Name
Abstract | ||
|---|---|---|
We present an efficient algorithm for the redundancy elimination problem: Given an underspecified semantic representation (USR) of a scope ambiguity, compute an USR with fewer mutually equivalent readings. The algorithm operates on underspecified chart representations which are derived from dominance graphs; it can be applied to the USRs computed by large-scale grammars. We evaluate the algorithm on a corpus, and show that it reduces the degree of ambiguity significantly while taking negligible runtime. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.3115/1220175.1220227 | ACL |
Keywords | Field | DocType |
underspecified chart representation,underspecified representation,large-scale grammar,equivalent reading,redundancy elimination problem,negligible runtime,underspecified semantic representation,dominance graph,improved redundancy elimination algorithm,scope ambiguity,efficient algorithm | Rule-based machine translation,Graph,Computer science,Algorithm,Theoretical computer science,Redundancy (engineering),Natural language processing,Chart,Artificial intelligence,Semantic representation,Ambiguity,Machine learning | Conference |
Volume | Citations | PageRank |
P06-1 | 2 | 0.37 |
References | Authors | |
9 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alexander Koller | 1 | 438 | 35.50 |
| Stefan Thater | 2 | 756 | 38.54 |