MIRACLE Progress in Monolingual Information Retrieval at Ad-Hoc CLEF 2007

This paper presents the 2007 MIRACLE’s team approach to the Ad-Hoc Information Retrieval track. The main work carried out for this campaign has been around monolingual experiments, in the standard and in the robust tracks. The most important contributions have been the general introduction of automatic named-entities extraction and the use of Wikipedia resources. For the2007 campaign, runs were submitted for the following languages and tracks: a) Monolingual: Bulgarian, Hungarian, and Czech. b) Robust monolingual: French, English and Portuguese

Bootstrapping named entity resources for adaptive question answering systems

Los Sistemas de Búsqueda de Respuestas (SBR) amplían las capacidades de un buscador de información tradicional con la capacidad de encontrar respuestas precisas a las preguntas del usuario. El objetivo principal es facilitar el acceso a la información y disminuir el tiempo y el esfuerzo que el usuario debe emplear para encontrar una información concreta en una lista de documentos relevantes. En esta investigación se han abordado dos trabajos relacionados con los SBR. La primera parte presenta una arquitectura para SBR en castellano basada en la combinación y adaptación de diferentes técnicas de Recuperación y de Extracción de Información. Esta arquitectura está integrada por tres módulos principales que incluyen el análisis de la pregunta, la recuperación de pasajes relevantes y la extracción y selección de respuestas. En ella se ha prestado especial atención al tratamiento de las Entidades Nombradas puesto que, con frecuencia, son el tema de las preguntas o son buenas candidatas como respuestas. La propuesta se ha encarnado en el SBR del grupo MIRACLE que ha sido evaluado de forma independiente durante varias ediciones en la tarea compartida CLEF@QA, parte del foro de evaluación competitiva Cross-Language Evaluation Forum (CLEF). Se describen aquí las participaciones y los resultados obtenidos entre 2004 y 2007. El SBR de MIRACLE ha obtenido resultados moderados en el desempeño de la tarea con tasas de respuestas correctas entre el 20% y el 30%. Entre los resultados obtenidos destacan los de la tarea principal de 2005 y la tarea piloto de Búsqueda de Respuestas en tiempo real de 2006, RealTimeQA. Esta última tarea, además de requerir respuestas correctas incluía el tiempo de respuesta como un factor adicional en la evaluación. Estos resultados respaldan la validez de la arquitectura propuesta como una alternativa viable para los SBR sobre colecciones textuales y también corrobora resultados similares para el inglés y otras lenguas. Por otro lado, el análisis de los resultados a lo largo de las diferentes ediciones de CLEF así como la comparación con otros SBR apunta nuevos problemas y retos. Según nuestra experiencia, los sistemas de QA son más complicados de adaptar a otros dominios y lenguas que los sistemas de Recuperación de Información. Este problema viene heredado del uso de herramientas complejas de análisis de lenguaje como analizadores morfológicos, sintácticos y semánticos. Entre estos últimos se cuentan las herramientas para el Reconocimiento y Clasificación de Entidades Nombradas (NERC en inglés) así como para la Detección y Clasificación de Relaciones (RDC en inglés). Debido a la di cultad de adaptación del SBR a distintos dominios y colecciones, en la segunda parte de esta tesis se investiga una propuesta diferente basada en la adquisición de conocimiento mediante métodos de aprendizaje ligeramente supervisado. El objetivo de esta investigación es adquirir recursos semánticos útiles para las tareas de NERC y RDC usando colecciones de textos no anotados. Además, se trata de eliminar la dependencia de herramientas de análisis lingüístico con el fin de facilitar que las técnicas sean portables a diferentes dominios e idiomas. En primer lugar, se ha realizado un estudio de diferentes algoritmos para NERC y RDC de forma semisupervisada a partir de unos pocos ejemplos (bootstrapping). Este trabajo propone primero una arquitectura común y compara diferentes funciones que se han usado en la evaluación y selección de resultados intermedios, tanto instancias como patrones. La principal propuesta es un nuevo algoritmo que permite la adquisición simultánea e iterativa de instancias y patrones asociados a una relación. Incluye también la posibilidad de adquirir varias relaciones de forma simultánea y mediante el uso de la hipótesis de exclusividad obtener mejores resultados. Como característica distintiva el algoritmo explora la colección de textos con una estrategia basada en indización, que permite adquirir conocimiento de grandes colecciones. La estrategia de selección de candidatos y la evaluación se basan en la construcción de un grafo de instancias y patrones, que justifica nuestro método para la selección de candidatos. Este procedimiento es semejante al frente de exploración de una araña web y permite encontrar las instancias más parecidas a las semillas con las evidencias disponibles. Este algoritmo se ha implementado en el sistema SPINDEL y para su evaluación se ha comenzado con el caso concreto de la adquisición de recursos para las clases de Entidades Nombradas más comunes, Persona, Lugar y Organización. El objetivo es adquirir nombres asociados a cada una de las categorías así como patrones contextuales que permitan detectar menciones asociadas a una clase. Se presentan resultados para la adquisición de dos idiomas distintos, castellano e inglés, y para el castellano, en dos dominios diferentes, noticias y textos de una enciclopedia colaborativa, Wikipedia. En ambos casos el uso de herramientas de análisis lingüístico se ha limitado de acuerdo con el objetivo de avanzar hacia la independencia de idioma. Las listas adquiridas mediante bootstrapping parten de menos de 40 semillas por clase y obtienen del orden de 30.000 instancias de calidad variable. Además se obtienen listas de patrones indicativos asociados a cada clase de entidad. La evaluación indirecta confirma la utilidad de ambos recursos en la clasificación de Entidades Nombradas usando un enfoque simple basado únicamente en diccionarios. La mejor configuración obtiene para la clasificación en castellano una medida F de 67,17 y para inglés de 55,99. Además se confirma la utilidad de los patrones adquiridos que en ambos casos ayudan a mejorar la cobertura. El módulo requiere menor esfuerzo de desarrollo que los enfoques supervisados, si incluimos la necesidad de anotación, aunque su rendimiento es inferior por el momento. En definitiva, esta investigación constituye un primer paso hacia el desarrollo de aplicaciones semánticas como los SBR que requieran menos esfuerzo de adaptación a un dominio o lenguaje nuevo.