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In this paper, we will present a first attempt to classify commonly confused words in German by consulting their communicative functions in corpora. Although the use of so-called paronyms causes frequent uncertainties due to similarities in spelling, sound and semantics, up until now the phenomenon has attracted little attention either from the perspective of corpus linguistics or from cognitive linguistics. Existing investigations rely on structuralist models, which do not account for empirical evidence. Still, they have developed an elaborate model based on formal criteria, primarily on word formation (cf. Lăzărescu 1999). Looking from a corpus perspective, such classifications are incompatible with language in use and cognitive elements of misuse.
This article sketches first lexicological insights into a classification model as derived from semantic analyses of written communication. Firstly, a brief description of the project will be provided. Secondly, corpus-assisted paronym detection will be focused. Thirdly, in the main section the paper concerns the description of the datasets for paronym classification and the classification procedures. As a work in progress, new insights will continually be extended once spoken and CMC data are added to the investigations.
This paper presents a short insight into a new project at the "Institute for the German Language” (IDS) (Mannheim). It gives an insight into some basic ideas for a corpus-based dictionary of spoken German, which will be developed and compiled by the new project "The Lexicon of spoken German” (Lexik des gesprochenen Deutsch, LeGeDe). The work is based on the "Research and Teaching Corpus of Spoken German” (Forschungs- und Lehrkorpus Gesprochenes Deutsch, FOLK), which is implemented in the "Database for Spoken German” (Datenbank für Gesprochenes Deutsch, DGD). Both resources, the database and the corpus, have been developed at the IDS.
This paper presents a survey on hate speech detection. Given the steadily growing body of social media content, the amount of online hate speech is also increasing. Due to the massive scale of the web, methods that automatically detect hate speech are required. Our survey describes key areas that have been explored to automatically recognize these types of utterances using natural language processing. We also discuss limits of those approaches.
The Manatee corpus management system on which the Sketch Engine is built is efficient, but unable to harness the power of today’s multiprocessor machines. We describe a new, compatible implementation of Manatee which we develop in the Go language and report on the performance gains that we obtained.
In the first volume of Corpus Linguistics and Linguistic Theory, Gries (2005. Null-hypothesis significance testing of word frequencies: A follow-up on Kilgarriff. Corpus Linguistics and Linguistic Theory 1(2). doi:10.1515/ cllt.2005.1.2.277. http://www.degruyter.com/view/j/cllt.2005.1.issue-2/cllt.2005. 1.2.277/cllt.2005.1.2.277.xml: 285) asked whether corpus linguists should abandon null-hypothesis significance testing. In this paper, I want to revive this discussion by defending the argument that the assumptions that allow inferences about a given population – in this case about the studied languages – based on results observed in a sample – in this case a collection of naturally occurring language data – are not fulfilled. As a consequence, corpus linguists should indeed abandon null-hypothesis significance testing.
As a consequence of a recent curation project, the Dortmund Chat Corpus is available in CLARIN-D research infrastructures for download and querying. In a legal expertise it had been recommended that standard measures of anonymisation be applied to the corpus before its republication. This paper reports about the anonymisation campaign that was conducted for the corpus. Anonymisation has been realised as categorisation, and the taxonomy of anonymisation categories applied is introduced and the method of applying it to the TEI files is demonstrated. The results of the anonymisation campaign as well as issues of quality assessment are discussed. Finally, pseudonymisation as an alternative to categorisation as a method of the anonymisation of CMC data is discussed, as well as possibilities of an automatisation of the process.
Our paper describes an experiment aimed to assessment of lexical coverage in web corpora in comparison with the traditional ones for two closely related Slavic languages from the lexicographers’ perspective. The preliminary results show that web corpora should not be considered ― inferior, but rather ― different.
We use a convolutional neural network to perform authorship identification on a very homogeneous dataset of scientific publications. In order to investigate the effect of domain biases, we obscure words below a certain frequency threshold, retaining only their POS-tags. This procedure improves test performance due to better generalization on unseen data. Using our method, we are able to predict the authors of scientific publications in the same discipline at levels well above chance.
