize=12)
-plt.xticks(rotation=45, ha="right", fontsize=10)
+plt.bar(tag_counts.keys(), tag_counts.values(), color="#36A2EB")
+plt.title("CoNLL 2025 NER: Tag Distribution")
+plt.xlabel("NER Tag")
+plt.ylabel("Count")
+plt.xticks(rotation=45, ha="right")
 plt.grid(axis="y", linestyle="--", alpha=0.7)
 plt.tight_layout()
 plt.savefig("ner_tag_distribution.png")
-plt.show()
 ```
 
 ---
@@ -468,8 +461,8 @@ The *CoNLL 2025 NER Dataset* excels with its **broad entity coverage**, **compac
 ## Community & Support 🌐
 
 Join the NER community:
-- 📍 Explore the dataset page (URL TBD) 🌟
-- 🛠️ Report issues or contribute at the repository (URL TBD) 🔧
+- 📍 Explore the [Hugging Face dataset page](https://huggingface.co/datasets/boltuix/conll2025-ner) 🌟
+- 🛠️ Report issues or contribute at the [repository](https://huggingface.co/datasets/boltuix/conll2025-ner) 🔧
 - 💬 Discuss on Hugging Face forums or submit pull requests 🗣️
 - 📚 Learn more via [Hugging Face Datasets docs](https://huggingface.co/docs/datasets) 📖
 
@@ -481,4 +474,4 @@ Your feedback shapes the *CoNLL 2025 NER Dataset*! 😊
 
 **May 28, 2025** — Released with 36 NER tags, enhanced use cases, and visualizations.
 
-**[Unlock Entity Insights Now](#download-instructions)** 🚀
+**[Unlock Entity Insights Now](https://huggingface.co/datasets/boltuix/conll2025-ner)** 🚀