Building an annotated textual inference corpus for motion and space

Authors:
Kirk Roberts
Affiliations:
University of Texas at Dallas, Richardson, TX
Venue:
TextInfer '09 Proceedings of the 2009 Workshop on Applied Textual Inference
Year:
2009

Citing 1
Cited 1

Class-Based Construction of a Verb Lexicon

Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence

Towards component-based textual entailment

IWCS '11 Proceedings of the Ninth International Conference on Computational Semantics

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents an approach for building a corpus for the domain of motion and spatial inference using a specific class of verbs. The approach creates a distribution of inference features that maximize the discriminatory power of a system trained on the corpus. The paper addresses the issue of using an existing textual inference system for generating the examples. This enables the corpus annotation method to assert whether more data is necessary.