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The paper reports the results of the curation project ChatCorpus2CLARIN. The goal of the project was to develop a workflow and resources for the integration of an existing chat corpus into the CLARIN-D research infrastructure for language resources and tools in the Humanities and the Social Sciences (http://clarin-d.de). The paper presents an overview of the resources and practices developed in the project, describes the added value of the resource after its integration and discusses, as an outlook, to what extent these practices can be considered best practices which may be useful for the annotation and representation of other CMC and social media corpora.
This paper presents the application of the <tiger2/> format to various linguistic scenarios with the aim of making it the standard serialisation for the ISO 24615 [1] (SynAF) standard. After outlining the main characteristics of both the SynAF metamodel and the <tiger2/> format, as extended from the initial Tiger XML format [2], we show through a range of different language families how <tiger2/> covers a variety of constituency and dependency based analyses.
Ph@ttSessionz and Deutsch heute are two large German speech databases. They were created for different purposes: Ph@ttSessionz to test Internet-based recordings and to adapt speech recognizers to the voices of adolescent speakers, Deutsch heute to document regional variation of German. The databases differ in their recording technique, the selection of recording locations and speakers, elicitation mode, and data processing.
In this paper, we outline how the recordings were performed, how the data was processed and annotated, and how the two databases were imported into a single relational database system. We present acoustical measurements on the digit items of both databases. Our results confirm that the elicitation technique affects the speech produced, that f0 is quite comparable despite different recording procedures, and that large speech technology databases with suitable metadata may well be used for the analysis of regional variation of speech.
There have been several attempts to annotate communicative functions to utterances of verbal feedback in English previously. Here, we suggest an annotation scheme for verbal and non-verbal feedback utterances in French including the categories base, attitude, previous and visual. The data comprises conversations, maptasks and negotiations from which we extracted ca. 13,000 candidate feedback utterances and gestures. 12 students were recruited for the annotation campaign of ca. 9,500 instances. Each instance was annotated by between 2 and 7 raters. The evaluation of the annotation agreement resulted in an average best-pair kappa of 0.6. While the base category with the values acknowledgement, evaluation, answer, elicit and other achieves good agreement, this is not the case for the other main categories. The data sets, which also include automatic extractions of lexical, positional and acoustic features, are freely available and will further be used for machine learning classification experiments to analyse the form-function relationship of feedback.
The present paper reports the first results of the compilation and annotation of a blog corpus for German. The main aim of the project is the representation of the blog discourse structure and relations between its elements (blog posts, comments) and participants (bloggers, commentators). The data included in the corpus were manually collected from the scientific blog portal SciLogs. The feature catalogue for the corpus annotation includes three types of information which is directly or indirectly provided in the blog or can be construed by means of statistical analysis or computational tools. At this point, only directly available information (e.g. title of the blog post, name of the blogger etc.) has been annotated. We believe, our blog corpus can be of interest for the general study of blog structure or related research questions as well as for the development of NLP methods and techniques (e.g. for authorship detection).
We present an implemented XML data model and a new, simplified query language for multi-level annotated corpora. The new query language involves automatic conversion of queries into the underlying, more complicated MMAXQL query language. It supports queries for sequential and hierarchical, but also associative (e.g. coreferential) relations. The simplified query language has been designed with non-expert users in mind.
Linguistic query systems are special purpose IR applications. We present a novel state-of-the-art approach for the efficient exploitation of very large linguistic corpora, combining the advantages of relational database management systems (RDBMS) with the functional MapReduce programming model. Our implementation uses the German DEREKO reference corpus with multi-layer linguistic annotations and several types of text-specific metadata, but the proposed strategy is language-independent and adaptable to large-scale multilingual corpora.
We present a gold standard for semantic relation extraction in the food domain for German. The relation types that we address are motivated by scenarios for which IT applications present a commercial potential, such as virtual customer advice in which a virtual agent assists a customer in a supermarket in finding those products that satisfy their needs best. Moreover, we focus on those relation types that can be extracted from natural language text corpora, ideally content from the internet, such as web forums, that are easy to retrieve. A typical relation type that meets these requirements are pairs of food items that are usually consumed together. Such a relation type could be used by a virtual agent to suggest additional products available in a shop that would potentially complement the items a customer has already in their shopping cart. Our gold standard comprises structural data, i.e. relation tables, which encode relation instances. These tables are vital in order to evaluate natural language processing systems that extract those relations.
