Introduction to Linguistic Annotation and Text Analytics

Figure 2.2: Levels of linguistic annotations. Afterthetexthasbeentokenizedintodistinctwords,eachwordcanbelabeledwithawordcategory (Noun, Verb, etc.).This task is part-of-speech tagging. It deals with the linguistic level of morphology, ...

Author: Graham Wilcock

Publisher: Morgan & Claypool Publishers

ISBN: 9781598297386

Category: Computers

Page: 149

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formats using XSLT transformations. The two main text analytics architectures, GATE and UIMA, are then described and compared, with practical exercises showing how to configure and customize them. The final chapter is an introduction to text analytics, describing the main applications and functions including named entity recognition, coreference resolution and information extraction, with practical examples using both open source and commercial tools." --Book Jacket.

Provenance and Annotation of Data

The AstroDAS portal and annotation server web service interfaces are implemented through Apache Axis2; the annotation server uses a PostgreSQL or IBM DB2 database, accessed by the web service interface through JDBC.

Author: Ian Foster

Publisher: Springer

ISBN: 9783540463030

Category: Computers

Page: 292

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This book constitutes the thoroughly referred post-proceedings of the International Provenance and Annotation Workshops, IPAW 2006, held in Chicago, Il, USA in May 2006. The 26 revised full papers presented together with two keynote papers were carefully selected for presentation during two rounds of reviewing and improvement. The papers are organized in topical sections.

Collaborative Annotation for Reliable Natural Language Processing

are aware of no example of annotation using a second-order language. Jean Véronis concluded his state-of-the-art of the automatic annotation technology in 2000 with a figure summarizing the situation [VÉR 00].

Author: Karën Fort

Publisher: John Wiley & Sons

ISBN: 9781119307655

Category: Computers

Page: 192

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This book presents a unique opportunity for constructing a consistent image of collaborative manual annotation for Natural Language Processing (NLP). NLP has witnessed two major evolutions in the past 25 years: firstly, the extraordinary success of machine learning, which is now, for better or for worse, overwhelmingly dominant in the field, and secondly, the multiplication of evaluation campaigns or shared tasks. Both involve manually annotated corpora, for the training and evaluation of the systems. These corpora have progressively become the hidden pillars of our domain, providing food for our hungry machine learning algorithms and reference for evaluation. Annotation is now the place where linguistics hides in NLP. However, manual annotation has largely been ignored for some time, and it has taken a while even for annotation guidelines to be recognized as essential. Although some efforts have been made lately to address some of the issues presented by manual annotation, there has still been little research done on the subject. This book aims to provide some useful insights into the subject. Manual corpus annotation is now at the heart of NLP, and is still largely unexplored. There is a need for manual annotation engineering (in the sense of a precisely formalized process), and this book aims to provide a first step towards a holistic methodology, with a global view on annotation.

Natural Language Annotation for Machine Learning

Annotation format standards Linguistic annotation projects are being done all over the world for many different, but often complementary, reasons. Because of this, in the past few years ISO has been developing the Linguistic Annotation ...

Author: James Pustejovsky

Publisher: "O'Reilly Media, Inc."

ISBN: 9781449359768

Category: Computers

Page: 342

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Create your own natural language training corpus for machine learning. Whether you’re working with English, Chinese, or any other natural language, this hands-on book guides you through a proven annotation development cycle—the process of adding metadata to your training corpus to help ML algorithms work more efficiently. You don’t need any programming or linguistics experience to get started. Using detailed examples at every step, you’ll learn how the MATTER Annotation Development Process helps you Model, Annotate, Train, Test, Evaluate, and Revise your training corpus. You also get a complete walkthrough of a real-world annotation project. Define a clear annotation goal before collecting your dataset (corpus) Learn tools for analyzing the linguistic content of your corpus Build a model and specification for your annotation project Examine the different annotation formats, from basic XML to the Linguistic Annotation Framework Create a gold standard corpus that can be used to train and test ML algorithms Select the ML algorithms that will process your annotated data Evaluate the test results and revise your annotation task Learn how to use lightweight software for annotating texts and adjudicating the annotations This book is a perfect companion to O’Reilly’s Natural Language Processing with Python.

Provenance and Annotation of Data and Processes

Provenance-based rating can be decomposed in a generic part involving a provenance graph traversal and annotation manipulation, and an application-specific part computing actual ratings for a given purpose in an application.

Author: Bertram Ludäscher

Publisher: Springer

ISBN: 9783319164625

Category: Computers

Page: 298

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This book constitutes the revised selected papers of the 5th International Provenance and Annotation Workshop, IPAW 2014, held in Cologne, Germany in June 2014. The 14 long papers, 20 short papers and 4 extended abstracts presented were carefully reviewed and selected from 53 submissions. The papers include tools that enable provenance capture from software compilers, from web publications and from scripts, using existing audit logs and employing both static and dynamic instrumentation.