We present an event-related potentials (ERP) study that addresses the question of how pieces of information pertaining to semantic roles and event structure interact with each other and with the verb’s meaning. Specifically, our study investigates German verb-final clauses with verbs of motion such as fliegen ‘fly’ and schweben ‘float, hover,’ which are indeterminate with respect to agentivity and event structure. Agentivity was tested by manipulating the animacy of the subject noun phrase and event structure by selecting a goal adverbial, which makes the event telic, or a locative adverbial, which leads to an atelic reading. On the clause-initial subject, inanimates evoked an N400 effect vis-à-vis animates. On the adverbial phrase in the atelic (locative) condition, inanimates showed an N400 in comparison to animates. The telic (goal) condition exhibited a similar amplitude like the inanimate-atelic condition. Finally, at the verbal lexeme, the inanimate condition elicited an N400 effect against the animate condition in the telic (goal) contexts. In the atelic (locative) condition, items with animates evoked an N400 effect compared to inanimates. The combined set of findings suggest that clause-initial animacy is not sufficient for agent identification in German, which seems to be completed only at the verbal lexeme in our experiment. Here non-agents (inanimates) changing their location in a goal-directed way and agents (animates) lacking this property are dispreferred and this challenges the assumption that change of (locational) state is generally a defining characteristic of the patient role. Besides this main finding that sheds new light on role prototypicality, our data seem to indicate effects that, in our view, are related to complexity, i.e., minimality. Inanimate subjects or goal arguments increase processing costs since they have role or event structure restrictions that animate subjects or locative modifiers lack.
Catching the common cause: extraction and annotation of causal relations and their participants
(2017)
In this paper, we present a simple, yet effective method for the automatic identification and extraction of causal relations from text, based on a large English-German parallel corpus. The goal of this effort is to create a lexical resource for German causal relations. The resource will consist of a lexicon that describes constructions that trigger causality as well as the participants of the causal event, and will be augmented by a corpus with annotated instances for each entry, that can be used as training data to develop a system for automatic classification of causal relations. Focusing on verbs, our method harvested a set of 100 different lexical triggers of causality, including support verb constructions. At the moment, our corpus includes over 1,000 annotated instances. The lexicon and the annotated data will be made available to the research community.
The paper presents best practices and results from projects dedicated to the creation of corpora of computer-mediated communication and social media interactions (CMC) from four different countries. Even though there are still many open issues related to building and annotating corpora of this type, there already exists a range of tested solutions which may serve as a starting point for a comprehensive discussion on how future standards for CMC corpora could (and should) be shaped like.
CMC Corpora in DeReKo
(2017)
We introduce three types of corpora of computer-mediated communication that have recently been compiled at the Institute for the German Language or curated from an external project and included in DeReKo, the German Reference Corpus, namely Wikipedia (discussion) corpora, the Usenet news corpus, and the Dortmund Chat Corpus. The data and corpora have been converted to I5, the TEI customization to represent texts in DeReKo, and are researchable via the web-based IDS corpus research interfaces and in the case of Wikipedia and chat also downloadable from the IDS repository and download server, respectively.
This paper discusses changes of lexicographic traditions with respect to approaches to meaning descriptions towards more cognitive perspectives. I will uncover how cognitive aspects can be incorporated into meaning descriptions based on corpus-driven analysis. The new German Online dictionary “Paronyme − Dynamisch im Kontrast” (Storjohann 2014; 2016) is concerned with easily confused words such as effektiv/effizient, sensibel/sensitiv. It is currently in the process of being developed and it aims at adopting a more conceptual and encyclopaedic approach to meaning by incorporating cognitive features. As a corpus-guided reference work it strives to adequately reflect ideas such as conceptual structure, categorisation and knowledge. Contrastive entries emphasise aspects of usage, comparing conceptual categories and indicate the (metonymic) mapping of knowledge. Adaptable access to lexicographic details and variable search options offer different foci and perspectives on linguistic information, and authentic examples reflect prototypical structures. Some of the cognitive features are demonstrated with the help of examples. Firstly, I will outline how patterns of usage imply conceptual categories as central ideas instead of sufficiently logical criteria of semantic distinction. In this way, linguistic findings correlate better with how users conceptualise language. Secondly, it is pointed out how collocates are treated as family members and fillers in contexts. Thirdly, I will demonstrate how contextual structure and functions are included summarising referential information. Details are drawn from corpus data, they are usage-based linguistic patterns illustrating conversational interaction and semantic negotiations in contemporary public discourse. Finally, I will outline consultation routines which activate different facets of structural knowledge, e.g. through changes of the ordering of information or through the visualisation of semantic networks.
