Explore The Google Cloud Natural Language API for NLP Work

From conversational chatbots on sales pages to the AI assistants on our smartphones, natural language processing (NLP) is revolutionizing the way we humans interact with machines. Google Cloud Natural Language API exposes a suite of powerful, out-of-the-box NLP features that businesses can leverage within their applications without having to create their own training data sets. In this article we’ll take a closer look at NLP, Google Cloud Natural Language API, and what it can do for your business.

What is natural language processing?

Natural language processing (NLP) is the use of a computer program to process speech and language data. NLP is related to computational linguistics and artificial intelligence. It is used in applications such as online assistants, automatic question-answering systems, machine translation, speech recognition, speech synthesis, and information retrieval. It can be used to intelligently filter comments across social media for spam or add speech-to-text functionality to your apps. It can even be used to authorize bank transactions via voice authentication. These are just a handful of examples of how NLP brings natural language understanding to software applications.

What are the benefits of NLP for your business?

NLP is more than just a technology buzzword, it can bring real value to your business in a myriad of ways. Examples of ways Google Cloud Natural Language API can help your business include:

• Leveraging sentiment analysis within your chat and email clients to track customer satisfaction over time.
• Using entity sentiment analysis to track approval ratings of executives across social media and news.
• Extracting data from text information scraped from the web to assist with market research.
• Analyzing language used by a target market to help craft better marketing messages
• Identifying trends in your industry across social media channels.

What is Google Cloud Natural Language API?

Google Cloud Natural Language API lets you leverage machine learning models pre-trained by Google to perform various NLP tasks, including sentiment analysis, entity extraction, and content classification. The Natural Language API gives businesses access to the same deep learning technologies behind Google Search’s ability to answer specific user questions and the language-understanding system behind Google Assistant. With Natural Language API, you can create your own NLP-powered apps without having to deal with the costs and overhead of storing and managing your own training data sets.

Google Cloud Natural Language API features

Google Cloud Natural Language API boats a number of features that let you make the most of unstructured language data. Like any REST API it gives you the ability to make JSON requests and responses to manipulate plain text. Let's take a look at some of the things you can do with this powerful API.

Sentiment analysis

Read an online product review, and you’ll instantly be able to tell whether that review was positive, neutral, or negative, just from the tone of the customer’s written voice. Sentiment analysis is the NLP analogue of this human ability to judge the tone of a piece of text. Natural Language API measures sentiment with a numerical score which can be positive or negative and a magnitude which measures intensity from 0 to 1. In this way it's possible to quickly determine the general sentiment of a whole body of text.

Entity analysis

When you read an article on the web and come across a public figure or a reference to a historical event, you don’t typically need the author of the text to describe those things to you to understand what is being said because of your familiarity with these popular subjects. Achieving the same level of insight with a computer typically requires large amounts of training data. Natural Language API already has that training data and the built-in capability for entity recognition and entity extraction. Identify entities within documents—including contracts, invoices, and receipts—and apply labels by type such as contact information, organization, location, and products. The API also allows you to quantify the centrality or importance of an entity to the rest of the document by assigning salience scores to entities.

Entity sentiment analysis

Combine sentiment analysis and entity analysis together and you get the ability to determine the sentiment (positive or negative) around specific entities within a body of text. The API identifies entities, assigns them numerical scores and magnitude, and then aggregates these scores into an overall sentiment score. This added granularity can be very powerful. For example, you can programmatically crawl bulk reviews to understand customer opinions around specific products or features, extracting actionable insights for improving them.

Syntax analysis

It goes without saying that if a computer is to understand human speech the way we do, it must be familiar with grammatical rules and know the difference between nouns, verbs, and adjectives. Syntax analysis or syntactic analysis is the branch of linguistics concerned with breaking language into parts. In the context of NLP, that means breaking down text into a series of sentences and tokens (generally words) and tagging them with metadata based on their grammatical function. Syntax analysis takes each word and returns a rich analysis of grammatical information such as whether a word is a noun or a verb, if it’s the subject of a sentence, its case, its tense and even its grammatical mood. By developing a semantic structure of a given token in relation to all other tokens within a text document (using dependency trees), it's possible for a computer to understand sentences and how they work.

Content classification

Google Cloud Natural Language API comes with an easy-to-use text classification model that can classify content into a hierarchy of categories with subcategories. For example, a blog post covering music theory behind Mozart’s Lacrimosa would be classified under the following hierarchy: Arts & Entertainment/Music & Audio/Classical Music. You can find a complete list of built-in content categories here.

Google Cloud Natural Language API vs. Google AutoML Natural Language

While Google Cloud Natural Language API gives you plug-and-play access to NLP features that perform well out of the box, not everyone will be satisfied with cookie cutter models the API provides.

For users with more specialized needs, Google AutoML Natural Language gives you the ability to provide your own training data to create your own custom machine learning models. It’s still a cloud service with all the convenience and perks of a public REST API that works seamlessly with Google Cloud Storage, but with the additional ability to create content classification, entity analysis, and sentiment analysis models that are tailored to your needs. Additionally AutoML offers support for large custom data sets, including 5,000 classification labels, 1 million documents, and 10 MB document size.

The following table breaks down the key differences between Natural Language API and AutoML Natural Language:

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What talent do you need to use NLP in Your business?

The nice thing about Google Cloud Natural Language API is that you don’t need to hire someone with a background in machine learning to use it. A REST API developer experienced making JSON requests is all that’s required to add basic NLP functionality to your apps.

That said, there are definitely advantages to hiring an NLP pro to unlock the full disruptive potential of this technology. Here are some examples of skills you might look for in an NLP engineer:

• Software development
• Working knowledge of NLP
• Experience making JSON requests via REST APIs
• Python development experience
• Data science and analytics
• Google Cloud Platform, Cloud Console, and other cloud services
  

Interested in leveraging Natural Language API in your business? Consider consulting with an NLP engineer on Upwork today.