13 Natural Language Processing Examples to Know

Natural language processing is an aspect of artificial intelligence that analyzes data to gain a greater understanding of natural human language. NLP can affect a multitude of digital communications including email, online chats and messaging, social media posts, and more. It’s an intuitive behavior used to convey information and meaning with semantic cues such as words, signs, or images. It’s been said that language is easier to learn and comes more naturally in adolescence because it’s a repeatable, trained behavior—much like walking. That’s why machine learning and artificial intelligence (AI) are gaining attention and momentum, with greater human dependency on computing systems to communicate and perform tasks. And as AI and augmented analytics get more sophisticated, so will Natural Language Processing (NLP).

The more comfortable the service is, the more people are likely to use the app. Uber took advantage of this concept and developed a Facebook Messenger chatbot, thereby creating a new source of revenue for themselves. Natural Language Processing (NLP), Cognitive services and AI an increasingly popular topic in business and, at this point, seems all but necessary for successful companies. NLP holds power to automate support, analyse feedback and enhance customer experiences. Although implementing AI technology might sound intimidating, NLP is a relatively pure form of AI to understand and implement and can propel your business significantly. This article will cover some of the common Natural Language Processing examples in the industry today.

Best Natural Language Processing Packages in R Language

Examples include novels written under a pseudonym, such as JK Rowling’s detective series written under the pen-name Robert Galbraith, or the pseudonymous Italian author Elena Ferrante. In politics we have the anonymous New York Times op-ed I Am Part of the Resistance Inside the Trump Administration, which sparked a witch-hunt for its author, and the open question about who penned Dominic Cummings’ rose garden statement. By counting the one-, two- and three-letter sequences in a text (unigrams, bigrams and trigrams), a language can be identified from a short sequence of a few sentences only. A slightly more sophisticated technique for language identification is to assemble a list of N-grams, which are sequences of characters which have a characteristic frequency in each language. For example, the combination ch is common in English, Dutch, Spanish, German, French, and other languages.

• Natural language processing offers the flexibility for performing large-scale data analytics that could improve the decision-making abilities of businesses.
• Description logics separate the knowledge one wants to represent from the implementation of underlying inference.
• This makes it easier to store information in databases, which have a fixed structure.
• Imagine there’s a spike in negative comments about your brand on social media; sentiment analysis tools would be able to detect this immediately so you can take action before a bigger problem arises.
• NLP first rose to prominence as the backbone of machine translation and is considered one of the most important applications of NLP.

Instead of wasting time navigating large amounts of digital text, teams can quickly locate their desired resources to produce summaries, gather insights and perform other tasks. One of the most challenging and revolutionary things artificial intelligence (AI) can do is speak, write, listen, and understand human language. Natural language processing (NLP) is a form of AI that extracts meaning from human language to make decisions based on the information. This technology is still evolving, but there are already many incredible ways natural language processing is used today.

The Future of Natural Language Generation

Well-formed frame expressions include frame instances and frame statements (FS), where a FS consists of a frame determiner, a variable, and a frame descriptor that uses that variable. A frame descriptor is a frame symbol and variable along with zero or more slot-filler pairs. A slot-filler pair includes a slot symbol (like a role in Description Logic) and a slot filler which can either be the name of an attribute or a frame statement. The language supported only the storing and retrieving of simple frame descriptions without either a universal quantifier or generalized quantifiers.

Stephen Krashen of USC and Tracy Terrell of the University of California, San Diego. One is text classification, which analyzes a piece of open-ended text and categorizes it according to pre-set criteria. For instance, if you have an email coming in, a text classification model could automatically examples of natural language forward that email to the correct department. Then, through grammatical structuring, the words and sentences are rearranged so that they make sense in the given language. You may have seen predictive text pop up in an email you’re drafting on Gmail, or even in a text you’re crafting.

Machine Translation (MT)

Duplicate detection collates content re-published on multiple sites to display a variety of search results. Any time you type while composing a message or a search query, NLP helps you type faster.

Our articles feature information on a wide variety of subjects, written with the help of subject matter experts and researchers who are well-versed in their industries. This allows us to provide articles with interesting, relevant, and accurate information. Certain subsets of AI are used to convert text to image, whereas NLP supports in making sense through text analysis.

NLP limitations

MonkeyLearn can help you build your own natural language processing models that use techniques like keyword extraction and sentiment analysis. Predictive text and its cousin autocorrect have evolved a lot and now we have applications like Grammarly, which rely on natural language processing and machine learning. We also have Gmail’s Smart Compose which finishes your sentences for you as you type. If the sentence within the scope of a lambda variable includes the same variable as one in its argument, then the variables in the argument should be renamed to eliminate the clash. The other special case is when the expression within the scope of a lambda involves what is known as “intensionality”.