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In this article, we describe the architecture of the LIMA (Libre Multilingual Analyzer) framework and its recent evolution with the addition of new text analysis modules based on deep neural networks. We extended the functionality of LIMA in terms of the number of supported languages while preserving existing configurable architecture and the availability of previously developed rule-based and statistical analysis components. Models were trained for more than 60 languages on the Universal Dependencies 2.5 corpora, WikiNer corpora, and CoNLL-03 dataset. Universal Dependencies allowed us to increase the number of supported languages and generate models that could be integrated into other platforms. This integration of ubiquitous Deep Learning Natural Language Processing models and the use of standard annotated collections using Universal Dependencies can be viewed as a kind of model and data interoperability, complementary to the technical interoperability between systems. [ABSTRACT FROM AUTHOR]

Copyright of Procesamiento del Lenguaje Natural is the property of Sociedad Espanola para el Procesamiento del Lenguaje Natural and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Comparative Literature / Primerjalna Književnost is the property of Slovenian Comparative Literature Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article investigates the stylometric usefulness of morphosyntactic annotation. Focusing on the style of literary texts, it argues that including morphosyntactic annotation in analyses of style has at least two important advantages: (1) maintaining a topic agnostic approach and (2) providing input variables that are interpretable in traditional grammatical terms. This study demonstrates how widely available Universal Dependency parsers can generate useful morphological and syntactic data for texts in a range of languages. These data can serve as the basis for input features that are strongly informative about the style of individual novels, as indicated by accuracy in classification tests. The interpretability of such features is demonstrated by a discussion of the weakness of an "authorial" signal as opposed to the clear distinction among individual works. [ABSTRACT FROM AUTHOR]

This article deals with one of the aspects involved in the compilation of a treebank of Old English within the framework of Universal Dependencies. More specifically, this study addresses the question of how to account for the remarkable degree of Old English morphological relatedness in a type of treebank designed to stress syntactic similarities across languages. The solution proposed and assessed in this study is the addition of an extra field of annotation for morphological relatedness. The data of this analysis comprise 1106 derivatives attaching the prefix un-. Out of these, there are around 80 morphologically complex nouns, adjectives, verbs, and adverbs whose derivation cannot be described gradually, 33 of which are unique formations or hapax legomena according to the attestations provided by the Dictionary of Old English Corpus. The main conclusion is that the specification of short-distance and long-distance morphological relatedness provides the Old English treebank with a paradigmatic dimension that can be particularly relevant for languages with relatively generalised and transparent derivational morphology. [ABSTRACT FROM AUTHOR]

Multi-domain spoken dialogue is a challenging field where the objective of the most proposed ideas is to mimic the human–human dialogue. This paper proposes to tackle the domain selection problem in the context of multi-domain spoken dialogue as a set theory problem to resolve. First, we built each dialogue domain as an ontology following an architecture with some rules to respect. Second, each ontology is considered as a set and its concepts are the elements. Third, an ontology-based classifier is used to map the user sentence into a set of ontologies concepts and to generate an intersection between these concepts. Finally, a new turn analysis and domain selection algorithm is proposed to infer the intended domain from the user sentence using the intersection set and three techniques, namely Domain Rewards, Dominant Concept, and Current Domain. To evaluate the proposed approach, a corpus of 120 simulated dialogues was built to cover four application domains. In our experiment, the assessment of the system is performed by considering all possibilities of a natural verbal interaction where a changing of semantic context occurs during the dialogue. The obtained results show that the system accuracy reaches a satisfactory performance of 83.13% while the average number of turns by dialogue is 6.79. [ABSTRACT FROM AUTHOR]

[rev. of] E. DI NUOVO, Introducing Valico-DU. A Parallel, Learner Italian Treebank for Language Learning Research, Bologna, Pàtron, 2023

Old Permic, also known as Old Komi, is an extinct variety of Komi that was spoken in the late Middle Ages in the lower Vychegda river basin in Northeastern European Russia, in an area that currently is not Komi-speaking. This language variety is attested in fragmentary records from the 14th to 17th century written both in the Old Permic alphabet and in Cyrillic. These records are of significant importance for research on the history of the Komi language. Here we introduce our attempt towards a new Universal Dependencies treebank that will eventually contain the existing corpus of Old Permic in a structured and CoNLL-U annotated format. This will be the first time this material is being made openly available in digital format, and our contribution describes the current state of the art and remaining challenges.

