We want to design a neural network that segments an English word into preļ¬xes, root, and suļ¬xes using a BIO labelling scheme.
For example, the word āunprepossessingā has the labelling: (āuā, B-pre), (ānā, I-pre), (āpā, B-pre), (ārā, I-pre), (āeā, I-pre), (āpā, B-root), (āoā, I- root), (āsā, I-root), (āsā, I-root), (āeā, I-root), (āsā, I-root), (āsā, I-root), (āiā, B-suf), (ānā, I-suf), (āgā, I-suf). Note that due to the nature of the application, O will not be used.
Fully specify a neural network to solve this problem. Describe:
⢠how the inputs and outputs are encoded
⢠the structure of the network
⢠the loss function used
Describe the network in enough detail that one could implement it using PyTorch. You may describe it in terms of common abstractions (e.g. āuse a standard LSTM cell of such-and-such sizeā) if thatās useful.
You do not need to deļ¬ne batch sizes, learning rates, and other optimization parameters.
You may assume that the input contains only lowercase Latin letters.
Please work independently. You should turn in a document (.txt, .md, or .pdf) answering the above.
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