-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Question Answering (QA) systems add new capabilities to traditional search engines with the ability to find precise answers to user questions. Their objective is to enable easier information access by reducing the time and effort that the user requires to find a concrete information among a list of relevant documents. In this thesis we have carried out two works related with QA systems. The first part introduces an architecture for QA systems for Spanish which is based on the combination and adaptation of different techniques from Information Retrieval (IR) and Information Extraction (IE). This architecture is composed by three modules that include question analysis, relevant passage retrieval and answer extraction and selection. The appropriate processing of Named Entities (NE) has received special attention because of their importance as question themes and candidate answers. The proposed architecture has been implemented as part of the MIRACLE QA system. This system has taken part in independent evaluations like the CLEF@QA track in the Cross-Language Evaluation Forum (CLEF). Results from 2004 to 2007 campaigns as well as the details and the evolution of the system have been described in deep. The MIRACLE QA system has obtained moderate performance with a first answer accuracy ranging between 20% and 30%. Nevertheless, it is important to highlight the results obtained in the 2005 main QA task and the RealTimeQA pilot task in 2006. The last one included response time as an important additional variable of the evaluation. These results back the proposed architecture as an option for QA from textual collection and confirm similar findings obtained for English and other languages. On the other hand, the analysis of the results along evaluation campaigns and the comparison with other QA systems point problems with current systems and new challenges. According to our experience, it is more dificult to tailor QA systems to different domains and languages than IR systems. The problem is inherited by the use of complex language analysis tools like POS taggers, parsers and other semantic analyzers, like NE Recognition and Classification (NERC) and Relation Detection and Characterization (RDC) tools. The second part of this thesis tackles this problem and proposes a different approach to adapting QA systems for di erent languages and collections. The proposal focuses on acquiring knowledge for the semantic analyzers based on lightly supervised approaches. The goal is to obtain useful resources that help to perform NERC or RDC using as few annotated resources as possible. Besides, we try to avoid dependencies from other language analysis tools with the purpose that these methods apply to different languages and domains. First of all, we have study previous work on building NERC and RDC modules with few supervision, particularly bootstrapping methods. We propose a common framework for different bootstrapping systems that help to unify different evaluation functions for intermediate results. The main proposal is a new algorithm that is able to simultaneously acquire instances and patterns associated to a relation of interest. It also uses mutual exclusion among relations to reduce concept drift and achieve better results. A distinctive characteristic is that it uses a query based exploration strategy of the text collection which enables their use for larger collections. Candidate selection and evaluation are based on incrementally building a graph of instances and patterns which also justifies our evaluation function. The discovery approach is analogous to the front of exploration in a web crawler and it is able to find the most similar instances to the available seeds. This algorithm has been implemented in the SPINDEL system. We have selected for evaluation the task of acquiring resources for the most common NE classes, Person, Location and Organization. The objective is to acquire name instances that belong to any of the classes as well as contextual patterns that help to detect mentions of NE that belong to that class. We present results for the acquisition of resources from raw text from two different languages, Spanish and English. We also performed experiments for Spanish in two different collections, news and texts from a collaborative encyclopedia, Wikipedia. Both cases are tackled with limited language analysis tools and resources. With an initial list of 40 instance seeds, the bootstrapping process is able to acquire large name lists containing up to 30.000 instances with a variable quality. Besides, large lists of indicative patterns are obtained too. Our indirect evaluation confirms the utility of both resources to classify NE using a simple dictionary recognition approach. Best results for Spanish obtained a F-score of 67,17 and for English this value is 55,99. The module requires much less development effort than annotation for supervised algorithms although the performance is not in pair yet. This research is a first step towards the development of semantic applications like QA for a new language or domain with no annotated corpora that requires less adaptation effort

