منابع مشابه
Ordinal Common-sense Inference
Humans have the capacity to draw commonsense inferences from natural language: various things that are likely but not certain to hold based on established discourse, and are rarely stated explicitly. We propose an evaluation of automated common-sense inference based on an extension of recognizing textual entailment: predicting ordinal human responses of subjective likelihood of an inference hol...
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Enabling Ambient Intelligence systems to understand the activities that are taking place in a supervised context is a rather complicated task. Moreover, this task cannot be successfully addressed while overlooking the mechanisms (common-sense knowledge and reasoning) that entitle us, as humans beings, to successfully undertake it. This work is based on the premise that Ambient Intelligence syst...
متن کاملNaturalLI: Natural Logic Inference for Common Sense Reasoning
Common-sense reasoning is important for AI applications, both in NLP and many vision and robotics tasks. We propose NaturalLI: a Natural Logic inference system for inferring common sense facts – for instance, that cats have tails or tomatoes are round – from a very large database of known facts. In addition to being able to provide strictly valid derivations, the system is also able to produce ...
متن کاملCommon Sense
I like your columns, but they’re really all just common sense,” a client told me. He didn’t have a software background, and my columns were his first introduction to systematic ways of understanding software projects. To my chagrin, the net effect of a well-written column appeared to be that he thought software engineering was trivial! The idea that good software engineering “is all just common...
متن کاملOn Nonparametric Predictive Inference for Ordinal Data
Nonparametric predictive inference (NPI) is a powerful frequentist statistical framework based only on an exchangeability assumption for future and past observations, made possible by the use of lower and upper probabilities. In this paper, NPI is presented for ordinal data, which are categorical data with an ordering of the categories. The method uses a latent variable representation of the ob...
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ژورنال
عنوان ژورنال: Transactions of the Association for Computational Linguistics
سال: 2017
ISSN: 2307-387X
DOI: 10.1162/tacl_a_00068