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We address the task of distinguishing implicitly abusive sentences on identity groups (“Muslims contaminate our planet”) from other group-related negative polar sentences (“Muslims despise terrorism”). Implicitly abusive language are utterances not conveyed by abusive words (e.g. “bimbo” or “scum”). So far, the detection of such utterances could not be properly addressed since existing datasets displaying a high degree of implicit abuse are fairly biased. Following the recently-proposed strategy to solve implicit abuse by separately addressing its different subtypes, we present a new focused and less biased dataset that consists of the subtype of atomic negative sentences about identity groups. For that task, we model components that each address one facet of such implicit abuse, i.e. depiction as perpetrators, aspectual classification and non-conformist views. The approach generalizes across different identity groups and languages.
In this paper we present work in developing a computerized grammar for the Latin language. It demonstrates the principles and challenges in developing a grammar for a natural language in a modern grammar formalism. The grammar presented here provides a useful resource for natural language processing applications in different fields. It can be easily adopted for language learning and use in language technology for Cultural Heritage like translation applications or to support post-correction of document digitization.
Content
1 Predicting learner knowledge of individual words using machine learning
Drilon Avdiu, Vanessa Bui, Klára Ptacinová Klimci´ková
2 Automatic Generation and Semantic Grading of Esperanto Sentences in a Teaching Context
Eckhard Bick
3 Toward automatic improvement of language produced by non-native language learners
Mathias Creutz, Eetu Sjöblom
4 Linguistic features and proficiency classification in L2 Spanish and L2 Portuguese
Iria del Ri´o
5 Integrating large-scale web data and curated corpus data in a search engine supporting German literacy education
Sabrina Dittrich, Zarah Weiss, Hannes Schröter, Detmar Meurers
6 Formalism for a language agnostic language learning game and productive grid generation
Sylvain Hatier, Arnaud Bey, Mathieu Loiseau
7 Understanding Vocabulary Growth Through An Adaptive Language Learning System
Elma Kerz, Andreas Burgdorf, Daniel Wiechmann, Stefan Meeger,Yu Qiao, Christian Kohlschein, Tobias Meisen
8 Summarization Evaluation meets Short-Answer Grading
Margot Mieskes, Ulrike Padó
9 Experiments on Non-native Speech Assessment and its Consistency
Ziwei Zhou, Sowmya Vajjala, Seyed Vahid Mirnezami
10 The Impact of Spelling Correction and Task Context on Short Answer Assessment for Intelligent Tutoring Systems
Ramon Ziai, Florian Nuxoll, Kordula De Kuthy, Björn Rudzewitz, Detmar Meurers
Content
1 Substituto - A Synchronous Educational Language Game for Simultaneous Teaching and Crowdsourcing
Marianne Grace Araneta, Gülsen Eryigit, Alexander König, Ji-Ung Lee, Ana Luís, Verena Lyding, Lionel Nicolas, Christos Rodosthenous and Federico Sangati
2 The Teacher-Student Chatroom Corpus
Andrew Caines, Helen Yannakoudakis, Helena Edmondson, Helen Allen, Pascual Pérez-Paredes, Bill Byrne and Paula Buttery
3 Polygloss - A conversational agent for language practice
Etiene da Cruz Dalcol and Massimo Poesio
4 Show, Don’t Tell: Visualising Finnish Word Formation in a Browser-Based Reading Assistant
Frankie Robertson
MULLE is a tool for language learning that focuses on teaching Latin as a foreign language. It is aimed for easy integration into the traditional classroom setting and syllabus, which makes it distinct from other language learning tools that provide standalone learning experience. It uses grammar-based lessons and embraces methods of gamification to improve the learner motivation. The main type of exercise provided by our application is to practice translation, but it is also possible to shift the focus to vocabulary or morphology training.
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.
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 present a language learning application that relies on grammars to model the learning outcome. Based on this concept we can provide a powerful framework for language learning exercises with an intuitive user interface and a high reliability. Currently the application aims to augment existing language classes and support students by improving the learner attitude and the general learning outcome. Extensions beyond that scope are promising and likely to be added in the future.
