Revisiting floating quantifiers: The syntax of the Modern Greek OLA

This work is a contribution to the long-standing debate on the floating quantifier phe- nomenon in syntax and semantics. It investigates the properties of the Modern Greek floating quantifier ola ‘all’, to determine whether it belongs to the nominal or the verbal domain, and to provide an answer to the enduring question of how floating questions are generated. Regarding its categorial status, it is argued that ola is a quantifier that is part of the DP extended projection, based on evidence from its syntactic behavior. With respect to floating, the fundamental argument is that it is a product of split PF and LF privileg- ing of copies of the ola-phrase. Split privileging redefines the labor carried out by each component. Syntax is responsible for the movement of the QP, composed of ola and its DP restriction, and the interfaces are each tasked with activating either one or both QP copies. Consequently, LF-movement for scope assignment is dispensed with, and the PF rule pronounce higher copy now co-exists with additional spellout options. There is a considerable amount of research dedicated to determining how syntax interacts with the interfaces. Bobaljik (2002) and Tsoulas and Yeo (2017) present arguments in favor of minimizing the labor of covert syntax, and Boskovic and Nunes (2007) argue for a computational mechanism where more than one chain link can be active at each interface. This study is aligned with these efforts, and extends this line of argument to capture the floating quantifier phenomenon involved in constructions with ola

Artificial general intelligence: Proceedings of the Second Conference on Artificial General Intelligence, AGI 2009, Arlington, Virginia, USA, March 6-9, 2009

Artificial General Intelligence (AGI) research focuses on the original and ultimate goal of AI – to create broad human-like and transhuman intelligence, by exploring all available paths, including theoretical and experimental computer science, cognitive science, neuroscience, and innovative interdisciplinary methodologies. Due to the difficulty of this task, for the last few decades the majority of AI researchers have focused on what has been called narrow AI – the production of AI systems displaying intelligence regarding specific, highly constrained tasks. In recent years, however, more and more researchers have recognized the necessity – and feasibility – of returning to the original goals of the field. Increasingly, there is a call for a transition back to confronting the more difficult issues of human level intelligence and more broadly artificial general intelligence

Image categorisation using parallel network constructs: an emulation of early human colour processing and context evaluation

PhD ThesisTraditional geometric scene analysis cannot attempt to address the understanding of human vision. Instead it adopts an algorithmic approach, concentrating on geometric model fitting. Human vision, however, is both quick and accurate but very little is known about how the recognition of objects is performed with such speed and efficiency. It is thought that there must be some process both for coding and storage which can account for these characteristics. In this thesis a more strict emulation of human vision, based on work derived from medical psychology and other fields, is proposed. Human beings must store perceptual information from which to make comparisons, derive structures and classify objects. It is widely thought by cognitive psychologists that some form of symbolic representation is inherent in this storage. Here a mathematical syntax is defined to perform this kind of symbolic description. The symbolic structures must be capable of manipulation and a set of operators is defined for this purpose. The early visual cortex and geniculate body are both inherently parallel in operation and simple in structure. A broadly connectionist emulation of this kind of structure is described, using independent computing elements, which can perform segmentation, re-colouring and generation of the base elements of the description syntax. Primal colour information is then collected by a second network which forms the visual topology, colouring and position information of areas in the image as well as a full description of the scene in terms of a more complex symbolic set. The idea of different visual contexts is introduced and a model is proposed for the accumulation of context rules. This model is then applied to a database of natural images.EPSRC CASE award: Neural Computer Sciences,Southampton

Proceedings of the Eighth Italian Conference on Computational Linguistics CliC-it 2021

The eighth edition of the Italian Conference on Computational Linguistics (CLiC-it 2021) was held at Università degli Studi di Milano-Bicocca from 26th to 28th January 2022. After the edition of 2020, which was held in fully virtual mode due to the health emergency related to Covid-19, CLiC-it 2021 represented the first moment for the Italian research community of Computational Linguistics to meet in person after more than one year of full/partial lockdown

Semantic Domains in Akkadian Text

The article examines the possibilities offered by language technology for analyzing semantic fields in Akkadian. The corpus of data for our research group is the existing electronic corpora, Open richly annotated cuneiform corpus (ORACC). In addition to more traditional Assyriological methods, the article explores two language technological methods: Pointwise mutual information (PMI) and Word2vec.Peer reviewe

CyberResearch on the Ancient Near East and Eastern Mediterranean

CyberResearch on the Ancient Near East and Neighboring Regions provides case studies on archaeology, objects, cuneiform texts, and online publishing, digital archiving, and preservation. Eleven chapters present a rich array of material, spanning the fifth through the first millennium BCE, from Anatolia, the Levant, Mesopotamia, and Iran. Customized cyber- and general glossaries support readers who lack either a technical background or familiarity with the ancient cultures. Edited by Vanessa Bigot Juloux, Amy Rebecca Gansell, and Alessandro Di Ludovico, this volume is dedicated to broadening the understanding and accessibility of digital humanities tools, methodologies, and results to Ancient Near Eastern Studies. Ultimately, this book provides a model for introducing cyber-studies to the mainstream of humanities research

Transforming structured descriptions to visual representations. An automated visualization of historical bookbinding structures.

In cultural heritage, the documentation of artefacts can be both iconographic and textual, i.e. both pictures and drawings on the one hand, and text and words on the other are used for documentation purposes. This research project aims to produce a methodology to transform automatically verbal descriptions of material objects, with a focus on bookbinding structures, into standardized and scholarly-sound visual representations. In the last few decades, the recording and management of documentation data about material objects, including bookbindings, has switched from paper-based archives to databases, but sketches and diagrams are a form of documentation still carried out mostly by hand. Diagrams hold some unique information, but often, also redundant information already secured through verbal means within the databases. This project proposes a methodology to harness verbal information stored within a database and automatically generate visual representations. A number of projects within the cultural heritage sector have applied semantic modelling to generate graphic outputs from verbal inputs. None of these has considered bookbindings and none of these relies on information already recorded within databases. Instead they develop an extra layer of modelling and typically gather more data, specifically for the purpose of generating a pictorial output. In these projects qualitative data (verbal input) is often mixed with quantitative data (measurements, scans, or other direct acquisition methods) to solve the problems of indeterminateness found in verbal descriptions. Also, none of these projects has attempted to develop a general methodology to ascertain the minimum amount ii of information that is required for successful verbal-to-visual transformations for material objects in other fields. This research has addressed these issues. The novel contributions of this research include: (i) a series of methodological recommendations for successful automated verbal-to-visual intersemiotic translations for material objects — and bookbinding structures in particular — which are possible when whole/part relationships, spatial configurations, the object’s logical form, and its prototypical shapes are communicated; (ii) the production of intersemiotic transformations for the domain of bookbinding structures; (iii) design recommendations for the generation of standardized automated prototypical drawings of bookbinding structures; (iv) the application — never considered before — of uncertainty visualization to the field of the archaeology of the book. This research also proposes the use of automatically generated diagrams as data verification tools to help identify meaningless or wrong data, thus increasing data accuracy within databases