Survey on Lexical Resources Focused on Multiword Expressions for the Purposes of NLP (2025)

Abstract: Lexica of MWEs have always been a valuable resource for various NLP tasks. This paper presents the results of a comprehensive survey on multiword lexical resources that extends a previous one from 2016 to the present. We analyze a diverse set of lexica across multiple languages, reporting on aspects such as creation date, intended usage, languages covered and linguality type, content, acquisition method, accessibility, and linkage to other language resources. Our findings highlight trends in MWE lexicon development focusing on the representation level of languages. This survey aims to support future efforts in creating MWE lexica for NLP applications by identifying these gaps and opportunities.

## motivation multiword expressions (mwes) pose a unique challenge in natural language processing (nlp), primarily due to their semantic non-compositionality. this characteristic makes their automatic identification in text crucial for semantically driven downstream applications. despite recent advances, including the advent of large (and small) language models, mwes' inherent complexity and distributional properties continue to impede their effective processing. lexical resources, that is, computational lexica dedicated to mwes, are essential to address these challenges @xcite . our objective is to provide a comprehensive overview of the current landscape of mwe-related computational lexica that have been created for nlp purposes. the identification of relevant resources was meant to be as exhaustive as possible. special emphasis was placed on the languages featured in the resources and their levels of representation in the nlp ecosystem. thus, the survey aims to serve as a first step in highlighting the extent to which less-represented languages are included and supported in existing resources. the paper is organized as follows. section 2 presents previous surveys that focus on mwes and outlines the new features offered by the current one. section 3 discusses the sources and methodology we adopted to compile the list of resources with their relevant characteristics. the overview of the current landscape of mwe lexical resources is presented in section 4, before concluding the paper by setting objectives for future work (section 5). ## previous surveys we are aware of four surveys heretofore focused on mwes: @xcite focused on the types of mwes that were more frequently annotated in treebanks at that time, namely named entities, phrasal verbs, and prepositional mwes. @xcite compared the way in which light verb constructions and verbal idioms were annotated in treebanks and proposed general guidelines for this. the survey by @xcite is focused on the methodologies and features required to implement mwe detection systems and is therefore of little relevance to our work. our survey builds on the one by @xcite (henceforth, 'the parseme survey') that, in the framework of the parseme cost action foot_0 , provided a comprehensive overview of mwe resources, including lists, lexica (either dedicated to mwes or including them alongside other lexical entries), and corpora such as treebanks available at that moment. the survey was based, on the one hand, on keyword querying of three language resource platforms: meta-share @xcite , elra foot_1 and siglex-mwe foot_2 . on the other hand, the linguistic community was approached and asked to fill in a form about resources familiar to them. general information about each resource was recorded, such as its name, a link to it, its type, contact information, the language(s) covered, its size, the maximum length of the contained mwes, whether it includes non-contiguous expressions, its license and accessibility policies, as well as some more advanced information: relevant publications describing it, its special mwe features and the grammatical or lexical formalism (when applicable). our work extends the scope of the parseme survey by exploring and updating the state of mwe resources from 2016 to the end of 2024. several resources published before 2016, either not included in the parseme survey or significantly updated after that, have also been added. moreover, our survey expands the description of each lexical resource in terms of several criteria presented in section 4. ## data collection we aimed at a comprehensive collection of relevant data that would enable us to draw an accurate picture of the mwe resource landscape by cataloging mwe-related lexica and detailing their properties. to achieve this, we defined the criteria for resource inclusion, which focused on retaining only computational lexica, databases, and lists centered on mwes while excluding corpora, terminological databases, and named entity lists, thus departing from the approach of @xcite , that considered both lexical resources and parsed corpora, i.e., treebanks, in their survey. the sources for collecting information about mwe lexica include the following major repositories and databases: 1. european language grid (elg) foot_3 @xcite . this is the largest platform where language technologies and language resources alike, developed by public or private bodies, are cataloged and stored to increase their visibility among potential users and developers and to facilitate access to them. the catalog can be searched with keywords. to find the lexical resources of mwes, we searched within the category lexical / conceptual resource using the word 'expressions' and obtained 71 results. we examined their description to decide upon their inclusion in the dataset. 2. acl anthology foot_4 is an extensive repository of research publications from conferences in the field of computational linguistics. we retrieved all publications between 2016 and 2024 with their bibliographic description, including the title, keywords, and abstracts. we have automatically filtered the publications based on a pre-compiled list of 18 search terms (e.g., 'mwe', 'multiword expression', 'phraseme', etc.). a list of 1,251 publications was retrieved and was then checked by the authors. 3. europhras conference proceedings repository foot_5 provides lists of publications with relevant metadata. all publications after 2016 were checked. the resources retrieved overlapped with those from the elg and acl repositories. 