Introduction: NLP modelling and tasks performed by them are becoming an integral part of our daily realities (everyday or research). A central concern of NLP research is that for many of their users, these models still largely operate as black boxes with limited reflections on why the model makes certain predictions, how their usage is skewed towards certain content types, what are the underlying social, cultural biases etc. The open source Language Interoperability Tool aim to change this for the better and brings transparency to the visualization and understanding of NLP models. The pre-print describing the tool comes with rich documentation and description of the tool (including case studies of different kinds) and gives us an honest SWOT analysis of it.
OpenMethods Spotlights showcase people and epistemic reflections behind Digital Humanities tools and methods. You can find here brief interviews with the creator(s) of the blogs or tools that are highlighted on OpenMethods to humanize and contextualize them. In the first episode, Alíz Horváth is talking with Hilde de Weerdt at Leiden University about MARKUS, a tool that offers offers a variety of functionalities for the markup, analysis, export, linking, and visualization of texts in multiple languages, with a special focus on Chinese and now Korean as well.
East Asian studies are still largely underrepresented in digital humanities. Part of the reason for this phenomenon is the relative lack of tools and methods which could be used smoothly with non-Latin scripts. MARKUS, developed by Brent Ho within the framework of the Communication and Empire: Chinese Empires in Comparative Perspective project led by Hilde de Weerdt at Leiden University, is a comprehensive tool which helps mitigate this issue. Selected as a runner up in the category “Best tool or suite of tools” in the DH2016 awards, MARKUS offers a variety of functionalities for the markup, analysis, export, linking, and visualization of texts in multiple languages, with a special focus on Chinese and now Korean as well.
Introduction: GROBID is an already well-known open source tool in the field of Digital Humanities, originally built to extract and parse bibliographical metadata from scholarly works. The acronym stands for GeneRation Of BIbliographic Data.
Shaped by use cases and adoptions to a range of different DH and non-DH settings, the tool has been progressively evolved into a suite of technical features currently applied to various fields, like that of journals, dictionaries and archives.
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Historical newspapers, already available in many digitized collections, may represent a significant source of information for the reconstruction of events and backgrounds, enabling historians to cast new light on facts and phenomena, as well as to advance new interpretations. Lausanne, University of Zurich and C2DH Luxembourg, the ‘impresso – Media Monitoring of the Past’ project wishes to offer an advanced corpus-oriented answer to the increasing need of accessing and consulting collections of historical digitized newspapers.
[…] Thanks to a suite of computational tools for data extraction, linking and exploration, impresso aims at overcoming the traditional keyword-based approach by means of the application of advanced techniques, from lexical processing to semantically deepened n-grams, from data modelling to interoperability.
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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.]
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.
Introduction: Apart from its buoyant conclusion that authorship attribution methods are rather robust to noise (transcription errors) introduced by optical character recognition and handwritten text recognition, this article also offers a comprehensive read on the application of sophisticated computational techniques for testing and validation in a data curation process.
Introduction: Ecologists are much aided by historical sources of information on human-animal interaction. But how does one cope with the plethora of different descriptions for the same animal in the historic record? A Dutch research group reports on how to aggregate ‘Bunzings’, ‘Ullingen’, and ‘Eierdieven’ (‘Egg-thieves’) into a useful historical ecology knowledge base.
Introduction: This software paper describes ‘stylo’ – an R package for stylometric research and text processing.