Deverbal nouns pose challenges for semantic annotation frameworks that aim to represent event structures consistently across lexical categories. This paper examines problematic phenomena in the annotation of deverbal nouns in Czech and Latin within the Universal Meaning Representation (UMR) framework, addressing both manual graph construction and rule-based automatic conversion from existing resources. Current UMR guidelines lack operational criteria for deciding when a noun should be treated as an eventive concept, particularly in the absence of a PropBank-like lexicon with sufficient nominal coverage. We therefore propose practical annotation principles: deverbal nouns denoting events (such as učení ‘teaching’), results of events (řešení ‘solution’), or event participants (učitel ‘teacher’) should be related to underlying event concepts (represented as verbs in their particular senses, i.e., učit-001 ‘to teach’, vyřešit-001 ‘to solve’, and učit-001 ‘to teach’, respectively), while other deverbal nouns should remain unrelated to respective events (such as učebna ‘teaching room’). To reduce inter-annotator variation, we further suggest systematic strategies for selecting verbal labels, including the use of light-verb constructions, synonymous verbs, and a preference for imperfective verbs in Czech aspectual pairs. For automatic conversion, we outline a rule-based approach that combines multiple lexical resources and frequency-based heuristics to identify corresponding verb senses. Our findings provide guidelines for more consistent UMR annotation across languages.

The paper presents the first shared task on parsing Uniform Meaning Representation (UMR), a graph-based framework for cross-linguistic semantic annotation of typologically diverse languages. The task requires systems to enrich plain text with sentence-level structure, node–token alignment, and document-level relations. It involves processing data for seven languages from four language families (Indo-European, Sino-Tibetan, Na-Dene, and Algic). Six languages have at least some training data; for one language, data is not available, leading to a zero-shot scenario. The training dataset as well as the gold-standard test set for all seven languages is released and made available for follow-up research. We present the task setup and evaluation methodology, using two graph matching approaches – a traditional, and an alignment-sensitive one, tailored specifically for UMR. Two participating systems are compared, each representing different modeling approaches. Results highlight the challenges of UMR parsing, particularly for alignment prediction and document-level semantics, and reveal substantial variation across languages and annotation conditions.

Uniform Meaning Representation (UMR) is a semantic framework designed to represent the meaning of texts in a structured and interpretable manner. In this paper, we evaluate the results of the automatic conversion of existing resources to UMR, focusing on Czech (PDT-C treebank) and Latin (LDT treebank). We present both quantitative and qualitative evaluations based on a comparison between manually and automatically generated UMR structures for a sample of Czech and Latin sentences. The findings indicate comparable results of the automatic conversion for both languages. The key challenges prove to be the higher level of semantic abstraction required by UMR and the fact that UMR allows for capturing semantic structure in multiple ways, potentially with varying levels of granularity.

For many years, there has been attempts to compare predicate-argument labeling schemas between formalism, typically under the dependency assumptions (even if the annotation by these schemas could have been performed on either constituent-based specifications or dependency ones). Given the growing number of resources that link various lexical resources to one another, as well as thanks to parallel annotated corpora (with or without annotation), it is now possible to do more in-depth studies of those correspondences. We present here a high-coverage pilot study of mapping the labeling system used in PropBank (for English) to Czech, which has so far used mainly valency lexicons (in several closely related forms) for annotation projects, under a different level of specification and different theoretical assumptions. The purpose of this study is both theoretical (comparing the argument labeling schemes) and practical (to be able to annotate Czech under the standard UMR specifications).

Valency lexicons usually describe valency behavior of verbs in non-reflexive and non-reciprocal constructions. However, reflexive and reciprocal constructions are common morphosyntactic forms of verbs. Both of these constructions are characterized by regular changes in morphosyntactic properties of verbs, thus they can be described by grammatical rules. On the other hand, the possibility to create reflexive and/or reciprocal constructions cannot be trivially derived from the morphosyntactic structure of verbs as it is conditioned by their semantic properties as well. A large-coverage valency lexicon allowing for rule based generation of all well formed verb constructions should thus integrate the information on reflexivity and reciprocity. In this paper, we propose a semi-automatic procedure, based on grammatical constraints on reflexivity and reciprocity, detecting those verbs that form reflexive and reciprocal constructions in corpus data. However, exploitation of corpus data for this purpose is complicated due to the diverse functions of reflexive markers crossing the domain of reflexivity and reciprocity. The list of verbs identified by the previous procedure is thus further used in an automatic experiment, applying word embeddings for detecting semantically similar verbs. These candidate verbs have been manually verified and annotation of their reflexive and reciprocal constructions has been integrated into the valency lexicon of Czech verbs VALLEX.