Event extraction, grounded in semantic relationships, can serve as a simplified relation extraction. In this study, we propose an efficient open-domain event annotation framework tailored for subsequent information extraction, with a specific focus on its applicability to low-resource languages. The proposed event annotation method, which is based on event semantic elements, demonstrates substantial time-efficiency gains over traditional Universal Dependencies (UD) tagging. We show how language-specific pretraining outperforms multilingual counterparts in entity and relation extraction tasks and emphasize the importance of task- and language-specific fine-tuning for optimal model performance. Furthermore, we demonstrate the improvement of model performance upon integrating UD information during pre-training, achieving the F1 score of 71.16 and 60.43% for entity and relation extraction respectively. In addition, we showcase the usage of our extracted event graph for improving node classification in a retail banking domain. This work provides valuable guidance on improving information extraction and outlines a methodology for developing training datasets, particularly for low-resource languages.

We use Universal Dependencies (UD) for the study of cross-linguistic diachronic syntactic complexity reduction. Specifically, we look at whether and how scientific English and German minimize the length of syntactic dependency relations in the Late Modern period (ca. 1650–1900). Our linguistic analysis follows the assumption that over time, scientific discourse cross-linguistically develops towards an increasingly efficient syntactic code by minimizing Dependency Length (DL) as a factor of syntactic complexity. For each language, we analyse a large UD-annotated scientific and general language corpus for comparison. While on a macro level, our analysis suggests that there is an overall diachronic cross-linguistic and cross-register reduction in Average Dependency Length (ADL), on the micro level we find that only scientific language shows a sentence length independent reduction of ADL, while general language shows an overall decrease of ADL due to sentence length reduction. We further analyse the syntactic constructions responsible for this reduction in both languages, showing that both scientific English and German increasingly make use of short, intra-phrasal dependency relations while long dependency relations such as clausal embeddings become rather disfavoured over time. [ABSTRACT FROM AUTHOR]

In this paper we present some preliminary remarks on the preparation of a morphosyntactically annotated treebank for Saho within the Universal Dependencies (UD) framework, an annotation scheme used in a large collection of corpora, where Cushitic languages are still marginally represented. We discuss some issues concerning tokenization, morphology, and syntax, with particular reference to cases where deviations from the descriptions proposed in the literature on Saho are deemed necessary, in order to accommodate Saho data within the UD architecture, and cases where some peculiarities of the Saho language require an expansion of the inventories put forward in UD. [ABSTRACT FROM AUTHOR]

Muitas organizações têm dificuldade em recuperar e extrair informações dos seus repositórios de documentos técnicos, em especial operadoras de óleo e gás que há várias décadas acumulam relatórios e documentos geocientíficos. No entanto, a maior parte dos recursos linguísticos para o processamento de linguagem natural é extraída de páginas da internet em inglês. Neste artigo, apresentamos os recursos linguísticos desenvolvidos ao longo do projeto Petrolês, com ênfase no PetroNer, corpus padrão ouro anotado com entidades do domínio, dependências sintáticas, e alinhado a uma ontologia de conceitos geológicos. Relatamos o processo de construção do PetroGold, treebank padrão ouro usado na geração de um modelo customizado para anotação de dependências sintáticas, e detalhamos o processo de anotação de entidades no PetroNer, realizado por meio de regras. Também realizamos um estudo sobre a aplicação das regras no corpus e, por fim, descrevemos características linguísticas do material que compõe o Petrolês, comparando-o com um corpus de textos jornalísticos.

Copyright of Diachronica is the property of John Benjamins Publishing Co. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Question classification based on Bloom's Taxonomy (BT) has been widely accepted and used as a guideline in designing examination questions in many institutions of higher learning. The misclassification of questions may happen when the classification task is conducted manually due to a discrepancy in the understanding of BT by academics. Hence, several automated examination question classification systems have been proposed by researchers to perform question classification accurately. Most of this research has focused on specific subject areas only or single-sentence type questions. There has been a lack of research on question classification for multi-sentence type and multi-subject questions. This paper proposes a question classification system (QCS) to perform the examination of question classification using a semantic and synthetic approach. The questions were taken from various subjects of an engineering diploma course, and the questions were either single- or multiple-sentence types. The QCS was developed using a natural language toolkit (NLTK), Stanford POS tagger (SPOS), Stanford parser's universal dependencies (UD), and WordNet similarity approaches. The QCS used the NLTK to process the questions into sentences and then word tokens, such as SPOS, to tag the word tokens and UD to identify the important word tokens, which were the verbs of the examination questions. The identified verbs were then compared with the BT's verbs list in terms of word sense using the WordNet similarity approach before finally classifying the questions according to BT. The developed QCS achieved an overall 83% accuracy in the classification of a set of 200 examination questions, according to BT. [ABSTRACT FROM AUTHOR]

