2,598 research outputs found
The Catalogue of the Hodgson Collection in the British Library
A report on the completion of the online catalogue of the Hodgson collection in the British Library, including a biography of Brian Houghton Hodgson (1901-94)
Linguistically-Informed Neural Architectures for Lexical, Syntactic and Semantic Tasks in Sanskrit
The primary focus of this thesis is to make Sanskrit manuscripts more
accessible to the end-users through natural language technologies. The
morphological richness, compounding, free word orderliness, and low-resource
nature of Sanskrit pose significant challenges for developing deep learning
solutions. We identify four fundamental tasks, which are crucial for developing
a robust NLP technology for Sanskrit: word segmentation, dependency parsing,
compound type identification, and poetry analysis. The first task, Sanskrit
Word Segmentation (SWS), is a fundamental text processing task for any other
downstream applications. However, it is challenging due to the sandhi
phenomenon that modifies characters at word boundaries. Similarly, the existing
dependency parsing approaches struggle with morphologically rich and
low-resource languages like Sanskrit. Compound type identification is also
challenging for Sanskrit due to the context-sensitive semantic relation between
components. All these challenges result in sub-optimal performance in NLP
applications like question answering and machine translation. Finally, Sanskrit
poetry has not been extensively studied in computational linguistics.
While addressing these challenges, this thesis makes various contributions:
(1) The thesis proposes linguistically-informed neural architectures for these
tasks. (2) We showcase the interpretability and multilingual extension of the
proposed systems. (3) Our proposed systems report state-of-the-art performance.
(4) Finally, we present a neural toolkit named SanskritShala, a web-based
application that provides real-time analysis of input for various NLP tasks.
Overall, this thesis contributes to making Sanskrit manuscripts more accessible
by developing robust NLP technology and releasing various resources, datasets,
and web-based toolkit.Comment: Ph.D. dissertatio
Toiling with the Pāli Canon
The paper describes the preparation of a Buddhist corpus in the Middle Indo-Aryan language Pāli, which is available only in a flat TEI format, for content-based analysis. This task includes transforming the file into a hierarchical TEI P5 representation, followed by tokenisation (including sandhi resolution), lemmatisation, and POS tagging
Inseri as a Potential IT Framework for the Research Projects in Humanities: Use Case of Sanskrit Manuscripts Project
Dedicated to the memory of Hans Cools who suddenly passed away in April 2021 in the middle of his thorough and fascinating work on Semantic Web Technology
Some of the most tedious technical problems that a scholar in the digital humanities faces today is connecting multiple software solutions from various origins, supplementing the missing ones, and making the whole into a consistent and stable workflow solution. [1] The subject of the present article, Inseri, is neither a special tool for manuscript transcription, nor an easy-to-use TEI editor: it is a framework that can hold those software pieces together in a precise way and help the researcher with the dataflow from one step of the project to the other. The aim of the article is to present, on the one hand, the philosophy of Inseri, and, on the other hand, to go through the typical stages of a manuscripts-based critical edition project, following the flow and the transformation of the data
Providing Access to Sources for India Studies at Indiana University Libraries: Piecing a Quilt
The Haworth Press, Inc. "author re-use of work" statement was used in the creation of the citation.Indiana University Libraries' cooperative collection development for a new India Studies Program during a four year period (1998-2001)is the focus. An appendix features practical tips for working in Hindi and Sanskrit languages
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