Automatic Verb Classification Based on Statistical Distributions of Argument Structure

Information and argument structures in Sociology research abstracts

The event structures expressed by sentences consist of relations among subevents and their participant roles, called thematic roles or relations. We will say that a theory of the thematic structure of sentences is strictly configurational if every thematic role distinction is represented by a configurationally distinct position in this structure. Strict Thematic Configurationality therefore implies an isomorphism between thematic relations and equivalence classes of positions in syntactic structures. Thus, given this principle, thematic or event-structural aspects of semantics must be purely syntactic. More specifically, meaning or interpretation in respect to these aspects must be a function of category type (functional properties) and configuration (purely formal structural/syntactic relations) only. There can be no representation of thematic relations as substantive categories or features. The syntactic forms representing thematic structure may or may not be identified with those of a component of grammatical syntax. However, a minimalist conception of Strict Thematic Configurationality would seem to require that they are: that there is no autonomous system of thematic relations apart from grammatical syntax.

Background : Some individuals with agrammatic aphasia have difficulty producing verbs when naming and generating sentences (Miceli, Silveri, Villa, & Caramazza, 1984; Saffran, Schwartz, & Marin, 1980; Zingeser & Berndt, 1990). And when verbs are produced there is an over-reliance on verbs requiring simple argument structure arrangements (Thompson, Lange, Schneider, & Shapiro, 1997; Thompson, Shapiro, Schneider, & Tait, 1994). Verbs, as argument-taking elements, show especially complex semantic and argument structure properties. This study investigated the role these properties have on verb production in individuals with agrammatic aphasia. Aim : This treatment study examined the extent to which semantic class and argument structure properties of verbs influenced the ability of seven individuals with agrammatic Broca's aphasia to retrieve verbs and then use them in correct sentence production. Verbs from two semantic classes and two argument structure categories were trained using either a semantic or an argument structure verb retrieval treatment. Specifically, acquisition and generalisation to trained and untrained verbs within and across semantic and argument structure categories was examined. In addition, the influence of verb production on each participant's sentence production was also examined. Methods & Procedures : Utilising a single-subject crossover design in combination with a multiple baseline design across subjects and behaviours, seven individuals with agrammatic aphasia were trained to retrieve verbs with specific argument structures from two semantic classes under two treatment conditions--semantic verb retrieval treatment and verb argument structure retrieval treatment. Treatment was provided on two-place and three-place motion or change of state verbs, counterbalanced across subjects and behaviours. A total of 102 verbs, depicted in black and white drawings, were utilised in the study, divided equally into motion and change of state verbs (semantic classes) and one-place, two-place, and three-place verbs (argument structure arrangements). Verbs were controlled for syllable length, picturability, phonological complexity, and frequency. These same stimulus items were used to elicit the sentence production probe. Outcomes & Results : Both treatments revealed significant effects in facilitating acquisition of verb retrieval in all participants. Minimal within and across verb category generalisation occurred. However, it was found that as retrieval of verbs improved, grammatical sentence production improved. This occurred without direct treatment on sentence, production.

The extraposition of a relative clause creates a discontinuous dependency between the relative clause and its host noun phrase, as in A man just entered the bank who claimed to have a gun. Since discontinuous dependencies are known to increase processing effort, a key question is why speakers produce them in the first place. Some factors known to affect extraposition – for example, the length of the relative clause and the main verb phrase – have received processing-based explanations, but others haven’t. We focus on two factors described by previous research: verb type and the grammatical function of the noun phrase hosting the relative clause. Specifically, extraposition from grammatical subjects is more common with unaccusative and passive verbs in English; further, extraposition is more common from grammatical objects than subjects in Dutch and German. We replicate these findings using corpus data from Persian. Further, we propose that verb type and grammatical function can be linked to a single underlying notion: argument structure. We demonstrate that argument structure modulates the likelihood of extraposition in Persian. We suggest that this occurs because speakers choose to extrapose relative clauses in order to keep the main clause verb close to its internal arguments. This explanation extends previous findings in psycholinguistics on the role of argument structure in speech planning during language production.