This paper presents the SAGT Turkish–German code-switching treebank, and observations and annotation challenges we encountered during its development. The treebank consists of transcriptions of bilingual conversations annotated with several layers: language IDs, lemmas, POS tags, morphological features, and dependency relations. The annotations follow the Universal Dependencies annotation scheme and the conventions used in monolingual treebanks as much as possible. We present and discuss a number of issues that arise because of the need for consistent multilingual annotation within a single treebank, as well as the informal language, which is where code-switching is observed most. Besides proposing solutions to these issues, we present some observations about code-switching phenomena that are only possible to observe in a data set with rich linguistic annotation. The treebank was annotated with a focus on quality of annotations through an iterative process of detecting and correcting annotation errors. We also present quantitative measures for indication of annotation quality. The code-switching treebank created in this study is released to the public through Universal Dependencies repositories. [ABSTRACT FROM AUTHOR]

This article presents a Universal Dependency (UD) annotation scheme for Mandarin Chinese, as well as the current UD Chinese HK treebank. Our focus is mainly on parts-of-speech tags and syntactic relations, with a quite large array of phenomena investigated. The main goal is to make transparent the linguistic consideration behind our annotation choices, and show how we articulated these choices with the criteria of Universal Dependencies. This scheme has been developed with reference to two other dependency schemes for this language, i.e. the Chinese Stanford Dependencies (Chang et al., 2009) and the Chinese Dependency Treebank (HIT-SCIR, 2010). We provide mappings between our scheme and the two others. The content of the UD Chinese HK treebank is discussed in relation to the other UD treebanks for Chinese, and the inter-annotator agreement on POS and dependency annotation is reported. Our proposed scheme is motivated by reasoned linguistic analysis, is suitable for cross-linguistic comparison, and produced a high level of agreement between annotators. [ABSTRACT FROM AUTHOR]

This article presents a discussion on the main linguistic phenomena which cause difficulties in the analysis of user-generated texts found on the web and in social media, and proposes a set of annotation guidelines for their treatment within the Universal Dependencies (UD) framework of syntactic analysis. Given on the one hand the increasing number of treebanks featuring user-generated content, and its somewhat inconsistent treatment in these resources on the other, the aim of this article is twofold: (1) to provide a condensed, though comprehensive, overview of such treebanks—based on available literature—along with their main features and a comparative analysis of their annotation criteria, and (2) to propose a set of tentative UD-based annotation guidelines, to promote consistent treatment of the particular phenomena found in these types of texts. The overarching goal of this article is to provide a common framework for researchers interested in developing similar resources in UD, thus promoting cross-linguistic consistency, which is a principle that has always been central to the spirit of UD. [ABSTRACT FROM AUTHOR]

Recently, the language-specific morphosyntactic annotation of InterCorp, a large multilingual parallel corpus, has been replaced by the language-uniform morphosyntactic and syntactic annotation following the guidelines of the Universal Dependencies project. Because the corpus is used predominantly by human users via a token-based concordancer, the CONLL-U format produced by the UDP ipe parser has been extended by attributes such as lemma of the token's syntactic head or morphosyntactic categories of the content verb's auxiliary. We conclude that despite some theoretical and practical issues, the new annotation is a promising solution to the issue of mutually incompatible tagsets within a single corpus. [ABSTRACT FROM AUTHOR]

We describe the first steps in preparation of a treebank of 14th-century Czech in the framework of Universal Dependencies. The Dresden and Olomouc versions of the Gospel of Matthew have been selected for this pilot study, which also involves modification of the annotation guidelines for phenomena that occur in Old Czech but not in Modern Czech. We describe some of these modifications in the paper. In addition, we provide some interesting observations about applicability of a Modern Czech parser to the Old Czech data. [ABSTRACT FROM AUTHOR]