4. phraseology and multiword expressions book series foot_6 of language science press was established in 2017. the series includes books and collections addressing topics related to theoretical, computational, and empirical approaches to multiword expressions, including lexical resources. several resources were identified in these publications that provide a detailed description of the linguistic information and representation of mwes. in addition to the above, we asked community members working on mwes for information on newly developed or updated resources not published in the examined repositories. as noted, a systematic approach was adopted in this survey to identify and select resources related to mwes. inclusion criteria were defined to ensure that the reviewed resources fall within the scope of the survey and reflect the current state of mwerelated lexica that can be used in nlp tasks. the following inclusion criteria were applied: (i) date of creation, update, or publication of the resource, (ii) foreseen usage, (iii) type of lexicon (i.e., computational as opposed to lexica aimed at human users), and (iv) description of mwe entries. for comparison, only 45% of the monolingual and 66% of the multilingual resources in the parseme survey @xcite are classified as mwe lexica; the most significant proportion of the resources are lists of mwes. in the present survey, we exclude lists unless they are supplied with linguistic information such as lemma, syntactic description, semantic properties, etc. summing up, the selected resources contain mwes as entries, focusing on syntactic, semantic, and other information relevant to their structure, meaning, and usage. resources that are freely available or have academic licenses were prioritized to support collaborative and accessible research. finally, the survey focuses on collections supporting nlp tasks involving mwes. ## mwe lexical resources: overview the result of this survey is a list of 66 resources (compared to 107 reported in the parseme survey) dedicated to mwes or containing mwes, alongside other words. the list records detailed information about each resource, such as publication date (or date of the last update), linguality (monolingual, bilingual, multilingual), resource type, acquisition method, licensing information, etc. these are extracted from the paper document-ing the resource, from the resource website, or observed via manual resource inspection. the resources included in the survey are presented in this section provides an overview of the lexical resources included in this survey along the following axes: (a) time span, (b) intended or foreseen usage of the resource, (c) linguality type (i.e., monolingual, bilingual, or multilingual lexicon) and language(s) covered, (d) types of mwes included, (e) acquisition method, (f) accessibility and type of license, (g) representativeness, as well as (h) linking of mwe lexica to other resources (corpora or other lexica). ## conclusions and outlook for future research we set out for this survey by examining several features of existing mwe resources. so, we described the macro-properties of computational lexica, such as linguality, availability, acquisition method, and linkage to external general lexica. in this section, we summarize and discuss our findings. regarding linguality, most lexica are either monolingual (e.g., arabic, portuguese, english) or bilingual (e.g., english-spanish, polish-english). the languages represented are predominantly european, with few exceptions, such as arabic, chinese, japanese, persian, hebrew, and korean. lessresourced languages are underrepresented. the observation made by @xcite , namely that bilingual and multilingual mwe resources, including lexical ones, are hard to find, is still valid. english remains the best-represented language, appearing in nearly half of the language pairs as a source, target, or pivot language. the scarcity of bilingual and multilingual mwe lexica remains a significant challenge that could impede research and development of machine translation and other nlp-involved domains. most resources are mwe-dedicated, but some present both one-word and multi-word entries. mwe-dedicated resources are generally independent and not linked to general lexica. resources tend to address the general language with few exceptions, such as lexica for specific purposes, i.e., expressions denoting sentiments. again, a phenomenon of neglecting within-language diversity is observed as these (predominantly colloquial) language aspects have not been documented. on the availability front, it is good news that most of the resources are included in comprehensive international catalogs or language repositories and are freely available, at least for research purposes. however, the description of the contents of the resources often lacks the detail and clarity required to understand precisely what type of information the resources offer. most of the resources were developed (semi-)automatically. however, the literature does not provide benchmarks or diagnostics for measuring the quality of resources, whether created automati-cally or manually. the size of the resources varies, but generally, resources are not big; this might indicate the effort required to develop such resources. we chose not to include any information on the size of the resources since it is not uniformly documented or the size information is entirely missing. our survey has highlighted the role of eufunded projects related to lexical resources, such as the cost actions parseme and unidive, and horizon-funded project elexis. these initiatives, as well as the european parliament resolution of 11 september 2018 on language equality in the digital age (2018/2028(ini)) 16 , have contributed significantly to the development of resources (see figure 1 ). related to this is the observation that more mwe resources have been developed recently for less-resourced languages rather than well-resourced ones. although this might be due, among others, to the fact that well-resourced languages already possess mwe resources, one should consider that eu initiatives such as the ones listed above provide special encouragement for studying less-resourced languages and language varieties, in line with the eu priority to preserve multilinguality in europe. our recommendations regarding the macroscopic properties of lexica are: -document the design and the contents of the resources thoroughly, clearly, and concisely. in our future research, we will further explore the types of (linguistic) information about mwes provided by these resources and the way in which it is described. we will further try to identify the best encoding practices.