In recent years, the Italian national institute of statistics (Istat), together with most National Statistical Institutes, is progressively moving from traditional production models based on the use of primary source of information - represented by direct surveys - to new production strategies based on the combined use of different primary and secondary sources of information. As result, new multisource statistical processes have been built, that guarantee a major improvement of both amount and quality of information about several phenomena of public interest. In this context, the Total Process Error (TPE) framework has been recently proposed in literature for assessing the quality of multisource processes. The TPE framework represents an evolution of the Zhang’s two-phase life-cycle approach and it additionally includes an operational tool to connect the steps of the multisource production process to the phases of the quality evaluation framework. TPE framework can be used both to support a multisource process design and to monitor an entire production process, in order to provide key elements to assess the quality of both the processes and their statistical outputs. In the present work, we describe as a case study in the new context of Istat production of official statistics the use of the TPE framework to support the process design of the Register for Public Administrations.

Background/Objectives: Antimicrobial resistance (AMR) is a growing global health threat, requiring an approach that integrates human, animal, and environmental health. Public awareness and responsible antibiotic use are key to combating AMR. This study examines the knowledge, attitudes, and practices related to antibiotic use among the general population in Serbia, exploring their impact on antimicrobial stewardship efforts. Methods: A cross-sectional study was conducted in December 2022 using a three-stage stratified random sample of the Serbian population. The Eurobarometer questionnaire was utilized with permission from the European Commission. Statistical analyses included multivariate ordinal logistic regression to identify predictors of desirable attitudes and behaviors related to antibiotic use. Results: Almost two-thirds of respondents (61.6%) reported not receiving any advice on rational antibiotic use, underscoring the need for education of the general population and raising awareness. A Higher Antibiotic Knowledge Score was associated with a 60% greater likelihood of favorable attitudes and a 21% greater likelihood of rational antibiotic use. Pharmacists were identified as the primary source of antibiotic-related information for the general population in Serbia, but there is limited public interest and awareness of antibiotic use in animals, as well as of the bans on using antibiotics to stimulate growth in farm animals within the EU. Conclusions: Through targeted educational interventions, strengthening interdisciplinary collaboration and AMR control measures is necessary for human and veterinary medicine. Although pharmacists are the primary source of information about antibiotics for the population in Serbia, collaboration with physicians and their empowerment should be introduced to strengthen antimicrobial stewardship further.

Semantic Role Labeling (SRL) is to determine the relationship between predicates and their arguments in a sentence. In order to determine the semantic roles, a large amount of corpus with annotated semantic roles is required. Nowadays the most widely used semantic corpus is Proposition Bank (PropBank) which is semantically annotated over the predicate and argument structure. But the Korean version of the PropBank could not be widely used because the corpus has limitation in size and be different from its original English version in its usability. To solve these problems, we also used another semantic tagged corpus, built by Sejong Plan, which is nation-wide Korean corpus construction project. However, the task of corpus construction with semantic roles defined in PropBank and Sejong is much time-consuming and these corpora use their own role sets. They finally require a way of converting one role to other side role(s). In this paper, we propose a method for automatically converting the roles. First, we use similarity between a given noun argument word to find a new role and noun words appearing in the example sentences of candidate roles. Second, we extract suffix of the argument word and estimate closeness between the suffix and candidate roles. Finally, the predicate itself is used for selection,that is we calculate the closeness between the predicate and the candidate roles. With these, the role is decided among multiple candidate roles. In the experiment, we convert 491 arguments automatically and about 78% of them show the agreement with manually annotated arguments.

The present volume is centered around five linguistic themes: argument structure and encoding strategies; argument structure and verb classes; unexpressed arguments; split intransitivity; and existential and presentational constructions. The articles also cover a variety of typologically different languages, and they offer new data from under-researched languages on the issues of event and argument structure. In some cases novel perspectives from widely discussed languages on highly debated topics are offered, also addressing more theoretical aspects concerning the predictability and derivation of linking. Several contributions apply current models of the lexicon–syntax interface to synchronic data. Other contributions focus on diachrony and are based on extensive use of corpora. Yet others, although empirically and theoretically grounded, privilege a methodological discussion, presenting analyses based on thorough and long-standing fieldwork.

