This thesis investigates non-arbitrariness in novel sets of signs (mappings between signals and meanings). Two common ways of characterizing signs – by the degree of motivatedness they exhibit and by the degree of systematic compositionality they exhibit – are not necessarily orthogonal. Thus, the emergence of arbitrariness and of systematic compositionality in language should be studied together. We focus on a particular interface of the two properties: the systematic re-use of arbitrary elements. Previous work that demonstrates how novel signs can emerge and then evolve to become arbitrary does not measure systematic compositionality. On the other hand, previous work on systematic compositionality proposes a mechanism for the evolution of systematic compositionality and a measure of the property, but does not address the evolution of arbitrariness. We propose a parallel theory of the emergence of the systematic re-use of arbitrary elements. Systematic compositionality emerges in novel, motivated signs and is maintained as the signs become arbitrary. We report a series of experiments that probe how the systematic re-use of arbitrary elements arises in novel communication systems. In Experiment 1, partners must create signs from scratch to communicate about items that share semantic features. The systematic re-use of arbitrary elements emerges. Further, the evolution of arbitrariness and systematic compositionality are parallel: even participants’ first drawings of items are systematically compositional, and this systematic compositionality is maintained as the signs become arbitrary. Experiment 2 demonstrates that naïve participants, who played no role in – indeed, did not even observe – the creation of the sign systems, can nonetheless detect the systematic compositionality in them and generalize from it. Experiment 3 shows that participants actually do make use of the systematic re-use of arbitrary elements that they observe in others’ sign systems, when faced with the task of communicating (rather than learning and reproducing). The systematic compositionality is not only maintained, but appears to be increasing, over generations of participants observing others’ signs. The increase in systematic compositionality occurs when pairs create signs for items they have not observed – presumably, as they generalize using the systematic compositionality they have observed. In sum, we present an alternative mechanism for the emergence of the systematic reuse of arbitrary elements: arbitrariness and systematic compositionality emerge in a parallel fashion within the dyad, and subsequent communicators maintain – or even increase – the structure they have observed. More generally, we demonstrate the importance of examining arbitrariness and systematic compositionality together.

This paper offers an alternative philosophy of whole number in which number-words are treated as being of the semantic-type modifier. Other accounts of number in which number-words are treated as names, syncategoremata, determiners, and predicates are considered and rejected based on their failure to provide number-words with the necessary compositional semantics. This leaves only modifiers as plausible candidates to play number-words' role in natural language. After the semantic-type modifier is chosen, a decision between number-words' being adjectival or adverbial modifiers must then be made. I argue that due to a lack of entities to be ascribed adjectival numerical properties we must settle on an adverbial treatment. After developing this treatment, I close with an attempt to explain seemingly singular-term uses of number-words in arithmetical statements like '2 + 2 = 4' in terms of these claims' stating the rules for substituting equivalent modifier-phrases in non-mathematical usages. / Master of Arts

The notion of ‘pattern’ originates in the work of Christopher Alexander and, in recent years, patterns have become a popular part of software development. A pattern is defined as a ‘three-part rule’: a relationship between a given context, a recurring system of forces peculiar to that context, and a specific spatial configuration that permits resolution of these forces. In essence, the ‘context’ of a pattern is the whole system under construction and its state in the construction process at the point at which the pattern is being applied. The nature of the context, therefore, changes at every step of the process and this has significant implications for how patterns should be used. Specifically, applying each pattern changes the context by changing the state of the system under construction and creates both a new design problem and a new context for the next pattern to be applied. The next picked pattern must have a certain criteria in order for it to be applied successfully and this is will be determined by the characteristics of the new context just created. The issue of composing pattern sequences is therefore more temporal than it is static and structural (as provided currently via pattern maps). The decision as to which one to use is temporally constrained in the sense that the choice is made only at a particular point in the construction process of some specific system, and may well be determined, or at least further constrained, by the current state of that system. The fundamental research question that is addressed here is: how is this dynamically changing context to be presented to guide pattern applications? In this thesis, a framework is presented to provide a systematic analysis of composition of pattern applications in terms of the properties of their context. Such an approach will reveal the ordering of patterns in space and time dimensions. Examples of composition of pattern applications include: - One pattern contains or generalises another smaller-scale pattern (this will be called in thesis refinement); - Two patterns are complementary, i.e., one pattern needs the other to be applied before (Sequential Order); - Two patterns solve different problems that overlap and coexist on the same level (Parallel Order); - Two patterns solve the same problem in alternative, but equally valid ways (Choice in Order). At the design phase, the framework provides mechanisms for analysing the choice of composition to ensure the correctness of a design or to compare between two different designs or to modify an existing design. This framework describes a pattern's context via a pair of constraints, known as Assumption and Commitment. In general, the Assumption is a constraint placed on the context and the Commitment is what the solution provided by the pattern commits to after the pattern's application. In addition, the thesis provides a set of composition rules that can be applied to aid in the analysis of the application of pattern sequences. The approach is domain independent as it does not depend on the nature of the catalogue from which the patterns originate. The work has been evaluated using various existing patterns from Ian Graham’s web usability (WU) pattern bank and the User Interface (UI) patterns of Welie.