We apply a decision tree based approach to pronoun resolution in spoken dialogue. Our system deals with pronouns with NP- and non-NP-antecedents. We present a set of features designed for pronoun resolution in spoken dialogue and determine the most promising features. We evaluate the system on twenty Switchboard dialogues and show that it compares well to Byron’s (2002) manually tuned system.
Creating and maintaining metadata for various kinds of resources requires appropriate tools to assist the user. The paper presents the metadata editor ProFormA for the creation and editing of CMDI (Component Metadata Infrastructure) metadata in web forms. This editor supports a number of CMDI profiles currently being provided for different types of resources. Since the editor is based on XForms and server-side processing, users can create and modify CMDI files in their standard browser without the need for further processing. Large parts of ProFormA are implemented as web services in order to reuse them in other contexts and programs.
In this paper we present a new approach to lexicographical design for the description of German speech act verbs. This approach is based on an action-theoretical semantic conception. The several conditions for linguistic action provide the basis for the elaboration of the central semantic features. The systematic relationship of these features is reflected in the organization of a lexical database which allows various possibilities of access to different types of lexical information.
In the following paper we shall give an outline of the semantic framework for describing speech act verbs, i. e. verbs of communication, with the practical goal of a semantical database for a (dictionary of) synonymy of German speech act verbs which enables the user not only to find a list of synonymous verbs but also enables him to gain an insight into the semantic relations between the words.
The semantic framework is based on
(i) a set of conditions for performing speech acts as the relevant domain of reference
(ii) the introduction of a notion of situation, or better type of situation
The performative as well as the descriptive use of the verbs can be reduced to their fundamental dependency on the situations in which they are used: on the one hand with regard to the possibility of the action itself, and on the other hand with regard to the possibility of their designation. For both ways of use the relevant aspects of the situation constitute the necessary conditions.
One of the most popular techniques used in HPSG-based studies to describe linguistic phenomena is the raising mechanism. Besides ordinary raising verbs or adjectives, this tool has been applied for handling verbal complexes and discontinuous constituents, among other phenomena. In this paper, a new application for raising within the HPSG paradigm will be discussed, thereby investigating data from the prepositional domain. We will analyze linguistic properties of word combinations in German consisting of a preposition, a noun, and another preposition (such as auf Grund von (‘by virtue of’)), thus arguing that raising is the most appropriate method for satisfactorily describing the crucial syntactic features which are typical for those expressions. The objective of this paper is thus to demonstrate the efficiency of the raising mechanism as used in HPSG, and therefore, to emphasize the importance of designing a satisfactory uniform theory of raising within this grammar framework.
One of the most popular techniques used in HPSG-based studies to describe linguistic phenomena is the raising mechanism. Besides ordinary raising verbs or adjectives, this tool has been applied for handling verbal complexes and discontinuous constituents, among other phenomena. In this paper, a new application for raising within the HPSG paradigm will be discussed, thereby investigating data from the prepositional domain. We will analyze linguistic properties of word combinations in German consisting of a preposition, a noun, and another preposition (such as auf Grund von (‘by virtue of’)), thus arguing that raising is the most appropriate method for satisfactorily describing the crucial syntactic features which are typical for those expressions. The objective of this paper is thus to demonstrate the efficiency of the raising mechanism as used in HPSG, and therefore, to emphasize the importance of designing a satisfactory uniform theory of raising within this grammar framework.
The understanding of story variation, whether motivated by cultural currents or other factors, is important for applications of formal models of narrative such as story generation or story retrieval. We present the first stage of an experiment to elicit natural narrative variation data suitable for evaluation with respect to story similarity, to qualitative and quantitative analysis of story variation, and also for data processing. We also present few preliminary results from the first stage of the experiment, using Red Riding Hood and Romeo and Juliet as base texts.
XML has been designed for creating structured documents, but the information that is encoded in these structures are, by definition, out of scope for XML. Additional sources, normally not easily interpretable by computers, such as documentation are needed to determine the intention of specific tags in a tag-set. The Component Metadata Infrastructure (CMDI) takes a rather pragmatic approach to foster interoperability between XML instances in the domain of metadata descriptions for language resources. This paper gives an overview of this approach.
