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In 2010, ISO published a standard for syntactic annotation, ISO 24615:2010 (SynAF). Back then, the document specified a comprehensive reference model for the representation of syntactic annotations, but no accompanying XML serialisation. ISO’s subcommittee on language resource management (ISO TC 37/SC 4) is working on making the SynAF serialisation ISOTiger an additional part of the standard. This contribution addresses the current state of development of ISOTiger, along with a number of open issues on which we are seeking community feedback in order to ensure that ISOTiger becomes a useful extension to the SynAF reference model.
This paper describes a first version of an integrated e-dictionary translating possessive constructions from English to Zulu. Zulu possessive constructions are difficult to learn for non-mother tongue speakers. When translating from English into Zulu, a speaker needs to be acquainted with the nominal classification of nouns indicating possession and possessor. Furthermore, (s)he needs to be informed about the morpho-syntactic rules associated with certain combinations of noun classes. Lastly, knowledge of morpho-phonetic changes is also required, because these influence the orthography of the output word forms. Our approach is a novel one in that we combine e-lexicography and natural language processing by developing a (web) interface supporting learners, as well as other users of the dictionary to produce Zulu possessive constructions. The final dictionary that we intend to develop will contain several thousand nouns which users can combine as they wish. It will also translate single words and frequently used multiword expressions, and allow users to test their own translations. On request, information about the morpho-syntactic and morpho-phonetic rules applied by the system are displayed together with the translation. Our approach follows the function theory: the dictionary supports users in text production, at the same time fulfilling a cognitive function.
Alors que de nombreuses études en analyse conversationnelle se sont intéressées à la manière dont des locuteurs co-construisent un tour de parole (notamment sur le plan syntaxique et prosodique), la façon dont la co-construction est ensuite évaluée n'a pas encore été étudiée en profondeur au sein de la littérature interactionniste. Ici, nous étudions deux pratiques permettant à un locuteur de valider une co-construction, à savoir l'acquiescement simple et l'hétéro-répétition de la complétion. En menant une analyse séquentielle et multimodale de plusieurs séquences de co-construction en français, nous montrons qu’à travers ces deux procédés – qui semblent au premier abord similaires dans leur fonctionnement – les locuteurs effectuent une évaluation très différente : tandis que l'acquiescement simple valide la complétion proposée uniquement comme une version possible, l'hétéro-répétition la valide comme étant une complétion complètement adéquate. Cette contribution met en évidence que les interactants exploitent des ressources audibles aussi bien que visibles afin de manifester si et dans quel sens ils acceptent la complétion de leur tour de parole de la part d’un coparticipant. Nous soulignons l’importance d’étudier en détail les différents formatages possibles des tours évaluant une complétion afin de pouvoir distinguer différentes formes « d’acceptation » et de révéler la manière dont les locuteurs peuvent finement négocier leur position en tant que (co-)auteur ou destinataire d’un tour de parole.
Measuring the quality of metadata is only possible by assessing the quality of the underlying schema and the metadata instance. We propose some factors that are measurable automatically for metadata according to the CMD framework, taking into account the variability of schemas that can be defined in this framework. The factors include among others the number of elements, the (re-)use of reusable components, the number of filled in elements. The resulting score can serve as an indicator of the overall quality of the CMD instance, used for feedback to metadata providers or to provide an overview of the overall quality of metadata within a repository. The score is independent of specific schemas and generalizable. An overall assessment of harvested metadata is provided in form of statistical summaries and the distribution, based on a corpus of harvested metadata. The score is implemented in XQuery and can be used in tools, editors and repositories.
Die vorliegende empirische Untersuchung befasst sich mit einer Umfrage zur Wörterbuchbenutzung bei 41 Studentinnen und Studenten des Dipartimento di Filologia, Letteratura e Linguistica der Universität Pisa, dasselbe Department, an dem auch das deutsch-italienische sprachwissenschaftliche Online-Wörterbuch DIL erarbeitet worden ist (vgl. Flinz: 2011). Die schriftliche Umfrage wurde in Anlehnung an Hartmanns 5. Hypothese „An analysis of users´ needs should precede dictionary design“ (1989) durchgeführt. Die wichtigsten Ergebnisse waren von großer Bedeutung für die Gestaltung der makro- und mikrostrukturellen Eigenschaften des Fachwörterbuches. Die Ergebnisse der Untersuchung und die daraus folgenden Reflektionen werden in thematischen Kernblöcken vorgestellt.
