La qualification est centrale à l'activité du juriste. Les règles de droit positif ne reçoivent application qu'au moment où les faits reçoivent une certaine qualification. Cette réalité prend une dimension particulière face au contrat, lequel est l'objet de multiples dispositions législatives. Le législateur a cru bon au fil du temps, de réglementer diverses formes contractuelles, les contrats nommés. On oppose à ceux-ci les contrats innommés, pure création extra-législative. La détermination de la nature du contrat passe par un processus de qualification indépendant de notions connexes et qui doit s'éloigner d'une méthode intuitive. La qualification du contrat passera principalement par l’analyse des obligations en vue d'identifier l'obligation fondamentale ou la prestation caractéristique du contrat. Il s'agit d'une analyse qu'on veut objective. Les parties auront peu d'influence sur la qualification qui sera ultérieurement donnée à leur contrat, celle-ci étant une question de droit en principe réservée au juge. Le juriste tentera d'abord de lier le contrat aux modèles nommés connus et prévus par le législateur, soit en lui donnant un seul nom ou en reconnaissant la nature mixte de la convention. Dans l'éventualité où ces tentatives ne sont pas concluantes, une qualification innommée devra être choisie. La distinction entre les différentes qualifications possible sera réalisée en fonction de la hiérarchie des obligations au contrat et par l'écart de celle-ci avec les modèles connus. / Qualification is paramount to any jurist. Rules of law can only be applied when particular facts are qualified accordingly. Contract law cannot escape this reality since all agreements are subject to numerous legal provisions, whether or not of public order. The law recognizes many contractual forms, which are deemed «named contracts», as opposed to «unnamed contracts», which are the result of a practical application. The nature of a contract is determined by an independant qualification process which excludes an intuitive method. Qualification will basically be achieved by the analysis of the obligations contained in the contract. This objective analysis will focus on the identification of a «fundamental obligation» or a «caracteristic prestation». Parties will have limited influence on the qualification of their contract, since this determination is a question of law and is left to the judicial authorities. Once the fundamental obligations are identified, the jurist will try to associate a specific contract with known legal contractual types. A contract may be related to a single type of contract or to many of them in the case of a mixed contract. If legal models are inapplicable, an unnamed qualification will be chosen. In order to distinguish between possible qualifications, one must examine the hierarchy of obligations in the contract and its proximity to known models.

According to the Constitution of South Africa, the government is required to make all the infor-mation in the ten indigenous languages of South Africa (excluding English), available to the public. For this reason, the government made the information, that already existed for these ten languages, available to the public and an effort is also been made to increase the amount of resources available in these languages (Groenewald & Du Plooy, 2010). This release of infor-mation further helps to implement Krauwer‟s (2003) idea that there is an inventory for the mini-mal number of language-related resources required for a language to be competitive at the level of research and teaching. This inventory is known as the "Basic Language Resource Kit" (BLARK). Since most of the languages in South Africa are resource scarce, it is of the best in-terest for the cultural growth of the country, that each of the indigenous South African languages develops their own BLARK. In Chapter 1, the need for the development of an implementable named entity recogniser (NER) for Afrikaans is discussed by first referring to the Constitution of South Africa’s (Republic of South Africa, 2003) language policy. Secondly, the guidelines of BLARK (Krauwer, 2003) are discussed, which is followed by a discussion of an audit that focuses on the number of re-sources and the distribution of human language technology for all eleven South African languages (Sharma Grover, Van Huyssteen & Pretorius, 2010). In respect of an audit conducted by Sharma Grover et al. (2010), it was established that there is a shortage of text-based tools for Afrikaans. This study focuses on this need for text-based tools, by focusing on the develop-ment of a NER for Afrikaans. In Chapter 2 a description is given on what an entity and a named entity is. Later in the chapter the process of technology recycling is explained, by referring to other studies where the idea of technology recycling has been applied successfully (Rayner et al., 1997). Lastly, an analysis is done on the differences that may occur between Afrikaans and Dutch named entities. These differences are divided into three categories, namely: identical cognates, non-identical cognates and unrelated entities. Chapter 3 begins with a description of Frog (van den Bosch et al, 2007), the Dutch NER used in this study, and the functions and operation of its NER-component. This is followed by a description of the Afrikaans-to-Dutch-converter (A2DC) (Van Huyssteen & Pilon, 2009) and finally the various experiments that were completed, are explained. The study consists of six experiments, the first of which was to determine the results of Frog on Dutch data. The second experiment evaluated the effectiveness of Frog on unchanged (raw) Afrikaans data. The following two experiments evaluated the results of Frog on “Dutched” Afrikaans data. The last two experiments evaluated the effectiveness of Frog on raw and “Dutched” Afrikaans data with the addition of gazetteers as part of the pre-processing step. In conclusion, a summary is given with regards to the comparisons between the NER for Afri-kaans that was developed in this study, and the NER-component that Puttkammer (2006) used in his tokeniser. Finally a few suggestions for future research are proposed. / MA (Applied Language and Literary Studies), North-West University, Vaal Triangle Campus, 2013

