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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.
We present a major step towards the creation of the first high-coverage lexicon of polarity shifters. In this work, we bootstrap a lexicon of verbs by exploiting various linguistic features. Polarity shifters, such as ‘abandon’, are similar to negations (e.g. ‘not’) in that they move the polarity of a phrase towards its inverse, as in ‘abandon all hope’. While there exist lists of negation words, creating comprehensive lists of polarity shifters is far more challenging due to their sheer number. On a sample of manually annotated verbs we examine a variety of linguistic features for this task. Then we build a supervised classifier to increase coverage. We show that this approach drastically reduces the annotation effort while ensuring a high-precision lexicon. We also show that our acquired knowledge of verbal polarity shifters improves phrase-level sentiment analysis.
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.
The possibilities of re-use and archiving of spoken and written corpora are affected by personality rights (depending on legal tradition also called: the right of publicity), copyright law and data protection / privacy laws. These recommendations include information about legal aspects which should be considered while creating corpora to ensure the greatest archivability and re-usability possible in compliance with current laws.
The information compiled here shall serve researchers who plan to create corpora or who are involved in evaluation of such measures as a guideline. This information is not exhaustive or to be considered as legal advice. Researchers should consult institutional legal departments and management before making legally relevant decisions. That said, further legal expertise should be sought if possible as early as project planning phases.
This paper deals with the creation of the first morphological treebank for German by merging two pre-existing linguistic databases. The first of these is the linguistic database CELEX which is a standard resource for German morphology. We build on its refurbished and modernized version. The second resource is GermaNet, a lexical-semantic network which also provides partial markup for compounds. We describe the state of the art and the essential characteristics of both databases and our latest revisions. As the merging involves two data sources with distinct annotation schemes, the derivation of the morphological trees for the unified resource is not trivial. We discuss how we overcome problems with the data and format, in particular how we deal with overlaps and complementary scopes. The resulting database comprises about 100,000 trees whose format can be chosen according to the requirements of the application at hand. In our discussion, we show some future directions for morphological treebanks. The Perl script for the generation of the data from the sources will be made publicly available on our website.
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.
This paper gives an insight into the basic concepts for a corpus-based lexical resource of spoken German, which is being developed by the project "The Lexicon of Spoken German"(Lexik des gesprochenen Deutsch, LeGeDe) at the "Institute for the German Language" (Institut für Deutsche Sprache, IDS) in Mannheim. The focus of the paper is on initial ideas of semi-automatic and automatic resources that assist the quantitative analysis of the corpus data for the creation of dictionary content. The work is based on the "Research and Teaching Corpus of Spoken German" (Forschungs- und Lehrkorpus Gesprochenes Deutsch, FOLK).
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.
Languages employ different strategies to transmit structural and grammatical information. While, for example, grammatical dependency relationships in sentences are mainly conveyed by the ordering of the words for languages like Mandarin Chinese, or Vietnamese, the word ordering is much less restricted for languages such as Inupiatun or Quechua, as these languages (also) use the internal structure of words (e.g. inflectional morphology) to mark grammatical relationships in a sentence. Based on a quantitative analysis of more than 1,500 unique translations of different books of the Bible in almost 1,200 different languages that are spoken as a native language by approximately 6 billion people (more than 80% of the world population), we present large-scale evidence for a statistical trade-off between the amount of information conveyed by the ordering of words and the amount of information conveyed by internal word structure: languages that rely more strongly on word order information tend to rely less on word structure information and vice versa. Or put differently, if less information is carried within the word, more information has to be spread among words in order to communicate successfully. In addition, we find that–despite differences in the way information is expressed–there is also evidence for a trade-off between different books of the biblical canon that recurs with little variation across languages: the more informative the word order of the book, the less informative its word structure and vice versa. We argue that this might suggest that, on the one hand, languages encode information in very different (but efficient) ways. On the other hand, content-related and stylistic features are statistically encoded in very similar ways.
The Google Ngram Corpora seem to offer a unique opportunity to study linguistic and cultural change in quantitative terms. To avoid breaking any copyright laws, the data sets are not accompanied by any metadata regarding the texts the corpora consist of. Some of the consequences of this strategy are analyzed in this article. I chose the example of measuring censorship in Nazi Germany, which received widespread attention and was published in a paper that accompanied the release of the Google Ngram data (Michel et al. (2010): Quantitative analysis of culture using millions of digitized books. Science, 331(6014): 176–82). I show that without proper metadata, it is unclear whether the results actually reflect any kind of censorship at all. Collectively, the findings imply that observed changes in this period of time can only be linked directly to World War II to a certain extent. Therefore, instead of speaking about general linguistic or cultural change, it seems to be preferable to explicitly restrict the results to linguistic or cultural change ‘as it is represented in the Google Ngram data’. On a more general level, the analysis demonstrates the importance of metadata, the availability of which is not just a nice add-on, but a powerful source of information for the digital humanities.
