Rapid Adaptation of NE Resolvers for Humanities Domains using Active Annotation

The entities mentioned in collections of scholarly articles in the Humanities (and in other scholarly domains) belong to different types from those familiar from news corpora, hence new resources need to be annotated to create supervised taggers for tasks such as ne extraction. However, in such domains there is a great need for making the best use possible of the annotators. One technique designed for this purpose is active annotation. We discuss our use of active annotation for annotating corpora of articles about Archaeology in the Portale della Ricerca Umanistica Trentina

From Index Locorum to Citation Network: an Approach to the Automatic Extraction of Canonical References and its Applications to the Study of Classical Texts

My research focusses on the automatic extraction of canonical references from publications in Classics. Such references are the standard way of citing classical texts and are found in great numbers throughout monographs, journal articles and commentaries. In chapters 1 and 2 I argue for the importance of canonical citations and for the need to capture them automatically. Their importance and function is to signal text passages that are studied and discussed, often in relation to one another as can be seen in parallel passages found in modern commentaries. Scholars in the field have long been exploiting this kind of information by manually creating indexes of cited passages, the so-called indices locorum. However, the challenge we now face is find new ways of indexing and retrieving information contained in the growing volume of digital archives and libraries. Chapters 3 and 4 look at how this problem can be tackled by translating the extraction of canonical citations into a computationally solvable problem. The approach I developed consists of treating the extraction of such citations as a problem of named entity extraction. This problem can be solved with some degree of accuracy by applying and adapting methods of Natural Language Processing. In this part of the dissertation I discuss the implementation of this approach as a working prototype and an evaluation of its performance. Once canonical references have been extracted from texts, the web of relations between documents that they create can be represented as a network. This network can then be searched, manipulated, visualised and analysed in various ways. In chapter 5 I focus specifically on how this network can be leveraged to search through bodies of secondary literature. Finally in chapter 6 I discuss how my work opens up new research perspectives in terms of visualisation, analysis and the application of such automatically extracted citation networks

Formal Linguistic Models and Knowledge Processing. A Structuralist Approach to Rule-Based Ontology Learning and Population

2013 - 2014The main aim of this research is to propose a structuralist approach for knowledge processing by means of ontology learning and population, achieved starting from unstructured and structured texts. The method suggested includes distributional semantic approaches and NL formalization theories, in order to develop a framework, which relies upon deep linguistic analysis... [edited by author]XIII n.s