Quantum mechanics

Commonsense knowledge

Discriminative model

Commonsense reasoning

Knowledge representation and reasoning

Event (particle physics)

Economics

Computer science

Visual arts

Cognitive science

Natural language processing

Physics

Utterance

Generative grammar

Psychology

Task (project management)

Cicero

Management

Inference

SemEval

Artificial intelligence

This paper addresses the problem of dialogue reasoning with contextualized commonsense inference. We curate CICERO, a dataset of dyadic conversations with five types of utterance-level reasoning-based inferences: cause, subsequent event, prerequisite, motivation, and emotional reaction. The dataset contains 53,105 of such inferences from 5,672 dialogues. We use this dataset to solve relevant generative and discriminative tasks: generation of cause and subsequent event; generation of prerequisite, motivation, and listener's emotional reaction; and selection of plausible alternatives. Our results ascertain the value of such dialogue-centric commonsense knowledge datasets. It is our hope that CICERO will open new research avenues into commonsense-based dialogue reasoning.

CICERO: A Dataset for Contextualized Commonsense Inference in Dialogues