Paper: Exploring Word Order Universals: a Probabilistic Graphical Model Approach

ACL ID P13-3022
Title Exploring Word Order Universals: a Probabilistic Graphical Model Approach
Venue Annual Meeting of the Association of Computational Linguistics
Session Student Session
Year 2013
Authors

In this paper we propose a probabilistic graph- ical model as an innovative framework for studying typological universals. We view lan- guage as a system and linguistic features as its components whose relationships are encoded in a Directed Acyclic Graph (DAG). Taking discovery of the word order universals as a knowledge discovery task we learn the graph- ical representation of a word order sub-system which reveals a finer structure such as direct and indirect dependencies among word order features. Then probabilistic inference enables us to see the strength of such relationships: given the observed value of one feature (or combination of features), the probabilities of values of other features can be calculated. Our model is not restricted to using only two val- ues of a fe...