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An ontology of masters of the Babylonian Talmud
Abstract
The purpose of this research is to build an ontology of the masters appearing in the Babylonian Talmud (BT). The ontology built so far has been shared as a Linked Open Data and it will be linked to existing vocabularies. This work has been developed in the context of the Babylonian Talmud Translation Project, where more than eighty Talmudists are working together, since 2012, at the translation (comprehensive of explicative notes and glossaries) of the Talmud into Italian. The construction of the resource has involved the application of tools leveraging on computational linguistics approaches. The ontology, already describing more than 500 masters, constitutes the first portion of a more comprehensive Talmudic Knowledge Base where the text itself, the terminology, the entities, and the concepts constituting the BT will be formalized and linked to each other.
Social network analysis of characters in historical works is a popular research methodology in the study of historical literature. This article proposes using this methodology to characterize and comparatively analyze editing styles of similar historical literary works to determine whether they were edited by the same hand. To that end, the study proposes constructing a network of characters for each of the works being studied and to compute standard statistical measures for these networks, thus producing a network-based profile for the editing style of each work, which can be compared to the profiles of various other works. To determine the effectiveness of this new approach, it was tested on two similar works from the realm of Rabbinic literature—the Mishnah and the Tosefta. Our findings show that despite the abundant structural, thematic, and linguistic similarities of the works, their network-based profiles demonstrated clear differences between them with respect to various parameters, like the degree of connectivity, density, and centrality of the networks and their communities, and also with respect to the usage of different types of relationships in each network. These differences are reflected in the network features of the works, rather than in their texts, and so it would be difficult to identify them using direct stylometric analysis on the texts of the works, especially given the stylistic and thematic similarity between them. The approach presented in this article forms a basis for developing automatic classifiers to identify different editors and editing styles based on works’ network-based profiles.
Wikidata has been widely used in Digital Humanities (DH) projects. However, a focused discussion regarding the current status, potential, and challenges of its application in the field is still lacking. A systematic review was conducted to identify and evaluate how DH projects perceive and utilize Wikidata, as well as its potential and challenges as demonstrated through use. This research concludes that: (1) Wikidata is understood in the DH projects as a content provider, a platform, and a technology stack; (2) it is commonly implemented for annotation and enrichment, metadata curation, knowledge modelling, and Named Entity Recognition (NER); (3) Most projects tend to consume data from Wikidata, whereas there is more potential to utilize it as a platform and a technology stack to publish data on Wikidata or to create an ecosystem of data exchange; and (4) Projects face two types of challenges: technical issues in the implementations and concerns with Wikidata’s data quality. In the discussion, this article contributes to addressing three issues related to coping with the challenges in the specific context of the DH field based on the research findings: the relevance and authority of other available domain sources; domain communities and their practices; and workflow design that coordinates technical and labour resources from projects and Wikidata.
La diffusione del Covid-19 nel corso del 2020 ha comportato cambiamenti
epocali nei comportamenti dei cittadini di tutto il mondo. Per cercare di comprendere
e anticipare le reazioni indotte in particolare dal lockdown sull’agire
umano, il gruppo di ricerca Mutamenti Sociali, Valutazione e Metodi
(MUSA) del Consiglio Nazionale delle Ricerche - Istituto di Ricerche sulla
Popolazione e le Politiche Sociali (CNR-IRPPS) ha istituito a marzo 2020
l’Osservatorio sui Mutamenti Sociali in Atto – Covid-19 (MSA-Covid-19)
con due primari obiettivi: indagare gli effetti dell’improvvisa interruzione
dell’interazione fisica nelle reti sociali, parentali e amicali, e studiare le conseguenze
del confinamento domestico, che ha prodotto una inedita intensificazione
della prossimità tra soggetti coabitanti. Attraverso un approccio
psicosociale, sono state condotte due ricerche su scala nazionale riguardanti
una molteplicità di dimensioni di analisi e di variabili afferenti al pensiero
e all’azione individuale. Il capitolo illustra i principali temi oggetto di indagine
e le informazioni fino ad oggi prodotte dall’Osservatorio, che riguardano
l’uso del tempo libero e del web, l’iperconnessione, gli stereotipi di
genere e la violenza di genere, la fiducia sistemica, le emozioni primarie e
le strategie di coping. Nella trattazione di queste tematiche vengono prese
in considerazione comparazioni significative tra i dati della prima e della
seconda ricerca.
The Qur’an is considered as the first source of knowledge and guidance for Muslims throughout the
world. It’s a difficult book to understand and to interpret without consulting domain experts and
Qur’anic commentaries (Tafsir books). Therefore it’s very sensitive to analyze and to model his
content for fear to make bad assumptions and axioms. In recent years a number of researches has been
done to facilitate the retrieval of knowledge from the Qur’an, but most of the available researches are
using human readable data resources and therefore cannot be reused and linked using semantic web
technologies. This is why in this project we will adopt an approach that enables humans and
computers to understand the Qur’an knowledge throughout the creation of a Qur’anic ontology. The
goal of the ontology is to build a computational model capable of representing as much as possible of
the concepts mentioned on the Qur’an and the relationships between them using Protégé-OWL. The
ontology can be queried using SPARQL queries. For non-technical users we will build a tool that
enables them to browse the content of the ontology.
