In this task, you will be presented with a context from an academic paper and a question separated with a 
. You have to answer the question based on the context.

In case of polysemous words, only the first word sense (usually the most common) is taken into account. 
 Question: How do they handle polysemous words in their entity library?
only the first word sense (usually the most common) is taken into account

word embedding, input encoder, alignment, aggregation, and prediction 
 Question: what is the architecture of the baseline model?
word embedding, input encoder, alignment, aggregation, and prediction.

Figure FIGREF9 illustrates the overall architecture of the proposed Attentional Encoder Network (AEN), which mainly consists of an embedding layer, an attentional encoder layer, a target-specific attention layer, and an output layer. Embedding layer has two types: GloVe embedding and BERT embedding. Accordingly, the models are named AEN-GloVe and AEN-BERT. 
 Question: How is their model different from BERT?

overall architecture of the proposed Attentional Encoder Network (AEN), which mainly consists of an embedding layer, an attentional encoder layer, a target-specific attention layer, and an output layer.