This paper presents the current results of an ongoing research project on corpus distribution of prepositions and pronouns within Polish preposition-pronoun contractions. The goal of the project is to provide a quantitative description of Polish preposition-pronoun contractions taking into consideration morphosyntactic properties of their components. It is expected that the results will provide a basis for a revision of the traditionally assumed inflectional paradigms of Polish pronouns and, thus, for a possible remodeling of these paradigms. The results of corpus-based investigations of the distribution of prepositions within preposition-pronoun contractions can be used for grammar-theoretical and lexicographic purposes.
This paper presents the system architecture as well as the underlying workflow of the Extensible Repository System of Digital Objects (ERDO) which has been developed for the sustainable archiving of language resources within the Tübingen CLARIN-D project. In contrast to other approaches focusing on archiving experts, the described workflow can be used by researchers without required knowledge in the field of long-term storage for transferring data from their local file systems into a persistent repository.
This paper describes the lexical database tool LOLA (Linguistic-Oriented Lexical database Approach) which has been developed for the construction and maintenance of lexicons for the machine translation system LMT. First, the requirements such a tool should meet are discussed, then LMT and the lexical information it requires, and some issues concerning vocabulary acquisition are presented. Afterwards the architecture and the components of the LOLA system are described and it is shown how we tried to meet the requirements worked out earlier. Although LOLA originally has been designed and implemented for the German-English LMT prototype, it aimed from the beginning at a representation of lexical data that can be reused for other LMT or MT prototypes or even other NLP applications. A special point of discussion will therefore be the adaptability of the tool and its components as well as the reusability of the lexical data stored in the database for the lexicon development for LMT or for other applications.
Feedback utterances are among the most frequent in dialogue. Feedback is also a crucial aspect of linguistic theories that take social interaction, involving language, into account. This paper introduces the corpora and datasets of a project scrutinizing this kind of feedback utterances in French. We present the genesis of the corpora (for a total of about 16 hours of transcribed and phone force-aligned speech) involved in the project. We introduce the resulting datasets and discuss how they are being used in on-going work with focus on the form-function relationship of conversational feedback. All the corpora created and the datasets produced in the framework of this project will be made available for research purposes.
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.
This paper presents a survey on the role of negation in sentiment analysis. Negation is a very common linguistic construction that affects polarity and, therefore, needs to be taken into consideration in sentiment analysis.
We will present various computational approaches modeling negation in sentiment analysis. We will, in particular, focus on aspects such as level of representation used for sentiment analysis, negation word detection and scope of negation. We will also discuss limits and challenges of negation modeling on that task.
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.
This paper presents Release 2.0 of the SALSA corpus, a German resource for lexical semantics. The new corpus release provides new annotations for German nouns, complementing the existing annotations of German verbs in Release 1.0. The corpus now includes around 24,000 sentences with more than 36,000 annotated instances. It was designed with an eye towards NLP applications such as semantic role labeling but will also be a useful resource for linguistic studies in lexical semantics.
We describe a simple and efficient Java object model and application programming interface (API) for (possibly multi-modal) annotated natural language corpora. Corpora are represented as elements like Sentences, Turns, Utterances, Words, Gestures and Markables. The API allows linguists to access corpora in terms of these discourse-level elements, i.e. at a conceptual level they are familiar with, with the flexibility offered by a general purpose programming language. It is also a contribution to corpus standardization efforts because it is based on a straightforward and easily extensible data model which can serve as a target for conversion of different corpus formats.
We investigate whether prototypicality or prominence of semantic roles can account for role-related effects in sentence interpretation. We present two acceptability-rating experiments testing three different constructions: active, personal passive and DO-clefts involving the same type of transitive verbs that differ with respect to the agentive role features they select. Our results reveal that there is no cross-constructional advantage for prototypical roles (e.g., agents), hence disconfirming a central tenet of role prototypicality. Rather, acceptability clines depend on the construction under investigation, thereby highlighting different role features. This finding is in line with one core assumption of the prominence account stating that role features are flexibly highlighted depending on the discourse function of the respective construction.
