Creating Hierarchical Relations in a Multilingual Event-type Ontology (2025)

Abstract: This paper describes the work on hierarchization of the SynSemClass event-type ontology. The original resource has been extended by a hierarchical structure to model specialization and generalization relations between classes that are formally and technically unrelated in the original ontology. The goal is to enable one to use the ontology enriched by the hierarchical concepts for annotation of running texts in symbolic meaning representations, such as UMR or PDT. The hierarchy is in principle built bottom-up, based on existing SSC classes (concepts). This approach differs from other approaches to semantic classes, such as in WordNet or VerbNet. Although the hierarchical relations are similar, the underlying nodes in the hierarchy are not. In this paper, we describe the challenges related to the principles chosen: single-tree constraint and finding features for the definitions of specificity/generality. Also, a pilot inter-annotator experiment is described that shows the difficulty of the hierarchization task.

## introduction the synsemclass (ssc) multilingual 1 event-type ontology @xcite is a lexical-semantic resource that links similar resources, such as framenet @xcite , wordnet @xcite , verbnet @xcite and others, and unifies them under a single scheme. each entry in synsemclass @xcite , a class, corresponds to one eventive concept (state or process). every concept is specified in multiple ways so that the human reader can understand what the concept is. the following are the main features describing a class, e.g., kill (fig. 1 ): the organization of this paper is as follows: sect. 2 explains why we have decided to build the hierarchy, and in sect. 3 we mention other works on this topic. in sect. 4, our approach to hierarchical scheme is presented, sect. 5 describes some challenging issues (sect. 5.1) and tools used (sect. 5.2). sect. 6 discusses the current state of the hierarchy with some statistics. we conclude and draw future plans in sect. 7. sect. 8 in the extra space lists the limitations of the current state of the hierarchy. ## motivation although synsemclass is a resource that is meant to be used in document annotation (perhaps in addition to or on top of another meaning representation scheme, such as uniform meaning representation (umr) @xcite ), such annotation would be very difficult to perform accurately and efficiently given the properties of the synsemclass ontology as described in the previous paragraph @xcite . the problem is the unrelatedness of the different classes in the ontology: in the hypothetical (but certainly not uncommon) case that the annotator sees an expression (verb, noun, and mwe) that is not found among the class members of any class (or is found, but it is used in a new or different sense clearly not corresponding to the concept of the class in which it is found), all the classes would have to be considered, one by one, to find a suitable one (or determine that it does not exist in the resource). 3 there are now 1500+ classes in synsemclass -so 3 one can imagine a better way of pre-annotation, namely the use of current state-of-the-art technology, such as llms. however, even that assumes at least some data to be fully annotated manually, if only for the development and evaluation of such tool(s). therefore, we have determined that a hierarchy over the concepts (as represented by the classes) in synsemclass is necessary. the existence of such a hierarchy, connecting all the classes by a generalization/specialization relation, would reduce the effort required to find the appropriate class in the hierarchy by going top-down and selecting an appropriate hierarchical node (and the class represented by (linked from) it) in just a few steps. however, given the existence of hierarchies integrated in other resources, one might ask why to build a new one. we have had two main reasons: first, the underlying synsemclass resource is richer than the aforementioned ones in terms of being multilingual (or "interlingual") from the start, build bottom up, interlinked to other resources, has explicit mappings to syntactic resources in the languages it refers to, and has exemplification based on real corpora. second, when inspecting the links to resources with similar hierarchies (wordnet, framenet, verbnet) included in synsemclass, there was often a multiple number of possible generalizations. 4 while the differences might be due to a different view on the synset/class concept, it is clear that there is no simple way to get a common hierarchy. that is why we are exploiting the gap and trying to fill it; the main novelty is the complexity of the linked resources in the combined resource, that is, the hierarchy plus the data in the underlining ontology. we believe that both the actual creation and the use for textual annotation in the future can benefit from this complex information, which can guide annotators' understanding of the concepts in the hierarchy. in addition, this approach combines the "bottom-up view ", built within the synsem-class ontology itself, with the top-down view when starting with the top-level ontology, as most current approaches do. we are aware of the fact that