This is one of the oldest approaches to POS tagging. However, how can one assign the correct tag to the words? POS Tagging Approaches These sentences use the word “This” in various contexts. Similarly, many words in the English dictionary has multiple possible POS tags. In the sentences, “Book the flight” and “I like to read books”, we see that book can act as a Verb or Noun. Similar to most NLP problems, POS tagging suffers from ambiguity. Some examples from Penn Treebank: Part Of Speech The Penn TreeBank Tag Set is most used for the English language.
However, in the first example, it acts as a Verb but takes the role of a Noun in the latter.Īlthough we are using the generic names of the tags, in real practice, we refer a tagset for tags. Notice how the word Book appears in both sentences. Similarly, “I like to read book” is represented as. A POS tagger considers surrounding words while assigning a tag.įor example, the previous sentence, “Book the flight”, will become a list of each word with its corresponding POS tag –. Since this task involves considering the sentence structure, it cannot be done at the Lexical level. It converts a sentence into a list of words with their tags. POS tagging refers to the automatic assignment of a tag to words in a given sentence. This sentence contains Noun (Book), Determinant (the) and a Verb (flight). A sentence consists of words with a sensible Part of Speech structure. This category provides more details about the word and its meaning in the context.
The major POS tags are Nouns, Verbs, Adjectives, Adverbs. Part of Speech is the classification of words based on their role in the sentence. To achieve this, the given sentence structure is compared with the common language rules. A sentence is syntactically correct when the Parts of Speech of the sentence follow the rules of grammar. As discussed in Stages of Natural Language Processing, Syntax Analysis deals with the arrangement of words to form a structure that makes grammatical sense.
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