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We present a simple tool for extracting text and markup information from printouts of (not only) scientific documents. While the heavy-lifting OCR is done by off-the-shelf tesseract, our focus is on detection, extraction, and basic categorization of color-highlighted text sections, as well as on providing a framework for downstream processing of extraction results. The tool can be useful for document analysis tasks that must, or benefit from being able to, use printed paper.
The CLARIN Concept Registry (CCR) is the common semantic ground for most CMDI-based profiles to describe language-related resources in the CLARIN universe. While the CCR supports semantic interoperability within this universe, it does not extend beyond it. The flexibility of CMDI, however, allows users to use other term or concept registries when defining their metadata components. In this paper, we describe our use of schema.org, a light ontology used by many parties across disciplines.
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.
Datenmanagement wird durch die Forschungsföderungsorganisationen (etwa in Horizon 2020 der EU, die Allianz der deutschen Wissenschaftsorganisationen oder in DFG geförderten Projekten) mehr und mehr Teil der Forschungslandschaft. Für die Computerlinguistik ist das Forschungsdatenmanagement aber auch Teil des Forschungsgebietes: Datenmodellierung und Transformation für die nachhaltige Datenspeicherung gehören in den Bereich der Texttechnologie und Textlinguistik, ebenso die Modellierung der beschreibenden Daten zu Datensätzen.
Contents:
1. Andreas Dittrich: Intra-connecting a small exemplary literary corpus with semantic web technologies for exploratory literary studies, S. 1
2. John Kirk, Anna Čermáková: From ICE to ICC: The new International Comparable Corpus, S. 7
3. Dawn Knight, Tess Fitzpatrick, Steve Morris, Jeremy Evas, Paul Rayson, Irena Spasic, Mark Stonelake, Enlli Môn Thomas, Steven Neale, Jennifer Needs, Scott Piao, Mair Rees, Gareth Watkins, Laurence Anthony, Thomas Michael Cobb, Margaret Deuchar, Kevin Donnelly, Michael McCarthy, Kevin Scannell: Creating CorCenCC (Corpws Cenedlaethol Cymraeg Cyfoes – The National Corpus of Contemporary Welsh), S. 13
4. Marc Kupietz, Andreas Witt, Piotr Bański, Dan Tufiş, Dan Cristea, Tamás Váradi: EuReCo - Joining Forces for a European Reference Corpus as a sustainable base for cross-linguistic research, S. 15
5. Harald Lüngen, Marc Kupietz: CMC Corpora in DeReKo, S. 20
6. David McClure, Mark Algee-Hewitt, Douris Steele, Erik Fredner, Hannah Walser: Organizing corpora at the Stanford Literary Lab, S. 25
7. Radoslav Rábara, Pavel Rychlý ,Ondřej Herman: Accelerating corpus search using multiple cores, S. 30
8. John Vidler, Stephen Wattam: Keeping Properties with the Data: CL-MetaHeaders – An Open Specification, S. 35
9. Vladimir Benko: Are Web Corpora Inferior? The Case of Czech and Slovak, S. 43
10. Edyta Jurkiewicz-Rohrbacher, Zrinka Kolaković, Björn Hansen: Web Corpora – the best possible solution for tracking phenomena in underresourced languages: clitics in Bosnian, Croatian and Serbian, S. 49
11. Vít Suchomel: Removing Spam from Web Corpora Through Supervised Learning Using FastText, S. 56
Unlike traditional text corpora collected from trustworthy sources, the content of web based corpora has to be filtered. This study briefly discusses the impact of web spam on corpus usability and emphasizes the importance of removing computer generated text from web corpora.
The paper also presents a keyword comparison of an unfiltered corpus with the same collection of texts cleaned by a supervised classifier trained using FastText. The classifier was able to recognize 71% of web spam documents similar to the training set but lacked both precision and recall when applied to short texts from another data set.
Corpus researchers, along with many other disciplines in science are being put under continual pressure to show accountability and reproducibility in their work. This is unsurprisingly difficult when the researcher is faced with a wide array of methods and tools through which to do their work; simply tracking the operations done can be problematic, especially when toolchains are often configured by the developers, but left largely as a black box to the user. Here we present a scheme for encoding this ‘meta data’ inside the corpus files themselves in a structured data format, along with a proof-of-concept tool to record the operations performed on a file.
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 article describes a series of ongoing efforts at the Stanford Literary Lab to manage a large collection of literary corpora (~40 billion words). This work is marked by a tension between two competing requirements – the corpora need to be merged together into higher-order collections that can be analyzed as units; but, at the same time, it’s also necessary to preserve granular access to the original metadata and relational organization of each individual corpus. We describe a set of data management practices that try to accommodate both of these requirements – Apache Spark is used to index data as Parquet tables on an HPC cluster at Stanford. Crucially, the approach distinguishes between what we call “canonical” and “combined” corpora, a variation on the well-established notion of a “virtual corpus” (Kupietz et al., 2014; Jakubíek et al., 2014; van Uytvanck, 2010).
The paper presents best practices and results from projects dedicated to the creation of corpora of computer-mediated communication and social media interactions (CMC) from four different countries. Even though there are still many open issues related to building and annotating corpora of this type, there already exists a range of tested solutions which may serve as a starting point for a comprehensive discussion on how future standards for CMC corpora could (and should) be shaped like.
Editorial
(2016)
Gegenstand des Workshop-Beitrags ist die Verknüpfung heterogener linguistischer Ressourcen. Eine bedeutende Teilmenge von Ressourcen in der gegenwärtigen linguistischen Forschung und Anwendung besteht zum einen aus XML-annotierten Textdokumenten und zum anderen aus externen Ressourcen wie Grammatiken, Lexika oder Ontologien. Es wird eine Architektur vorgestellt, die eine Integration heterogener Ressourcen erlaubt, wobei die Methoden zur Integration unabhängig von der jeweiligen Anwendung sind und somit verschiedene Verknüpfungen ermöglichen. Eine exemplarische Anwendung der Methodologie ist die Analyse anaphorischer Beziehungen.