Automated Reasoning from Polarized Parse Trees

EasyChair Preprint 225

Abstract

This paper contributes to symbolic inference from text, including naturally occurring text. The idea is to take sentences in a framework like CCG, and then run a polarizing algorithm like the one in Hu and Moss 2018 to determine inferential polarity markings of all the constituents. From this, it is just a small step to obtain an inference engine which is both simple to describe and implement and at the same time is surprisingly powerful. We have implemented the basic inference step. This paper is work in progress, also going into detail on our projected next steps. The overall goal is to have a working symbolic inference system which covers "in-practice" inference and also is correct and efficient.

Keyphrases: CCG, inference, monotonicity, polarity

@booklet{EasyChair:225,
  author    = {Hai Hu and Thomas Icard and Larry Moss},
  title     = {Automated Reasoning from Polarized Parse Trees},
  doi       = {10.29007/69wv},
  howpublished = {EasyChair Preprint 225},
  year      = {EasyChair, 2018}}