A cascaded finite-state parser for syntactic analysis of Swedish

Authors:
Dimitrios Kokkinakis;Sofie Johansson Kokkinakis
Affiliations:
Göteborg University, Göteborg, Sweden;Göteborg University, Göteborg, Sweden
Venue:
EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
Year:
1999

Citing 4
Cited 6

Some advances in transformation-based part of speech tagging

AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Finite-State Language Processing

Finite-State Language Processing
Compiling and using finite-state syntactic rules

COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 1
Does tagging help parsing?: a case study on finite state parsing

FSMNLP '09 Proceedings of the International Workshop on Finite State Methods in Natural Language Processing

Finite-State Transducer Cascade to Extract Proper Names in Texts

CIAA '01 Revised Papers from the 6th International Conference on Implementation and Application of Automata
Concordancing Revised or How to Aid the Recognition of New Senses in Very Large Corpora

NLP '00 Proceedings of the Second International Conference on Natural Language Processing
A shallow parser based on closed-class words to capture relations in biomedical text

Journal of Biomedical Informatics
Finite-state transducer cascades to extract named entities in texts

Theoretical Computer Science - Implementation and application automata
Dependency Parsing with an Extended Finite-State Approach

Computational Linguistics
Text mining approach for knowledge extraction in Sahîh Al-Bukhari

Computers in Human Behavior

Quantified Score

Hi-index	0.00

Visualization

Abstract

This report describes the development of a parsing system for written Swedish and is focused on a grammar, the main component of the system, semiautomatically extracted from corpora. A cascaded, finite-state algorithm is applied to the grammar in which the input contains coarse-grained semantic class information, and the output produced reflects not only the syntactic structure of the input, but grammatical functions as well. The grammar has been tested on a variety of random samples of different text genres, achieving precision and recall of 94.62% and 91.92% respectively, and average crossing rate of 0.04, when evaluated against manually disambiguated, annotated texts.