This paper investigates linguistic complexity across natural languages from a corpus-based perspective and relies on the assumptions of linguistic profiling as a methodological framework. We focus in particular on the domain of syntactic complexity and analyze the distribution of a set of features taken as proxies of complexity phenomena at sentence level, which were extracted from 63 treebanks annotated according to the Universal Dependencies formalism. This dataset guarantees that the features considered are modeling the same linguistic phenomena in different treebanks, allowing reliable comparison among languages. We show that our approach is able to identify tendencies of structural proximity between languages not necessarily in line with typologically-supported classification, thus shedding light on new corpus-based findings. [ABSTRACT FROM AUTHOR]

This article investigates the stylometric usefulness of morphosyntactic annotation. Focusing on the style of literary texts, it argues that including morphosyntactic annotation in analyses of style has at least two important advantages: (1) maintaining a topic agnostic approach and (2) providing input variables that are interpretable in traditional grammatical terms. This study demonstrates how widely available Universal Dependency parsers can generate useful morphological and syntactic data for texts in a range of languages. These data can serve as the basis for input features that are strongly informative about the style of individual novels, as indicated by accuracy in classification tests. The interpretability of such features is demonstrated by a discussion of the weakness of an “authorial” signal as opposed to the clear distinction among individual works.

This article deals with one of the aspects involved in the compilation of a treebank of Old English within the framework of Universal Dependencies. More specifically, this study addresses the question of how to account for the remarkable degree of Old English morphological relatedness in a type of treebank designed to stress syntactic similarities across languages. The solution proposed and assessed in this study is the addition of an extra field of annotation for morphological relatedness. The data of this analysis comprise 1106 derivatives attaching the prefix un-. Out of these, there are around 80 morphologically complex nouns, adjectives, verbs, and adverbs whose derivation cannot be described gradually, 33 of which are unique formations or hapax legomena according to the attestations provided by the Dictionary of Old English Corpus. The main conclusion is that the specification of short-distance and long-distance morphological relatedness provides the Old English treebank with a paradigmatic dimension that can be particularly relevant for languages with relatively generalised and transparent derivational morphology.

Com o avanço da área de Processamento de Linguagem Natural (PLN), corpora são recursos que têm tido um lugar de destaque. Mais do que subsidiar estudos linguísticos, eles constituem as bases para o treinamento de modelos de Aprendizagem de Máquina e para o desenvolvimento de aplicações computacionais de ponta. Particularmente, há grande necessidade de corpora anotados, porém sua geração requer outro recurso essencial, o manual de anotação, que instancia o modelo de anotação de interesse para a língua em questão e delineia as decisões de anotação que devem ser adotadas. Neste artigo, exploramos questões relacionadas ao desenvolvimento de manuais para a anotação de corpus em português brasileiro segundo o modelo internacional Universal Dependencies, amplamente adotado na área. Partimos da discussão da evolução do PLN e o uso de corpora, passamos pelas questões, recursos e ferramentas fundamentais relacionados à representação sintática, discutimos o modelo Universal Dependencies e apresentamos as principais decisões tomadas na instanciação de suas diretrizes no português brasileiro. Por questões práticas e de didática, dividimos o manual em duas partes: o Manual de Anotação de PoS tags (anotação morfossintática) e o Manual de Anotação Relações de Dependência. Ambos foram resultado do processo relatado neste artigo e estão disponíveis para livre acesso no site do projeto POeTiSA na Web.

The aim of this article is to take the first steps toward the compilation of a treebank of Old English compatible with the framework of Universal Dependencies (UD). Such a treebank will comprise morphological and syntactic annotation of Old English texts adequate for cross-linguistic comparison, diachronic analysis and natural language processing. The article, therefore, engages in four tasks: (i) identifying the Old English exponents of UD lexical categories; (ii) selecting the Old English exponents of UD morphological features; (iii) finding the areas of Old English morphology that require token indexing in the UD format; and (iv) checking on the relevance of the universal set of dependency relations. The data have been extracted from ParCorOEv2, an open access annotated parallel corpus Old English-English. The main conclusions are that the annotation format calls for two additional fields (gloss and morphological relatedness) and that enhanced dependencies are required in order to account for some syntactic phenomena.

