The aim of this study is to examine the semantic architecture of the motif complex the four elements, i.e. fire, air, water and earth, in the Swedish poet Gunnar Ekelöf’s poem A Mölna Elegy (1960). The poem belongs to the same polyphonic and quotative-allusive tradition as T. S. Eliot’s The Waste Land and Ezra Pound’s Cantos. The four elements may be regarded both as four separate motifs and as constituting one semantically coherent motif complex. The latter reading has to do with the fact that the phrase the four elements is not itself present in the text. Thus, the thesis includes the assumption that this motif complex, heavily suggested by items in the text but still omitted, might function as a text matrix, from which a number of themes emerge such as life–death and time. The thesis has a theoretical anchoring in ideas about semantic frames (Barsalou) when discussing semantic relations between the different element-related words in the poem, and how these words may be linked to the concepts ‘fire’, ‘air’, water’ and ‘earth’ respectively. Traditional lexical relations such as hyponymy, antonymy and meronymy only catch the more obvious relations such as fire–glow, warm–cold and tree–branch, but are unable to explain pragmatically based relations between words linked to the same conceptual domain, such as sea–jetty, water–sink, fly–air and the like. To some extent, the thesis also draws upon Riffaterre’s theories about a poem’s matrix and how meaning arises in such texts. A major finding of the study is the heavy lexical presence of the four elements in the poem, expressed and suggested by a great number of semantically heterogeneous words. This semantic pattern is analysed in detail with the aid of semantic frame theory. A further discovery is that most of the element words imply dichotomies such as motion–repose, warmth–cold, light–dark or soft–hard. The elements have most of the dichotomies in common, which strongly suggests a union of all the four elements. Such a union is also suggested by several conspicuous compounds never earlier recorded in Swedish, such as glödstänk (‘glowspray’), vindstänk (‘windspray’), eldsus (‘fire sough’) and vågsus (‘wave sough’). The meetings of element are also described at the syntactic level as an explicit amalgamation of all four elements, which suggests a theme not earlier noticed. This theme may tentatively be called the cyclical amalgamation.

Les systèmes de dialogue homme-machine ont pour objectif de permettre un échange oral efficace et convivial entre un utilisateur humain et un ordinateur. Leurs domaines d'applications sont variés, depuis la gestion d'échanges commerciaux jusqu'au tutorat ou l'aide à la personne. Cependant, les capacités de communication de ces systèmes sont actuellement limités par leur aptitude à comprendre la parole spontanée. Nos travaux s'intéressent au module de compréhension de la parole et présentent une proposition entièrement basée sur des approches stochastiques, permettant l'élaboration d'une hypothèse sémantique complète. Notre démarche s'appuie sur une représentation hiérarchisée du sens d'une phrase à base de frames sémantiques. La première partie du travail a consisté en l'élaboration d'une base de connaissances sémantiques adaptée au domaine du corpus d'expérimentation MEDIA (information touristique et réservation d'hôtel). Nous avons eu recours au formalisme FrameNet pour assurer une généricité maximale à notre représentation sémantique. Le développement d'un système à base de règles et d'inférences logiques nous a ensuite permis d'annoter automatiquement le corpus. La seconde partie concerne l'étude du module de composition sémantique lui-même. En nous appuyant sur une première étape d'interprétation littérale produisant des unités conceptuelles de base (non reliées), nous proposons de générer des fragments sémantiques (sous-arbres) à l'aide de réseaux bayésiens dynamiques. Les fragments sémantiques générés fournissent une représentation sémantique partielle du message de l'utilisateur. Pour parvenir à la représentation sémantique globale complète, nous proposons et évaluons un algorithme de composition d'arbres décliné selon deux variantes. La première est basée sur une heuristique visant à construire un arbre de taille et de poids minimum. La seconde s'appuie sur une méthode de classification à base de séparateurs à vaste marge pour décider des opérations de composition à réaliser. Le module de compréhension construit au cours de ce travail peut être adapté au traitement de tout type de dialogue. Il repose sur une représentation sémantique riche et les modèles utilisés permettent de fournir des listes d'hypothèses sémantiques scorées. Les résultats obtenus sur les données expérimentales confirment la robustesse de l'approche proposée aux données incertaines et son aptitude à produire une représentation sémantique consistante / Spoken dialog systems enable users to interact with computer systems via natural dialogs, as they would with human beings. These systems are deployed into a wide range of application fields from commercial services to tutorial or information services. However, the communication skills of such systems are bounded by their spoken language understanding abilities. Our work focus on the spoken language understanding module which links the automatic speech recognition module and the dialog manager. From the user’s utterance analysis, the spoken language understanding module derives a representation of its semantic content upon which the dialog manager can decide the next best action to perform. The system we propose introduces a stochastic approach based on Dynamic Bayesian Networks (DBNs) for spoken language understanding. DBN-based models allow to infer and then to compose semantic frame-based tree structures