This paper aims to address these problems by dealing with theoretical and methodological questions concerning the national effects of the Bologna Process and the role national factors play in determining the impact of these effects. Altogether the purpose of the paper is to serve as a starting point for future research – both as a guide for systematic and comparative empirical work on higher education, but also for further theoretical and methodological reasoning concerning research on (higher) education policy. As higher education research so far particularly lacks an approach allowing for a competitive and systematic falsification of theoretical arguments by clearly indicating testable and specific hypothesis as well as variables behind the research design (Goedegebuure/Vught 1996) we propose to fall back on neighbouring disciplines, namely social science to improve and enhance the analysis (Slaughter 2001: 398; Altbach 2002: 154; Teichler 1996a: 433, 2005: 448). Several strands of research have to be considered – namely literature on Europeanization as well as insights and approaches of studies dealing with cross-national policy convergence. Taking into account the non-obligatory and mainly intergovernmental character of the Bologna Process the main focus of the paper is on factors related to the effects of transnational communication. The inherent goal is to extend the research agenda on higher education (McLendon 2003: 184ff) and to leave behind the restriction of to analyse only a few cases by striving for a research design that allows for systematic testing and sufficient explanations of cross-national policy convergence at the interface between the Bologna Process and domestic factors.
Annotating Discourse Relations in Spoken Language: A Comparison of the PDTB and CCR Frameworks
(2016)
In discourse relation annotation, there is currently a variety of different frameworks being used, and most of them have been developed and employed mostly on written data. This raises a number of questions regarding interoperability of discourse relation annotation schemes, as well as regarding differences in discourse annotation for written vs. spoken domains. In this paper, we describe ouron annotating two spoken domains from the SPICE Ireland corpus (telephone conversations and broadcast interviews) according todifferent discourse annotation schemes, PDTB 3.0 and CCR. We show that annotations in the two schemes can largely be mappedone another, and discuss differences in operationalisations of discourse relation schemes which present a challenge to automatic mapping. We also observe systematic differences in the prevalence of implicit discourse relations in spoken data compared to written texts,find that there are also differences in the types of causal relations between the domains. Finally, we find that PDTB 3.0 addresses many shortcomings of PDTB 2.0 wrt. the annotation of spoken discourse, and suggest further extensions. The new corpus has roughly theof the CoNLL 2015 Shared Task test set, and we hence hope that it will be a valuable resource for the evaluation of automatic discourse relation labellers.
Feedback utterances are among the most frequent in dialogue. Feedback is also a crucial aspect of all linguistic theories that take social interaction involving language into account. However, determining communicative functions is a notoriously difficult task both for human interpreters and systems. It involves an interpretative process that integrates various sources of information. Existing work on communicative function classification comes from either dialogue act tagging where it is generally coarse grained concerning the feed- back phenomena or it is token-based and does not address the variety of forms that feed- back utterances can take. This paper introduces an annotation framework, the dataset and the related annotation campaign (involving 7 raters to annotate nearly 6000 utterances). We present its evaluation not merely in terms of inter-rater agreement but also in terms of usability of the resulting reference dataset both from a linguistic research perspective and from a more applicative viewpoint.
In this paper, we investigate the practical applicability of Co-Training for the task of building a classifier for reference resolution. We are concerned with the question if Co-Training can significantly reduce the amount of manual labeling work and still produce a classifier with an acceptable performance.
This work exploited coarticulation and loud speech as natural sources of perturbation in order to determine whether articulatory covariation (motor equivalent behavior) can be observed inspeech that is not artificially perturbed. Articulatory analyses of jaw and tongue movement in the production of alveolar consonants by German speakers were performed. The sibilant /s/ shows virtually no articulatory covariation under the influence of natural perturbations, whereas other alveolar consonants show more obvious compensatory behavior. Our conclusion is that an effect of natural sources of perturbation is noticable, but sounds are affected to different degrees.
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.
Common Crawl is a considerably large, heterogeneous multilingual corpus comprised of crawled documents from the internet, surpassing 20TB of data and distributed as a set of more than 50 thousand plain text files where each contains many documents written in a wide variety of languages. Even though each document has a metadata block associated to it, this data lacks any information about the language in which each document is written, making it extremely difficult to use Common Crawl for monolingual applications. We propose a general, highly parallel, multithreaded pipeline to clean and classify Common Crawl by language; we specifically design it so that it runs efficiently on medium to low resource infrastructures where I/O speeds are the main constraint. We develop the pipeline so that it can be easily reapplied to any kind of heterogeneous corpus and so that it can be parameterised to a wide range of infrastructures. We also distribute a 6.3TB version of Common Crawl, filtered, classified by language, shuffled at line level in order to avoid copyright issues, and ready to be used for NLP applications.
