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This paper summarizes results of a theoretical analysis of syntactic behavior of Czech light verb constructions and their verification in the linguistic annotation of a large amount of these constructions. The concept of LVCs is based on the observation that nouns denoting actions, states, or properties have a strong tendency to select semantically underspecified verbs, which leads to a specific rearrangement of valency complementations of both nouns and verbs in the syntactic structure. On the basis of the description of deep and surface syntactic properties of LVCs, a formal model of their lexicographic representation is proposed here. In addition, the resulting data annotation, capturing almost 1,500 LVCs, is described in detail. This annotation has been integrated in a new version of the VALLEX lexicon, release 3.5.

The aim of the contribution is to introduce a database of linguistic forms and their functions built with the use of the multi-layer annotated corpora of Czech, the Prague Dependency Treebanks. The purpose of the Prague Database of Forms and Functions (ForFun) is to help the linguists to study the form-function relation, which we assume to be one of the principal tasks of both theoretical linguistics and natural language processing. We demonstrate possibilities of the exploitation of the ForFun database. This article is largely based on a paper presented at the 16th International Workshop on Treebanks and Linguistic Theories in Prague (Bejček et al., 2017).

We introduce a corpus based description of selected adverbial meanings in Czech sentences. Its basic repertory is one of a long lasting tradition in both scientific and school grammars. However, before the corpus era, researchers had to rely on their own excerption; but nowadays, current syntax has a vast material basis in the form of electronic corpora available. On the case of spatial adverbials, we describe our methodology which we used to acquire a detailed, comprehensive, well-arranged description of meanings of adverbials including a list of formal realizations with examples. Theoretical knowledge stemming from this work will lead into an improval of the annotation of the meanings in the Prague Dependency Treebanks which serve as the corpus sources for our research. The Prague Dependency Treebanks include data manually annotated on the layer of deep syntax and thus provide a large amount of valuable examples on the basis of which the meanings of adverbials can be defined more accurately and subcategorized more precisely. Both theoretical and practical results will subsequently be used in NLP, such as machine translation.

In this article, we introduce a project aimed at enhancing a valency lexicon of Czech verbs with semantic information. For this purpose, we make use of FrameNet, a semantically oriented lexical resource. At the present stage, semantic frames from FrameNet have been mapped to eight groups of verbs with various semantic and syntactic properties. The feasibility of this task has been verified by the achieved inter-annotator agreement measured on two semantically and syntactically different groups of verbs – verbs of communication and exchange (85.9% and 78.5%, respectively). Based on the upper level semantic frames from the relation of ‘Inheritance’ built in FrameNet, the verbs of these eight groups have been classified into more coherent semantic classes. Moreover, frame elements from these upper level semantic frames have been assigned to valency complementations of the verbs of the listed groups as semantic roles. As in case of semantic frames, the achieved interannotator agreement concerning assigning frame elements measured on verbs of communication and exchange has been promising (95.6% and 91.2%, respectively). As a result, 1 270 lexical units pertaining to the verbs of communication, mental action, psych verbs, social interaction, verbs of exchange, motion, transport and location (2 129 Czech verbs in total if perfective and imperfective verbs being counted separately) have been classified into syntactically and semantically coherent classes and their valency complementations have been characterized by semantic roles adopted from the FrameNet lexical database.

Multiword Expressions (MWEs) are important linguistic units that require special treatment in many NLP applications. It is thus desirable to be able to recognize them automatically. Semantically annotated corpora should mark MWEs in a clear way that facilitates development of automatic recognition tools. In the present paper we discuss various corpus design decisions from this perspective. We propose guidelines that should lead to MWE-friendly annotation and evaluate them on numerous sentence examples. Our experience of identifying MWEs in the Prague Dependency Treebank provides the base for the discussion and examples from other languages are added whenever appropriate.

This paper presents a sophisticated way to search valency lexicons. We provide a visualization of lexicons with such built-in searching that allows users to draw sophisticated queries in a graphical mode. We exploit the PML-TQ, a query language based on the tree editor TrEd. For demonstration purposes, we focus on VALLEX and PDT-VALLEX, two Czech valency lexicons of verbs. We propose a common lexicon data format supported by PML-TQ. This format offers easy viewing both lexicons, parallel searching and interlinking them. The proposed method is universal and can be used for other hierarchically structured lexicons.

This paper presents our experience with the lexico-semantic annotation of the Prague Dependency Treebank (PDT) We have used the Czech WordNet (CWN) as an annotation lexicon (repository of lexical meanings) and we annotate each word which is included in the CWN Based on the error analysis we have performed some experiments with modification of the annotation lexicon (CWN) and consequent re-annotation of occurrences of selected lemmas We present the results of the annotations and improvements achieved by our corrections.