from speech transcriptions. First, we developed a semantic knowledge source covering the domain of our experimental corpus (MEDIA, a French corpus for tourism information and hotel booking). The semantic frames were designed according to the FrameNet paradigm and a hand-craft rule-based approach was used to derive the seed annotated training data.Then, to derive automatically the frame meaning representations, we propose a system based on a two decoding step process using DBNs : first basic concepts are derived from the user’s utterance transcriptions, then inferences are made on sequential semantic frame structures, considering all the available previous annotation levels. The inference process extracts all possible sub-trees according to lower level information and composes the hypothesized branches into a single utterance-span tree. The composition step investigates two different algorithms : a heuristic minimizing the size and the weight of the tree ; a context-sensitive decision process based on support vector machines for detecting the relations between the hypothesized frames. This work investigates a stochastic process for generating and composing semantic frames using DBNs. The proposed approach offers a convenient way to automatically derive semantic annotations of speech utterances based on a complete frame hierarchical structure. Experimental results, obtained on the MEDIA dialog corpus, show that the system is able to supply the dialog manager with a rich and thorough representation of the user’s request semantics

Meaning has been established pervasively as a central concept throughout disciplines that were involved in cognitive revolution. Its metaphoric usage comes to be, first and foremost, through the interpreter’s constraint: representational relationships and contents are considered to be in the “eye” or mind of the observer and shared properties among observers themselves are knowable through interlinguistic phenomena, such as translation. Despite the instability of meaning in relation to its underdetermination by reference, it can be a tertium comparationis or “third comparator” for extended human cognition if gauged through invariants that exist in transfer processes such as translation, as all languages and cultures are rooted in pan-human experience and, thus, share and express species-specific ontology. Meaning, seen as a cognitive competence, does not stop outside of the body but extends, depends, and partners with other agents and the environment. A novel approach for exploring the transfer properties of some constituent items of the original natural semantic metalanguage in English, that is, semantic primitives, is presented: FrameNet’s semantic frames, evoked by the primes SEE and FEEL, were extracted from EuroParl, a parallel corpus that allows for the automatic word alignment of items with their synonyms. Large Ontology Multilingual Extraction was used. Afterward, following the Semantic Mirrors Method, a procedure that consists back-translating into source language, a translatological examination of translated and original versions of items was performed. A fully automated pipeline was designed and tested, with the purpose of exploring associated frame shifts and, thus, beginning a research agenda on their alleged universality as linguistic features of translation, which will be complemented with and contrasted against further massive feedback through a citizen science approach, as well as cognitive and neurophysiological examinations. Additionally, an embodied account of frame semantics is proposed.

過往對於情緒分析的研究顯少聚焦在讀者情緒，往往著眼於筆者情緒之研究。讀者情緒是指讀者閱讀文章後產生之情緒感受。然而相同一篇文章可能會引起讀者多種情緒反應，甚至產生與筆者迥異之情緒感受，也突顯其讀者情緒分析存在更複雜的問題。本研究之目的在於辨識讀者閱讀文章後之切確情緒，而文件分類的方法能有效地應用於讀者情緒偵測的研究，除了能辨識出正確的讀者情緒之外，並且能保留讀者情緒文件之相關內容。然而，目前的資訊檢索系統仍缺乏對隱含情緒之文件有效的辨識能力，特別是對於讀者情緒的辨識。除此之外，基於機器學習的方法難以讓人類理解，也很難查明辨識失敗的原因，進而無法了解何種文章引發讀者切確的情緒感受。有鑑於此，本研究提出一套基於語意框架(frame-based approach, FBA)之讀者情緒偵測研究的方法，FBA能模擬人類閱讀文章的方式外，並且可以有效地建構讀者情緒之基礎知識，以形成讀者情緒的知識庫。FBA具備高自動化抽取語意概念的基礎知識，除了利用語法結構的特徵，我們進一步考量周邊語境和語義關聯，將相似的知識整合成具有鑑別力之語意框架，並且透過序列比對(sequence alignment)的方式進行讀者情緒文件之匹配。經實驗結果顯示證明，本研究方法能有效地運用於讀者情緒偵測之相關研究。 / Previous studies on emotion classification mainly focus on the writer's emotional state. By contrast, this research emphasizes emotion detection from the readers' perspective. The classification of documents into reader-emotion categories can be applied in several ways, and one of the applications is to retain only the documents that cause desired emotions for enabling users to retrieve documents that contain relevant contents and at the same time instill proper emotions. However, current IR systems lack of ability to discern emotion within texts, reader-emotion has yet to achieve comparable performance. Moreover, the pervious machine learning-based approaches are generally not human understandable, thereby, it is difficult to pinpoint the reason for recognition failures and understand what emotions do articles trigger in their readers. We propose a flexible semantic frame-based approach (FBA) for reader's emotion detection that simulates such process in human perception. FBA is a highly automated process that incorporates various knowledge sources to learn semantic frames that characterize an emotion and is comprehensible for humans from raw text. Generated frames are adopted to predict readers' emotion through an alignment-based matching algorithm that allows a semantic frame to be partially matched through a statistical scoring scheme. Experiment results demonstrate that our approach can effectively detect readers' emotion by exploiting the syntactic structures and semantic associations in the context as well as outperforms currently well-known statistical text classification methods and the stat-of-the-art reader-emotion detection method.