The effect of manipulation of a speaker’s voice as well as exposure to a native speaker’s utterance was investigated regarding the pronunciation of stops by German learners of French. Three subject groups, a Control (CG), a Manipulation (MG), and a Native Speaker (NG) Group, were recorded on two subsequent days. The MG was presented with a manipulation of their voice on the second day and the NG listened to a native French speaker, while the CG did not receive any feedback. Results show that speakers of the MG and NG were able to extract useful information from the respective feedback and successfully adapted to it. Participants were able to reduce their voice onset time values, although speakers of the NG reduced it to a greater extent.
We present data-driven methods for the acquisition of LFG resources from two German treebanks. We discuss problems specific to semi-free word order languages as well as problems arising from the data structures determined by the design of the different treebanks. We compare two ways of encoding semi-free word order, as done in the two German treebanks, and argue that the design of the TiGer treebank is more adequate for the acquisition of LFG resources. Furthermore, we describe an architecture for LFG grammar acquisition for German, based on the two German treebanks, and compare our results with a hand-crafted German LFG grammar.
We present an implemented machine learning system for the automatic detection of nonreferential it in spoken dialog. The system builds on shallow features extracted from dialog transcripts. Our experiments indicate a level of performance that makes the system usable as a preprocessing filter for a coreference resolution system. We also report results of an annotation study dealing with the classification of it by naive subjects.
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.
This paper describes work directed towards the development of a syllable prominence-based prosody generation functionality for a German unit selection speech synthesis system. A general concept for syllable prominence-based prosody generation in unit selection synthesis is proposed. As a first step towards its implementation, an automated syllable prominence annotation procedure based on acoustic analyses has been performed on the BOSS speech corpus. The prominence labeling has been evaluated against an existing annotation of lexical stress levels and manual prominence labeling on a subset of the corpus. We discuss methods and results and give an outlook on further implementation steps.
Bootstrapping Supervised Machine-learning Polarity Classifiers with Rule-based Classification
(2010)
In this paper, we explore the effectiveness of bootstrapping supervised machine-learning polarity classifiers using the output of domain-independent rule-based classifiers. The benefit of this method is that no labeled training data are required. Still, this method allows to capture in-domain knowledge by training the supervised classifier on in-domain features, such as bag of words.
We investigate how important the quality of the rule-based classifier is and what features are useful for the supervised classifier. The former addresses the issue in how far relevant constructions for polarity classification, such as word sense disambiguation, negation modeling, or intensification, are important for this self-training approach. We not only compare how this method relates to conventional semi-supervised learning but also examine how it performs under more difficult settings in which classes are not balanced and mixed reviews are included in the dataset.
Active learning has been applied to different NLP tasks, with the aim of limiting the amount of time and cost for human annotation. Most studies on active learning have only simulated the annotation scenario, using prelabelled gold standard data. We present the first active learning experiment for Word Sense Disambiguation with human annotators in a realistic environment, using fine-grained sense distinctions, and investigate whether AL can reduce annotation cost and boost classifier performance when applied to a real-world task.
This paper describes the application of probabilistic part of speech taggers to the Dzongkha language. A tag set containing 66 tags is designed, which is based on the Penn Treebank. A training corpus of 40,247 tokens is utilized to train the model. Using the lexicon extracted from the training corpus and lexicon from the available word list, we used two statistical taggers for comparison reasons. The best result achieved was 93.1% accuracy in a 10-fold cross validation on the training set. The winning tagger was thereafter applied to annotate a 570,247 token corpus.
The availability of large multi-parallel corpora offers an enormous wealth of material to contrastive corpus linguists, translators and language learners, if we can exploit the data properly. Necessary preparation steps include sentence and word alignment across multiple languages. Additionally, linguistic annotation such as partof- speech tagging, lemmatisation, chunking, and dependency parsing facilitate precise querying of linguistic properties and can be used to extend word alignment to sub-sentential groups. Such highly interconnected data is stored in a relational database to allow for efficient retrieval and linguistic data mining, which may include the statistics-based selection of good example sentences. The varying information needs of contrastive linguists require a flexible linguistic query language for ad hoc searches. Such queries in the format of generalised treebank query languages will be automatically translated into SQL queries.
Data Management is one of the core activities of all CLARIN centres providing data and services for the academia. In PARTHENOS, European initiatives and projects in the area of the humanities and social sciences assembled to compare policies and procedures. One of the areas of interest is data management. The data management landscape shows a lot of proliferation, for which an abstraction level is introduced to help centres, such as CLARIN centres, in the process of providing the best possible services to users with data management needs.