We investigate the correlations between A- and P-lability for verbal arguments with other typological parameters using large, syntactically annotated corpora of online news in 28 languages. To estimate how much lability is observed in a language, we measure associations between Verbs or Verb + Noun combinations and the alternating constructions in which they occur. Our correlational analyses show that high P-lability scores correlate strongly with the following parameters: little or no case marking; weaker associations between lexemes and the grammatical roles A and P; rigid order of Subject and Object; and a high proportion of verb-medial clauses (SVO). Low P-lability correlates with the presence of case marking, stronger associations between nouns and grammatical roles, relatively flexible ordering of Subject and Object, and verb-final order. As for A-lability, it is not correlated with any other parameters. A possible reason is that A-lability is a result of more universal discourse processes, such as deprofiling of the object, and also exhibits numerous lexical and semantic idiosyncrasies. The fact that P-lability is strongly correlated with other parameters can be interpreted as evidence for a more general typology of languages, in which some tend to have highly informative morphosyntactic and lexical cues, whereas others rely predominantly on contextual environment, which is possibly due to fixed word order. We also find that P-lability is more strongly correlated with the other parameters than any of these parameters are with each other, which means that it can be a very useful typological variable.

This study quantitatively examines the first five universals of Greenberg's basic word order typology based on 74 large-scale annotated corpora from two perspectives. The results show that (1) the dominant orders extracted from corpora concur with those retrieved from the World Atlas of Language Structures (henceforth, WALS) and provide knowledge of dominant orders to languages absent in the WALS, demonstrating the feasibility of adopting corpora to determine dominant orders in typological studies; (2) approaching word order as a discrete variable suggests that the relative order of adjective and noun cannot be predicted by the relative orders of object and verb and genitive and noun, which means the violation of Greenberg's related universal; (3) approaching word order as a continuous variable also indicates the violation of this universal; and (4) the language samples based on the annotated corpora database further demonstrates that languages that are in line with this universal are rare and internally heterogeneous. Our findings suggest the possibility of drawing typological conclusions based on the frequencies and probabilities extracted from corpora materials and demonstrate that a more cautious adoption of the well-known universals is needed, indicating the importance of viewing word order features from various perspectives to better capture the characteristics of natural languages. [ABSTRACT FROM AUTHOR]

Copyright of Domínios de Lingu@gem is the property of Dominios de Lingu@gem and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Procesamiento del Lenguaje Natural is the property of Sociedad Espanola para el Procesamiento del Lenguaje Natural and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Question classification based on Bloom’s Taxonomy (BT) has been widely accepted and used as a guideline in designing examination questions in many institutions of higher learning. The misclassification of questions may happen when the classification task is conducted manually due to a discrepancy in the understanding of BT by academics. Hence, several automated examination question classification systems have been proposed by researchers to perform question classification accurately. Most of this research has focused on specific subject areas only or single-sentence type questions. There has been a lack of research on question classification for multi-sentence type and multi-subject questions. This paper proposes a question classification system (QCS) to perform the examination of question classification using a semantic and synthetic approach. The questions were taken from various subjects of an engineering diploma course, and the questions were either single- or multiple-sentence types. The QCS was developed using a natural language toolkit (NLTK), Stanford POS tagger (SPOS), Stanford parser’s universal dependencies (UD), and WordNet similarity approaches. The QCS used the NLTK to process the questions into sentences and then word tokens, such as SPOS, to tag the word tokens and UD to identify the important word tokens, which were the verbs of the examination questions. The identified verbs were then compared with the BT’s verbs list in terms of word sense using the WordNet similarity approach before finally classifying the questions according to BT. The developed QCS achieved an overall 83% accuracy in the classification of a set of 200 examination questions, according to BT.

Copyright of Jezikoslovlje is the property of University of Osijek, Faculty of Philosophy and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, we introduce the resources that we developed for Turkish dependency parsing, which include a novel manually annotated treebank (BOUN Treebank), along with the guidelines we adopted, and a new annotation tool (BoAT). The manual annotation process that we employed was shaped and implemented by a team of four linguists and five Natural Language Processing (NLP) specialists. Decisions regarding the annotation of the BOUN Treebank were made in line with the Universal Dependencies (UD) framework as well as our recent efforts for unifying the Turkish UD treebanks through manual re-annotation. To the best of our knowledge, the BOUN Treebank is the largest Turkish UD treebank. It contains a total of 9761 sentences from various topics including biographical texts, national newspapers, instructional texts, popular culture articles, and essays. In addition, we report the parsing results of a state-of-the-art dependency parser obtained over the BOUN Treebank as well as two other treebanks in Turkish. Our results demonstrate that the unification of the Turkish annotation scheme and the introduction of a more comprehensive treebank lead to improved performance with regards to dependency parsing. [ABSTRACT FROM AUTHOR]

Copyright of Procesamiento del Lenguaje Natural is the property of Sociedad Espanola para el Procesamiento del Lenguaje Natural and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)