This paper discusses how cognitive aspects can be incorporated into lexicographic meaning descriptions based on corpus-driven analysis. The new German Online dictionary “Paronyme − Dynamisch im Kontrast” is concerned with easily confused words such as effektiv/effizient, sensibel/sensitiv. It is currently in the process of being developed and it aims at adopting a more conceptual and encyclopedic approach to meaning. Contrastive entries emphasize usage, comparing conceptual categories and indicating the mapping of knowledge. Adaptable access to lexicographic details offers different perspectives on information, and authentic examples reflect prototypical structures.
Some of the cognitive features are demonstrated with the help of examples. Firstly, I will outline how patterns of usage imply conceptual categories as central ideas instead of sufficiently logical criteria of semantic distinction. In this way, linguistic findings correlate better with how users conceptualize language. Secondly, it is pointed out how collocates are family members and fillers in contexts. Thirdly, I will demonstrate how contextual structure and function are included by summarizing referential information. Details are drawn from corpus data; they are usage-based patterns illustrating conversational interaction and semantic negotiation in contemporary public discourse. Finally, I will show flexible consultation routines where the focus on structural knowledge changes.
The paper reports on the results of a scientific colloquium dedicated to the creation of standards and best practices which are needed to facilitate the integration of language resources for CMC stemming from different origins and the linguistic analysis of CMC phenomena in different languages and genres. The key issue to be solved is that of interoperability – with respect to the structural representation of CMC genres, linguistic annotations metadata, and anonymization/pseudonymization schemas. The objective of the paper is to convince more projects to partake in a discussion about standards for CMC corpora and for the creation of a CMC corpus infrastructure across languages and genres. In view of the broad range of corpus projects which are currently underway all over Europe, there is a great window of opportunity for the creation of standards in a bottom-up approach.
We present an approach to making existing CLARIN web services usable for spoken language transcriptions. Our approach is based on a new TEI-based ISO standard for such transcriptions. We show how existing tool formats can be transformed to this standard, how an encoder/decoder pair for the TCF format enables users to feed this type of data through a WebLicht tool chain, and why and how web services operating directly on the standard format would be useful.
In my talk, I present an empirical approach to detecting and describing proverbs as frozen sentences with specific functions in current language use. We have developed this approach in the EU project ‘SprichWort’ (based on the German Reference Corpus). The first chapter illustrates selected aspects of our complex, iterative procedure to validate proverb candidates. Based on our corpus-driven lexpan methodology of slot analysis I then discuss semantic restrictions of proverb patterns. Furthermore, I show different degrees of proverb quality ranging from genuine proverbs to non-proverb realizations of the same abstract pattern. On the one hand, the corpus validation reveals that proverbs are definitely perceived and used as relatively fixed entities and often as sentences. On the other hand, proverbs are not only interpreted as an interesting unique phenomenon but also as part of the whole lexicon, embedded in networks of different lexical items.
Creating CorCenCC (Corpws Cenedlaethol Cymraeg Cyfoes - The National Corpus of Contemporary Welsh)
(2017)
CorCenCC is an interdisciplinary and multiinstitutional project that is creating a large-scale, open-source corpus of contemporary Welsh. CorCenCC will be the first ever large-scale corpus to represent spoken, written and electronicallymediated Welsh (compiling an initial data set of 10 million Welsh words), with a functional design informed, from the outset, by representatives of all anticipated academic and community user groups.
In the NLP literature, adapting a parser to new text with properties different from the training data is commonly referred to as domain adaptation. In practice, however, the differences between texts from different sources often reflect a mixture of domain and genre properties, and it is by no means clear what impact each of those has on statistical parsing. In this paper, we investigate how differences between articles in a newspaper corpus relate to the concepts of genre and domain and how they influence parsing performance of a transition-based dependency parser. We do this by applying various similarity measures for data point selection and testing their adequacy for creating genre-aware parsing models.
In the NLP literature, adapting a parser to new text with properties different from the training data is commonly referred to as domain adaptation. In practice, however, the differences between texts from different sources often reflect a mixture of domain and genre properties, and it is by no means clear what impact each of those has on statistical parsing. In this paper, we investigate how differences between articles in a newspaper corpus relate to the concepts of genre and domain and how they influence parsing performance of a transition-based dependency parser. We do this by applying various similarity measures for data point selection and testing their adequacy for creating genre-aware parsing models.