This thesis is focused on temporal information processing, which is a task framed in the field of natural language processing. The aim of this task is to obtain the temporal location and ordering of the events expressed in text or discourse, which requires the automatic interpretation of temporal expressions, events, and the temporal relations between them. The majority of current approaches are based on morphosyntactic knowledge. However, temporal entities are often ambiguous at that language analysis level. Our hypothesis is that the linguistic expression of time is a semantic phenomenon and therefore, to achieve a better extraction performance, temporal information must be processed using semantics. To prove this hypothesis, we present a semantic approach to temporal information processing: TIPSem. This is an automated system that includes features based on lexical semantics, semantic roles, and temporal semantics, in addition to morphosyntactic features. TIPSem has been empirically evaluated through the participation in the TempEval-2 international evaluation exercise and subsequent experiments based on this test. The results obtained firmly support the presented hypothesis and their analysis demonstrates that semantic features aid in handling morphosyntactic ambiguity and favour generalization capabilities. These conclusions have been reached for different languages (i.e., English, Spanish, Italian, and Chinese), which supports the defended hypothesis at a multilingual level. Finally, as compared with the state of the art, TIPSem obtains a very competitive performance level and introduces a remarkable improvement in event processing. TIPSem has been applied to the problem of graphical representation of temporal information. We have developed a dynamic interface which brings users time-based access to information: Time-Surfer. The results obtained through a user-oriented evaluation of this interface demonstrate that TIPSem’s performance is also satisfactory from an extrinsic standpoint. / This PhD thesis has been supported by the Spanish Government, in projects: TIN-2006-15265-C06-01, TIN-2009-13391-C04-01 and PROMETEO/2009/119, where Hector Llorens is funded under a FPI grant (BES-2007-16256).

Un área relativamente nueva en la Inteligencia Artificial es la argumentación rebatible, la cual modela el proceso de razona-miento en el cual se producen y se evalúan argumentos a fa-vor y en contra de una proposición para verificar la aceptabi-lidad de dicha proposición. Se han definido diferentes sistemas formales para argumentación rebatible como una forma de representar las características más interesantes del razona-miento de sentido común. La idea central de estos sistemas radica en que una determinada propuesta será aceptada, si el argumento que le da soporte se considera aceptable luego de realizado cierto análisis. Este análisis se realiza teniendo en cuenta a todos los contraargumentos disponibles.Por lo tanto, en el conjunto de los argumentos del sistema, algunos argu-mentos serán aceptables o justificados o garantizados, mien-tras que otros no lo serán. De esta manera, la argumentación rebatible permite razonar con información incompleta e incier-ta, y define una manera adecuada de razonar para el manejo de la inconsistencia presente en los sistemas basados en el conocimiento. Los sistemas argumentativos abstractos son formalismos para lograr razonamiento rebatible donde algunas componentes se mantienen sin especificar. En ellos la principal abstracción está en la estructura de los argumentos. En este tipo de sistemas, el énfasis está puesto en dilucidar cuestio-nes semánticas, tales como encontrar el conjunto de argu-mentos aceptados. La mayoría de ellos está basado en la no-ción abstracta de ataque, representada como una relación entre los miembros del conjunto de argumentos disponibles. Si dos argumentos (A; B) forman parte de una relación de ataque, la aceptación del argumento B depende de la acep-tación de A pero no al revés, i:e:, resulta necesario determi-nar si A es aceptado o no para aceptar a B, pero la aceptabi-lidad de A no depende de la aceptabilidad del argumento B. Aunque en la literatura se encuentran varios marcos de argu-mentación (o frameworksen Inglés) ninguno de ellos incluye la noción de tiempo, a pesar de tratarse de un concepto cotidia-no en el razonamiento de sentido común. La representación del tiempo es una tarea difícil pero necesaria para la resolu-ción de problemas de diversas tareas, tales como Basede Datos, Simulación, Sistemas Expertos e Inteligencia Artificial. El objetivo principal de esta Tesis es brindar una formalización para lograr razonamiento argumentativo temporal. Para ello se tomará como punto de partida