Geographic information extraction from texts

A large volume of unstructured texts, containing valuable geographic information, is available online. This information – provided implicitly or explicitly – is useful not only for scientific studies (e.g., spatial humanities) but also for many practical applications (e.g., geographic information retrieval). Although large progress has been achieved in geographic information extraction from texts, there are still unsolved challenges and issues, ranging from methods, systems, and data, to applications and privacy. Therefore, this workshop will provide a timely opportunity to discuss the recent advances, new ideas, and concepts but also identify research gaps in geographic information extraction

Leveraging Semantic Annotations for Event-focused Search & Summarization

Today in this Big Data era, overwhelming amounts of textual information across different sources with a high degree of redundancy has made it hard for a consumer to retrospect on past events. A plausible solution is to link semantically similar information contained across the different sources to enforce a structure thereby providing multiple access paths to relevant information. Keeping this larger goal in view, this work uses Wikipedia and online news articles as two prominent yet disparate information sources to address the following three problems: • We address a linking problem to connect Wikipedia excerpts to news articles by casting it into an IR task. Our novel approach integrates time, geolocations, and entities with text to identify relevant documents that can be linked to a given excerpt. • We address an unsupervised extractive multi-document summarization task to generate a fixed-length event digest that facilitates efficient consumption of information contained within a large set of documents. Our novel approach proposes an ILP for global inference across text, time, geolocations, and entities associated with the event. • To estimate temporal focus of short event descriptions, we present a semi-supervised approach that leverages redundancy within a longitudinal news collection to estimate accurate probabilistic time models. Extensive experimental evaluations demonstrate the effectiveness and viability of our proposed approaches towards achieving the larger goal.Im heutigen Big Data Zeitalters existieren überwältigende Mengen an Textinformationen, die über mehrere Quellen verteilt sind und ein hohes Maß an Redundanz haben. Durch diese Gegebenheiten ist eine Retroperspektive auf vergangene Ereignisse für Konsumenten nur schwer möglich. Eine plausible Lösung ist die Verknüpfung semantisch ähnlicher, aber über mehrere Quellen verteilter Informationen, um dadurch eine Struktur zu erzwingen, die mehrere Zugriffspfade auf relevante Informationen, bietet. Vor diesem Hintergrund benutzt diese Dissertation Wikipedia und Onlinenachrichten als zwei prominente, aber dennoch grundverschiedene Informationsquellen, um die folgenden drei Probleme anzusprechen: • Wir adressieren ein Verknüpfungsproblem, um Wikipedia-Auszüge mit Nachrichtenartikeln zu verbinden und das Problem in eine Information-Retrieval-Aufgabe umzuwandeln. Unser neuartiger Ansatz integriert Zeit- und Geobezüge sowie Entitäten mit Text, um relevante Dokumente, die mit einem gegebenen Auszug verknüpft werden können, zu identifizieren. • Wir befassen uns mit einer unüberwachten Extraktionsmethode zur automatischen Zusammenfassung von Texten aus mehreren Dokumenten um Ereigniszusammenfassungen mit fester Länge zu generieren, was eine effiziente Aufnahme von Informationen aus großen Dokumentenmassen ermöglicht. Unser neuartiger Ansatz schlägt eine ganzzahlige lineare Optimierungslösung vor, die globale Inferenzen über Text, Zeit, Geolokationen und mit Ereignis-verbundenen Entitäten zieht. • Um den zeitlichen Fokus kurzer Ereignisbeschreibungen abzuschätzen, stellen wir einen semi-überwachten Ansatz vor, der die Redundanz innerhalb einer langzeitigen Dokumentensammlung ausnutzt, um genaue probabilistische Zeitmodelle abzuschätzen. Umfangreiche experimentelle Auswertungen zeigen die Wirksamkeit und Tragfähigkeit unserer vorgeschlagenen Ansätze zur Erreichung des größeren Ziels

