“O‘zbekiston Milliy universitetining ilm-fan rivoji va jamiyat taraqqiyotida tutgan o‘rni” mavzusidagi xalqaro ilmiy-amaliy konferensiya, 2023 yil, 12 may 105
that mainly express possession and indicate the relationship between a person and an object. Conjunctions join two phrases,
clauses, or sentences. The auxiliary words in a sentence link the noun to another category. Complements add extra meaning
to words and sentences [4].
A simplified form of this (such Grammar) is usually taught to school-aged children to identify words like
nouns, verbs, adjectives, adverbs , and other parts of speech. Identifying Parts of Speech tags is a much more complex process than simply
comparing Parts of Speech tags. This is because there is no general approach to POS tagging in NLP. One word can belong to
different tags in different sentences based on the context [3; 5].
It is not possible to manually index (record) Parts of Speech tags for the given language corpus. Dictionaries are
constantly adding new words from different languages, and it’s impossible to expand POS tags by themselves manually.
That's why we use a machine-based POS tag.
The main part POS tagging POS tagging itself cannot solve any NLP problems. POS tagging is one of the first steps in the NLP pipeline and is a
prerequisite for simplifying many NLP tasks.
POS tagging algorithms are divided into two separate groups [6,7]:
POS taggers basedon rules.
Stochastic POS taggers. The E.Brill POS tagging method is one of the first and most widely used English POS taggers and uses algorithms based
on rules [8].
POS tagging based on rules Automatic POS tagging is one area of NLP where statistical methods are more effective than rule-based methods.
Conventional rule-based approaches use context information to tag unknown or ambiguous words. POS is performed by
analyzing the linguistic features of a word, the preceding and following words, and other aspects in order to eliminate
ambiguity in tagging. For example, if the preceding word is an adjective, then the word in question is most likely to be a noun.
This information is coded in the form of rules [9].
An example of a grammar rule:
If the indefinite/unknown X word is preceded by a determiner and followed by a noun, mark it as an adjective.
It is very difficult to manually define a set of rules. So, we need some automated method or system is needed to do
this.