Current Natural Language Processing (NLP) systems feature high-complexity processing pipelines that require the use of components at different levels of linguistic and application specific processing. These components often have to interface with external e.g. machine learning and information retrieval libraries as well as tools for human annotation and visualization. At the UKP Lab, we are working on the Darmstadt Knowledge Processing Software Repository (DKPro) (Gurevych et al., 2007a; Müller et al., 2008) to create a highly flexible, scalable and easy-to-use toolkit that allows rapid creation of complex NLP pipelines for semantic information processing on demand. The DKPro repository consists of several main parts created to serve the purposes of different NLP application areas
In this paper we investigate the problem of grammar inference from a different perspective. The common approach is to try to infer a grammar directly from example sentences, which either requires a large training set or suffers from bad accuracy. We instead view it as a problem of grammar restriction or sub-grammar extraction. We start from a large-scale resource grammar and a small number of examples, and find a sub-grammar that still covers all the examples. To do this we formulate the problem as a constraint satisfaction problem, and use an existing constraint solver to find the optimal grammar. We have made experiments with English, Finnish, German, Swedish and Spanish, which show that 10–20 examples are often sufficient to learn an interesting domain grammar. Possible applications include computer-assisted language learning, domain-specific dialogue systems, computer games, Q/A-systems, and others.
Controlled Natural Languages (CNLs) have many applications including document authoring, automatic reasoning on texts and reliable machine translation, but their application is not limited to these areas. We explore a new application area of CNLs, the use of CNLs in computer-assisted language learning. In this paper we present a a web application for language learning using CNLs as well as a detailed description of the properties of the family of CNLs it uses.
We present a light-weight tool for the annotation of linguistic data on multiple levels. It is based on the simplification of annotations to sets of markables having attributes and standing in certain relations to each other. We describe the main features of the tool, emphasizing its simplicity, customizability and versatility
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.
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.
Beyond the stars: exploiting free-text user reviews to improve the accuracy of movie recommendations
(2009)
In this paper we show that the extraction of opinions from free-text reviews can improve the accuracy of movie recommendations. We present three approaches to extract movie aspects as opinion targets and use them as features for the collaborative filtering. Each of these approaches requires different amounts of manual interaction. We collected a data set of reviews with corresponding ordinal (star) ratings of several thousand movies to evaluate the different features for the collaborative filtering. We employ a state-of-the-art collaborative filtering engine for the recommendations during our evaluation and compare the performance with and without using the features representing user preferences mined from the free-text reviews provided by the users. The opinion mining based features perform significantly better than the baseline, which is based on star ratings and genre information only.
This paper presents the Lehnwortportal Deutsch, a new, freely accessible publication platform for resources on German lexical borrowings in other languages, to be launched in the second half of 2022. The system will host digital-native sources as well as existing, digitized paper dictionaries on loanwords, initially for some 15 recipient languages. All resources remain accessible as individual standalone dictionaries; in addition, data on words (etyma, loanwords etc.) together with their senses and relations to each other is represented as a cross-resource network in a graph database, with careful distinction between information present in the original sources and the curated portal network data resulting from matching and merging information on, e. g., lexical units appearing in multiple dictionaries. Special tooling is available for manually creating graphs from dictionary entries during digitization and for editing and augmenting the graph database. The user interface allows users to browse individual dictionaries, navigate through the underlying graph and ‘click together’ complex queries on borrowing constellations in the graph in an intuitive way. The web application will be available as open source.
Germany’s diverse history in the 20th century raises the question of how social upheavals were constituted in and through political discourse. By analysing basic concepts, the research network “The 20th century in basic concepts” (based at the Leibniz institutes IDS, ZfL, ZZF) aims to identify continuities and discontinuities in political and social discourse. In this way, historical sediments of the present are to be uncovered and those challenges identified that emerged in the course of the 20th century and continue to shape political discourse until the present.
We present a supervised machine learning AND system which tackles semantic similarity between publication titles by means of word embeddings. Word embeddings are integrated as external components, which keeps the model small and efficient, while allowing for easy extensibility and domain adaptation. Initial experiments show that word embeddings can improve the Recall and F score of the binary classification sub-task of AND. Results for the clustering sub-task are less clear, but also promising and overall show the feasibility of the approach.
The demo presents a minimalist, off-the-shelf AND tool which provides a fundamental AND operation, the comparison of two publications with ambiguous authors, as an easily accessible HTTP interface. The tool implements this operation using standard AND functionality, but puts particular emphasis on advanced methods from natural language processing (NLP) for comparing publication title semantics.
This paper describes the TEI-based ISO standard 24624:2016 ‘Transcription of spoken language’ and other formats used within CLARIN for spoken language resources. It assesses the current state of support for the standard and the interoperability between these formats and with rele- vant tools and services. The main idea behind the paper is that a digital infrastructure providing language resources and services to researchers should also allow the combined use of resources and/or services from different contexts. This requires syntactic and semantic interoperability. We propose a solution based on the ISO/TEI format and describe the necessary steps for this format to work as an exchange format with basic semantic interoperability for spoken language resources across the CLARIN infrastructure and beyond.
