In Artificial Intelligence, Sequence Tagging is a sort of pattern recognition task that includes the algorithmic task of a categorical tag to every individual from a grouping of observed values. It consists of various sequence labeling tasks: Part-of-speech (POS) tagging, Named Entity Recognition (NER), and Chunking.

POS-labeling gives a grammatical feature name to each word in a sentence; Named Entity Recognition requires recognizing named elements, similar to individual or association names; chunking targets distinguishing syntactic constituents inside a sentence, similar to the noun or verb phrase.

Here, we will cover the details of datasets used in Sequence Tagging. Further, we will execute these datasets using Tensorflow  and Pytorch  library.

#part of speech #pytorch #tensorflow