such a hierarchy cannot be fully built in a simple tree-shaped form. however, we do believe that the core of such hierarchical set of relations can, despite the fact that the individual languages might sometimes have incompatible tendencies in expressing hyperonymy and hyponymy. the fact that the underlying ontology stress concepts rather than lexical (syn)sets should help, since all the context (links to entries in the other resources, including wordnet), syntactic and semantic properties present at each entry, can be taken into account when considering the often conflicting grounds for determining the hierarchical structure. at the same time, if this hierarchy exists, synsemclass could also serve other purposes, such as enabling a comparison to other lexical resources and their hierarchies thanks to the rich linking scheme within synsemclass, linguistic and cognitive research on generalization and specialization, or language acquisition. ## related work the work described here relates closely to other lexical resources that include information about hierarchical relations among concepts, for example, wordnet @xcite or framenet @xcite . the princeton wordnet (pwn) is a large lexical database of english that groups words into interrelated sets of cognitive synonyms (synsets) and that is organized as a network where the synsets' relations are encoded through a super-ordinate relation (hyponymy/hyperonymy). pwn represents a concept as lists of the word senses that can be used to express the concept. verb synsets also add the relation of troponymy in such a way that the nodes at the bottom of the tree denote specifications of a more general event @xcite . the multilingual eurowordnet @xcite introduced some major design changes, among them new semantic and lexical relations that may be specific to individual languages foot_2 @xcite @xcite . in addition, a framework for a 'global grid' was established that defines a universal core lexical inventory and establishes guidelines for its cross-linguistic encoding @xcite . framenet, a resource containing information about lexical and predicate argument semantics, is based on the principles of frame semantics, where frames (conceptual structures that describe different types of entities, situations and events) are organized into a network where more abstract frames (super-frames) are connected to less abstract frames (sub-frames). these relations include, but are not limited to: inheritance -the relationship between a parent frame and its child frame; using (or weak-inheritance) -the relation between a frame that is related in some way to a super-frame; subframe -a relation between a complex frame that denotes a sequence of states and transitions and the individual frames that separately denote each state; and perspective -the relation between frames denoting different perspectives over a neutral frame and the neutral frame itself. in addition to the hierarchy of frames arranged according to the frame-to-frame relations, framenet works with the second hierarchy, i.e., hierarchy of semantic types, which indicates the basic types of fillers of frame elements, marks non-lexical types of frames, and records important semantic differences between lexical units belonging to the same frame @xcite ). various proposals have been put forward to align the information contained in both resources aiming at the development of an ontology of events. babelnet @xcite is a prime example. for slavic languages specifically, @xcite set the foundations for the development of an ontology of stative predicates in bulgarian and russian by elaborating on framenet hierarchical classification through its mapping with wordnet. another example of an ontology that integrates information from lexical resources (with upperlevel ontologies such as dolce @xcite ) is the rich event ontology @xcite , which provides a structure of event concepts connected at various levels of specificity and establishes relations between events and between events and the key objects and participants involved. there are other ontologies, but as far as we know, there is no multilingual synonyms ontology with a hierarchical scheme built bottom-up. i.e., as in synsemclass, with so much empirical material available for determining the hierarchical relations with much higher certainty (than wordnet(s)' only lexically-based synsets). we also have to stress here that the multilingual wordnets are developed top-down working with a shared set of so-called base concepts and an equivalence relation for each synset to the closest concept from an inter-lingual-index. the general approach of eurowordnet is to build wordnets mainly from existing resources @xcite . compatibility between the eurowordnet languages and the inter-lingual-index with respect to lexical coverage and relations depends on which of the two basic methods for building the european wordnets was followed: either english synsets are translated into the target language and the relations are copied (expand method), or synsets are created for the target language, interlinked with the pwn relations, and subsequently translated into english for mapping with ili entries @xcite . for the discussion of near-synonymy, there are both theoretical lexicographic works