Finding answers to definition questions on the web

Fundamentally, question answering systems are designed for automatically responding to queries posed by users in natural language. The first step in the answering process is query analysis, and its goal is to classify the query in concert with a set of pre-specified types. Traditionally, these classes include: factoid, definition, and list. Systems thereafter chose the answering method in congruence with the class recognised in this early phase. In short, this thesis focuses exclusively on strategies to tackle definition questions (e.g.\u27; Who is Ben Bernanke?"). This sort of question has become especially interesting in recent years, due to its significant number of submissions to search engines. Most advances in definition question answering have been made under the umbrella of the Text REtrieval Conference (TREC). This is, more precisely, a framework for testing systems operating on a collection of news articles. Thus, the objective of chapter one is to describe this framework along with presenting additional introductory aspects of definition question answering including: (a) how definition questions are prompted by individuals; (b) the different conceptions of definition, and thus of answers; and (c) the various metrics exploited for assessing systems. Since the inception of TREC, systems have put to the test manifold approaches to discover answers, throwing some light onto several key aspects of this problem. On this account, chapter four goes over a selection of some notable TREC systems. This selection is not aimed at completeness, but rather at highlighting the leading features of these systems. For the most part, systems benefit from knowledge bases (e.g., Wikipedia) for obtaining descriptions about the concept being defined (a.k.a. definiendum). These descriptions are thereafter projected onto the array of candidate answers as a means of discerning the correct answer. In other words, these knowledge bases play the role of annotated resources, and most systems attempt to find the answer candidates across the collection of news articles that are more similar to these descriptions. The cornerstone of this thesis is the assumption that it is plausible to devise competitive, and hopefully better, systems without the necessity of annotated resources. Although this descriptive knowledge is helpful, it is the belief of the author that they are built on two wrong premises: 1.It is arguable that senses or contexts related to the definiendum across knowledge bases are the same senses or contexts for the instances across the array of answer candidates. This observation also extends to the fact that not all descriptions within the group of putative answers are necessarily covered by knowledge bases, even though they might refer to the same contexts or senses. 2.Finding an efficient projection strategy does not necessarily entail a good procedure for discerning descriptive knowledge, because it shifts the goal of the task to a more like this set" instead of analysing whether or not each candidate bears the characteristics of a description. In other words, the coverage given by knowledge bases for a specific definiendum is not wide enough to learn all the characteristics that typify its descriptions, so that systems are capable of identifying all answers within the set of candidates. From another angle, a conventional projection methodology can be seen as a finder of lexical analogies. All in all, this thesis investigates into models that disregard this kind of annotated resource and projection strategy. In effect, it is the belief of the author that a robust technique of this sort can be integrated with traditional projection methodologies, and in this way bringing about an enhancement in performance. The major contributions of this thesis are presented in chapters five, six and seven. There are several ways of understanding this structure. For example, chapter five presents a general framework for answering definition questions in several languages. The primary goal of this study is to design a lightweight definition question answering system operating on web-snippets and two languages: English and Spanish. The idea is to utilise web-snippets as a source of descriptive information in several languages, and the high degree of language independency is achieved by making allowances for as little linguistic knowledge as possible. To put it more precisely, this system accounts for statistical methods and a list of stop-words, as well as a set of language-dependent definition patterns. In detail, chapter five branches into two more specific studies. The first study is essentially aimed at capitalising on redundancy for detecting answers (e.g., word frequency counts across answer candidates). Although this type of feature has been widely used by TREC systems, this study focuses on its impact on different languages, and its benefits when applied to web-snippets instead of a collection of news documents. An additional motivation behind targeting web-snippets is the hope of studying systems working on more heterogenous corpora, without incurring the need of downloading full-documents. For instance, on the Internet, the number of distinct senses for the definiendum considerably increases, ergo making it necessary to consider a sense discrimination technique. For this purpose, the system presented in this chapter takes advantage of an unsupervised approach premised on Latent Semantic Analysis. Although the outcome of this study shows that sense discrimination is hard to achieve when operating solely on web snippets, it also reveals that they are a fruitful source of descriptive knowledge, and that their extraction poses exciting challenges. The second branch extends this first study by exploiting multilingual knowledge bases (i.e. Wikipedia) for ranking putative answers. Generally speaking, it makes use of word association norms deduced from sentences that match definitions patterns across Wikipedia. In order to adhere to the premise of not profiting from articles related to a specific definiendum, these sentences are anonymised by replacing the concept with a placeholder, and the word norms are learnt from all training sentences, instead of only from the Wikipedia page about the particular definiendum. The results of this study signify that this use of these resources can also be beneficial; in particular, they reveal that word association norms are a cost-efficient solution. However, the size of the corpus markedly decreases for languages different from English, thus indicating their insufficiency to design models for other languages. Later, chapter six gets more specific and deals only with the ranking of answer candidates in English. The reason for abandoning the idea of Spanish is the sparseness observed across both the redundancy from the Internet and the training material mined from Wikipedia. This sparseness is considerably greater than in the case of English, and it makes learning powerful statistical models more difficult. This chapter presents a novel way of modeling definitions grounded on n-gram language models inferred from the lexicalised dependency tree representation of the training material acquired in