Natural Language Processing Building Blocks Language Stemming and Lemmatization Part Of Speech POS Tagging Syntatic and Semantic Analysis Morphological Analysis Named Entity Recognition Lexical Semantics Word Embedding Recurrent Neural Network Long-Short Term Memory Generative Adversarial Network Encoder Decoder NLP project pipeline Spell Checking Algorithm NLP Quiz

Lexical semantics

Lexical semantics is a subfield of natural language processing (NLP) that focuses on understanding the meaning of individual words and their relationships with other words. It deals with the nuances of word meanings, their sense distinctions, and how words interact in various linguistic contexts. Lexical semantics aims to capture the rich and intricate ways words contribute to the overall meaning of sentences and text.

Let's explore lexical semantics with an example:

Example Words: "Bank" (1) and "Bank" (2)

Sentence 1: "I deposited my money in the bank."

Sentence 2: "The boat is by the riverbank."

In these sentences, the word "bank" has two different meanings based on the context. Lexical semantics helps us distinguish between these meanings:

  1. Bank (1): Financial Institution In Sentence 1, "bank" refers to a financial institution where money is deposited. It's a noun associated with finance.

  2. Bank (2): Riverbank In Sentence 2, "bank" refers to the land beside a river. It's a noun associated with geography.

Lexical semantics enables NLP systems to understand these distinctions, even when the same word is used with different meanings in different contexts. The relationships between words based on synonyms, antonyms, hyponyms, and hypernyms are also part of lexical semantics. For example:

  • Synonym: "Buy" and "Purchase"
  • Antonym: "Happy" and "Sad"
  • Hyponym-Hypernym: "Rose" (hyponym) and "Flower" (hypernym)

In NLP applications, lexical semantics plays a critical role:

  • Word sense disambiguation: Determining the correct sense of a word in context.
  • Information retrieval: Improving the accuracy of search queries by considering word meanings.
  • Sentiment analysis: Understanding the sentiment conveyed by words in text.
  • Text generation: Ensuring appropriate word usage for generating coherent and meaningful text.

Lexical semantics aims to capture the intricate interplay between words and their meanings in context, contributing to the overall comprehension and effective processing of natural language.

Lexical semantics


Enroll Now

  • Python Programming
  • Machine Learning