An excellent example of a phenomenon bridging a lexicon and a grammar is provided by grammaticalized alternations (e.g., passivization, reflexivity, and reciprocity): these alternations represent productive grammatical processes which are, however, lexically determined. While grammaticalized alternations keep lexical meaning of verbs unchanged, they are usually characterized by various changes in their morphosyntactic structure. In this contribution, we demonstrate on the example of reciprocity and its representation in the valency lexicon of Czech verbs, VALLEX how a linguistic description of complex (and still systemic) changes characteristic of grammaticalized alternations can benefit from an integration of grammatical rules into a valency lexicon. In contrast to other types of grammaticalized alternations, reciprocity in Czech has received relatively little attention although it closely interacts with various linguistic phenomena (e.g., with light verbs, diatheses, and reflexivity).

Valency lexicons typically describe only unmarked usages of verbs (the active form); however, verbs prototypically enter different surface structures. In this paper, we focus on the so-called diatheses, i.e., the relations between different surface syntactic manifestations of verbs that are brought about by changes in the morphological category of voice, e.g., the passive diathesis. The change in voice of a verb is prototypically associated with shifts of some of its valency complementations in the surface structure. These shifts are implied by changes in morphemic forms of the involved valency complementations and are regular enough to be captured by syntactic rules. However, as diatheses are lexically conditioned, their applicability to an individual lexical unit of a verb is not predictable from its valency frame alone. In this work, we propose a representation of this linguistic phenomenon in a valency lexicon of Czech verbs, VALLEX, with the aim to enhance this lexicon with the information on individual types of Czech diatheses. In order to reduce the amount of necessary manual annotation, a semi-automatic method is developed. This method draws evidence from a large morphologically annotated corpus, relying on grammatical constraints on the applicability of individual types of diatheses.

This paper presents the fully automatic linking of two valency lexicons of Czech verbs: VALLEX and PDT-VALLEX. Despite the same theoretical background adopted by these lexicons and the same linguistic phenomena they focus on, the fully automatic mapping of these resouces is not straightforward. We demonstrate that converting these lexicons into a common format represents a relatively easy part of the task whereas the automatic identification of pairs of corresponding valency frames (representing lexical units of verbs) poses difficulties. The overall achieved precision of 81% can be considered satisfactory. However, the higher number of lexical units a verb has, the lower the precision of their automatic mapping usually is. Moreover, we show that especially (i) supplementing further information on lexical units and (ii) revealing and reconciling regular discrepancies in their annotations can greatly assist in the automatic merging.

CLARA (Common Language Resources and Their Applications) is a Marie Curie Initial Training Network which ran from 2009 until 2014 with the aim of providing researcher training in crucial areas related to language resources and infrastructure. The scope of the project was broad and included infrastructure design, lexical semantic modeling, domain modeling, multimedia and multimodal communication, applications, and parsing technologies and grammar models. An international consortium of 9 partners and 12 associate partners employed researchers in 19 new positions and organized a training program consisting of 10 thematic courses and summer/winter schools. The project has resulted in new theoretical insights as well as new resources and tools. Most importantly, the project has trained a new generation of researchers who can perform advanced research and development in language resources and technologies.

This paper investigates the mapping between two semantic formalisms, namely the tectogrammatical layer of the Prague Dependency Treebank 2.0 (PDT) and (Robust) Minimal Recursion Semantics ((R)MRS). It is a first attempt to relate the dependency-based annotation scheme of PDT to a compositional semantics approach like (R)MRS. A mapping algorithm that converts PDT trees to (R)MRS structures is developed, associating (R)MRSs to each node on the dependency tree. Furthermore, composition rules are formulated and the relation between dependency in PDT and semantic heads in (R)MRS is analyzed. It turns out that structure and dependencies, morphological categories and some coreferences can be preserved in the target structures. Moreover, valency and free modifications are distinguished using the valency dictionary of PDT as an additional resource. The validation results show that systematically correct underspecified target representations can be obtained by a rule-based mapping approach, which is an indicator that (R)MRS is indeed robust in relation to the formal representation of Czech data. This finding is novel, for Czech, with its free word order and rich morphology, is typologically different than languages analyzed with (R)MRS to date.

The main objective of this paper is to introduce an alternation-based model of valency lexicon of Czech verbs VALLEX. Alternations describe regular changes in valency structure of verbs -- they are seen as transformations taking one lexical unit and return a modified lexical unit as a result. We characterize and exemplify “syntactically-based” and “semantically-based” alternations and their effects on verb argument structure. The alternation-based model allows to distinguish a minimal form of lexicon, which provides compact characterization of valency structure of Czech verbs, and an expanded form of lexicon useful for some applications.