We examine the task of relation extraction in the food domain by employing distant supervision. We focus on the extraction of two relations that are not only relevant to product recommendation in the food domain, but that also have significance in other domains, such as the fashion or electronics domain. In order to select suitable training data, we investigate various degrees of freedom. We consider three processing levels being argument level, sentence level and feature level. As external resources, we employ manually created surface patterns and semantic types on all these levels. We also explore in how far rule-based methods employing the same information are competitive.
We examine the task of separating types from brands in the food domain. Framing the problem as a ranking task, we convert simple textual features extracted from a domain-specific corpus into a ranker without the need of labeled training data. Such method should rank brands (e.g. sprite) higher than types (e.g. lemonade). Apart from that, we also exploit knowledge induced by semi-supervised graph-based clustering for two different purposes. On the one hand, we produce an auxiliary categorization of food items according to the Food Guide Pyramid, and assume that a food item is a type when it belongs to a category unlikely to contain brands. On the other hand, we directly model the task of brand detection using seeds provided by the output of the textual ranking features. We also harness Wikipedia articles as an additional knowledge source.
Automatic Food Categorization from Large Unlabeled Corpora and Its Impact on Relation Extraction
(2014)
We present a weakly-supervised induction method to assign semantic information to food items. We consider two tasks of categorizations being food-type classification and the distinction of whether a food item is composite or not. The categorizations are induced by a graph-based algorithm applied on a large unlabeled domain-specific corpus. We show that the usage of a domain-specific corpus is vital. We do not only outperform a manually designed open-domain ontology but also prove the usefulness of these categorizations in relation extraction, outperforming state-of-the-art features that include syntactic information and Brown clustering.
We report on the two systems we built for Task 1 of the German Sentiment Analysis Shared Task, the task on Source, Subjective Expression and Target Extraction from Political Speeches (STEPS). The first system is a rule-based system relying on a predicate lexicon specifying extraction rules for verbs, nouns and adjectives, while the second is a translation-based system that has been obtained with the help of the (English) MPQA corpus.
We present the German Sentiment Analysis Shared Task (GESTALT) which consists of two main tasks: Source, Subjective Expression and Target Extraction from Political Speeches (STEPS) and Subjective Phrase and Aspect Extraction from Product Reviews (StAR). Both tasks focused on fine-grained sentiment analysis, extracting aspects and targets with their associated subjective expressions in the German language. STEPS focused on political discussions from a corpus of speeches in the Swiss parliament. StAR fostered the analysis of product reviews as they are available from the website Amazon.de. Each shared task led to one participating submission, providing baselines for future editions of this task and highlighting specific challenges. The shared task homepage can be found at https://sites.google.com/site/iggsasharedtask/.
The annotation of parts of speech (POS) in linguistically annotated corpora is a fundamental annotation layer which provides the basis for further syntactic analyses, and many NLP tools rely on POS information as input. However, most POS annotation schemes have been developed with written (newspaper) text in mind and thus do not carry over well to text from other domains and genres. Recent discussions have concentrated on the shortcomings of present POS annotation schemes with regard to their applicability to data from domains other than newspaper text.
Dieser Artikel gibt einen Einblick in das GeoBib-Projekt und die Problematik der Verwendung von historischen Karten und der daraus abgeleiteten Geodaten in einem WebGIS. Das GeoBib-Projekt hat zum Ziel, eine annotierte und georeferenzierte Online-Bibliographie der frühen deutsch- bzw. polnischsprachigen Holocaust- und Lagerliteratur von 1933 bis 1949 bereitzustellen. Zu diesem Zeitraum werden historische Karten und Geodaten gesammelt, aufbereitet und im zugehörigen WebGIS des GeoBib-Portals visualisiert. Eine Besonderheit ist die aufwendige Recherche von Geodaten und Kartenmaterial für den Zeitraum zwischen 1933 und 1949. Die Problematiken bezüglich der Recherche und späteren Visualisierung historischer Geodaten und des Kartenmaterials sind ein Hauptaugenmerk in diesem Artikel. Weiterhin werden Konzepte für die Visualisierung von historischem, unvollständigem Kartenmaterial präsentiert und ein möglicher Lösungsweg für die bestehenden Herausforderungen aufgezeigt.
