mlsanityData to 14 Oct 2026

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

arXiv 2107.03884 ↗First posted 8 Jul 2021cs.CL cs.AIcited by 1

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Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 13 of its 34 references that are in the map. First posted on arXiv 8 Jul 2021.

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13 of 34 references.

References · 13

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  9. 2021Which Linguist Invented the Lightbulb? Presupposition Verification for Question-Answeringcited by 41
  10. 2020ConjNLI: Natural Language Inference Over Conjunctive Sentencescited by 27
  11. 2020Resolving Intent Ambiguities by Retrieving Discriminative Clarifying Questionscited by 16
  12. 2018Sentences with Gapping: Parsing and Reconstructing Elided Predicatescited by 4
1 more
  1. 2021Recognizing and Splitting Conditional Sentences for Automation of Business Processes Managementcited by 1

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Citing papers per year: 2021: 1.

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  1. 2021NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentationcited by 73