Add task categories, language, and tags to dataset card metadata

This PR improves the dataset card for `NeedleChain` by adding relevant metadata:
- `task_categories: question-answering`
- `language: en`
- `tags: llm-evaluation, long-context, reasoning, benchmark`

These additions enhance the dataset's discoverability and proper categorization on the Hugging Face Hub.

README.md

@@ -73,9 +73,17 @@ configs:
     path: data/k100-*
   - split: k200
     path: data/k200-*
+task_categories:
+- question-answering
+language:
+- en
+tags:
+- llm-evaluation
+- long-context
+- reasoning
+- benchmark
 ---
 
-
 ## NeedleChain: Measuring Intact Long-Context Reasoning Capability of Large Language Models
 
 <p align="center">
@@ -89,10 +97,9 @@ configs:
   <img src="needlechain.png" width="500"/>
 </p>
 
-NeedleChain is a benchmark designed to evaluate LLMs' intact long-context understanding. 
+NeedleChain is a benchmark designed to evaluate LLMs' intact long-context understanding.
 Every provided context consists of query-relevant information, requiring a comprehensive understanding to answer the given query.
 
 ---
 
-For manual creation of NeedleChain datasets, please refer to our official github repository.
-
+For manual creation of NeedleChain datasets, please refer to our official github repository.