Uncertain about Uncertainty: Different ways of processing fuzziness in digital humanities data
(2014)
The GeoBib project is constructing a georeferenced online bibliography of early Holocaust and camp literature published between 1933 and 1949 (Entrup et al. 2013a). Our immediate objectives include identifying the texts of interest in the first place, composing abstracts for them, researching their history, and annotating relevant places and times. Relations between persons, texts, and places will be visualized using digital maps and GIS software as an integral part of the resulting GeoBib information portal. The combination of diverse data from varying sources not only enriches our knowledge of these otherwise mostly forgotten texts; it also confronts us with vague, uncertain or even conflicting information. This situation yields challenges for all researchers involved – historians, literary scholars, geographers and computer scientists alike. While the project operates at the intersection of historical and literary studies, the involved computer scientists are in charge of providing a working environment (Entrup et al. 2013b) and processing the collected information in a way that is formalized yet capable of dealing with inevitable vagueness, uncertainty and contradictions. In this paper we focus on the problems and opportunities of encoding and processing fuzzy data.
“My Curiosity was Satisfied, but not in a Good Way”: Predicting User Ratings for Online Recipes
(2014)
In this paper, we develop an approach to automatically predict user ratings for recipes at Epicurious.com, based on the recipes’ reviews. We investigate two distributional methods for feature selection, Information Gain and Bi-Normal Separation; we also compare distributionally selected features to linguistically motivated features and two types of frameworks: a one-layer system where we aggregate all reviews and predict the rating vs. a two-layer system where ratings of individual reviews are predicted and then aggregated. We obtain our best results by using the two-layer architecture, in combination with 5 000 features selected by Information Gain. This setup reaches an overall accuracy of 65.60%, given an upper bound of 82.57%.
We investigate how the granularity of POS tags influences POS tagging, and furthermore, how POS tagging performance relates to parsing results. For this, we use the standard “pipeline” approach, in which a parser builds its output on previously tagged input. The experiments are performed on two German treebanks, using three POS tagsets of different granularity, and six different POS taggers, together with the Berkeley parser. Our findings show that less granularity of the POS tagset leads to better tagging results. However, both too coarse-grained and too fine-grained distinctions on POS level decrease parsing performance.
Recent work on error detection has shown that the quality of manually annotated corpora can be substantially improved by applying consistency checks to the data and automatically identifying incorrectly labelled instances. These methods, however, can not be used for automatically annotated corpora where errors are systematic and cannot easily be identified by looking at the variance in the data. This paper targets the detection of POS errors in automatically annotated corpora, so-called silver standards, showing that by combining different measures sensitive to annotation quality we can identify a large part of the errors and obtain a substantial increase in accuracy.
We discovered several recurring errors in the current version of the Europarl Corpus originating both from the web site of the European Parliament and the corpus compilation based thereon. The most frequent error was incompletely extracted metadata leaving non-textual fragments within the textual parts of the corpus files. This is, on average, the case for every second speaker change. We not only cleaned the Europarl Corpus by correcting several kinds of errors, but also aligned the speakers’ contributions of all available languages and compiled every- thing into a new XML-structured corpus. This facilitates a more sophisticated selection of data, e.g. querying the corpus for speeches by speakers of a particular political group or in particular language combinations.
This study presents the results of a large-scale comparison of various measures of pitch range and pitch variation in two Slavic (Bulgarian and Polish) and two Germanic (German and British English) languages. The productions of twenty-two speakers per language (eleven male and eleven female) in two different tasks (read passages and number sets) are compared. Significant differences between the language groups are found: German and English speakers use lower pitch maxima, narrower pitch span, and generally less variable pitch than Bulgarian and Polish speakers. These findings support the hypothesis that inguistic communities tend to be characterized by particular pitch profiles.
