Category: Digital Humanities

Automatic annotation of incomplete and scattered bibliographical references in Digital Humanities papers

Automatic annotation of incomplete and scattered bibliographical references in Digital Humanities papers

The reviewed article presents the project BILBO and illustrates the application of several appropriate machine-learning techniques to the constitution of proper reference corpora and the construction of efficient annotation models. In this way, solutions are proposed for the problem of extracting and processing useful information from bibliographic references in digital documentation whatever their bibliographic styles are. It proves the usefulness and high degree of accuracy of CRF techniques, which involve finding the most effective set of features (including three types of features: input, local and global features) of a given corpus of well-structured bibliographical data (with labels such as surname, forename or title). Moreover, this approach has not only been proven efficient when applied to such traditional, well-structured bibliographical data sets, but it also originally contributes to the processing of more complicated, less-structured references such as the ones contained in footnotes by applying SVM with new features for sequence classification.

[Click ‘Read more’ for the full post.]

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Web Scraping with Python for Beginners | The Digital Orientalist

Web Scraping with Python for Beginners | The Digital Orientalist

Introduction: In this blog post, James Harry Morris introduces the method of web scraping. Step by step from the installation of the packages, readers are explained how they can extract relevant data from websites using only the Python programming language and convert it into a plain text file. Each step is presented transparently and comprehensibly, so that this article is a prime example of OpenMethods and gives readers the equipment they need to work with huge amounts of data that would no longer be possible manually.

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A World of Possibilities: a corpus-based approach to the diachrony of modality in Latin

A World of Possibilities: a corpus-based approach to the diachrony of modality in Latin

Introduction: Hosted at the University of Lausanne, “A world of possibilities. Modal pathways over an extra-long period of time: the diachrony in the Latin language” (WoPoss) is a project under development exploiting a corpus-based approach to the study and reconstruction of the diachrony of modality in Latin.
Following specific annotation guidelines applied to a set of various texts pertaining to the time span between 3rd century BCE and 7th century CE, the work team lead by Francesca Dell’Oro aims at analyzing the patterns of modality in the Latin language through a close consideration of lexical markers.

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Pipelines for languages: not only Latin! The Italian NLP Tool (Tint)

Pipelines for languages: not only Latin! The Italian NLP Tool (Tint)

The StandforCore NLP wishes to represent a complete Java-based set of tools for various aspects of language analysis, from annotation to dependency parsing, from lemmatization
to coreference resolution. It thus provides a range of tools which
can be potentially applied to other languages apart from English.

Among the languages to which the StandfordCore NLP is mainly applied there is Italian, for which the Tint pipeline has been developed as described in the paper “Italy goes to Stanford: a collection of CoreNLP modules for Italian” by Alessio Palmero Apostolo and Giovanni Moretti.

On the Tint webpage the whole pipeline can be found and downloaded: it comprises tokenization and sentence splitting, morphological analysis and lemmatization, part-of-speech tagging, named-entity recognition and dependency parsing, including wrappers under construction. [Click ‘Read more’ for the whole post.]

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DH Research Software Engineers – For We Are Many

DH Research Software Engineers – For We Are Many

Introduction: This white paper is an outcome of a DH2019 workshop dedicated to foster closer collaboration among technology-oriented DH researchers and  developers of tools to support Digital Humanities research. The paper briefly outlines the most pressing issues in their collaboration and addresses topics such as: good practices to ease mutual understanding between scholars and researchers; software development and academic career and recognition; or sustainability and funding.

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Approaching Linked Data

Approaching Linked Data

Introduction: Linked Data and Linked Open Data are gaining an increasing interest and application in many fields. A recent experiment conducted in 2018 at Furman University illustrates and discusses some of the challenges from a pedagogical perspective posed by Linked Open Data applied to research in the historical domain.

“Linked Open Data to navigate the Past: using Peripleo in class” by Chiara Palladino describes the exploitation of the search-engine Peripleo in order to reconstruct the past of four archeologically-relevant cities. Many databases, comprising various types of information, have been consulted, and the results, as highlighted in the contribution by Palladino, show both advantages and limitations of a Linked Open Data-oriented approach to historical investigations.

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Do humanists need BERT?

Do humanists need BERT?

Introduction: Ted Underwood tests a new language representation model called “Bidirectional Encoder Representations from Transformers” (BERT) and asks if humanists should use it. Due to its high degree of difficulty and its limited success (e.g. in questions of genre detection) he concludes, that this approach will be important in the future but it’s nothing to deal with for humanists at the moment. An important caveat worth reading.

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‘Voyant Tools’

‘Voyant Tools’

Introduction: Digital humanists looking for tools in order to visualize and analyze texts can rely on ‘Voyant Tools’ (https://voyant-tools.org), a software package created by S.Sinclair and G.Rockwell. Online resources are available in order to learn how to use Voyant. In this post, we highlight two of them: “Using Voyant-Tools to Formulate Research Questions for Textual Data” by Filipa Calado (GC Digital Fellows and the tutorial “Investigating texts with Voyant” by Miriam Posner.

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