论文信息 - Parsing Morphologically Complex Words

Parsing Morphologically Complex Words

We present a method for probabilistic parsing of German words. Our approach uses a morphological analyzer based on weighted finitestate transducers to segment words into lexical units and a probabilistic context free grammar trained on a manually created set of word trees for the parsing step.

Thomas Hanneforth | Kay-Michael Würzner

[1] Ulrich Heid,et al. Design and Application of a Gold Standard for Morphological Analysis: SMOR as an Example of Morphological Evaluation , 2010, LREC.

[2] Arto Salomaa,et al. Semirings, Automata, Languages , 1985, EATCS Monographs on Theoretical Computer Science.

[3] Alexander Geyken,et al. dlexDB : eine lexikalische Datenbank für die psychologische und linguistische Forschung , 2011 .

[4] Hubert Comon,et al. Tree automata techniques and applications , 1997 .

[5] Taylor L. Booth,et al. Probabilistic Representation of Formal Languages , 1969, SWAT.

[6] Michael Collins,et al. Head-Driven Statistical Models for Natural Language Parsing , 2003, CL.

[7] Gary Libben,et al. Are morphological structures computed during word recognition? , 1993 .

[8] Eugene Charniak,et al. Statistical Techniques for Natural Language Parsing , 1997, AI Mag..

[9] Thomas Hanneforth,et al. TAGH: A Complete Morphology for German Based on Weighted Finite State Automata , 2005, FSMNLP.