This article presents preliminary results indicating that speakers have a different pitch range when they speak a foreign language compared to the pitch variation that occurs when they speak their native language. To this end, a learner corpus with French and German speakers was analyzed. Results suggest that speakers indeed produce a smaller pitch range in the respective L2. This is true for both groups of native speakers. A possible explanation for this finding is that speakers are less confident in their productions, therefore, they concentrate more on segments and words and subsequently refrain from realizing pitch range more native-like. For language teaching, the results suggest that learners should be trained extensively on the more pronounced use of pitch in the foreign language.
Designing a Bilingual Speech Corpus for French and German Language Learners: a Two-Step Process
(2014)
We present the design of a corpus of native and non-native speech for the language pair French-German, with a special emphasis on phonetic and prosodic aspects. To our knowledge there is no suitable corpus, in terms of size and coverage, currently available for the target language pair. To select the target L1-L2 interference phenomena we prepare a small preliminary corpus (corpus1), which is analyzed for coverage and cross-checked jointly by French and German experts. Based on this analysis, target phenomena on the phonetic and phonological level are selected on the basis of the expected degree of deviation from the native performance and the frequency of occurrence. 14 speakers performed both L2 (either French or German) and L1 material (either German or French). This allowed us to test, recordings duration, recordings material, the performance of our automatic aligner software. Then, we built corpus2 taking into account what we learned about corpus1. The aims are the same but we adapted speech material to avoid too long recording sessions. 100 speakers will be recorded. The corpus (corpus1 and corpus2) will be prepared as a searchable database, available for the scientific community after completion of the project.
This study investigates cross-language differences in pitch range and variation in four languages from two language groups: English and German (Germanic) and Bulgarian and Polish (Slavic). The analysis is based on large multi-speaker corpora (48 speakers for Polish, 60 for each of the other three languages). Linear mixed models were computed that include various distributional measures of pitch level, span and variation, revealing characteristic differences across languages and between language groups. A classification experiment based on the relevant parameter measures (span, kurtosis and skewness values for pitch distributions for each speaker) succeeded in separating the language groups.
Recent work suggests that concreteness and imageability play an important role in the meanings of figurative expressions. We investigate this idea in several ways. First, we try to define more precisely the context within which a figurative expression may occur, by parsing a corpus annotated for metaphor. Next, we add both concreteness and imageability as “features” to the parsed metaphor corpus, by marking up words in this corpus using a psycholinguistic database of scores for concreteness and imageability. Finally, we carry out detailed statistical analyses of the augmented version of the original metaphor corpus, cross-matching the features of concreteness and imageability with others in the corpus such as parts of speech and dependency relations, in order to investigate in detail the use of such features in predicting whether a given expression is metaphorical or not.
Der Beitrag beschäftigt sich mit den verschiedenen Such-, Auffindungs- und Auswahlsprozessen, die für die fremdsprachige Produktion notwendig sind und von DICONALE-online, einem onomasiologisch-konzeptuell ausgerichteten, zweisprachig-bilateral konzipierten Verbwörterbuch der spanischen und deutschen Gegenwartsspache, besonders berücksichtigt werden. Der Ausgangspunkt von DICONALE ist ein unbefriedigendes Informationsangebot in den bestehenden ein- und zweisprachigen Lernerwörterbüchern für den L2-output und bestätigt das Projektteam in der Notwendigkeit, ein neuartiges benutzer- und situationsdefiniertes online-Nachschlagewerk zu erstellen. Zwei Bezugsrahmen bilden die Grundlage für einen komplexen, konzeptuell und framegeleiteten Zugriffspfad, der dem Benutzer bei der Suche und Auswahl von Ausdrucksmöglichkeiten und der adäquaten Anwendung behilflich sein soll. Das Novum dieses Wörterbuchprojekts besteht hauptsachlich darin, eine onomasiologisch-konzeptuelle Perspektive für den fremdsprachigen Produktionsprozess nutzbar zu machen und mit einem semasiologischen Zugriff zu verbinden, durch den es möglich ist, die inter- und intralingualen Unterschiede zwischen den Lexemen eines lexikalisch-semantischen (Sub)Paradigmas hervorzuheben. Ziel des Beitrages ist es daher, den Ausgangspunkt, sowie die theoretischen und methodologischen Grundlagen von DICONALE-online unter der speziellen Perspektive der Benutzer- und Situationsorientiertheit zur Diskussion zu stellen, die einzelnen Zugriffspfade für den Such- und Auffindungsprozess vorzustellen und das Angebot zur Auswahl und zum adäquaten Gebrauch aus inter- und intralingualer Perspektive zu präsentieren.