We describe a series of five statistical models of the translation process and give algorithms for estimating the parameters of these models given a set of pairs of sentences that are translations of one another. We define a concept of word-by-word alignment between such pairs of sentences. For any given pair of such sentences each of our models assigns a probability to each of the possible word-by-word alignments. We give an algorithm for seeking the most probable of these alignments. Although the algorithm is suboptimal, the alignment thus obtained accounts well for the word-by-word relationships in the pair of sentences. We have a great deal of data in French and English from the proceedings of the Canadian Parliament. Accordingly, we have restricted our work to these two languages; but we feel that because our algorithms have minimal linguistic content they would work well on other pairs of languages. We also feel, again because of the minimal linguistic content of our algorithms, that it is reasonable to argue that word-by-word alignments are inherent in any sufficiently large bilingual corpus.
In this paper we introduce the DOLCE upper level ontology, the first module of a Foundational Ontologies Library being developed within the WonderWeb project. DOLCE is presented here in an intuitive way; the reader should refer to the project deliverable for a detailed axiomatization. A comparison with WordNet's top-level taxonomy of nouns is also provided, which shows how DOLCE, used in addition to the OntoClean methodology, helps isolating and understanding some major WordNet's semantic limita- tions. We suggest that such analysis could hopefully lead to an "ontologi- cally sweetened" WordNet, meant to be conceptually more rigorous, cogni- tively transparent, and efficiently exploitable in several applications.
In recent years, there is growing interest in IT for Islamic Knowledge. Researchers in religious studies have started to use ontologies to improve knowledge construction and extraction from religious texts such as the Qur’an and Hadith. An ontology can be used to describe a logical domain theory with very expressive, complex, and meaningful information. Recent research has been done in Arabic language ontology and on holy Qur'an ontology but they are still incomplete. Also there are some other issues including the process used to extract and construct an ontology that needs extra work. This paper describes our actual and ongoing work in developing an ontology. Our approach is to investigate the applicability of ontology methods of formal Knowledge Representation from Artificial Intelligence and Text Analytics research to capture and represent abstract concepts in the Qur'an. We will implement three ontology methods. The first one is to elicit or extract the abstract concepts from experts in the domain. Another approach is to semi-automatically extract concepts from text sources from the domain. The last approach is to find existing partial ontologies for the domain, and try to unify and re-use them. Finally to evaluate our general Qur'an ontology, we will investigate practical use of the ontology in a semantic search application. We have implemented the third approach, merging of existing ontologies, The experimental verification result reveals that our proposed merging methods work well, as checked by human expert. A similarity measure was applied for ontology merging, and we report a high accuracy and recall through experiments.
Traduco is a web-based collaborative tool aimed at supporting the translation of texts that pose particular challenging interpretative issues. Nowadays, Computer-Assisted Translation (CAT) tools are mainly applied to the translation of technical manuals or legislative texts and are aimed at speeding up the translation process. Traduco extends most of the standard components of a traditional CAT tool with specific features necessary to support the interpretation and translation of complex texts (like the Babylonian Talmud, that we here present as a case study), which pose particular comprehension issues. Traduco goes beyond the translation and its printing: it includes features for the addition of notes and annotations and the creation of glossaries. Translators, editors, supervisors, and end-users accessing Traduco are able to use components that can ease the translation process through the use of CAT technologies, the supervision and managing of the whole process of translation and publishing, the exporting of translations and notes in standard formats for desktop publishing software and TEI format, and, soon, the possibility to perform automatic linguistic analysis of the text. Moreover, Traduco allows the users to insert notes, comments, annotations, and bibliographical references. The design and development of Traduco required the adoption of a multidisciplinary approach, leveraging on advances in software engineering, computational linguistics, knowledge engineering, and publishing.
This article presents general background information about the FrameNet project, including an introduction to its basic assumptions and goals, a description of its precursors, and information about its evolution during the six years of the project. The companion articles in this special issue of IJL describe various aspects of the project in greater detail.
Events have become central elements in the representation of data from domains such as history, cultural heritage, multimedia and geography. The Simple Event Model (SEM) is created to model events in these various domains, without making assumptions about the domain-specific vocabularies used. SEM is designed with a minimum of semantic commitment to guarantee maximal interoperability. In this paper, we discuss the general requirements of an event model for Web data and give examples from two use cases: historic events and events in the maritime safety and security domain. The advantages and disadvantages of several existing event models are discussed in the context of the historic example. We discuss the design decisions underlying SEM. SEM is coupled with a Prolog API that enables users to create instances of events without going into the details of the implementation of the model. By a tight coupling to existing Prolog packages, the API facilitates easy integration of event instances to Linked Open Data. We illustrate use of the API with examples from the maritime domain.
Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.
Because meaningful sentences are composed of meaningful words, any system that hopes to process natural languages as people do must have information about words and their meanings. This information is traditionally provided through dictionaries, and machine-readable dictionaries are now widely available. But dictionary entries evolved for the convenience of human readers, not for machines. WordNet ¹ provides a more effective combination of traditional lexicographic information and modern computing. WordNet is an online lexical database designed for use under program control. English nouns, verbs, adjectives, and adverbs are organized into sets of synonyms, each representing a lexicalized concept. Semantic relations link the synonym sets [4].
Introduction The World Wide Web has the potential to become a primary source for storing and accessing linguistic data, including data of the sort that are routinely collected by field linguists. Having large amounts of linguistic data on the Web will give linguists, indigenous communities, and language learners access to resources that have hitherto been difficult to obtain. For linguists, scientific data from the world's languages will be just as accessible as information in on-line newspapers. For indigenous communities, the Web will be a powerful instrument for maintaining language as a cultural resource. For students and educators, a new tool will be available for teaching and learning minority and endangered languages. For linguists in particular, having linguistic data on the Web means that data from different languages can be automatically searched and compared. Furthermore, the Webwould provide ready computational resources for the development of machine translation and other