the study of chapter five. These models are contextual in the sense that they are built in relation to the semantic of the sentence. Generally, these semantics can be perceived as the distinct types of definienda (e.g., footballer, language, artist, disease, and tree). This study, in addition, investigates the effect of some features on these context models (i.e., named entities, and part-of-speech tags). Overall, the results obtained by this approach are encouraging, in particular in terms of increasing the accuracy of the pattern matching. However, in all likelihood, it was experimentally observed that a training corpus comprising only positive examples (descriptions) is not enough to achieve perfect accuracy, because these models cannot deduce the characteristics that typify non-descriptive content. More essential, as future work, context models give the chance to study how different contexts can be amalgamated (smoothed) in agreement with their semantic similarities in order to ameliorate the performance. Subsequently, chapter seven gets even more specific and it searches for the set of properties that can aid in discriminating descriptions from other kinds of texts. Note that this study regards all kinds of descriptions, including those mismatching definition patters. In so doing, Maximum Entropy models are constructed on top of an automatically acquired large-scale training corpus, which encompasses descriptions from Wikipedia and non-descriptions from the Internet. Roughly speaking, different models are constructed as a means of studying the impact of assorted properties: surface, named entities, part-of-speech tags, chunks, and more interestingly, attributes derived from the lexicalised dependency graphs. In general, results corroborate the efficiency of features taken from dependency graphs, especially the root node and n-gram paths. Experiments conducted on testing sets of various characteristics suggest that it is also plausible to find attributes that can port to other corpora. The second and the third are extra chapters. The former examines different strategies to trawl the Web for descriptive knowledge. In essence, this chapter touches on several strategies geared towards boosting the recall of descriptive sentences across web snippets, especially sentences that match widespread definition patterns. This is a side, but instrumental study to the core of this thesis, as it is necessary for systems targeted at the Internet to develop effective crawling techniques. On the contrary, chapter three has two goals: (a) presenting some components used by the strategies outlined in the last three chapters, this way helping to focus on key aspects of the ranking methodologies, and hence to clearly present the relevant aspects of approaches laid out in these three chapters; and (b) fleshing out some characteristics that make separating the genuine from the misleading answer candidates difficult; particularly, across sentences matching definition patterns. Chapter three is helpful for understanding part of the linguistic phenomena that the posterior chapters deal with. On a final note about the organisation of this thesis, since there is a myriad of techniques, chapter six and seven start dissecting the related work closer to each strategy. The main contribution of each chapter begins at section 6.5 and 7.6, respectively. These two sections start with a discussion and comparison between the proposed methods and the related work presented in their corresponding preceding sections. This organisation is directed at facilitating the contextualisation of the proposed approaches as there are different question answering systems with manifold characteristics.Frage-Antwort-Systeme sind im Wesentlichen dafür konzipiert, von Benutzern in natürlicher Sprache gestellte Anfragen automatisiert zu beantworten. Der erste Schritt im Beantwortungsprozess ist die Analyse der Anfrage, deren Ziel es ist, die Anfrage entsprechend einer Menge von vordefinierten Typen zu klassifizieren. Traditionell umfassen diese: Faktoid, Definition und Liste. Danach wählten die Systeme dieser frühen Phase die Antwortmethode entsprechend der zuvor erkannten Klasse. Kurz gesagt konzentriert sich diese Arbeit ausschließlich auf Strategien zur Lösung von Fragen nach Definitionen (z.B. ,,emph{Wer ist Ben Bernanke?}"). Diese Art von Anfrage ist in den letzten Jahren besonders interessant geworden, weil sie in beachtlicher Zahl bei Suchmaschinen eingeht. Die meisten Fortschritte in Bezug auf die Beantwortung von Fragen nach Definitionen wurden unter dem Dach der Text Retrieval Conference (TREC) gemacht. Das ist, genauer gesagt, ein Framework zum Testen von Systemen, die mit einer Auswahl von Zeitungsartikeln arbeiten. Daher, zielt Kapitel eins auf eine Beschreibung dieses Rahmenwerks ab, zusammen mit einer Darstellung weiterer einführender Aspekte der Beantwortung von Definitionsanfragen. Diesen schließen u.a. ein: (a) wie Definitionsanfragen von Personen gestellt werden; (b) die unterschiedlichen Begriffe von Definition und folglich auch Antworten; und (c) die unterschiedlichen Metriken, die zur Bewertung von Systemen genutzt werden. Seit Anbeginn von TREC haben Systeme vielfältige Ansätze, Antworten zu entdecken, auf die Probe gestellt und dabei eine Reihe von zentralen Aspekten dieses Problems beleuchtet. Aus diesem Grund behandelt Kapitel vier eine Auswahl einiger bekannter TREC Systeme. Diese Auswahl zielt nicht auf Vollständigkeit ab, sondern darauf, die wesentlichen Merkmale dieser Systeme hervorzuheben. Zum größten Teil nutzen die Systeme Wissensbasen (wie z.B. Wikipedia), um Beschreibungen des zu definierenden Konzeptes (auch als Definiendum bezeichnet) zu erhalten. Diese Beschreibungen werden danach auf eine Reihe von möglichen Antworten projiziert, um auf diese Art die richtige Antwort zu ermitteln. Anders ausgedrückt nehmen diese Wissensbasen die Funktion von annotierten Ressourcen ein, wobei die meisten Systeme versuchen, die Antwortkandidaten in einer Sammlung von Zeitungsartikeln zu finden, die diesen Beschreibungen ähnlicher sind. Den Grundpfeiler dieser Arbeit bildet die Annahme, dass es plausibel ist, ohne annotierte Ressourcen konkurrenzfähige, und hoffentlich bessere, Systeme zu entwickeln. Obwohl dieses deskriptive Wissen hilfreich ist, basieren sie nach Überzeugung des Autors auf zwei falschen Annahmen: 1. Es ist zweifelhaft, ob die Bedeutungen oder Kontexte, auf die sich das Definiendum bezieht, dieselben sind wie die der Instanzen in der Reihe der Antwortkandidaten. Darüber hinaus erstreckt sich diese Beobachtung auch auf die Tatsache, dass nicht alle Beschreibungen innerhalb der Gruppe der mutmaßlichen Antworten notwendigerweise von Wissensbasen abgedeckt werden, auch wenn sie sich auf dieselben Bedeutungen und Kontexte beziehen. 