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.
This paper presents an algorithm and an implementation for efficient tokenization of texts of space-delimited languages based on a deterministic finite state automaton. Two representations of the underlying data structure are presented and a model implementation for German is compared with state-of-the-art approaches. The presented solution is faster than other tools while maintaining comparable quality.
We present the use of count-based and predictive language models for exploring language use in the German Reference Corpus DeReKo. For collocation analysis along the syntagmatic axis we employ traditional association measures based on co-occurrence counts as well as predictive association measures derived from the output weights of skipgram word embeddings. For inspecting the semantic neighbourhood of words along the paradigmatic axis we visualize the high dimensional word embeddings in two dimensions using t-stochastic neighbourhood embeddings. Together, these visualizations provide a complementary, explorative approach to analysing very large corpora in addition to corpus querying. Moreover, we discuss count-based and predictive models w.r.t. scalability and maintainability in very large corpora.
The debate on the use of personal data in language resources usually focuses — and rightfully so — on anonymisation. However, this very same debate usually ends quickly with the conclusion that proper anonymisation would necessarily cause loss of linguistically valuable information. This paper discusses an alternative approach — pseudonymisation. While pseudonymisation does not solve all the problems (inasmuch as pseudonymised data are still to be regarded as personal data and therefore their processing should still comply with the GDPR principles), it does provide a significant relief, especially — but not only — for those who process personal data for research purposes. This paper describes pseudonymisation as a measure to safeguard rights and interests of data subjects under the GDPR (with a special focus on the right to be informed). It also provides a concrete example of pseudonymisation carried out within a research project at the Institute of Information Technology and Communications of the Otto von Guericke University Magdeburg.
In this paper we investigate the coverage of the two knowledge sources WordNet and Wikipedia for the task of bridging resolution. We report on an annotation experiment which yielded pairs of bridging anaphors and their antecedents in spoken multi-party dialog. Manual inspection of the two knowledge sources showed that, with some interesting exceptions, Wikipedia is superior to WordNet when it comes to the coverage of information necessary to resolve the bridging anaphors in our data set. We further describe a simple procedure for the automatic extraction of the required knowledge from Wikipedia by means of an API, and discuss some of the implications of the procedure’s performance.
We present an implemented system for the resolution of it, this, and that in transcribed multi-party dialog. The system handles NP-anaphoric as well as discourse-deictic anaphors, i.e. pronouns with VP antecedents. Selectional preferences for NP or VP antecedents are determined on the basis of corpus counts. Our results show that the system performs significantly better than a recency-based baseline.
In this paper, we present a suite of flexible UIMA-based components for information retrieval research which have been successfully used (and re-used) in several projects in different application domains. Implementing the whole system as UIMA components is beneficial for configuration management, component reuse, implementation costs, analysis and visualization.
This paper introduces LRTwiki, an improved variant of the Likelihood Ratio Test (LRT). The central idea of LRTwiki is to employ a comprehensive domain specific knowledge source as additional “on-topic” data sets, and to modify the calculation of the LRT algorithm to take advantage of this new information. The knowledge source is created on the basis of Wikipedia articles. We evaluate on the two related tasks product feature extraction and keyphrase extraction, and find LRTwiki to yield a significant improvement over the original LRT in both tasks.
We present WOMBAT, a Python tool which supports NLP practitioners in accessing word embeddings from code. WOMBAT addresses common research problems, including unified access, scaling, and robust and reproducible preprocessing. Code that uses WOMBAT for accessing word embeddings is not only cleaner, more readable, and easier to reuse, but also much more efficient than code using standard in-memory methods: a Python script using WOMBAT for evaluating seven large word embedding collections (8.7M embedding vectors in total) on a simple SemEval sentence similarity task involving 250 raw sentence pairs completes in under ten seconds end-to-end on a standard notebook computer.
Lexical resources are often represented in table form, e. g., in relational databases, or represented in specially marked up texts, for example, in document based XML models. This paper describes how it is possible to model lexical structures as graphs and how this model can be used to exploit existing lexical resources and even how different types of lexical resources can be combined.
Lexicon schemas and their use are discussed in this paper from the perspective of lexicographers and field linguists. A variety of lexicon schemas have been developed, with goals ranging from computational lexicography (DATR) through archiving (LIFT, TEI) to standardization (LMF, FSR). A number of requirements for lexicon schemas are given. The lexicon schemas are introduced and compared to each other in terms of conversion and usability for this particular user group, using a common lexicon entry and providing examples for each schema under consideration. The formats are assessed and the final recommendation is given for the potential users, namely to request standard compliance from the developers of the tools used. This paper should foster a discussion between authors of standards, lexicographers and field linguists.
