refactor(README): correct Mecab capitalization and clarify usage inst…

…ructions

README.md

@@ -30,7 +30,7 @@
 
 <!-- Links: -->
 
-`eKoNLPy` is a Korean Natural Language Processing (NLP) Python library specifically designed for economic analysis. It extends the functionality of the `MeCab` tagger from KoNLPy to improve the handling of economic terms, financial institutions, and company names, classifying them as single nouns. Additionally, it incorporates sentiment analysis features to determine the tone of monetary policy statements, such as Hawkish or Dovish.
+`eKoNLPy` is a Korean Natural Language Processing (NLP) Python library specifically designed for economic analysis. It extends the functionality of the `Mecab` tagger from KoNLPy to improve the handling of economic terms, financial institutions, and company names, classifying them as single nouns. Additionally, it incorporates sentiment analysis features to determine the tone of monetary policy statements, such as Hawkish or Dovish.
 
 > **Note**
 >
@@ -40,7 +40,7 @@
 >
 > eKoNLPy is built on the [fugashi](https://github.com/polm/fugashi) and [mecab-ko-dic](https://github.com/LuminosoInsight/mecab-ko-dic) libraries. For more information on using the `Mecab` tagger, please refer to the [fugashi documentation](https://github.com/polm/fugashi). As eKoNLPy no longer relies on the [KoNLPy](https://konlpy.org) library, Java is not required for its use. This makes eKoNLPy compatible with Windows, Linux, and Mac OS, without the need for Java installation. You can also use eKoNLPy on Google Colab.
 
-If you wish to tokenize general Korean text with eKoNLPy, you do not need to install the `KoNLPy` library. Instead, utilize `ekonlpy.mecab.MeCab` as a replacement for `ekonlpy.tag.Mecab`.
+If you wish to tokenize general Korean text with eKoNLPy, you do not need to install the `KoNLPy` library. Instead, utilize the same `ekonlpy.Mecab` class with the `use_original_tagger=True` option.
 
 However, if you plan to use the [Korean Sentiment Analyzer (KSA)](#korean-sentiment-analyzer-ksa), which employs the `Kkma` morpheme analyzer, you will need to install the [KoNLPy](https://konlpy.org) library.
 
@@ -75,7 +75,7 @@ ekonlpy --input "안녕하세요"
 
 > [('안녕', 'NNG'), ('하', 'XSV'), ('세요', 'EP')]
 
-### cf. MeCab POS Tagging (fugashi)
+### cf. Original Mecab POS Tagging (fugashi)
 
 ```python
 from ekonlpy import Mecab