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.
Unknown words are a challenge for any NLP task, including sentiment analysis. Here, we evaluate the extent to which sentiment polarity of complex words can be predicted based on their morphological make-up. We do this on German as it has very productive processes of derivation and compounding and many German hapax words, which are likely to bear sentiment, are morphologically complex. We present results of supervised classification experiments on new datasets with morphological parses and polarity annotations.
Recently, a claim was made, on the basis of the German Google Books 1-gram corpus (Michel et al., Quantitative Analysis of Culture Using Millions of Digitized Books. Science 2010; 331: 176–82), that there was a linear relationship between six non-technical non-Nazi words and three ‘explicitly Nazi words’ in times of World War II (Caruana-Galizia. 2015. Politics and the German language: Testing Orwell’s hypothesis using the Google N-Gram corpus. Digital Scholarship in the Humanities [Online]. http://dsh.oxfordjournals.org/cgi/doi/10.1093/llc/fqv011 (accessed 15 April 2015)). Here, I try to show that apparent relationships like this are the result of misspecified models that do not take into account the temporal aspect of time-series data. The main point of this article is to demonstrate why such analyses run the risk of incorrect statistical inference, where potential effects are both meaningless and can potentially lead to wrong conclusions.
Multinomial processing tree (MPT) models are a class of measurement models that account for categorical data by assuming a finite number of underlying cognitive processes. Traditionally, data are aggregated across participants and analyzed under the assumption of independently and identically distributed observations. Hierarchical Bayesian extensions of MPT models explicitly account for participant heterogeneity by assuming that the individual parameters follow a continuous hierarchical distribution.We provide an accessible introduction to hierarchical MPT modeling and present the user-friendly and comprehensive R package TreeBUGS, which implements the two most important hierarchical MPT approaches for participant heterogeneity—the beta-MPT approach (Smith & Batchelder, Journal of Mathematical Psychology 54:167-183, 2010) and the latent-trait MPT approach (Klauer, Psychometrika 75:70-98, 2010). TreeBUGS reads standard MPT model files and obtains Markov-chain Monte Carlo samples that approximate the posterior distribution. The functionality and output are tailored to the specific needs of MPT modelers and provide tests for the homogeneity of items and participants, individual and group parameter estimates, fit statistics, and within- and between-subjects comparisons, as well as goodness-of-fit and summary plots. We also propose and implement novel statistical extensions to include continuous and discrete predictors (as either fixed or random effects) in the latent-trait MPT model.
Modeling the properties of German phrasal compounds within a usage-based constructional approach
(2017)
This paper discusses phrasal compounds in German (e.g.“Man-muss-doch-überalles-reden-können”-Credo, ‘one-should-be-able-to-talk-about-everything motto’). It provides the first empirically based investigation and description of this wordformation type within the theoretical framework of construction grammar. While phrasal compounds pose a problem for “traditional” generative approaches, I argue that a usage-based constructional model (e.g. Langacker 1987; Goldberg 2006) which takes into consideration aspects of frequency provides a suitable approach to modeling and explaining their properties. For this purpose, a large inventory of phrasal compounds was extracted from the German Reference Corpus (DeReKo) and modeled as pairings of form and meaning at different levels of specificity and abstractness within a bottom-up process.
Overall, this paper not only presents a new and original approach to phrasal compounds, but also offers interesting perspectives for dealing with composition in general.
Researchers interested in the sounds of speech or the physical gestures of Speakers make use of audio and video recordings in their work. Annotating these recordings presents a different set of requirements to the annotation of text. Special purpose tools have been developed to display video and audio Signals and to allow the creation of time-aligned annotations. This chapter reviews the most widely used of these tools for both manual and automatic generation of annotations on multimodal data.
This paper provides a formal semantic analysis of past interpretation in Medumba (Grassfields Bantu), a graded tense language. Based on original fieldwork, the study explores the empirical behavior and meaning contribution of graded past morphemes in Medumba and relates these to the account of the phenomenon proposed in Cable (Nat Lang Semant 21:219–276, 2013) for Gĩkũyũ. Investigation reveals that the behavior of Medumba gradedness markers differs from that of their Gĩkũyũ counterparts in meaningful ways and, more broadly, discourages an analysis as presuppositional eventuality or reference time modifiers. Instead, the Medumba markers are most appropriately analyzed as quantificational tenses. It also turns out that Medumba, though belonging to the typological class of graded tense languages, shows intriguing similarities to genuinely tenseless languages in allowing for temporally unmarked sentences and exploiting aspectual and pragmatic cues for reference time resolution. The more general cross-linguistic implication of the study is that the set of languages often subsumed under the label “graded tense” does not in fact form a natural class and that more case-by-case research is needed to refine this category.