We describe a simple procedure for the automatic creation of word-level alignments between printed documents and their respective full-text versions. The procedure is unsupervised, uses standard, off-the-shelf components only, and reaches an F-score of 85.01 in the basic setup and up to 86.63 when using pre- and post-processing. Potential areas of application are manual database curation (incl. document triage) and biomedical expression OCR.
pyMMAX2 is an API for processing MMAX2 stand-off annotation data in Python. It provides a lightweight basis for the development of code which opens up the Java- and XML-based ecosystem of MMAX2 for more recent, Python-based NLP and data science methods. While pyMMAX2 is pure Python, and most functionality is implemented from scratch, the API re-uses the complex implementation of the essential business logic for MMAX2 annotation schemes by interfacing with the original MMAX2 Java libraries. pyMMAX2 is available for download at http://github.com/nlpAThits/pyMMAX2.
We introduce a novel scientific document processing task for making previously inaccessible information in printed paper documents available to automatic processing. We describe our data set of scanned documents and data records from the biological database SABIO-RK, provide a definition of the task, and report findings from preliminary experiments. Rigorous evaluation proved challenging due to lack of gold-standard data and a difficult notion of correctness. Qualitative inspection of results, however, showed the feasibility and usefulness of the task.
In diesem Beitrag widmen wir uns der Frage, welche Schritte unternommen werden müssen, um Skripte, die bei der Aufbereitung und/oder Auswertung von Forschungsdaten Anwendung finden, so FAIR wie möglich zu gestalten. Dabei nehmen wir sowohl Reproduzierbarkeit, also den Weg von den (Roh)daten zu den Ergebnissen einer Studie, als auch Wiederverwertbarkeit, also die Möglichkeit, die Methoden einer Studie mittels des Skripts auf andere Daten anzuwenden, in den Fokus und beleuchten dabei die folgenden Aspekte: Arbeitsumgebung, Datenvalidierung, Modularisierung, Dokumentation und Lizenz.
In conversation, speakers need to plan and comprehend language in parallel in order to meet the tight timing constraints of turn taking. Given that language comprehension and speech production planning both require cognitive resources and engage overlapping neural circuits, these two tasks may interfere with one another in dialogue situations. Interference effects have been reported on a number of linguistic processing levels, including lexicosemantics. This paper reports a study on semantic processing efficiency during language comprehension in overlap with speech planning, where participants responded verbally to questions containing semantic illusions. Participants rejected a smaller proportion of the illusions when planning their response in overlap with the illusory word than when planning their response after the end of the question. The obtained results indicate that speech planning interferes with language comprehension in dialogue situations, leading to reduced semantic processing of the incoming turn. Potential explanatory processing accounts are discussed.
Lors de la négociation située de l'alternance des tours de parole en interaction (Sacks, Schegloff et Jefferson, 1974), les participants s'orientent vers la complétude possible des unités de construction de tour. Grâce à une complétion différée d'un tour de parole précédent, un locuteur peut revendiquer son droit à la parole au-delà d'un tour intercalaire d'un autre locuteur. Cet article exploite différentes formes de cette "delayed completion" (Lerner, 1989) en français parlé. À l'aide du cadre théorique de l'Analyse conversationnelle (ten Have, 1999), nous démontrerons que ce procédé ne relève pas uniquement d'une alternance de tour de parole problématique, mais aussi de séquences collaboratives, qui sont en lien étroit avec le phénomène des constructions syntaxiques collaboratives. En s'intéressant à ces structures syntaxiques émergentes, il est possible de démontrer la négociation située et locale - tour par tour – du droit à la parole et de la dynamique de l'alternance des tours en conversation ordinaire. A base d'une collection d'extraits issus d'interactions naturelles enregistrées en audio ou en vidéo, différentes manières de revendiquer ou de partager son tour seront illustrées. Lors des analyses, une attention particulière sera dédiée à quelques phénomènes récurrents dans les séquences de complétion différée. Ainsi, l'exploitation de certaines conjonctions en tant que marqueurs discursifs ou la présence d'allongements vocaliques en fin du premier segment semblent indiquer des co-occurrences de ressources audibles spécifiques à différents types de complétion différée en conversation française.
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.
