Improving accuracy in LUIS with patterns

Since LUIS became generally available last year several new features have been added to make it easier to create and train robust natural language models for your applications. If you’ve used LUIS in the past, hopefully you’re pretty familiar with intents and entities, and how to train your model to use them by using utterances. In this post, we’ll go over….

Contributing to LUIS with Microsoft/Recognizers-Text – Part 3

Welcome to the final article of this series! Hopefully if you’re reading this, you know that this is article is part of an ongoing guide on how to extend the Microsoft/Recognizers-Text project to support new languages. This exciting new open-source project released by the LUIS team provides robust recognition and resolution for unit entities commonly expressed in everyday language. In our previous….

Contributing to LUIS with Microsoft/Recognizers-Text – Part 2

Previously in part 1, we gave an updated overview of the Recognizers-Text library which is used to power many of the prebuilt entities in LUIS. We provided a step-by-step guide to creating your own language specific definitions for both the .NET and Javascript versions of the project in YAML, and generating the platform-specific definitions using the tools already provided by the project.….

Contributing to LUIS with Microsoft/Recognizers-Text – Part 1

Last year, we announced a new recognizer library by the LUIS team, which provides robust recognition and resolution for common units expressed in everyday human interaction. Since then, the code base has changed considerably, and the library has been expanded to include more pre-built entities including date-time, currency, dimensions, and age. Today, we’ll take a look into the code base of Recognizers-Text,….

LUIS quick start with list entities

Since LUIS was first previewed, it’s certainly changed a lot! General availability for LUIS was announced back in December last month, with an expanded limit to 500 intents and 100 entities per application, support for new regions, availability in 7 new regions (South Central US, East US, West US 2, East Asia, North Europe, Brazil South, Australia East), as well as increased….

Natural Language Understanding Services – a comparison

At this years’ SIGdial conference, researchers from the Technical University of Munich, department of informatics published the following paper – Evaluating Natural Language Understanding Services for Conversational Question Answering Systems Currently, there is no established way to evaluate different NLU (Natural Language Understanding) services. One of the primary goals of the research team was to define a way to compare these….

New Date Entities in LUIS

New date time entities in LUIS Previously we announced new number recognition in LUIS, but this was just the beginning! There are many more features coming to LUIS and the Bot Framework, of which today we are excited to announce that LUIS now has new pre-built date time entities which not only provide more accurate date-time recognition, but also contextual recognition for date….

New Number Recognizers in LUIS

The LUIS Team has developed a new recognizer library that provides greater accuracy in identifying numerics, and also allows the developer to provide context to which those numerics refer to. Luis now incorporates a new library for number recognition in Microsoft.Recognizers.Text.Numbers, which implements a solution using Regular Expressions. Regular Expressions (Regex) are a well established and proven method used to identify….