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Benefiting from strong generalization ability, pre-trained vision-language models (VLMs), e.g., CLIP, have been widely utilized in zero-shot scene understanding. Unlike simple recognition tasks, grounded situation recognition (GSR) requires the model not only to classify salient activity (verb) in the image, but also to detect all semantic roles that participate in the action. This complex task usually involves three steps: verb recognition, semantic role grounding, and noun recognition. Directly employing class-based prompts with VLMs and grounding models for this task suffers from several limitations, e.g., it struggles to distinguish ambiguous verb concepts, accurately localize roles with fixed verb-centric template input, and achieve context-aware noun predictions. In this paper, we argue that these limitations stem from the model's poor understanding of verb/noun classes. To this end, we introduce a new approach for zero-shot GSR via Language EXplainer (LEX), which significantly boosts the model's comprehensive capabilities through three explainers: 1) verb explainer, which generates general verb-centric descriptions to enhance the discriminability of different verb classes; 2) grounding explainer, which rephrases verb-centric templates for clearer understanding, thereby enhancing precise semantic role localization; and 3) noun explainer, which creates scene-specific noun descriptions to ensure context-aware noun recognition. By equipping each step of the GSR process with an auxiliary explainer, LEX facilitates complex scene understanding in real-world scenarios. Our extensive validations on the SWiG dataset demonstrate LEX's effectiveness and interoperability in zero-shot GSR.

This study describes the thematic roles of Somali; a language that manifests unorthodox grammatical structures due to the use of the focus particle. A mapping of some language features related to the semantic-syntactic interface is carried out. The effect of the meaning of the lexical items is tested to whether it affects the syntactic structures of the sentences. It was found that the word order of Somali is determined by pragmatic and sociolinguistics factors. The focus particle of Somali plays a key-role in the Surface structure of the sentences. However; the thematic roles of the language appear not to be influenced by the grammatical manifestation of the language at the surface structure. Rather, they are determined at the deep structure level. Somali, being a pro-drop language, shows that predicates require obligatory external arguments while internal arguments are determined by the verb class and kind. Some structures show that certain verbs require PPs as obligatory arguments. Keywords: Somali, Theta Theory, Thematic Roles

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Sources of information and HRT prescribing practices among gynecologists in Puebla, Mexico

ObjectiveTo assess primary sources of information about dietary supplements (DS) and to determine if the sources differ between geographic regions.MethodsQuestionnaires and verification of supplement labels were used to assess DS use and sources of information for 646 healthy male and female subjects aged 21–75 who had been recruited for lipoprotein assessment studies at Tufts University and UC Davis. A chi‐square test with an alpha of 0.05 was used.ResultsDS were taken by 65.2% of participants (M 49.5%; F 50.5%). In contrast to earlier studies that showed physicians were infrequent sources of DS information, this study found the most common source of DS advice for all respondents was physicians (52.4%). Other sources of information differed significantly depending on geographic location. Those in the east were more likely to ask health food retailers or pharmacists (p<0.001). Those in the west were more likely to rely on family (p=0.002) and friends (p=0.021) and magazines/journals/news and the internet (p<0.001).ConclusionWhen DS use is discussed with health care providers more informed use and fewer possible drug‐DS interactions may occur. Physicians may benefit from increased education about DS since they will be accountable for accurate information regarding DS use. (Research support: Bastyr University)

This study is qualitative descriptive research that examines the English speech act verb “order” in English. The purpose of this study is to analyse the argument structure and its role in semantics. The type of data used in this study is secondary data sourced from the Corpus of Contemporary American English (COCA). The research instrument utilized in this study is a human instrument supported by hardware such as a computer, along with software such as Microsoft Word and Microsoft Excel, as well as note-taking tools like pen and paper. Data for this study was collected using the corpus linguistics method and observation methods with note-taking techniques. The data were analysed by using the macro role theory by van Vallin & Lapolla (1997). The study results indicate that the verb "order" can have two arguments, the actor argument and the undergoer argument, and each argument can have its semantic role. The actor argument can entail the semantic role of the agent, while the undergoer argument can entail the semantic role of the theme.