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The first chapter consists of an overview of the southern plantation as it survives in cultural imagination, especially in William Faulkner’s Absalom, Absalom! and Margaret Mitchell’s Gone With the Wind. The second chapter discusses A Streetcar Named Desire and how Williams reimagines the plantation in an urban setting through the New Orleans Marigny neighborhood. The third chapter examinesWilliams’s reinvention of the rural plantation in Cat on a Hot Tin Roof. The conclusion explores how Williams’s work is used as a blueprint in representing the plantation in postsouthern literature and culture.

Algorithms for classifying pre-tagged person entities in tweets into one of eight profession categories are presented. A classifier using a semi-supervised learning algorithm that takes into consideration the local context surrounding the entity in the tweet, hash tag information, and topic signature scores is described. In addition to the classifier, this research investigates two dictionaries containing the professions of persons. These two dictionaries are used in their own classification algorithms which are independent of the classifier. The method for creating the first dictionary dynamically from the web and the algorithm that accesses this dictionary to classify a person into one of the eight profession categories are explained next. The second dictionary is freebase, an openly available online database that is maintained by its online community. The algorithm that uses freebase for classifying a person into one of the eight professions is described. The results also show that classifications made using the automated constructed dictionary, freebase, or the classifier are all moderately successful. The results also show that classifications made with the automated constructed person dictionary are slightly more accurate than classifications made using freebase. Various hybrid methods, combining the classifier and the two dictionaries are also explained. The results of those hybrid methods show significant improvement over any of the individual methods.

In February 2024 Sewanee Theatre and Dance produced Tennessee Williams’ A Streetcar Named Desire. This thesis documents the role of the technical director from pre-production through closing. 3D Printing technology was used for this production to create scenery that evoked the imagery of 1940s New Orleans. This thesis also discusses the roles of a technical director and the challenges they face in the industry. A portion of this project was done remotely which provides a unique perspective of the role of a Technical Director.

Named entity recognition (NER) is the task of identifying the named entities (NEs) in the texts and classifying them into semantic categories such as person, organization, and place names and time, date, monetary, and percent expressions. NER has two principal aims: identification of NEs and classification of them into semantic categories. The local grammar (LG) approach has recently been shown to be superior to other NER techniques such as the probabilistic approach, the symbolic approach, and the hybrid approach in terms of being able to work with untagged corpora. The LG approach does not require using any dictionaries and gazetteers, which are lists of proper nouns (PNs) used in NER applications, unlike most of the other NER systems. As a consequence, it is able to recognize NEs in previously unseen texts at minimal costs. Most of the NER systems are costly due to manual rule compilation especially in large tagged corpora. They also require some semantic and syntactic analyses to be applied before pattern generation process, which can be avoided by using the LG approach. In this thesis, we tried to acquire LGs for person names from a large untagged Turkish financial news corpus by using an approach successfully applied to a Reuter&rsquo / s financial English news corpus recently by H. N. Traboulsi. We explored its applicability to Turkish language by using frequency, collocation, and concordance analyses. In addition, we constructed a list of Turkish reporting verbs. It is an important part of this study because there is no major study about reporting verbs in Turkish.

An important core technology in the development of human language technology applications is an automatic morphological analyser. Such a morphological analyser consists of various modules, one of which is a tokeniser. At present no tokeniser exists for Afrikaans and it has therefore been impossible to develop a morphological analyser for Afrikaans. Thus, in this research project such a tokeniser is being developed, and the project therefore has two objectives: i)to postulate a tag set for integrated tokenisation, and ii) to develop an algorithm for integrated tokenisation. In order to achieve the first object, a tag set for the tagging of sentences, named-entities, words, abbreviations and punctuation is proposed specifically for the annotation of Afrikaans texts. It consists of 51 tags, which can be expanded in future in order to establish a larger, more specific tag set. The postulated tag set can also be simplified according to the level of specificity required by the user. It is subsequently shown that an effective tokeniser cannot be developed using only linguistic, or only statistical methods. This is due to the complexity of the task: rule-based modules should be used for certain processes (for example sentence recognition), while other processes (for example named-entity recognition) can only be executed successfully by means of a machine-learning module. It is argued that a hybrid system (a system where rule-based and statistical components are integrated) would achieve the best results on Afrikaans tokenisation. Various rule-based and statistical techniques, including a TiMBL-based classifier, are then employed to develop such a hybrid tokeniser for Afrikaans. The final tokeniser achieves an ∫-score of 97.25% when the complete set of tags is used. For sentence recognition an ∫-score of 100% is achieved. The tokeniser also recognises 81.39% of named entities. When a simplified tag set (consisting of only 12 tags) is used to annotate named entities, the ∫-score rises to 94.74%. The conclusion of the study is that a hybrid approach is indeed suitable for Afrikaans sentencisation, named-entity recognition and tokenisation. The tokeniser will improve if it is trained with more data, while the expansion of gazetteers as well as the tag set will also lead to a more accurate system / Thesis (M.A. (Applied Language and Literary Studies))--North-West University, Potchefstroom Campus, 2006.

