Reversible stochastic attribute-value grammars

Een bekende vraag in de taalkunde is de vraag of de mens twee onafhankelijke modules heeft voor taalbegrip en taalproductie. In de computertaalkunde zijn taalbegrip (ontleding) en taalproductie (generatie) in de recente geschiedenis eigenlijk altijd als twee afzonderlijke taken en dus modules behandeld. De hoofdstelling van dit proefschrift is dat ontleding en generatie op een computer door één component uitgevoerd kan worden, zonder slechter te presteren dan afzonderlijke componenten voor ontleding en generatie. De onderliggende redenering is dat veel voorkeuren gedeeld moeten zijn tussen productie en begrip, omdat het anders niet mogelijk zou zijn om een geproduceerde zin te begrijpen. Om deze stelling te onderbouwen is er eerst een generator voor het Nederlands ontwikkeld. Deze generator is vervolgens geïntegreerd met een bestaande ontleder voor het Nederlands. Het proefschrift toont aan dat er inderdaad geen significant verschil is tussen de prestaties van de geïntegreerde module en afzonderlijke begrips- en productiecomponenten. Om een beter begrip te krijgen hoe het gecombineerde model werkt, wordt er zogenaamde `feature selectie’ toegepast. Dit is een techniek om de belangrijkste eigenschappen die een begrijpelijke en vloeiende zin karakteriseren op te sporen. Het proefschrift toont aan dat dit met een klein aantal, voornamelijk taalkundig geïnformeerde eigenschappen bepaald kan worden

Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation

This paper surveys the current state of the art in Natural Language Generation (NLG), defined as the task of generating text or speech from non-linguistic input. A survey of NLG is timely in view of the changes that the field has undergone over the past decade or so, especially in relation to new (usually data-driven) methods, as well as new applications of NLG technology. This survey therefore aims to (a) give an up-to-date synthesis of research on the core tasks in NLG and the architectures adopted in which such tasks are organised; (b) highlight a number of relatively recent research topics that have arisen partly as a result of growing synergies between NLG and other areas of artificial intelligence; (c) draw attention to the challenges in NLG evaluation, relating them to similar challenges faced in other areas of Natural Language Processing, with an emphasis on different evaluation methods and the relationships between them.Comment: Published in Journal of AI Research (JAIR), volume 61, pp 75-170. 118 pages, 8 figures, 1 tabl

Effects of hot isostatic pressing on the elastic modulus and tensile properties of 316L parts made by powder bed laser fusion

The microstructure and mechanical properties of 316 L steel have been examined for parts built by a powder bed laser fusion process, which uses a laser to melt and build parts additively on a layer by layer basis.Relative density and porosity determined using various experimental techniques were correlated against laser energy density. Based on porosity sizes, morphology and distributions, the porosity was seen to transition between an irregular, highly directional porosity at the low laser energy density and a smaller, more rounded and randomly distributed porosity at higher laser energy density, thought to be caused by keyhole melting. In both cases, the porosity was reduced by hot isostatic pressing (HIP).High throughput ultrasound based measurements were used to calculate elasticity properties and show that the lower porosities from builds with higher energy densities have higher elasticity moduli in accordance with empirical relationships, and hot isostatic pressing improves the elasticity properties to levels associated with wrought/rolled 316 L. However, even with hot isostatic pressing the best properties were obtained from samples with the lowest porosity in the as-built condition.A finite element stress analysis based on the porosity microstructures was undertaken, to understand the effect of pore size distributions and morphology on the Young's modulus. Over 1–5% porosity range angular porosity was found to reduce the Young's modulus by 5% more than rounded porosity. Experimentally measured Young's moduli for samples treated by HIP were closer to the rounded trends than the as-built samples, which were closer to angular trends.Tensile tests on specimens produced at optimised machine parameters displayed a high degree of anisotropy in the build direction and test variability for as-built parts, especially between vertical and horizontal build directions. The as-built properties were generally found to have a higher yield stress, but lower upper tensile strength and elongation than published data for wrought/hot-rolled plate 316 L. The hot isostatically pressed parts showed a homogenisation of the properties across build directions and properties much more akin to those of wrought/hot-rolled 316 L, with an increase in elongation and upper tensile strength, and a reduction in yield over the as-built samples

Spiral Growth Manufacturing (SGM): A Continuous Additive Manufacturing Technology for Powder Processing

