Project Debater APIs: Decomposing the AI Grand Challenge

TL;DR

This paper introduces Project Debater APIs, a suite of AI services for argument analysis, summarization, and key point extraction, enabling practical applications in debate and opinion analysis.

Contribution

It presents a comprehensive set of APIs for complex debate-related AI tasks, including a novel Key Point Analysis technology for extracting main points from text collections.

Findings

APIs demonstrate strong performance in argument mining and summarization

Key Point Analysis effectively identifies main points in diverse texts

APIs enable practical applications in debate and opinion analysis

Abstract

Project Debater was revealed in 2019 as the first AI system that can debate human experts on complex topics. Engaging in a live debate requires a diverse set of skills, and Project Debater has been developed accordingly as a collection of components, each designed to perform a specific subtask. Project Debater APIs provide access to many of these capabilities, as well as to more recently developed ones. This diverse set of web services, publicly available for academic use, includes core NLP services, argument mining and analysis capabilities, and higher-level services for content summarization. We describe these APIs and their performance, and demonstrate how they can be used for building practical solutions. In particular, we will focus on Key Point Analysis, a novel technology that identifies the main points and their prevalence in a collection of texts such as survey responses and user reviews.