Natural Language Interface for Knowledge Graphs? Welcome to Sherlock™.
By David Hughes / Principal Graph Consultant
May 4, 2023
Reading Time: 5 minutes
In this article, we’ll explore the potential of a natural language interface to your knowledge graph (KG) and how it can help democratize insights, making data-driven decision-making accessible to everyone in your organization. Everyone has seen the power of natural language interfaces on large language models (LLMs), imagine what would be possible with the same capabilities on any data store of information. With the power of a natural language interface on your KG (or any data store), your organization can unlock data epiphanies that drive growth, innovation, and success.
Introduction to Sherlock™ & What is Natural Language Interface?
For companies, data is often referred to as the new oil, or the new gold. Companies do their best to collect it, analyze it, and use it to make informed decisions that drive business growth and innovation. However, for many organizations, the real challenge lies in turning raw data into actionable insights. This is where knowledge graphs come in – they provide a uniquely powerful approach to organizing and connecting disparate data points to uncover hidden relationships and patterns. But up until now, this data has often been limited to a core few who know how to interact with this kind of data and data store, and who are able to draw out critical new insights.
But to answer the question, “What is a natural language interface?”, see here:
What if you could take it a step further and actually democratize the insights to be gained from knowledge graphs, by making them accessible to everyone in your organization through normal, natural language questions typed or spoken by your users?
That’s where a natural language interface comes in, providing a user-friendly way for everyone to tap into the power of your knowledge graph and unlock epiphanies that can drive business success. For this reason, Graphable has developed a natural language interface named Sherlock™. It is your organization’s interface to data democratization, powerful insights from buried data, and your AI partner in discovery (launched in alpha in March 2023, we invite you try this new open beta).
Understanding Natural Language User Interface Queries
At the heart of a natural language interface to your knowledge graph is natural language processing (NLP), a branch of artificial intelligence that enables machines to understand and interpret human language (also see these articles Natural Language is Structured Data and What is Text Analytics?). NLP involves analyzing and interpreting large amounts of natural language data to derive insights and meaning. Recent advances in NLP have been powered by the development of large language models (LLMs) that can analyze vast amounts of language data and generate accurate predictions about the meaning behind words and phrases.
Existing Natural Language User Interface Examples
While this technology is relatively new in the context of knowledge graphs, it has already been widely adopted in other industries, such as healthcare, finance, and customer service. In healthcare, for instance, NLP is used to analyze medical records and detect patterns that can help physicians make more accurate diagnoses.
In finance, NLP is used to monitor social media and news articles to gain insights into market sentiment and make better investment decisions. In customer service, NLP is used to provide chatbots and virtual assistants with the ability to understand and respond to customer inquiries, providing faster and more accurate support. Now, it is available for any industry on any database, for non-technical users to start leveraging the power of your data even more.
How Sherlock™ Works
A natural language interface to your knowledge graph enables users to extract insights from complex data using simple, natural language queries. Sherlock™ queries a graph database using natural language queries by leveraging the semantic structure and topology of the knowledge graph. By using a large language model (LLM) to interpret the natural language request of a user, Sherlock™ can understand the meaning behind the words and identify the relationships between different data points.
This enables Sherlock™ to identify the most relevant data and return it to the user in a way that is easy to understand and to take action in time to impact the business. The results are returned to the user in an interpretable format, enabling them to refine their query and further explore the data in a user-friendly and intuitive way. By combining the power of a knowledge graph with natural language processing, this innovative product empowers users to uncover insights that might have been hidden in the data otherwise.
Sherlock™ App Capabilities
Sherlock™ is a powerful new service that offers a range of capabilities designed to make data exploration on a data store simple and intuitive. The service enables users to create natural language queries that can be validated and explained to ensure accuracy. Additionally, the system offers query inspection features, which enable users to explore the underlying structure of the graph database and identify potential relationships between different data points. Another key feature of the service is query composition, which allows users to build subsequent queries based on the results of their initial query.
Overall, Sherlock™ offers a range of key features that make it an invaluable tool for exploring complex data sets. For example, it can be used in healthcare to identify correlations between different medical conditions or to monitor patient outcomes over time. In finance, the system can be used to analyze market trends and identify opportunities for investment. And in customer service, it can be used to identify trends in customer behavior and improve the overall customer experience.
With its powerful combination of natural language processing and knowledge graph technology, the natural language interface is poised to revolutionize the way we interact with data and unlock new insights that were previously inaccessible.
Want to see Sherlock™ in action? Check out this 1 Minute Overview Video.
This article release marks the beta release of Sherlock™. Graphable has ongoing development efforts to create/integrate new features over time. For example, soon the system will have the ability to query the results of a query, which will make it easy to explore the data in even greater detail.
Benefits of Sherlock™
The natural language interface to your knowledge graph offers a range of benefits for businesses and individuals alike. One of the key benefits of this innovative service is that it enables non-technical users to access complex and even previously inaccessible data stores and data sets in a user-friendly and intuitive way. This uniquely advances companies along the analytics maturity model journey, while actually lowering the bar for non-technical users.
This means that individuals across an organization can use the service to extract insights and drive decision-making, regardless of their technical expertise, using simple natural language questions. Another benefit of the service is that it can save time and increase efficiency by enabling users to quickly and easily explore data sets and identify correlations and patterns that might have been missed otherwise.
By automating the process of data exploration and analysis using simple natural language questions from non-technical humans, the service frees up valuable time and resources, enabling organizations to focus on more strategic initiatives. Ultimately, the natural language interface to your knowledge graph provides a powerful new capability for unlocking insights and driving business success, empowering organizations to make informed decisions and stay ahead of the competition.
In conclusion, the natural language interface to your knowledge graph is a game-changing service that can help open the way for companies to leverage non-technical employees to unlock new insights that were previously much less accessible, by simply giving them the opportunity to interact with complex data stores through natural language questions. By combining the power of a knowledge graph with natural language processing, this innovative product Sherlock™ empowers users to extract valuable insights from complex data sets in a user-friendly and intuitive way- simple natural language questions.
If you’re interested in learning more about how this natural language interface to your knowledge graph can benefit your organization, don’t hesitate to reach out to Graphable, the company that offers this cutting-edge service. Our team of experts is standing by to help you explore the potential of this powerful new product and unlock new opportunities for growth and innovation.
So why wait? Contact us today and discover the power of Sherlock™ or sign up at sherlock.graphable.ai. After signing up be sure to check out our detailed overview video.
Graphable delivers insightful graph database (e.g. Neo4j consulting) / machine learning (ml) / natural language processing (nlp) projects as well as graph and Domo consulting for BI/analytics, with measurable impact. We are known for operating ethically, communicating well, and delivering on-time. With hundreds of successful projects across most industries, we thrive in the most challenging data integration and data science contexts, driving analytics success.
Still learning? Check out a few of our introductory articles to learn more:
- What is a Graph Database?
- What is Neo4j (Graph Database)?
- What Is Domo (Analytics)?
- What is Hume (GraphAware)?
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