Cette contribution discute différents enjeux dégagés lors d’une étude des pratiques professionnelles plurilingues : ces enjeux ont émergé d’une analyse menée collaborativement par deux équipes de chercheurs, à Lyon et à Paris, participant au projet européen DYLAN (6e programme cadre) et élaborant ensemble l’analyse empirique d’un extrait d’une réunion de travail, enregistrée dans le cadre d’une collaboration sur un même terrain. Cette analyse est l’occasion de thématiser de manière exemplaire un certain nombre de questions surgissant de l’étude des contacts des langues dans les contextes professionnels, concernant aussi bien les enjeux épistémologiques que l'engagement du chercheur sur le terrain.
The current state of the art for metadata provision allows for a very flexible approach, catering for the needs of different archives and communities, referring to common data category registries that describe the meaning of a data category at least to authors of metadata. Component models for metadata provisions are for example used by CLARIN and META-SHARE, but there is also an increased flexibility in other metadata schemas such as Dublin Core, which is usually not seen as appropriate for meaningful description of language resources.
Making resources available for others and putting this to a second use in other projects has never been more widely accepted as a sensible efficient way to avoid a waste of efforts and resources. However, when it comes to the details, there is still a vast number of problems. This workshop has aimed at being a forum to address issues and challenges in the concrete work with metadata for LRs, not restricted to a single initiative for archiving LRs. It has allowed for exchange and discussion and we hope that the reader finds the articles here compiled interesting and useful.
This paper describes the ongoing work to integrate WebLicht into the CLARIN infrastructure. It introduces the CLARIN infrastructure for scholars in the humanities and social sciences as well as WebLicht - an orchestration and execution environment that is built upon Service Oriented Architecture principles. The integration of WebLicht into the CLARIN infrastructure involves adapting it to the standards and practices used within CLARIN, including distributed repositories, CMDI metadata, and persistent identifiers.
The ISOcat registry reloaded
(2012)
The linguistics community is building a metadata-based infrastructure for the description of its research data and tools. At its core is the ISOcat registry, a collaborative platform to hold a (to be standardized) set of data categories (i.e., field descriptors). Descriptors have definitions in natural language and little explicit interrelations. With the registry growing to many hundred entries, authored by many, it is becoming increasingly apparent that the rather informal definitions and their glossary-like design make it hard for users to grasp, exploit and manage the registry’s content. In this paper, we take a large subset of the ISOcat term set and reconstruct from it a tree structure following the footsteps of schema.org. Our ontological re-engineering yields a representation that gives users a hierarchical view of linguistic, metadata-related terminology. The new representation adds to the precision of all definitions by making explicit information which is only implicitly given in the ISOcat registry. It also helps uncovering and addressing potential inconsistencies in term definitions as well as gaps and redundancies in the overall ISOcat term set. The new representation can serve as a complement to the existing ISOcat model, providing additional support for authors and users in browsing, (re-)using, maintaining, and further extending the community’s terminological metadata repertoire.
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.
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.
To optimize the sharing and reuse of existing data, many funding organizations now require researchers to specify a management plan for research data. In such a plan, researchers are supposed to describe the entire life cycle of the research data they are going to produce, from data creation to formatting, interpretation, documentation, short-term storage, long-term archiving and data re-use. To support researchers with this task, we built DMPTY, a wizard that guides researchers through the essential aspects of managing data, elicits information from them, and finally, generates a document that can be further edited and linked to the original research proposal.
Linguistics is facing the challenge of many other sciences as it continues to grow into increasingly complex subfields, each with its own separate or overarching branches. While linguists are certainly aware of the overall structure of the research field, they cannot follow all developments other than those of their subfields. It is thus important to help specialists but also newcomers alike to bushwhack through evolved or unknown territory of linguistic data. A considerable amount of research data in linguistics is described with metadata. While studies described and published in archived journals and conference proceedings receive a quite homogeneous set of metadata tags — e.g., author, title, publisher —, this does not hold for the empirical data and analyses that underlie such studies. Moreover, lexicons, grammars, experimental data, and other types of resources come in different forms; and to make things worse, their description in terms of metadata is also not uniform, if existing at all. These problems are well-known and there are now a number of international initiatives — e.g., CLARIN, FlareNet, MetaNet, DARIAH — to build infrastructures for managing linguistic resources. The NaLiDa project, funded by the German Research Foundation, aims at facilitating the management and access to linguistic resources originating from German research institutions. In cooperation with the German SFB 833 research center, we are developing a combination of faceted and full-text search to give integrated access through heterogeneous metadata sets. Our approach is supported by a central registry for metadata field descriptors, and a component repository for structured groups of data categories as larger building blocks.