This paper presents the first release of the KiezDeutsch Korpus (KiDKo), a new language resource with multiparty spoken dialogues of Kiezdeutsch, a newly emerging language variety spoken by adolescents from multi-ethnic urban areas in Germany. The first release of the corpus includes the transcriptions of the data as well as a normalisation layer and part-of-speech annotations. In the paper, we describe the main features of the new resource and then focus on automatic POS tagging of informal spoken language. Our tagger achieves an accuracy of nearly 97% on KiDKo. While we did not succeed in further improving the tagger using ensemble tagging, we present our approach to using the tagger ensembles for identifying error patterns in the automatically tagged data.
We study the influence of information structure on the salience of subjective expressions for human readers. Using an online survey tool, we conducted an experiment in which we asked users to rate main and relative clauses that contained either a single positive or negative or a neutral adjective. The statistical analysis of the data shows that subjective expressions are more prominent in main clauses where they are asserted than in relative clauses where they are presupposed. A corpus study suggests that speakers are sensitive to this differential salience in their production of subjective expressions.
We compare several different corpus- based and lexicon-based methods for the scalar ordering of adjectives. Among them, we examine for the first time a low- resource approach based on distinctive- collexeme analysis that just requires a small predefined set of adverbial modifiers. While previous work on adjective intensity mostly assumes one single scale for all adjectives, we group adjectives into different scales which is more faithful to human perception. We also apply the methods to both polar and non-polar adjectives, showing that not all methods are equally suitable for both types of adjectives.
This contribution presents an XML Schema for annotating a high level narratological category: speech, thought and writing representation (ST&WR). It focusses on two aspects: Firstly, the original Schema is presented as an example for the challenge to encode a narrative feature in a structured and flexible way and secondly, ways of adapting this Schema to TEI are considered, in Order to make it usable for other, TEI-based projects.
This contribution presents the newest version of our ’Wortverbindungsfelder’ (fields of multi-word expressions), an experimental lexicographic resource that focusses on aspects of MWEs that are rarely addressed in traditional descriptions: Contexts, patterns and interrelations. The MWE fields use data from a very large corpus of written German (over 6 billion word forms) and are created in a strictly corpus-based way. In addition to traditional lexicographic descriptions, they include quantitative corpus data which is structured in new ways in order to show the usage specifics. This way of looking at MWEs gives insight in the structure of language and is especially interesting for foreign language learners.
This paper introduces the Aix Map Task corpus, a corpus of audio and video recordings of task-oriented dialogues. It was modelled after the original HCRC Map Task corpus. Lexical material was designed for the analysis of speech and prosody, as described in Astésano et al. (2007). The design of the lexical material, the protocol and some basic quantitative features of the existing corpus are presented. The corpus was collected under two communicative conditions, one audio-only condition and one face-to-face condition. The recordings took place in a studio and a sound attenuated booth respectively, with head-set microphones (and in the face-to-face condition with two video cameras). The recordings have been segmented into Inter-Pausal-Units and transcribed using transcription conventions containing actual productions and canonical forms of what was said. It is made publicly available online.
