This dataset $($FinancialPhraseBank$)$ contains the sentiments for financial news headlines from the perspective of a retail investor. The dataset contains two columns, "Sentiment" and "News Headline". The sentiment can be negative or positive. Perform sentiment analysis on the data. Please perform the following steps:

Language Detection

Named Entity Recognition

Extract top key phrases

Extract Uni$-$Gram features $($retain only $500$ columns$)$ by performing pre$-$processing

Split the data into train and test $(70$:$30)$

Build classification models $($at least $2$ different model$)$

Interpret model results