such as @xcite , and also the computationally-oriented view by (edmonds and hirst, 2002). ## the hierarchy we have conceived the hierarchy as a single, rooted tree, in which ideally the synsemclass classes are assigned 1:1 to its nodes and where the edges represent the more general or more specialised conceptual relation between the parent and the child nodes in the tree. however, after testing a few examples, it was clear that this is not feasible to do directly, for the same reasons that the direct use of synsemclass with its flat, set-like structure would be inefficient to use for annotation. looking at any concept, the question that was not easy to answer was "which concept might be the next more general one among all the other synsemclass concepts?" -without going through every other class. in sect. 5 we explain how we proceeded, using some preprocessing to extract some candidates for these relations. as a working solution, we have decided to scrap the 1:1 requirement of linking the hierarchy nodes to synsemclass classes for now and temporarily allow both empty nodes in the hierarchy, as well as nodes with multiple synsemclass classes assigned to them, to be split later. however, each synsem-class class is (perhaps also temporarily) linked to only one node in the hierarchy to maintain at least some structure in it. we believe that this is not limiting at this time. having done so, we have to distinguish the original synsemclass concepts as represented by the set of class members (verbs or nouns) in its flat structure (in this paper, we will call them sycs), and the nodes in the hierarchy tree (hics, for hierarchical concepts). each hic (node in the hierarchy tree) is charac-terized by a series of features, or descriptors, as illustrated by the example in fig. 2 , for the hic ownership transfer: all of these parts constitute a complex description of hic (hierarchical concept). they serve (similarly to the synsemclass class features and descriptors, as we see them) primarily for human understanding of the concepts. we have created the base hierarchical structure (sect. 5). to verify the approach fully, we have linked each class in the ontology (illustrated, e.g., in fig. 1 ) to a node in the hierarchy. the top level of the hierarchy is shown schematically in fig. 3 ; 7 for the hic possession or ownership, we are showing the full expanded path (internal nodes in light blue) to this hic (which is a leaf in the hierarchy tree, shown in light green). ## current state all the classes (sycs) from synsemclass have been assigned to the tree nodes of the conceptual hierarchy tree nodes (hics). there are 1538 sycs in the version of synsemclass that we have been working with. the current hierarchy has 663 nodes; this means that there are around 2.5 classes (sycs) per node in the hierarchy. this is still far from the goal of having (close to) 1:1 correspondence between hics and sycs, but a larger number of nodes than many existing hierarchies currently have. in this section, we present some quantitative indicators. ## conclusions and future work we have created a novel hierarchy of eventive concepts linked to an existing event-type ontology, synsemclass. each its class is linked to one node in the hierarchy. the hierarchy is a fully connected rooted tree, currently containing 663 hics, with about 2.5 synsemclass classes linked to each hic. we have identified problems that arise while building such a hierarchy: defining each concept clearly, finding criteria for splitting nodes into its child nodes when multiple possibilities exist, and finding a set of synsemclass classes representing each concept (node in the hierarchy) efficiently. perhaps not surprisingly, the existing resources do not consistently define its entries, as demonstrated by the multiplicity and fuzziness of relation mappings between these resources (using synsem-class links). the hierarchies in these resources also differ substantially (framenet's vs. wordnet's hyponymy/hyperonymy relation vs. the shallow verb-net hierarchy). all of this poses a challenge for the refinement of the hierarchy over synsemclass as we have developed it so far, in several respects: we have performed a pilot annotation comparison (annotator agreement experiments) for the (re)assignment of 50 classes to the current hierarchy tree ( the numbers indicate low accuracy against the data when annotators also agree, and only slightly above 50 percent accuracy for each of the two independently, and between themselves. this is to be expected since it is a very hard task, both mentally and from the statistical point of view (the random uniform baseline is 1/663). but it is an approximation of the text annotation task, since the synsem-class classes (sycs) to be assigned to the hierarchy nodes (hics) correspond, by and large, to the verb senses that text annotators will have to determine during such annotation, which will also serve as the relevant test and evaluation experiment. the current full version of the hierarchy is published in a new version of synsemclass (v5.5). 11 nevertheless, there is still work to do, such as split some of the leaves of the hierarchy tree, populate some nodes with new links to the synsemclass classes, and refine the concepts definitions.