2. Eine effiziente Projektionsstrategie zu finden bedeutet nicht notwendigerweise auch ein gutes Verfahren zur Feststellung von deskriptivem Wissen, denn es verschiebt die Zielsetzung der Aufgabe hin zu einem ,,mehr wie diese Menge" statt zu analysieren, ob jeder Kandidat den Charakteristika einer Beschreibung entspricht oder nicht. Anders ausgedrückt ist die Abdeckung, die durch Wissensbasen für ein spezifisches Definiendum gegeben ist, nicht umfassend genug, um alle Charakteristika, die für seine Beschreibungen kennzeichnend sind, zu erlernen, so dass die Systeme in der Lage sind, alle Antworten innerhalb der Kandidatenmenge zu identifizieren. Eine konventionelle Projektionsstrategie kann aus einem anderen Blickwinkel als Prozedur zum Finden lexikalischer Analogien betrachtet werden. Insgesamt untersucht diese Arbeit Modelle, die Strategien dieser Art in Verbindung mit annotierten Ressourcen und Projektion außer Acht lassen. Tatsächlich ist es die Überzeugung des Autors, dass eine robuste Technik dieser Art mit traditionellen Methoden der Projektion integriert wird und so eine Leistungssteigerung ermöglichen kann. Die größeren Beiträge dieser Arbeit werden in den Kapiteln fünf, sechs und sieben präsentiert. Es gibt mehrere Wege diese Struktur zu verstehen. Kapitel fünf, beispielsweise, präsentiert einen allgemeinen Rahmen für die Beantwortung von Fragen nach Definitionen in mehreren Sprachen. Das primäre Ziel dieser Studie ist es, ein leichtgewichtiges System zur Beantwortung von Fragen nach Definitionen zu entwickeln, das mit Web-Snippets und zwei Sprachen arbeitet: Englisch und Spanisch. Die Grundidee ist, von Web-Snippets als Quelle deskriptiver Information in mehreren Sprachen zu profitieren, wobei der hohe Grad an Sprachunabhängigkeit dadurch erreicht wird, dass so wenig linguistisches Wissen wie möglich berücksichtigt wird. Genauer gesagt berücksichtigt dieses System statistische Methoden und eine Liste von Stop-Wörtern sowie eine Reihe von sprach-spezifischen Definitionsmustern. Im Einzelnen teilt sich Kapitel fünf in zwei spezifischere Studien auf. Die erste Studie zielt im Grunde darauf ab, aus Redundanz für die Ermittlung von Antworten Kapital zu schlagen (z.B. Worthäufigkeiten über verschiedene Antwortkandidaten hinweg). Obwohl eine solche Eigenschaft unter TREC Systemen weit verbreitet ist, legt diese Studie den Schwerpunkt auf die Auswirkungen auf verschiedene Sprachen und auf ihre Vorteile bei der Anwendung auf Web-Snippets statt Zeitungsartikeln. Eine weitere Motivation dahinter, Web-Snippets ins Auge zu fassen, ist die Hoffnung, Systeme zu studieren, die mit heterogenen Corpora arbeiten, ohne es nötig zu machen, vollständige Dokumente herunter zu laden. Im Internet, beispielsweise, steigt die Zahl verschiedener Bedeutungen für das Definiendum deutlich an, was es notwendig macht, eine Technik zur Unterscheidung von Bedeutungen in Betracht zu ziehen. Zu diesem Zweck nutzt das System, das in diesem Kapitel vorgestellt wird, einen unüberwachten Ansatz, der auf der Latent Semantic Analysis basiert. Auch wenn das Ergebnis dieser Studie zeigt, dass die Unterscheidung von Bedeutungen allein anhand von Web-Snippets schwer zu erreichen ist, so lässt es doch auch erkennen, dass sie eine fruchtbare Quelle deskriptiven Wissens darstellen und dass ihre Extraktion spannende Herausforderungen bereithält. Der zweite Teil erweitert diese erste Studie durch die Nutzung mehrsprachiger Wissensbasen (d.h. Wikipedia), um die möglichen Antworten in eine Rangfolge einzureihen. Allgemein ausgedrückt profitiert sie von Wortassoziationsnormen, die von Sätzen gelernt werden, die über Wikipedia hinweg zu Definitionsmustern passen. Um an der Prämisse festzuhalten, keine Artikel mit Bezug auf eine spezifisches Definiendum zu nutzen, werden diese Sätze anonymisiert, indem der Begriff mit einem Platzhalter ersetzt wird, und die Wortnormen werden von allen Sätzen der Trainingsmenge gelernt, statt nur von dem Wikipedia-Artikel, der sich auf das spezielle Definiendum bezieht. Die Ergebnisse dieser Studie zeigen, dass diese Nutzung dieser Ressourcen ebenfalls vorteilhaft sein kann; speziell zeigen sie auf, dass Wortassoziationsnormen eine kosteneffiziente Lösung darstellen. Allerdings nehmen die Corpusgrößen über andere Sprachen als Englisch deutlich ab, was auf deren Unzulänglichkeit für die Konstruktion von Modellen für andere Sprachen hinweist. Kapitel sechs, weiter hinten, wird spezieller und handelt ausschließlich von der Einordnung von Antwortkandidaten in englischer Sprache in eine Rangfolge. Der Grund dafür, hier Spanisch außer Acht zu lassen, ist die geringe beobachtete Dichte, sowohl in Bezug auf redundante Information im Internet als auch in Bezug auf Trainingsmaterial, das von Wikipedia erworben wurde. Diese geringe Dichte ist deutlich stärker ausgeprägt als im Fall der englischen Sprache und erschwert das Erlernen mächtiger statischer Modelle. Dieses Kapitel präsentiert einen neuartigen Weg, Definitionen zu modellieren, die in n-gram Sprachmodellen verankert sind, die aus der lexikalisierten Darstellung des Abhängigkeitsbaumes des in Kapitel fünf erworbenen Trainingsmaterials gelernt wurden. Diese Modelle sind kontextuell in dem Sinne, dass sie in Bezug auf die Semantikdes Satzes konstruiert werden. Im Allgemeinen können diese Semantiken als unterschiedliche Typen von Definienda betrachtet werden (z.B. Fußballer, Sprache, Künstler, Krankheit und Baum). Diese Studie untersucht zusätzlich die Auswirkungen einiger Eigenschaften (nämlich benannter Entitäten und Part-of-speech-Tags) auf diese Kontextmodelle. Insgesamt sind die Ergebnisse, die mit diesem Ansatz erhalten wurden, ermutigend, insbesondere in Bezug auf eine Steigerung der Genauigkeit des Musterabgleichs. Indes wurde höchstwahrscheinlich experimentell beobachtet, dass ein Trainingscorpus, das nur Positivbeispiele (Beschreibungen) enthält, nicht ausreicht, um perfekte Genauigkeit zu erreichen, da diese Modelle die Charakteristika nicht ableiten können, die für nicht-deskriptiven Inhalt kennzeichnend sind. Für die weitere Arbeit ermöglichen es Kontextmodelle zu untersuchen, wie unterschiedliche Kontexte in Übereinstimmung mit deren semantischen Ähnlichkeiten verschmolzen (geglättet) werden können, um die Leistung zu verstärken. Kapitel sieben wird anschließend sogar noch spezieller und sucht nach der Menge von Eigenschaften, die dabei helfen kann, Beschreibungen von anderen Textarten zu unterscheiden. Dabei sollte beachtet werden, dass diese Studie alle Arten von Beschreibungen berücksichtigt, einschließlich derer, die Definitionsmustern nicht genügen. Dadurch werden Maximum-Entropy-Modelle konstruiert, die auf einen automatisch akquirierten Corpus von großem Umfang aufsetzen, der Beschreibungen von Wikipedia und Nicht-Beschreibungen aus dem Internet umfasst. Grob gesagt werden unterschiedliche Modelle konstruiert, um die Auswirkungen verschiedenerlei Merkmale zu untersuchen: Oberfläche, benannte Entitäten, Part-of-speech-Tags, Chunks und, noch interessanter, von den lexikalisierten Abhängigkeitsgraphen abgeleitete Attribute. Im Allgemeinen bestätigen die Ergebnisse die Effizienz von Merkmalen, die Abhängigkeitsgraphen entnommen sind, insbesondere Wurzelknoten und n-gram-Pfaden. Experimente, die mit verschiedenen Testmengen diverser Charakteristika durchgeführt wurden, legen nahe, dass auch angenommen werden kann, dass Attribute gefunden werden, die sich auf andere Corpora übertragen lassen. Es gibt zwei weitere Kapitel: zwei und drei. Ersteres untersucht unterschiedliche Strategien, das Netz nach deskriptivem Wissen zu durchforsten. Im Wesentlichen analysiert dieses Kapitel einige Strategien, die darauf abzielen, die Trefferquote (den Recall) deskriptiver Sätze

