An algorithm for pronominal anaphora resolution
Computational Linguistics
Efficient Parsing for Natural Language: A Fast Algorithm for Practical Systems
Efficient Parsing for Natural Language: A Fast Algorithm for Practical Systems
Constraint Grammar: A Language-Independent System for Parsing Unrestricted Text
Constraint Grammar: A Language-Independent System for Parsing Unrestricted Text
Anaphora resolution: a multi-strategy approach
COLING '88 Proceedings of the 12th conference on Computational linguistics - Volume 1
A binding rule for Government-binding parsing
COLING '88 Proceedings of the 12th conference on Computational linguistics - Volume 1
Anaphora for everyone: pronominal anaphora resoluation without a parser
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
Anaphor resolution and the scope of syntactic constraints
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
Multilingual Anaphora Resolution
Machine Translation
Design and enhanced evaluation of a robust anaphor resolution algorithm
Computational Linguistics - Special issue on computational anaphora resolution
| Hi-index | 0.00 |
Syntactic coindexing restrictions are by now known to be of central importance to practical anaphor resolution approaches. Since, in particular due to structural ambiguity, the assumption of the availability of a unique syntactic reading proves to be unrealistic, robust anaphor resolution relies on techniques to overcome this deficiency. In this paper, two approaches are presented which generalize the verification of coindexing constraints to deficient descriptions. At first, a partly heuristic method is described, which has been implemented. Secondly, a provable complete method is specified. It provides the means to exploit the results of anaphor resolution for a further structural disambiguation. By rendering possible a parallel processing model, this method exhibits, in a general sense, a higher degree of robustness. As a practically optimal solution, a combination of the two approaches is suggested.