Refine
Year of publication
- 2015 (15) (remove)
Document Type
- Conference Proceeding (15) (remove)
Language
- English (15)
Has Fulltext
- yes (15)
Keywords
- Korpus <Linguistik> (10)
- Annotation (9)
- Corpus annotation (6)
- Corpus technology (6)
- Datenbanksystem (6)
- Large corpora (5)
- Corpus linguistics (4)
- Deutsch (4)
- Corpus management (3)
- Corpus query language (3)
Publicationstate
- Veröffentlichungsversion (15) (remove)
Reviewstate
- Peer-Review (15) (remove)
Publisher
- Institut für Deutsche Sprache (8)
- Association for Computational Linguistics ( ACL ); Curran Associates, Inc. (1)
- German Society for Computational Linguistics & Language Technology (GSCL) (1)
- Gesellschaft für Sprachtechnologie and Computerlinguistik (1)
- International Phonetic Association (IPA) (1)
- Linköping University Electronic Press (1)
The IMS Open Corpus Workbench (CWB) software currently uses a simple tabular data model with proven limitations. We outline and justify the need for a new data model to underlie the next major version of CWB. This data model, dubbed Ziggurat, defines a series of types of data layer to represent different structures and relations within an annotated corpus; each such layer may contain variables of different types. Ziggurat will allow us to gradually extend and enhance CWB’s existing CQP-syntax for corpus queries, and also make possible more radical departures relative not only to the current version of CWB but also to other contemporary corpus-analysis software.
In a project called "A Library of a Billion Words" we needed an implementation of the CTS protocol that is capable of handling a text collection containing at least 1 billion words. Because the existing solutions did not work for this scale or were still in development I started an implementation of the CTS protocol using methods that MySQL provides. Last year we published a paper that introduced a prototype with the core functionalities without being compliant with the specifications of CTS (Tiepmar et al., 2013). The purpose of this paper is to describe and evaluate the MySQL based implementation now that it is fulfilling the specifications version 5.0 rc.1 and mark it as finished and ready to use. Further information, online instances of CTS for all described datasets and binaries can be accessed via the projects website.
The Czech National Corpus (CNC) is a longterm project striving for extensive and continuous mapping of the Czech language. This effort results mostly in compilation, maintenance and providing free public access to a range of various corpora with the aim to offer a diverse, representative, and high-quality data for empirical research mainly in linguistics. Since 2012, the CNC is officially recognized as a research infrastructure funded by the Czech Ministry of Education, Youth and Sports which has caused a recent shift towards user service-oriented operation of the project. All project-related resources are now integrated into the CNC research portal at http://www.korpus.cz/. Currently, the CNC has an established and growing user community of more than 4,500 active users in the Czech Republic and abroad who put almost 1,900 queries per day using one of the user interfaces. The paper discusses the main CNC objectives for each particular domain, aiming at an overview of the current situation supplemented by an outline of future plans.
In this paper, I present the COW14 tool chain, which comprises a web corpus creation tool called texrex, wrappers for existing linguistic annotation tools as well as an online query software called Colibri2. By detailed descriptions of the implementation and systematic evaluations of the performance of the software on different types of systems, I show that the COW14 architecture is capable of handling the creation of corpora of up to at least 100 billion tokens. I also introduce our running demo system which currently serves corpora of up to roughly 20 billion tokens in Dutch, English, French, German, Spanish, and Swedish
Contents:
1. Michal Křen: Recent Developments in the Czech National Corpus, S. 1
2. Dan Tufiş, Verginica Barbu Mititelu, Elena Irimia, Stefan Dumitrescu, Tiberiu Boros, Horia Nicolai Teodorescu: CoRoLa Starts Blooming – An update on the Reference Corpus of Contemporary Romanian Language, S. 5
3. Sebastian Buschjäger, Lukas Pfahler, Katharina Morik: Discovering Subtle Word Relations in Large German Corpora, S. 11
4. Johannes Graën, Simon Clematide: Challenges in the Alignment, Management and Exploitation of Large and Richly Annotated Multi-Parallel Corpora, S. 15
5. Stefan Evert, Andrew Hardie: Ziggurat: A new data model and indexing format for large annotated text corpora, S. 21
6. Roland Schäfer: Processing and querying large web corpora with the COW14 architecture, S. 28
7. Jochen Tiepmar: Release of the MySQL-based implementation of the CTS protocol, S. 35
We present a quantitative approach to disambiguating flat morphological analyses and producing more deeply structured analyses. Based on existing morphological segmentations, possible combinations of resulting word trees for the next level are filtered first by criteria of linguistic plausibility and then by weighting procedures based on the geometric mean. The frequencies for weighting are derived from three different sources (counts of morphs in a lexicon, counts of largest constituents in a lexicon, counts of token frequencies in a corpus) and can be used either to find the best analysis on the level of morphs or on the next higher constituent level. The evaluation shows that for this task corpus-based frequency counts are slightly superior to counts of lexical data.
We investigate whether non-configurational languages, which display more word order variation than configurational ones, require more training data for a phenomenon to be parsed successfully. We perform a tightly controlled study comparing the dative alternation for English (a configurational language), German, and Russian (both non-configurational). More specifically, we compare the performance of a dependency parser when only canonical word order is present with its performance on data sets when all word orders are present. Our results show that for all languages, canonical data not only is easier to parse, but there exists no direct correspondence between the size of training sets containing free(er) word order variation and performance.
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.
With an increasing amount of text data available it is possible to automatically extract a variety of information about language. One way to obtain knowledge about subtle relations and analogies between words is to observe words which are used in the same context. Recently, Mikolov et al. proposed a method to efficiently compute Euclidean word representations which seem to capture subtle relations and analogies between words in the English language. We demonstrate that this method also captures analogies in the German language. Furthermore, we show that we can transfer information extracted from large non-annotated corpora into small annotated corpora, which are then, in turn, used for training NLP systems.
This article reports on the on-going CoRoLa project, aiming at creating a reference corpus of contemporary Romanian (from 1945 onwards), opened for online free exploitation by researchers in linguistics and language processing, teachers of Romanian, students. We invest serious efforts in persuading large publishing houses and other owners of IPR on relevant language data to join us and contribute the project with selections of their text and speech repositories. The CoRoLa project is coordinated by two Computer Science institutes of the Romanian Academy, but enjoys cooperation of and consulting from professional linguists from other institutes of the Romanian Academy. We foresee a written component of the corpus of more than 500 million word forms, and a speech component of about 300 hours of recordings. The entire collection of texts (covering all functional styles of the language) will be pre-processed and annotated at several levels, and also documented with standardized metadata. The pre-processing includes cleaning the data and harmonising the diacritics, sentence splitting and tokenization. Annotation will include morpho-lexical tagging and lemmatization in the first stage, followed by syntactic, semantic and discourse annotation in a later stage.
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.
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.
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.