New Studies and Research in Social Sciences

This study focuses on the “The Bureaucratic Personality” view through the three prominent woman authors’, who lived in a republican period of Turkey, bureaucratic types are indicated in their literary works. The focused questions are following: 1) How bureaucrats characteristics can be explained in Bureaucratic Personality view? 2) How can be clarified bureaucratic types within the three woman authors’, who lived in republican period, literary works? I have selected the following literary works in considering the research question: Şukufe Nihal "Yalnız Dönüyorum" Halide Edip Adıvar "Zeyno'nun Oğlu" and Halide Nusret "Gül'ün Babası Kim". In questioned literary works are noted as the data set. Bureaucrats’ characteristic and their manner for cases are noticed as indicators, in methodology, this paper is a theoric, exploration study. The study designed into three sections. In the first part Merton, Hummel, and Argrys studies are referenced as Bureaucratic Personality” theories, likewise, bureaucrats’ characteristics are explained. In the next section, bureaucratic types are noted within the Şukufe Nihal "Yalnız Dönüyorum", Halide Edip Adıvar "Zeyno'nun Oğlu", and Halide Nusret Zorlutuna "Gül'ün Babası Kim" literary works. In a similar vein, bureaucrats characteristic and their manner for cases are remarked. In the last part, bureaucratic types are analyzed through “The Bureaucratic Personality” view

The Language Zone: Joseph Brodsky and the Making of a Bilingual Poet

My dissertation unites several aspects of Joseph Brodsky’s writing under the arc of his development as a bilingual and transnational writer. I make the case that Brodsky’s poetic sensibility was originally transnational, i.e. exhibited an affinity with both foreign and domestic poetic traditions in pursuit of its own original poetics. I establish the trope of a speaker alone in a room as a leading poetic concept of Brodsky’s neo-Metaphysical style. The poems that are centered on this trope do not refer explicitly to the poetry of the British Baroque through intertextual references or imitation, which attests to the ability of Brodsky’s transnationally oriented poetry to process foreign traditions with subtlety and to incorporate key elements of it fully within his own idiom. I follow the new generation of researchers (Ishov, Berlina) in their attempt to “put Brodsky on the map of American studies” by paying close attention to Brodsky’s self-translation strategies and the reasons behind the negative reception of Brodsky’s English-language poetry during the time of its publication. Drawing on Jan Hokenson and Marcella Munson’s concept of the bilingual text, I discover in the “English Brodsky” the tendencies characteristic of most Modernist bilingual writing. My comparative analysis of the archival materials pertaining to the translation of the poem “Dekabrʹ vo Florentsii” (“December in Florence”) shows that Brodsky’s solutions as a self-translator aim at preserving the conceptual and stylistic unity of his bilingual oeuvre. I further read Brodsky’s English prose as an attempt to rehabilitate and explain his poetic credos: the insistence on formal versification, the importance of the continuity of the poetic tradition, and estrangement as the main function of the poetic utterance. I show that Brodsky’s English writing on Osip Mandelstam and Marina Tsvetaeva is self-revealing as it discloses the poet’s own motivations for writing prose. Analyzing Brodsky’s autobiographical essays “Less than One” and “In a Room and a Half,” I return to the trope of a room and read his prose as a form of translation commentary that provides his new audience with a rich cultural context that is essential for a full understanding of his bilingual project.2021-04-2

Exploring Written Artefacts

This collection, presented to Michael Friedrich in honour of his academic career at of the Centre for the Study of Manuscript Cultures, traces key concepts that scholars associated with the Centre have developed and refined for the systematic study of manuscript cultures. At the same time, the contributions showcase the possibilities of expanding the traditional subject of ‘manuscripts’ to the larger perspective of ‘written artefacts’

Towards a philosophy of theatre inspired by Aristotle’s poetics and post-structuralist aesthetics in relation to three South African plays

