A Deep Learning Approach towards Cross-Lingual Tweet Tagging

Named Entity Recognition (NER) is important in analysing the context of a statement and also the sentiments associated with it. Although Twitter Data is noisy, it is valuable due to the amount of information it can provide. Therefore, NER for Twitter Data is necessary. Our model aims to extract the named entities from tweets using a Recurrent Neural Network Core. Long Short Term Memory (LSTM) was used to learn long term dependencies in our supervised learning model. The sequence-to-sequence architecture was used in the implementation of our supervised learning model.