How to Answer: What is syntactic analysis and semantic analysis in the field of Natural Language Processing?
Advice and answer examples written specifically for an Advanced Machine Learning Engineer - Python job interview.
2. What is syntactic analysis and semantic analysis in the field of Natural Language Processing?
This question shows the developer's understanding of machine learning analytics.
NLP or Natural Language Processing is the technique used to analyze text in order to determine key metrics such as the sentiment of the text.
NLP applies two techniques to help the computer "understand" text:
1. Syntactic Analysis
2. Semantic Analysis
Syntactic Analysis analyses text using grammatical rules to identify sentence structure, how the words are organized, and how the words relate to each other.
Syntactic Analysis can be broken down into 4 main sub-tasks:
1. Tokenization: This process consists of breaking up the text into smaller components called tokens. This makes the text easier to analyze.
2. Part of Speech: PoS tagging or Part of Speech tagging labels the verbs, adjectives, adverbs, and nouns within the text. This provides context and helps to understand the meaning of the text.
3. Lemmatization and Stemming: This process consists of reducing inflected words to their base form. This makes the text easier to analyze.
4. Stop-word removal: This removes the frequently occurring words that don't add any semantic value. Some examples of words removed are: I, they, have, like, etc
Semantic Analysis
Semantic Analysis focuses on capturing the meaning of the text. There are two main steps involved in semantic analysis:
1. Word sense disambiguation - this is the process where the algorithm attempts to identify the context that the given word is being used.
2. Relationship extraction - this process attempts to understand how entities relate to each other within a given text. For example, it determines how a place or person may relate to each other within a given text.
Both syntactic and semantic techniques are used in NLP algorithms to help the algorithm "understand" text.
Written by Ryan Brown on July 6th, 2021