Provenance and Annotation of Data and Processes

Second International Provenance and Annotation Workshop, IPAW 2008, Salt Lake City, UT, USA, June 17-18, 2008 Juliana Freire, David Koop, Luc Moreau. data items, as specified by users. Since these paths are essentially forming a network ...

Author: Juliana Freire

Publisher: Springer Science & Business Media

ISBN: 9783540899648

Category: Business & Economics

Page: 328

View: 282

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Computinghasbeenanenormousacceleratortoscienceandindustryalikeandit has led to an information explosion in many di?erent ?elds. The unprecedented volume of data acquired from sensors, derived by simulations and data analysis processes, accumulated in warehouses, and often shared on the Web, has given risetoanew?eldofresearch: provenancemanagement.Provenance(alsoreferred to as audit trail, lineage, and pedigree) captures information about the steps used to generate a given data product. Such information provides important documentation that is key to preserving data, to determining the data's quality and authorship, to understanding, reproducing, as well as validating results. Provenancemanagement has become an active ?eld of research, as evidenced byrecentspecializedworkshops, surveys, andtutorials.Provenancesolutionsare needed in many di?erent domains and applications, from environmental science and physics simulations, to business processes and data integration in wa- houses. Not surprisingly, di?erent techniques and provenance models have been proposed in many areas such as work?ow systems, visualization, databases, d- ital libraries, and knowledge representation. An important challenge we face - dayishowtointegratethesetechniquesandmodelssothatcompleteprovenance can be derived for complex data products. The InternationalProvenanceand AnnotationWorkshop(IPAW 2008)wasa follow-up to previous workshopsin Chigago (2006, 2002)and Edinburgh (2003). It was held during June 17-18, in Salt Lake City, at the University of Utah campus. IPAW 2008 brought together computer scientists from di?erent areas and provenance users to discuss open problems related to the provenance of computational and non-computational artifacts. A total of 55 people attended the workshop.

Annotation for the Semantic Web

i : useslcon Question file : /// home / questionicon.jpg ? rdf : type 12A3DF65 Figure 9 : Adding an icon for all annotations of type Question . annotation reply Annotation Reply root " This is great " " I totally rdfrype XDoc.html ...

Author: Siegfried Handschuh

Publisher: IOS Press

ISBN: 158603345X

Category: Business & Economics

Page: 229

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The Digital Library Approach. Manual Annotations. Wrapping. Information Extraction & Linguistics. Graphics. Usage of Annotations.

Annotation

The comprehensive Papers of Benjamin Franklin , rich with detailed annotations , will be a literary treasure for all who wish to know more about him and his world . Changes in Staff Debra Chamberlain , a grants program assistant ...

Author:

Publisher:

ISBN: UIUC:30112075693470

Category: United States

Page:

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Annotation exploitation and evaluation of parallel corpora TC3 I

The system keeps raw corpora and annotations separate (stand-off annotation) and thus allows the creation of multiple annotation entries for the same corpus entry. Differently from other systems that replicate raw corpus data in ...

Author: Silvia Hansen-Schirra

Publisher: Language Science Press

ISBN: 9783946234852

Category: Language Arts & Disciplines

Page: 164

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Exchange between the translation studies and the computational linguistics communities has traditionally not been very intense. Among other things, this is reflected by the different views on parallel corpora. While computational linguistics does not always strictly pay attention to the translation direction (e.g. when translation rules are extracted from (sub)corpora which actually only consist of translations), translation studies are amongst other things concerned with exactly comparing source and target texts (e.g. to draw conclusions on interference and standardization effects). However, there has recently been more exchange between the two fields – especially when it comes to the annotation of parallel corpora. This special issue brings together the different research perspectives. Its contributions show – from both perspectives – how the communities have come to interact in recent years.

Provenance and Annotation of Data and Processes

6th International Provenance and Annotation Workshop, IPAW 2016, McLean, VA, USA, June 7-8, 2016, Proceedings Marta Mattoso, Boris Glavic. core of the architecture is the middle layer (Provenance-based Management) and its semantics ...

Author: Marta Mattoso

Publisher: Springer

ISBN: 9783319405933

Category: Computers

Page: 236

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This book constitutes the refereed proceedings of the 6th International Provenance and Annotation Workshop, IPAW 2016, held in McLean, VA, USA, in June 2016. The 12 revised full papers, 14 poster papers, and 2 demonstration papers presentedwere carefully reviewed and selected from 54 submissions. The papers feature state-of-the-art research and practice around the automatic capture, representation, and use of provenance. They are organized in topical sections on provenance capture, provenance analysis and visualization, and provenance models and applications.