Layered manufacturing (LM) technologies are a class of additive manufacturing processes which create three dimensional geometries directly from CAD data sequentially layer by layer. This group of technologies can process a variety of metallic, polymer and ceramic materials, as liquids, powders, or solid sheets or filaments. The material can be processed using a laser, such as melting a powder or curing a polymer resin or consolidated using a binder deposited from a print head. The build methodology used in all LM is fundamentally a start-stop process since the deposition of material and processing of each layer occurs ~equentially. Hence, the build rate can be slow (2 - 6 Layers per minute); consequently, LM technologies have largely found application as prototyping tools to speed up product development. In order for these technologies to be adopted as rapid manufacturing (RM) methods to directly manufacture complex components which cannot be manufactured by other means these speed limitations need to be addressed. This Thesis describes a new high speed RM process, Spiral Growth Manufacturing (SGM), whereby 3D parts are built by simultaneously depositing, levelling and selectively consolidating thin powder layers onto a rotating build platform. This build configuration has several advantages when compared to conventional layered manufacturing systems: firstly, the process is continuous with no layer preparation overheads; secondly, the material deposition and solidification process can be performed simultaneously by the addition of further 'build stations' radially distributed about the circumference of the machine. The work presented in this thesis focused on the design, development and testing ofthe Spiral Growth Manufacturing process. Two machines were developed; one used a bank of stationary inkjet heads to print material, either as a binder into a powder layer or as hard material from mixing two printed ink solutions and the other machine used a 90 W, flash lamp pumped Nd:YAG laser to process metal powders by localised melting. The main objective ofthe testing phase was to produce simple 3D objects from solidified layers by: a) ink jet printing a binding agent into the deposited plaster powder layers; and b) ink jet printing reactive materials to form plaster directly. The second machine was developed to exploit the considerable knowledge of Selective Laser Melting (SLM) at Liverpool, with the modification of a research SLM machine to SGM operation

Treebank-based acquisition of Chinese LFG resources for parsing and generation

This thesis describes a treebank-based approach to automatically acquire robust,wide-coverage Lexical-Functional Grammar (LFG) resources for Chinese parsing and generation, which is part of a larger project on the rapid construction of deep, large-scale, constraint-based, multilingual grammatical resources. I present an application-oriented LFG analysis for Chinese core linguistic phenomena and (in cooperation with PARC) develop a gold-standard dependency-bank of Chinese f-structures for evaluation. Based on the Penn Chinese Treebank, I design and implement two architectures for inducing Chinese LFG resources, one annotation-based and the other dependency conversion-based. I then apply the f-structure acquisition algorithm together with external, state-of-the-art parsers to parsing new text into "proto" f-structures. In order to convert "proto" f-structures into "proper" f-structures or deep dependencies, I present a novel Non-Local Dependency (NLD) recovery algorithm using subcategorisation frames and f-structure paths linking antecedents and traces in NLDs extracted from the automatically-built LFG f-structure treebank. Based on the grammars extracted from the f-structure annotated treebank, I develop a PCFG-based chart generator and a new n-gram based pure dependency generator to realise Chinese sentences from LFG f-structures. The work reported in this thesis is the first effort to scale treebank-based, probabilistic Chinese LFG resources from proof-of-concept research to unrestricted, real text. Although this thesis concentrates on Chinese and LFG, many of the methodologies, e.g. the acquisition of predicate-argument structures, NLD resolution and the PCFG- and dependency n-gram-based generation models, are largely language and formalism independent and should generalise to diverse languages as well as to labelled bilexical dependency representations other than LFG

Modeling Narrative Discourse

This thesis describes new approaches to the formal modeling of narrative discourse. Although narratives of all kinds are ubiquitous in daily life, contemporary text processing techniques typically do not leverage the aspects that separate narrative from expository discourse. We describe two approaches to the problem. The first approach considers the conversational networks to be found in literary fiction as a key aspect of discourse coherence; by isolating and analyzing these networks, we are able to comment on longstanding literary theories. The second approach proposes a new set of discourse relations that are specific to narrative. By focusing on certain key aspects, such as agentive characters, goals, plans, beliefs, and time, these relations represent a theory-of-mind interpretation of a text. We show that these discourse relations are expressive, formal, robust, and through the use of a software system, amenable to corpus collection projects through the use of trained annotators. We have procured and released a collection of over 100 encodings, covering a set of fables as well as longer texts including literary fiction and epic poetry. We are able to inferentially find similarities and analogies between encoded stories based on the proposed relations, and an evaluation of this technique shows that human raters prefer such a measure of similarity to a more traditional one based on the semantic distances between story propositions

Designing Service-Oriented Chatbot Systems Using a Construction Grammar-Driven Natural Language Generation System

Service oriented chatbot systems are used to inform users in a conversational manner about a particular service or product on a website. Our research shows that current systems are time consuming to build and not very accurate or satisfying to users. We find that natural language understanding and natural language generation methods are central to creating an e�fficient and useful system. In this thesis we investigate current and past methods in this research area and place particular emphasis on Construction Grammar and its computational implementation. Our research shows that users have strong emotive reactions to how these systems behave, so we also investigate the human computer interaction component. We present three systems (KIA, John and KIA2), and carry out extensive user tests on all of them, as well as comparative tests. KIA is built using existing methods, John is built with the user in mind and KIA2 is built using the construction grammar method. We found that the construction grammar approach performs well in service oriented chatbots systems, and that users preferred it over other systems