A Corpus and Cloze Evaluation for Deeper Understanding of Commonsense Stories
@inproceedings{Mostafazadeh2016ACA, title={A Corpus and Cloze Evaluation for Deeper Understanding of Commonsense Stories}, author={N. Mostafazadeh and Nathanael Chambers and Xiaodong He and Devi Parikh and Dhruv Batra and Lucy Vanderwende and Pushmeet Kohli and James F. Allen}, booktitle={NAACL}, year={2016} }
Representation and learning of commonsense knowledge is one of the foundational problems in the quest to enable deep language understanding. [] Key Method We created a new corpus of 50k five-sentence commonsense stories, ROCStories, to enable this evaluation. This corpus is unique in two ways: (1) it captures a rich set of causal and temporal commonsense relations between daily events, and (2) it is a high quality collection of everyday life stories that can also be used for story generation. Experimental…
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References
SHOWING 1-10 OF 53 REFERENCES
MCTest: A Challenge Dataset for the Open-Domain Machine Comprehension of Text
- Computer ScienceEMNLP
- 2013
MCTest is presented, a freely available set of stories and associated questions intended for research on the machine comprehension of text that requires machines to answer multiple-choice reading comprehension questions about fictional stories, directly tackling the high-level goal of open-domain machine comprehension.
Understanding script-based stories using commonsense reasoning
- Computer ScienceCognitive Systems Research
- 2004
Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks
- Computer ScienceICLR
- 2016
This work argues for the usefulness of a set of proxy tasks that evaluate reading comprehension via question answering, and classify these tasks into skill sets so that researchers can identify (and then rectify) the failings of their systems.
Unsupervised Learning of Narrative Event Chains
- Computer ScienceACL
- 2008
A three step process to learning narrative event chains using unsupervised distributional methods to learn narrative relations between events sharing coreferring arguments and introduces two evaluations: the narrative cloze to evaluate event relatedness, and an order coherence task to evaluate narrative order.
Episodic Logic Meets Little Red Riding Hood: A Comprehensive, Natural Representation for Language Un
- Computer Science
- 1999
A comprehensive framework for narrative understanding based on Episodic Logic (EL), developed and implemented as a semantic representation and commonsense knowledge representation that would serve the full range of interpretive and inferential needs of general NLU.
Learning to Tell Tales: A Data-driven Approach to Story Generation
- Computer ScienceACL
- 2009
This paper creates an end-to-end system that realizes the various components of the generation pipeline stochastically and follows a generate- and-and-rank approach where the space of multiple candidate stories is pruned by considering whether they are plausible, interesting, and coherent.
Searching for Storiness: Story-Generation from a Reader's Perspective
- Computer Science
- 1999
An approach to automatic story-generation based on an intuitive model of the cognitive states and processes within the mind of an imagined reader of the story is described.
CaTeRS: Causal and Temporal Relation Scheme for Semantic Annotation of Event Structures
- Computer ScienceEVENTS@HLT-NAACL
- 2016
A novel semantic annotation framework, called Causal and Temporal Relation Scheme (CaTeRS), which is unique in simultaneously capturing a comprehensive set of temporal and causal relations between events.
Identifying Personal Stories in Millions of Weblog Entries
- Computer ScienceICWSM 2009
- 2009
Efforts to develop a standard corpus for researchers in this area by identifying personal stories in the tens of millions of blog posts in the ICWSM 2009 Spinn3r Dataset are described.
Generating Coherent Event Schemas at Scale
- Computer ScienceEMNLP
- 2013
This work presents a novel approach to inducing open-domain event schemas that overcomes limitations of Chambers and Jurafsky's (2009) schemas and uses cooccurrence statistics of semantically typed relational triples, which it calls Rel-grams (relational n- grams).