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I understand the implicit value of part-of-speech tagging and have seen mentions about its use in parsing, text-to-speech conversion, etc.
Could you tell me how is the output of a PoS tagger formated ? Also, could you explain how is such an output used by other tasks/parts of an NLP system?
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POS tagging finds applications in Named Entity Recognition (NER), sentiment analysis, question answering, and word sense disambiguation. We will look at an example of word sense disambiguation in the following code. In the sentences I left the room and Left of the room , the word left conveys different meanings.
POS Tagging in NLTK is a process to mark up the words in text format for a particular part of a speech based on its definition and context. Some NLTK POS tagging examples are: CC, CD, EX, JJ, MD, NNP, PDT, PRP$, TO, etc. POS tagger is used to assign grammatical information of each word of the sentence.
What is Part-of-speech (POS) tagging ? It is a process of converting a sentence to forms – list of words, list of tuples (where each tuple is having a form (word, tag)). The tag in case of is a part-of-speech tag, and signifies whether the word is a noun, adjective, verb, and so on.
It is generally called POS tagging. In simple words, we can say that POS tagging is a task of labelling each word in a sentence with its appropriate part of speech. We already know that parts of speech include nouns, verb, adverbs, adjectives, pronouns, conjunction and their sub-categories.
Part of Speech (PoS) Tagging. Tagging is a kind of classification that may be defined as the automatic assignment of description to the tokens.
Here the descriptor is called tag, which may represent one of the part-of-speech, semantic information and so on. Now, if we talk about Part-of-Speech (PoS) tagging, then it may be defined as the process of assigning one of the parts of speech to the given word. It is generally called POS tagging.
POS tagging is an important part of NLP because it works as the prerequisite for further NLP analysis as follows − All the taggers reside in NLTK’s nltk.tag package. The base class of these taggers is TaggerI, means all the taggers inherit from this class.
One purpose of PoS tagging is to disambiguate homonyms. For instance, take this sentence :
I fish a fish
The same sentence in french would be Je pêche un poisson. Without tagging, fish would be translated the same way in both case, which would lead to a wrong traduction. However, after PoS tagging, the sentence would be
I_PRON fish_VERB a_DET fish_NOUN
From a computer point of view, both words are now distinct. This wat, they can be processed much more efficiently (in our example, fish_VERB will be translated to pêche and fish_NOUN to poisson).
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Basically, the goal of a POS tagger is to assign linguistic (mostly grammatical) information to sub-sentential units. Such units are called tokens and, most of the time, correspond to words and symbols (e.g. punctuation).
Considering the format of the output, it doesn't really matter as long as you get a sequence of token/tag pairs. Some POS taggers allow you to specify some specific output format, others use XML or CSV/TSV, and so on.
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