Orchestrate content markup and evaluate text analytics services to achieve best results and maintain metadata quality

NEW YORK, BASEL, Switzerlandand Sofia, Bulgaria, September 8, 2022 /PRNewswire/ — Ontotext is pleased to introduce Ontotext Metadata Studio – the latest addition to the company’s portfolio, built on top of GraphDB and Ontotext platform.

Ontotext Metadata Studio enables organizations to get the most out of their content by unlocking new business models or achieving significant cost optimizations by placing their own subject matter experts (SMEs) at the heart of any text analytics task.

A typical problem for organizations is the ability to automate the process of transforming their content into structured knowledge in predictable and manageable ways, while managing changes in the reference data set and accompanying model drift.

With the help of Ontotext Metadata Studio, these organizations can use their business analysts to define semantic objects as specific views, taking developers away from the complexity and particularities of the knowledge graph. This allows them to reference pre-existing domain knowledge modeled in their ontologies and annotate relevant documents following established annotation guidelines for the specific use case.

Ontotext Metadata Studio can be integrated with many text analytics services via GraphDB’s Text Mining plugin, e.g., spaCy, IBM Watson, Amazon Comprehend, Google NLP, Ontotext Tag (powering the Ontotext NOW demonstrator), etc. This allows the evaluation of a service or the suitability of a combination of services for the use case currently being explored against the ground truth data produced by the annotators. This can significantly reduce the time to market (TTM) for new product development, which studies point to as an important factor for product success.

In many fields, such as law and life sciences, for example, the time and availability of an expert in the field is very valuable. Ontotext Metadata Studio helps to use this time in the most efficient way. If the reference dataset resides in GraphDB, users don’t have to worry that it will ever get out of sync with the annotated data. Instead, they can use the time they usually spend on rework for more value-driven efforts.

When working with rich content, it’s always useful to have an overview of the metadata associated with it, so that’s where different reporting dashboards come into play.

A certain text analysis service returns a ton of common nouns, while another struggles to recognize metonymy in context? With Ontotext Metadata Studio, all of this knowledge and more is just a few clicks away!

“If you can’t measure it, you can’t improve it. Ontotext Metadata Studio and its reporting dashboards help measure the outcome of investment in various natural language technologies. The product and its model of common annotation become a central point to evaluate the organizational strategy in natural language and improve the synergy between SMBs and text engineers.” – Vassil Momtchev, CTO of Ontotext

Do you want to know the effectiveness of your investment in NLP technology? Schedule a demo now.

About Ontotext:

Ontotext is a world leader in enterprise knowledge graph technology and semantic database engines. Ontotext uses large knowledge graphs to enable unified data access and cognitive analytics through text mining and data integration across multiple sources. The Ontotext GraphDB Engine and Ontotext Platform powers the critical systems of the largest banks, media, credit bureaus, automotive and aerospace manufacturers.

Ontotext’s technology and solutions are widely used across the value chain of the most knowledge-intensive companies in the financial services, publishing, healthcare, pharmaceutical, manufacturing and public sector industries. . Leveraging AI and cognitive technologies, Ontotext helps companies gain competitive advantage, by connecting the dots of their proprietary knowledge and putting it in the context of global intelligence.

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