An important core technology in the development of human language technology applications is an automatic morphological analyser. Such a morphological analyser consists of various modules, one of which is a tokeniser. At present no tokeniser exists for Afrikaans and it has therefore been impossible to develop a morphological analyser for Afrikaans. Thus, in this research project such a tokeniser is being developed, and the project therefore has two objectives: i)to postulate a tag set for integrated tokenisation, and ii) to develop an algorithm for integrated tokenisation. In order to achieve the first object, a tag set for the tagging of sentences, named-entities, words, abbreviations and punctuation is proposed specifically for the annotation of Afrikaans texts. It consists of 51 tags, which can be expanded in future in order to establish a larger, more specific tag set. The postulated tag set can also be simplified according to the level of specificity required by the user. It is subsequently shown that an effective tokeniser cannot be developed using only linguistic, or only statistical methods. This is due to the complexity of the task: rule-based modules should be used for certain processes (for example sentence recognition), while other processes (for example named-entity recognition) can only be executed successfully by means of a machine-learning module. It is argued that a hybrid system (a system where rule-based and statistical components are integrated) would achieve the best results on Afrikaans tokenisation. Various rule-based and statistical techniques, including a TiMBL-based classifier, are then employed to develop such a hybrid tokeniser for Afrikaans. The final tokeniser achieves an ∫-score of 97.25% when the complete set of tags is used. For sentence recognition an ∫-score of 100% is achieved. The tokeniser also recognises 81.39% of named entities. When a simplified tag set (consisting of only 12 tags) is used to annotate named entities, the ∫-score rises to 94.74%. The conclusion of the study is that a hybrid approach is indeed suitable for Afrikaans sentencisation, named-entity recognition and tokenisation. The tokeniser will improve if it is trained with more data, while the expansion of gazetteers as well as the tag set will also lead to a more accurate system / Thesis (M.A. (Applied Language and Literary Studies))--North-West University, Potchefstroom Campus, 2006.

Denna uppsats är en undersökande studie inom Information Extraction. Huvudsyftet är att skapa och utvärdera metoder inom Information Extraction och undersöka hur de kan hjälpa till att förbättra det vetenskapliga resultatet av klassificering av textelement. En deluppgift är att utvärdera den befintliga marknaden för Information Extraction i Sverige.                       För att göra detta har vi skapat ett program bestående av två delar. Den första delen utgörs av ett basfall som är en enkel metod och den andra är mer avancerad och använder sig av olika tekniker inom området Information Extraction. Fältet vi undersöker är hur ofta män och kvinnor nämns i sju olika nyhetskällor i Sverige. Resultatet jämför dessa två metoder och utvärderar dem med vetenskapliga prestationsmått inom Information Extraction.                       Studiens resultat visar på liknande förekomster av män och kvinnor mellan basfallet och den mer avancerade metoden. Undantaget är att den mer avancerade metoden har ett högre vetenskapligt värde. Marknaden för Information Extraction i Sverige är dominerad av stora medieägda bolag, där media dessutom förser dessa företag med data att analysera. Detta gör att det blir svårt att konkurrera utan en ny innovativ idé. / This paper is an investigatory report about Information Extraction. The main purpose is to create and evaluate methods within Information Extraction and see how they can help improve the scientific result in classification of text elements. A subtask is to evaluate the existing market for Information Extraction in Sweden.                       For this task a two-part computer program has been created. The first part is just a baseline with a simple method and the second one is more advanced with tools used in the field Information Extraction. The field we investigate is how often men and women are mentioned in seven different newspapers in Sweden. The result compares these two methods and evaluates them using scientific measurements of information retrieval performance.                       The results of the study show similar occurrences of men and women between the baseline and the more advanced method. The exception being that the more advanced method has a higher scientific value. The market for Information Extraction in Sweden is dominated by large corporations owned by the media, which also provide the data for these kinds of companies to analyze. This makes it hard to compete without having a new innovative idea.