Tagging Grammatical Functions

Tagging Grammatical Functions Thorsten Brants, Wojciech Skut, Brigitte Krenn Universit~t des Saarlandes Computational Linguistics D-66041 Saarbr/icken, Germany {brant s, skut,krenn}@coli.uni-sb, de Abstract This paper addresses issues in automated treebank construction. We show how stan- dard part-of-speech tagging techniques ex- tend to the more general problem of struc- tural annotation, especially for determi- ning grammatical functions and syntactic categories. Annotation is viewed as an in- teractive process where manual and auto- matic processing alternate. Efficiency and accuracy results are presented. We also dis- cuss further automation steps. 1 Introduction The aim of the work reported here is to construct a corpus of German annotated with syntactic structu- res (treebank). The required size of the treebank and granularity of encoded information make it neces- sary. to ensure high annotation efficiency and accu- racy. Annotation automation has thus become one of the central issues of the project. In this section, we discuss the relation between au- tomatic and manual annotation. Section 2 focuses on the annotation format employed in our treebank. The annotation software is presented in section 3. Sections 4 and 5 deal with automatic assignment of grammatical functions and phrasal categories. Ex- periments on automating the annotation are presen- ted in section 6. 1.1 Automatic vs. Manual Annotation A problem for corpus annotation is the trade-off bet- ween efficiency, accuracy and coverage. Although accuracy increases significantly as annotators gain expertise, incorrect hand-parses still occur. Their frequency depends on the granularity of the enco- ded information. Due to this residual error rate, automatic anno- tation of frequently occurring phenomena is likely to yield better results than even well-trained hu- man annotators. For infrequently occurring con- structions, however, manual annotation is more re- liable, as is manual annotation of phenomena invol- ving non-syntactic information (e.g., resolution of attachment ambiguities based on world knowledge). As a consequence, efficiency and reliability of an- notation can be significantly increased by combining automatic annotation with human processing skills and supervision, especially if this combination is im- plemented as an interactive process. 2 Annotation Scheme Existing treebanks of English ((Marcus et al., 1994), (Sampson, 1995), (Black et al., 1996)) contain con- ventional phrase-structure trees augmented with an- notations for discontinuous constituents. As this en- coding strategy is not well-suited to a free word or- der language like German, we have focussed on a less surface-oriented level of description, most closely re- lated to the LFG f-structure, and representations used in dependency grammar. To avoid confusion with theory-specific constructs, we use the generic term argument structure to refer to our annotation format. The main advantages of the model are: it is relatively theory-independent and closely related to semantics. For more details on the linguistic speci- fications of the annotation scheme see (Skut et al., 1997). A similar approach has been also successfully applied in the TSNLP database, cf. (Lehmann et al., 1996). In contrast to conventional phrase-structure grammars, argument structure annotations are not influenced by word order. Local and non-local de- pendencies are represented in the same way, the …

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