Symmetric pattern matching analysis for English coordinate structures
ANLC '94 Proceedings of the fourth conference on Applied natural language processing
A rule-based approach to prepositional phrase attachment disambiguation
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 2
Measuring the Expressiveness of a Constrained Natural Language: An Empirical Study
RE '05 Proceedings of the 13th IEEE International Conference on Requirements Engineering
Identifying Nocuous Ambiguities in Natural Language Requirements
RE '06 Proceedings of the 14th IEEE International Requirements Engineering Conference
Using the web as an implicit training set: application to structural ambiguity resolution
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Automatic detection of nocuous coordination ambiguities in natural language requirements
Proceedings of the IEEE/ACM international conference on Automated software engineering
Extending Nocuous Ambiguity Analysis for Anaphora in Natural Language Requirements
RE '10 Proceedings of the 2010 18th IEEE International Requirements Engineering Conference
Automatic detection of nocuous coordination ambiguities in natural language requirements
Proceedings of the IEEE/ACM international conference on Automated software engineering
A generalised hybrid architecture for NLP
HYBRID '12 Proceedings of the Workshop on Innovative Hybrid Approaches to the Processing of Textual Data
Hi-index | 0.00 |
Nocuous ambiguity occurs when a linguistic expression is interpreted differently by different readers in a given context. We present an approach to automatically identify nocuous ambiguity that is likely to lead to misunderstandings among readers. Our model is built on a machine learning architecture. It learns from a set of heuristics each of which predicts a factor that may lead a reader to favor a particular interpretation. An ambiguity threshold indicates the extent to which ambiguity can be tolerated in the application domain. Collections of human judgments are used to train heuristics and set ambiguity thresholds, and for evaluation. We report results from applying the methodology to coordination and anaphora ambiguity. Results show that the method can identify nocuous ambiguity in text, and may be widened to cover further types of ambiguity. We discuss approaches to evaluation.