We present a novel NLP resource for the explanation of linguistic phenomena, built and evaluated exploring very large annotated language corpora. For the compilation, we use the German Reference Corpus (DeReKo) with more than 5 billion word forms, which is the largest linguistic resource worldwide for the study of contemporary written German. The result is a comprehensive database of German genitive formations, enriched with a broad range of intra- und extralinguistic metadata. It can be used for the notoriously controversial classification and prediction of genitive endings (short endings, long endings, zero-marker). We also evaluate the main factors influencing the use of specific endings. To get a general idea about a factor’s influences and its side effects, we calculate chi-square-tests and visualize the residuals with an association plot. The results are evaluated against a gold standard by implementing tree-based machine learning algorithms. For the statistical analysis, we applied the supervised LMT Logistic Model Trees algorithm, using the WEKA software. We intend to use this gold standard to evaluate GenitivDB, as well as to explore methodologies for a predictive genitive model.
Hosting Providers play an essential role in the development of Internet services such as e-Research Infrastructures. In order to promote the development of such services, legislators on both sides of the Atlantic Ocean introduced “safe harbour” provisions to protect Service Providers (a category which includes Hosting Providers) from legal claims (e.g. of copyright infringement). Relevant provisions can be found in § 512 of the United States Copyright Act and in art. 14 of the Directive 2000/31/EC (and its national implementations). The cornerstone of this framework is the passive role of the Hosting Provider through which he has no knowledge of the content that he hosts. With the arrival of Web 2.0, however, the role of Hosting Providers on the Internet changed; this change has been reflected in court decisions that have reached varying conclusions in the last few years. The purpose of this article is to present the existing framework (including recent case law from the US, Germany and France).
Part-of-speech tagging (POS-tagging) of spoken data requires different means of annotation than POS-tagging of written and edited texts. In order to capture the features of German spoken language, a distinct tagset is needed to respond to the kinds of elements which only occur in speech. In order to create such a coherent tagset the most prominent phenomena of spoken language need to be analyzed, especially with respect to how they differ from written language. First evaluations have shown that the most prominent cause (over 50%) of errors in the existing automatized POS-tagging of transcripts of spoken German with the Stuttgart Tübingen Tagset (STTS) and the treetagger was the inaccurate interpretation of speech particles. One reason for this is that this class of words is virtually absent from the current STTS. This paper proposes a recategorization of the STTS in the field of speech particles based on distributional factors rather than semantics. The ultimate aim is to create a comprehensive reference corpus of spoken German data for the global research community. It is imperative that all phenomena are reliably recorded in future part-of-speech tag labels.
Machine learning methods offer a great potential to automatically investigate large amounts of data in the humanities. Our contribution to the workshop reports about ongoing work in the BMBF project KobRA (http://www.kobra.tu-dortmund.de) where we apply machine learning methods to the analysis of big corpora in language-focused research of computer-mediated communication (CMC). At the workshop, we will discuss first results from training a Support Vector Machine (SVM) for the classification of selected linguistic features in talk pages of the German Wikipedia corpus in DeReKo provided by the IDS Mannheim. We will investigate different representations of the data to integrate complex syntactic and semantic information for the SVM. The results shall foster both corpus-based research of CMC and the annotation of linguistic features in CMC corpora.
This contribution presents the procedure used in the Handbuch deutscher Kommunikationsverben and in its online version Kommunikationsverben in the lexicographical internet portal OWID to divide sets of semantically similar communication verbs into ever smaller sets of ever closer synonyms. Kommunikationsverben describes the meaning of communication verbs on two levels: a lexical level, represented in the dictionary entries and by sets of lexical features, and a conceptual level, represented by different types of situations referred to by specific types of verbs. The procedure starts at the conceptual level of meaning where verbs used to refer to the same specific situation type are grouped together. At the lexical level of meaning, the sets of verbs obtained from the first step are successively divided into smaller sets on the basis of the criteria of (i) identity of lexical meaning, (ii) identity of lexical features, and (iii) identity of contexts of usage. The stepwise procedure applied is shown to result in the creation of a semantic network for communication verbs.
