Natural language understanding with commonsense reasoning: application to the winograd schema challenge

En 1950, Alan Turing propuso un test para evaluar el grado de inteligencia humana que podria presentar una maquina. La idea principal era realmente sencilla: llevar a cabo una charla abierta entre un evaluador y la maquina. Si dicho evaluador era incapaz de discernir si el examinado era una persona o una maquina, podria afirmarse que el test habia sido superado. Desde entonces, a lo largo de los ultimos 60 anos se han presentado numerosas propuestas a traves de los cuales se han puesto al descubierto ciertas debilidades del test. Quizas la mas importante es el hecho de centrarse en la inteligencia humana, dejando a un lado otros tipos de inteligencia. El test obliga en gran medida a definir en la maquina un comportamiento antropomorfico y de imitacion con el unico fin de pasar el test. Con el fin de superar estos y otros puntos debiles, Hector Levesque propuso en 2011 un nuevo reto, “The Winograd Schema Challenge”. Un sencillo test basado en Pregunta y Respuesta sobre una frase que describe una situacion cotidiana. En dicha frase se identifican dos agentes participantes, existiendo una referencia a uno de ellos a traves de (generalmente) un pronombre. La prueba consiste en entender a cual de los agentes esta haciendo siendo referenciado por dicho pronombre. Es decir, resolver la anafora o correferencia en cuestion. La clave del test esta en la definicion de la frase, que debe ser de tal que la solucion al problema no puede encontrarse mediante metodos estadisticos. El equilibrio existente entre los elementos asociados a la anafora es tal que solo es resoluble mediante una comprension de los conceptos descritos en la frase tal y como lo haria una persona. Es decir, a traves de la comprension del lenguaje natural conseguida gracias al conocimiento del dominio o mundo y utilizando cierto razonamiento de sentido comun. Este trabajo presenta una propuesta para resolver este reto de comprension de lenguaje natural definido por Levesque. Para ello se han utilizado diferentes modos de representacion del conocimiento con la idea de permitir en cierta medida aplicar los conceptos del razonamiento de sentido comun clasico del ser humano a traves de una aplicacion software desarrollada con dicho fin. ---ABSTRACT---In 1950, Alan Turing proposed a test to measure the degree of human intelligence that could present a machine or computer. The main idea was really simple: To carry out an open discussion between an evaluator and the machine. If the evaluator was unable to discern whether the examinee was a person or a machine, it could be argued that the test had been passed. Since then, over the last 60 years there have been numerous proposals that have finally revealed certain weaknesses in the test. Perhaps, the most important one is that it only focus on human intelligence, leaving aside other types of intelligence. The test also requires the machine to act as an anthropomorphic and imitation device with the sole purpose of passing the test behavior. In order to overcome these and other weaknesses, Hector Levesque proposed in 2011 a new test, "The Winograd Schema Challenge". A simple experiment based on Q & A over a phrase describing an everyday situation. In the sentence, there are two main participants or actors, and there is also a reference to one of them through (usually) a pronoun. The test consists of trying to find which agent is referenced by the pronoun. That is, it tries to solve an anaphora or coreference problem. The test key point is how the phrase is defined. It should be done in such a way that the solution to the problem could not be found through statistical methods. The balance between the elements associated with anaphora makes the problem only resolvable through a deeper understanding of the concepts described in the phrase (like would be done by a person). That is, by way of the natural language understanding achieved with the knowledge of the related domain or world and by using somehow what is known as commonsense reasoning. This paper presents a proposal to solve the understanding natural language challenge defined by Levesque. For this purpose, they have used different modes of knowledge representation with the idea of allowing the application of classical concepts of human commonsense reasoning. The results have been consolidated in a software application developed specifically for this purpose.