Paper: A Bayesian Model for Discovering Typological Implications

ACL ID P07-1009
Title A Bayesian Model for Discovering Typological Implications
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2007

A standard form of analysis for linguis- tic typology is the universal implication. These implications state facts about the range of extant languages, such as “if ob- jects come after verbs, then adjectives come after nouns.” Such implications are typi- cally discovered by painstaking hand anal- ysis over a small sample of languages. We propose a computational model for assist- ing at this process. Our model is able to discover both well-known implications as well as some novel implications that deserve further study. Moreover, through a careful application of hierarchical analysis, we are able to cope with the well-known sampling problem: languages are not independent.