The characterization of the Markan disciples has been and continues to be the object of much scholarly reflection and speculation. For many, the Markan author's presentation of Jesus' disciples holds a key, if not the key, to unlocking the purpose and function of the gospel as a whole. Commentators differ as to whether the Markan disciples ultimately serve a pedagogical or polemical function, yet they are generally agreed that the disciples in Mark come off rather badly, especially when compared to their literary counterparts in Matthew, Luke, and John. This narrative-critical study considers the characterization of the Markan disciples within the Sea Crossing movement (Mark 4:1-8:30). While commentators have, on the whole, interpreted the disciples' negative characterization in this movement in terms of lack of faith and/or incomprehension, neither of these, nor a combination of the two, fully accounts for the severity of language leveled against the disciples by the narrator (6:52) and Jesus (8:17-18). Taking as its starting point an argument by Jeffrey B. Gibson (1986) that the harshness of Jesus' rebuke in Mark 8:14-21 is occasioned not by the disciples' lack of faith or incomprehension but by their active resistance to his Gentile mission, this investigation uncovers additional examples of the disciples' resistance to Gentile mission, offering a better account of their negative portrayal within the Sea Crossing movement and helping explain many of their other failures. In short, this study argues that in Mark 4:1-8:26, the disciples are characterized as resistant to Jesus' Gentile mission and to their participation in that mission, the chief consequence being that they are rendered incapable of recognizing Jesus' vocational identity as Israel's Messiah (Thesis A). This leads to a secondary thesis, namely, that in Mark 8:27-30, Peter's recognition of Jesus' messianic identity indicates that the disciples have finally come to accept Jesus' Gentile mission and their participation in it (Thesis B). Chapter One: Introduction: offers a selective review of scholarly treatments of the Markan disciples, which shows that few scholars attribute resistance, let alone purposeful resistance, to the disciples. Chapter Two: The Rhetoric of Repetition: introduces the methodological tools, concepts, and perspectives employed in the study. It includes a section on narrative criticism, which focuses upon the story-as-discoursed and the implied author and reader, and a section on Construction Grammar, a branch of cognitive linguistics founded by Charles Fillmore and further developed by Paul Danove, which focuses upon semantic and narrative frames and case frame analysis. Chapter Three: The Sea Crossing Movement, Mark 4:1-8:30: addresses the question of Markan structure and argues that Mark 4:1-8:30 comprises a single, unified, narrative movement, whose action and plot is oriented to the Sea of Galilee and whose most distinctive feature is the network of sea crossings that transport Jesus and his disciples back and forth between Jewish and Gentile geopolitical spaces. Following William Freedman, Chapter Four: The Literary Motif: introduces two criteria (frequency and avoidability) for determining objectively what constitutes a literary motif and provides the methodological basis and starting point for the analyses performed in chapters five and six. Chapter Five: The Sea Crossing Motif: establishes and then carries out a lengthy narrative analysis of the Sea Crossing motif, which is oriented around Mark's use of ‎θάλασσα (thalassa) and πλοῖον (ploion), and Chapter Six: The Loaves Motif: does the same for The Loaves motif, oriented around Mark's use of ἄρτος (artos). Finally, Chapter Seven: The Narrative Logic of the Disciples (In)comprehension: draws together all narrative, linguistic, and exegetical insights of the previous chapters and offers a single coherent reading of the Sea Crossing movement that establishes Theses A and B.