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Natural Language Processing Homework Help

Natural Language Processing (NLP) is an AI method that uses a natural language such as English to communicate with intelligent systems. A natural language must be processed for the intelligent system like a robot to perform the task as per the instructions. This field strives to make computers perform useful tasks by interpreting the languages humans use. An NLP system can have two inputs and outputs:

  • Speech
  • Written text

Programming Homework Help has a talented team of online natural language processing programmers and developers. For close to a decade, our professionals have successfully helped thousands of students in countries such as the USA, UK, Australia, etc. By availing of our natural language processing homework help service, you too can put yourself in a better position to ace your homework in this area.

Components of NLP

Natural language processing consists of the following components

Natural language understanding (NLU)

NLU involves the following tasks:

  • Making useful representations from the mapping of a given input in a natural language
  • A thorough analysis of the different aspects of the language.

Natural Language Generation (NLG)

NLG focuses on producing meaningful phrases and sentences in the form of a natural language from some internal representation. Here are some of the tasks involved in this process:

Text Planning

This is the retrieval of relevant content from a knowledge base

Sentence Planning

This is the process of choosing the required words, forming meaningful phrases, and setting the tone of the sentence

Text Realization

Text realization involves mapping a sentence plan into the sentence structure.

The experts associated with us possess extensive knowledge of these two components. They can craft excellent solutions for homework related to NLU or NLG. If you are still in doubt, opt for our natural language processing homework help and see what you have been missing.

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Natural languages boast of an extremely rich form and structure. Also, they are very ambiguous. Here are some of the levels of ambiguity in Natural Languages:

  •  Lexical ambiguity

This type of ambiguity is at a very primitive level such as the word level. For example, should we treat the word board as a noun or a verb?

  • Syntax-level ambiguity

We can parse a sentence in different ways. For example, the sentence, “he lifted the beetle with a red cap” can also be written in the following ways: Did he use a red cap to lift the beetle? Or “The beetle was lifted using his red cap.”

  • Referential ambiguity

In natural languages, we can refer to something using a pronoun. For example. Henry ran the 100m race. He said, “I am tired.” – Exactly who is tired?

Lastly, an NLU can have different meanings and also mean the same thing. Are you asking yourself “where can I pay for a natural language processing project?” Do not go anywhere else. Our experts are capable of solving any natural language processing homework.

Terminologies used in Natural Language Processing

  • Phonology – It is the organization of sounds systematically
  • Morphology - This is the construction of words from primitive meaningful units
  • Morpheme – This is the primitive unit of meaning in a language
  • Syntax- It is the arrangement of words to make a coherent syntax. A syntax can also mean determining the structural role of words in the sentence and in phrases.
  • Semantics –It involves combining words to form meaningful phrases and sentences. Sematic simply deals with the meanings of words.
  • Pragmatics – It deals with the interpretation of the sentence i.e. understanding sentences in different situations.
  • Discourse – How a preceding sentence can affect the interpretation of the next sentence.
  • World knowledge – This is the general knowledge about the world

If you are not well-versed in the basics of natural language processing, you are bound to face challenges with your homework. Luckily for you, Programminghomeworkhelp.com is the number one provider of natural language processing project help. You can contact us at any time if you need assistance with your NLP homework help.

Natural Language Processing Homework Help Professionals 

Our NLP homework help is acquainted with all the major steps involved in NLP. The five main steps in NLP are:

1. Lexical Analysis

This is the process of identifying and analyzing the structure of words. The collection of words and phrases in a language is known as a lexicon. In the lexical analysis, we divide a whole chunk of texts into Paragraphs, sentences, and words.

2. Syntactic analysis

This process involves analyzing words in the sentence to check for grammar and arranging words in a manner that shows their relationship. For example, an English syntactic analyzer will reject a sentence such as "The school goes to a boy."

3. Semantic analysis

It involves drawing the dictionary meaning or the exact meaning from a text. Semantic analysis involves checking for how meaningful a text is. This is done by mapping syntactic structures and objects in the task domain. For example, the sentence “a cold sunny day” will be rejected by the semantic analyzer.

4. Discourse integration

The previous sentence will determine the meaning of any sentence. The first sentence brings about the meaning of the immediate or succeeding sentence.

5. Pragmatic Analysis

A pragmatic analysis involves re-interpreting what was said to what is actually meant. This type of analysis requires real-world knowledge

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Syntactic analysis implementation aspects

Researchers over time have developed several algorithms for syntactic analysis. In this article, we are going to discuss the following two methods:

  • Context-free grammar
  • Top-down parser

Context-free grammar

This type of grammar consists of rules with a single symbol on the left-hand side of the rewrite rules. For example, let us create a context-free grammar to parse this sentence "A bird eats grains."

  • Articles (DET) – a, an, and the
  • Nouns – bird, grains
  • Noun phrases (NP) – Article + Noun, Article + Adjective + Noun
  • Verbs – Eats, eating, ate
  • Verb Phrases (VP) – NP V, V NP
  • Adjective – Beautiful, colorful, chirping, small

The sentence is broken down into structured parts mentioned above by the parse tree. This helps the computer to easily process and understand it. For a parsing algorithm to construct this parse tree, a set of rewrite rules need to be constructed. These rules describe the tree structures that are legal.

The rules say that you can expand a certain symbol in the tree by the sequence of other symbols. The string combined by a noun phrase followed by a verb phrase is a sentence if there are two string noun phrases and verb phrases.

This is according to the first-order logic rule. The rewrite rules of our sentence are as follows. If you do not understand how the solution was arrived at, you can buy natural language processing homework here. Our experts will provide you with detailed solutions within the shortest time possible.

Sentence = NP VP




DET = a, the

ADJ = Colorful, beautiful

Noun – Bird, grains

Verb – eats, eat, eating

We can create the parse tree as shown in the diagram


Noun Phrase Verb Phrase

DET Noun verb Noun Phrase 

DET Noun

A bird eats grains

We have several other examples available for free on our website. You can also avail of our help with natural language processing homework if, for one reason or another, you cannot complete your homework on time.

Merits of the context tree grammar

  • It is a widely used method because it is simple in style.


  • This style is not precise, For example, according to the parser, a sentence like “The grain eats the bird” is syntactically correct, even though the sentence is incorrect. The parser will take it as a correct sentence.
  • Multiple sets of grammar should be prepared to bring out high precision. Also, completely different sets of rules for parsing singular and plural variations, passive sentences, and many more may be required. This can lead to the creation of huge sets of unimaginable rules.

The Top-Down Parser

This parser attempts to rewrite a sentence into a sequence of terminal symbols. These symbols should match the classes of the words in the input sentence until it is made up entirely of terminal symbols.

The symbols are then checked with the input sentence to see if they matched. In case there is no match, the process is repeated but with a different set of rules. The process should be repeated until a particular rule that describes the structure of the sentence is found.

Merits of the top-down parser symbol

  • It is easy to use and implement


  • The top-down parser is inefficient. The entire search process has to be repeated if an error occurs.
  • It is slow and takes a lot of time

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