I have attempted a reading of Aristotle in terms of mimesis, ethos, mythos, lexis, hamartia, anagnorisis, peripeteia, catharsis and anamnesis - as an existential “being there” (Dasein) of the characters’ freedom and actual historicity - in three of my plays in which I performed or witnessed in productions in England, Wales, three Scandinavian countries, the U.S. and South Africa. I have analysed other Southern African “womanist” performative drama and feminist theatre. I assume with the ancient Greeks that in serious theatre there is theoria, an educated, discursive looking, which involves a dialectics of logos in dianoia intertwined in the mythos – ethical truth in the discourse of the plot. Whilst aesthetics cannot be reduced to psychobiography, creative writing is motivated in part by the author’s and the dramatic subjects’ psychoanalytically understood personal and political unconscious placed in the ethos – the character on the stage. The aesthetics of tragedy relate to both peripeteia (reversals) and anagnorisis (recognition of responsibility) which occur within an arc of development, crisis and denouement of the vicissitudes of purported wisdom in understanding how performative drama and critical theatre have been presented in what has become known as The Struggle in a post-apartheid South Africa and post-colonial Zimbabwe by comparison with historical conditions in South America, India, even China. The values of nous, phronesis and sophia, intuitive, practical and interpretative wisdom are connected to the Nicomachean and Eudemian Ethics with which the tragic-comic hero and his Other are imbued or violate. The post-structuralist aesthetic as developed in the literary theory of the twentieth century is essentially the interaction of synchronic and diachronic language emerging from the signifiance and the semiosis of the chora (the feminine or maternal unconscious) within the de-familarisation techniques of Russian and Czech Formalism. This provides a creative and meaningful limit to a consciousness of being-white and beingblack- in-the-world against disempowering Nothingness or perceived Otherness threatening moral beings. Nothingness and the Other are characterised magically and as witch-craft in oral-cultures which deny the unconscious and resort to paranoia and persecution of Otherness in the subject projected onto the other – the “colonial personality”. Shades of Brown has been re-written as Jannie Veldsman – A Film 8 Scenario and I have incorporated into a revised The Cape Orchard a retrospective anticipation of the coming of the new South Africa. I reflect on what tragic drama on the stage and in real life in South Africa means now that the new South Africa is over its honeymoon period and faces serious problems of failed governance. Within the dialectic of an enlightened rabbinical morality of Hillel the Elder (“What is hateful to you do not do to others….” and “If I am not for myself who will be for me…?”) and Kant’s categorical imperative of human beings as a priori ends, I follow the fortunes of an old Jewish veteran of The Struggle, dating back to the Defiance Campaign of 1952/3. Fugard’s work is exemplary in fostering a sense of Sartre’s Nothingness and nihilation which “haunts” Being and is the space of undecidability in relation to my condition of freedom allowing the transcendence of Being. Being asserts reparation and redemption in the face of the depressive and paranoid subject/object split in the subject’s being-in-the-world. Plays ideally submerge this existentialist, psychoanalytic and Aristotelian dramaturgy in the form of Kierkegaard’s faith and Nietzsche’s will which are part of the Encompassing in Karl Jasper’s metaphysics - the residue of a Judaeo-Christian ethics facing the anomie and aporia of the postmodern. The new South Africa was only ostensibly built on Greek and Judaeo- Christian secular ethics – “truth and reconciliation”. It inherited state, revolutionary and criminal violence, as well as a sophisticated economic infrastructure, masspoverty and a segregated educational, social and welfare system which in the milieu of ANC incompetence and corruption have for the very poor got worse but to the benefit of a new African oligarchy, the beneficiaries of a dysfunctional affirmative action policy. What is to be done? Irigaray’s striking metaphor “the speculum of the Other woman” suggests that we are reflected by the instrument we use for investigating what may be Other to us: “we” are westerners trying to live in Africa. “We” are Other – not as autochthonous as the African majority. But the autochthonous can also behave as Other and may even fail to recognise the Other in themselves. Franz Fanon’s “colonial personality”, like ex-president Thabo Mbeki, misunderstands the colonial Other in himself which, disastrously, he projects and attacks in the imaginary and persecutory Other, only to suffer the return of the Real, as do the dramatic fictions Van Tonder in Shades of Brown, Dianne Cupido in The Cape Orchard and Harry Grossman the old man’s son in The Zulu and the Zeide (inspired by a short story by Dan Jacobson). 9 The Russian and Czech Formalists and Structuralists show us how to foreground the Real through techniques of de-familiarisation which can be applied to modernist and post-modernist “womanist” performance drama and feminist theatre. Defamilarisation, especially in an Africa struggling between failed and successful colonialism and often ruled by more or less corrupt elites, sensitizes us to a moral nihilism which characterises the failed African state - described by Conrad as a “heart of darkness” transcended in aletheia – being oneself in the self-showing light of one’s ethos operating through a personal and political unconscious mystified in the rhetoric of oral-cultures. Playwrights such as Yael Farber, Fraser Grace, Aletta Bezuidenhout and Fatima Dike express a semiosis of the unconscious and the signifiance and “absurdity” of logos suggesting that all is not lost in post-apartheid Southern Africa as regards human values, whilst struggling with the political correctness demanded in The Struggle. A partially successful colonialism in parts of Africa could within a British education system, produce a Wole Soyinka who transcends the propaganda of agit-prop by showing the parabolic arc of tragedy afflicted with peripeteia. The weight of African backwardness is not only the negative heritage of colonialism and slavery but Africa’s immersion in traditional partially modernised, but still patriarchal, often tribally and religiously split oral-cultures. These enable the colonial personality to unconsciously or opportunistically exploit his paranoiac sense of his victimage at the expense of the writing-cultures of development which entail anamnesis and the redemption through anagnorisis

Proceedings of the 23rd International Congress of Byzantine Studies : Round Tables

Following the 23rd International Congress of Byzantine Studies, the Organizing Committee decided to produce an online publication of Proceedings from the Round Tables. According to the official title of the congress, Byzantium - a World of Changes, AIEB together with the Organizing Committee, have decided to implement some changes to the concept of the Round Tables. The aim of these changes were to encourage discussion at the Round Tables by presenting preliminary papers at the website in advance. The idea was to introduce the topic and papers of the individual Round Tables that would be discussed, first between the participants, and then with the public present. Therefore, the conveners of the Round Tables were asked to create Round Tables with no more than 10 participants. They collected the papers, which were to be no longer than 18,000 characters in one of the official languages of the Congress and without footnotes or endnotes. Conveners provided a general statement on the goal of each roundtable and on the content of the papers. The present volume contains papers from 49 Round Tables carefully selected to cover a wide range of topics, developed over the last five years since the previous Congress. The topics show diversity within fields and subfields, ranging from history to art history, archeology, philosophy, literature, hagiography, and sigillography. The Round Tables displayed current advances in research, scholarly debates, as well as new methodologies and concerns germane to all aspects of international Byzantine studies. The papers presented in this volume were last sent to the congress organizers in the second week of August 2016 and represent the material that was on hand at that time and had been posted on the official website; no post-congress revisions have occurred. We present this volume in hope that it will be an initial step for further development of Round Tables into collections of articles and thematic books compiled and published following the Congress, in collaboration with other interested institutions and editors. With this volume, the organizers signal their appreciation of the efforts of more than 1600 participants who contributed, both to the Round Tables and to the Congress in general