CANDLE: Decomposing Conditional and Conjunctive Queries for Task-Oriented Dialogue Systems

Abstract

Domain-specific dialogue systems generally determine user intents by relying on sentence level classifiers that mainly focus on single action sentences. Such classifiers are not designed to effectively handle complex queries composed of conditional and sequential clauses that represent multiple actions. We attempt to decompose such queries into smaller single action subqueries that are reasonable for intent classifiers to understand in a dialogue pipeline. We release, CANDLE(Conditional & AND type Expressions), a dataset consisting of 4282 utterances manually tagged with conditional and sequential labels, and demonstrates this decomposition by training two baseline taggers.

References in corpus (4)

• DialoGLUE: A Natural Language Understanding Benchmark for Task-Oriented Dialogue
• Resolving Intent Ambiguities by Retrieving Discriminative Clarifying Questions
• Recognizing and Splitting Conditional Sentences for Automation of Business Processes Management
• Which Linguist Invented the Lightbulb? Presupposition Verification for Question-Answering