This paper reports on an ongoing lexicographical project that investigates Polish loanwords from German that were further borrowed into the East Slavic languages Russian, Ukrainian, and Belorussian. The results will be published as three separate dictionaries in the Lehnwortportal Deutsch, a freely available web portal for loanword dictionaries having German as their common source language. On the database level, the portal models lexicographical data as a cross-resource directed acyclic graph of relations between individual words, including German ‘metalemmata’ as normalized representations of diasystemic variants of German etyma. Amongst other things, this technology makes it possible to use the web portal as an ‘inverted loanword dictionary’ to find loanwords in different languages borrowed from the same German etymon. The different possible pathways of German loanwords that went through Polish into the East Slavic languages can be represented directly as paths in the graph. A dedicated in-house dictionary editing software system assists lexicographers in producing and keeping track of these paths even in complex cases where, e.g, only a derivative of a German loanword in Polish has been borrowed into Russian. The paper concludes with some remarks on the particularities of the dictionary/portal access structure needed for presenting and searching borrowing chains.
German lexical items with similar or related morphological roots and similar meaning potential are easily confused by native speakers and language learners. These include so-called paronyms such as effektiv/effizient , sensitive/sensibel, formell/formal/förmlich . Although these are generally not regarded as synonyms, empirical studies suggest that in some cases items of a paronym set have undergone meaning change and developed synonymous notions. In other cases, they remain similar in meaning, but show subtle differences in definition and restrictions of usage. Whereas the treatment of synonyms has received attention from corpus-linguists (cf. Partington 1998; Taylor 2003), the subject of paronyms has not been revisited with empirical, data-driven methods neither in terms of semantic theory nor in terms of practical lexicography. As a consequence, we also need to search for suitable corpus methods for detailed semantic investigation. Lexicographically, some German paronyms have been documented in printed dictionaries (e.g. Müller 1973; Pollmann & Wolk 2010). However, there is no corpus-assisted reference guide describing paronyms empirically and enabling readers to find the correct contemporary usage. Therefore, solutions to some lexicographic challenges are required.
We describe a systematic and application-oriented approach to training and evaluating named entity recognition and classification (NERC) systems, the purpose of which is to identify an optimal system and to train an optimal model for named entity tagging DeReKo, a very large general-purpose corpus of contemporary German (Kupietz et al., 2010). DeReKo 's strong dispersion wrt. genre, register and time forces us to base our decision for a specific NERC system on an evaluation performed on a representative sample of DeReKo instead of performance figures that have been reported for the individual NERC systems when evaluated on more uniform and less diverse data. We create and manually annotate such a representative sample as evaluation data for three different NERC systems, for each of which various models are learnt on multiple training data. The proposed sampling method can be viewed as a generally applicable method for sampling evaluation data from an unbalanced target corpus for any sort of natural language processing.
We present an approach to an aspect of managing complex access scenarios to large and heterogeneous corpora that involves handling user queries that, intentionally or due to the complexity of the queried resource, target texts or annotations outside of the given user’s permissions. We first outline the overall architecture of the corpus analysis platform KorAP, devoting some attention to the way in which it handles multiple query languages, by implementing ISO CQLF (Corpus Query Lingua Franca), which in turn constitutes a component crucial for the functionality discussed here. Next, we look at query rewriting as it is used by KorAP and zoom in on one kind of this procedure, namely the rewriting of queries that is forced by data access restrictions.
This paper gives an overview of recent developments in the German Reference Corpus DeReKo in terms of growth, maximising relevant corpus strata, metadata, legal issues, and its current and future research interface. Due to the recent acquisition of new licenses, DeReKo has grown by a factor of four in the first half of 2014, mostly in the area of newspaper text, and presently contains over 24 billion word tokens. Other strata, like fictional texts, web corpora, in particular CMC texts, and spoken but conceptually written texts have also increased significantly. We report on the newly acquired corpora that led to the major increase, on the principles and strategies behind our corpus acquisition activities, and on our solutions for the emerging legal, organisational, and technical challenges.
We start by trying to answer a question that has already been asked by de Schryver et al. (2006): Do dictionary users (frequently) look up words that are frequent in a corpus. Contrary to their results, our results that are based on the analysis of log files from two different online dictionaries indicate that users indeed look up frequent words frequently. When combining frequency information from the Mannheim German Reference Corpus and information about the number of visits in the Digital Dictionary of the German Language as well as the German language edition of Wiktionary, a clear connection between corpus and look-up frequencies can be observed. In a follow-up study, we show that another important factor for the look-up frequency of a word is its temporal social relevance. To make this effect visible, we propose a de-trending method where we control both frequency effects and overall look-up trends.