alguno de los diversos sistemas argumentativos con diferentes grados de abstracción de-sarrollados. El más abstracto de todos es el sistema desarrolla-do por Dung, que ha sido el marco inicial para muchos otros desarrollos. El framework abstracto de Dung será el sistema de partida elegido para extenderlo y lograr el objetivo plantea-do. En esta Tesis se presentan dos sistemas argumentativos abstractos. Ambos se encuentran basados en el sistema argu-mentativo de Dung y lo extienden agregándole un dimensión temporal. El tiempo aparece asociado a los argumentos indi-cando cuando los mismos están disponibles o son relevantes como piezas de razonamiento. Los sistemas desarrollados utilizan la misma primitiva de representación pero sobre es-tructuras temporales diferentes y adoptan estrategias de disponibilidad con diferentes grados de exibilidad. Los resulta-dos obtenidos permiten contar con la caracterización formal de los sistemas y su vinculación al sistema clásico. En parti-cular, se definen semánticas para los sistemas argumenta-tivos, basadas en las semanticas tradicionales del área; com-parándose las mismas con las definidas para el framework de Dung. Estos resultados están vinculados a áreas relaciona-das de las ciencias de la computación tales como argumen-tación, razonamiento temporal, y razonamiento de sentido común. / Argumentation is a relatively new area in Artificial Intelligence, that models the process of reasoning in which arguments for and against a proposal are analyzed in order to verify the acceptability of the proposal. Diferent formal systems of de-feasible argumentation have been defined as forms of repre-senting interesting characteristics of practical or common sen-se reasoning. The central idea in these systems is that a pro-position will be accepted if there exists an argument that supports it, and this argument is regarded as acceptable with respect to an analysis performed considering all the available counterarguments. Therefore, in the set of arguments of the system, some of them will be acceptable or justified or warranted arguments, while others will be not. In this manner, defeasible argumentation allows reasoning with incomplete and uncertain information and is suitable to handle inconsis-tency in knowledge-based systems. Abstract argumentation systems are formalisms for defeasible reasoning where some components remain unspecified, being the structure of argu-ments the main abstraction. In this type of systems, the emphasis is put on elucidating semantic questions, such as finding the set of accepted arguments. Most of them are ba-sed on the single abstract notion of attack represented as a relation among the set of available arguments. If two argu-ments (A; B) are in the attack relation then in order to accept B it is necessary to find out if A is accepted or not, but not the other way around. From that relation, several argument extensions are dened as sets of possible accepted arguments. Although there are several argumentation frame-works in the literature, none of them includes the notion of time, which is an everyday factor of common sense reaso-ning.Time representation involves a hard but necessary task in knowledge representation and reasoning. Application in several areas required time formalizations, among them we can mention Data Bases, Simulation, Expert Systems and Artificial Intelligence. The main objective of this Thesis is to provide an abstract formalization to address temporal argumentative rea-soning. In order to achieve this objective one of the several argumentative frameworks developed is used as starting point. The most abstract of all was developed by Dung, and precisely for this feature has been the starting point for many other developments. The abstract framework of Dung is the chosen system for being extended in order to achieve our objective. In this Thesis we present two abstract argumenta-tive systems called Timed Argumentative Frameworks. Both are based on Dung argumentative system and are extended to include a time dimension. Time is associated to arguments, indicating when they are available or are relevant as part of reasoning. These systems use the same primitive for time representation but different temporal structures. The strate-gies for representing the availability of arguments have different degrees of exibility. We define several semantic notions for these novel timed argumentation systems. The semantics are based on the traditional, classic ones develo-ped in the area. these new semantics are compared with those dened for the basic framework of Dung. These results are linked to related areas of computer science such as reaso-ning, temporal reasoning and common sense reasoning.