Language resources are often compiled for the purpose of variational analysis, such as studying differences between genres, registers, and disciplines, regional and diachronic variation, influence of gender, cultural context, etc. Often the sheer number of potentially interesting contrastive pairs can get overwhelming due to the combinatorial explosion of possible combinations. In this paper, we present an approach that combines well understood techniques for visualization heatmaps and word clouds with intuitive paradigms for exploration drill down and side by side comparison to facilitate the analysis of language variation in such highly combinatorial situations. Heatmaps assist in analyzing the overall pattern of variation in a corpus, and word clouds allow for inspecting variation at the level of words.
Data Mining with Shallow vs. Linguistic Features to Study Diversification of Scientific Registers
(2014)
We present a methodology to analyze the linguistic evolution of scientific registers with data mining techniques, comparing the insights gained from shallow vs. linguistic features. The focus is on selected scientific disciplines at the boundaries to computer science (computational linguistics, bioinformatics, digital construction, microelectronics). The data basis is the English Scientific Text Corpus (SCITEX) which covers a time range of roughly thirty years (1970/80s to early 2000s) (Degaetano-Ortlieb et al., 2013; Teich and Fankhauser, 2010). In particular, we investigate the diversification of scientific registers over time. Our theoretical basis is Systemic Functional Linguistics (SFL) and its specific incarnation of register theory (Halliday and Hasan, 1985). In terms of methods, we combine corpus-based methods of feature extraction and data mining techniques.
Newspapers became extremely popular in Germany during the 18th and 19th century, and thus increasingly influential for modern German. However, due to the lack of digitized historical newspaper corpora for German, this influence could not be analyzed systematically. In this paper, we introduce the Mannheim Corpus of Digital Newspapers and Magazines, which in its current release comprises 21 newspapers and magazines from the 18th and 19th century. With over 4.1 Mio tokens in about 650 volumes it currently constitutes the largest historical corpus dedicated to newspapers in German. We briefly discuss the prospect of the corpus for analyzing the evolution of news as a genre in its own right and the influence of contextual parameters such as region and register on the language of news. We then focus on one historically influential aspect of newspapers – their role in disseminating foreign words in German. Our preliminary quantitative results indeed indicate that newspapers use foreign words significantly more frequently than other genres, in particular belles lettres.
"FOLK is the ""Forschungs- und Lehrkorpus Gesprochenes Deutsch (FOLK)"" (eng.: research and teaching corpus of spoken German). The project has set itself the aim of building a corpus of German conversations which a) covers a broad range of interaction types in private, institutional and public settings, b) is sufficiently large and diverse and of sufficient quality to support different qualitative and quantitative research approaches, c) is transcribed, annotated and made accessible according to current technological standards, and d) is available to the scientific community on a sound legal basis and without unnecessary restrictions of usage. This paper gives an overview of the corpus design, the strategies for acquisition of a diverse range of interaction data, and the corpus construction workflow from recording via transcription an annotation to dissemination."
The Database for Spoken German (Datenbank für Gesprochenes Deutsch, DGD2, http://dgd.ids-mannheim.de) is the central platform for publishing and disseminating spoken language corpora from the Archive of Spoken German (Archiv für Gesprochenes Deutsch, AGD, http://agd.ids-mannheim.de) at the Institute for the German Language in Mannheim. The corpora contained in the DGD2 come from a variety of sources, some of them in-house projects, some of them external projects. Most of the corpora were originally intended either for research into the (dialectal) variation of German or for studies in conversation analysis and related fields. The AGD has taken over the task of permanently archiving these resources and making them available for reuse to the research community. To date, the DGD2 offers access to 19 different corpora, totalling around 9000 speech events, 2500 hours of audio recordings or 8 million transcribed words. This paper gives an overview of the data made available via the DGD2, of the technical basis for its implementation, and of the most important functionalities it offers. The paper concludes with information about the users of the database and future plans for its development.