No description available.

Thesis (Ph. D.)--Lund University, Dept. of Philosophy. / Includes bibliographical references (p. [263]-276) and index.

A remarkable thing about natural language is that we can use it to share our beliefs and thoughts about the world with other speakers of our language. In cases of successful communication, beliefs seem to be transferred from speakers to hearers by means of the hearer recovering the contents of the speaker’s utterances. This is so natural to us that we take it for granted in our everyday life, and rarely stop to think about how it's is possible. Nevertheless, it's a phenomenon that calls for explanation. It is natural to expect that natural language semantics has a key explanatory role to play here. In order to understand this role, we must relate the semantic values assigned to sentences by semantic theories with the contents of our speech acts. The simplest possible relation would be identity; the meaning of a sentence is simply the belief expressed by an assertion of the sentence in a given context of utterance. However, a number of problem cases in the literature suggest that this cannot be the case. This dissertation offers a critical assessment of the arguments for distinguishing the semantic value of a sentence from its so-called assertoric content, focusing on problems arising from the analysis of tense and temporal expressions. I conclude that they are indeed distinct, and offer a constructive account of how they must be related in order to allow for an explanation of communicative success.​

Sistemas de processamento de linguagem natural baseiam-se com frequência na hipótese de que a linguagem humana é composicional, ou seja, que o significado de uma entidade linguística pode ser inferido a partir do significado de suas partes. Essa expectativa falha no caso de expressões multipalavras (EMPs). Por exemplo, uma pessoa caracterizada como pão-duro não é literalmente um pão, e também não tem uma consistência molecular mais dura que a de outras pessoas. Técnicas computacionais modernas para inferir o significado das palavras com base na sua distribuição no texto vêm obtendo um considerável sucesso em múltiplas tarefas, especialmente após o surgimento de abordagens de word embeddings. No entanto, a representação de EMPs continua a ser um problema em aberto na área. Em particular, não existe um método consolidado que prediga, com base em corpora, se uma determinada EMP deveria ser tratada como unidade indivisível (por exemplo olho gordo) ou como alguma combinação do significado de suas partes (por exemplo tartaruga marinha). Esta tese propõe um modelo de predição de composicionalidade de EMPs com base em representações de semântica distribucional, que são instanciadas no contexto de uma variedade de parâmetros. Também é apresentada uma avaliação minuciosa do impacto desses parâmetros em três novos conjuntos de dados que modelam a composicionalidade de EMP, abrangendo EMPs em inglês, francês e português. Por fim, é apresentada uma avaliação extrínseca dos níveis previstos de composicionalidade de EMPs, através da tarefa de identificação de EMPs. Os resultados obtidos sugerem que a escolha adequada do modelo distribucional e de parâmetros de corpus pode produzir predições de composicionalidade que são comparáveis às observadas no estado da arte. / Natural language processing systems often rely on the idea that language is compositional, that is, the meaning of a linguistic entity can be inferred from the meaning of its parts. This expectation fails in the case of multiword expressions (MWEs). For example, a person who is a sitting duck is neither a duck nor necessarily sitting. Modern computational techniques for inferring word meaning based on the distribution of words in the text have been quite successful at multiple tasks, especially since the rise of word embedding approaches. However, the representation of MWEs still remains an open problem in the field. In particular, it is unclear how one could predict from corpora whether a given MWE should be treated as an indivisible unit (e.g. nut case) or as some combination of the meaning of its parts (e.g. engine room). This thesis proposes a framework of MWE compositionality prediction based on representations of distributional semantics, which we instantiate under a variety of parameters. We present a thorough evaluation of the impact of these parameters on three new datasets of MWE compositionality, encompassing English, French and Portuguese MWEs. Finally, we present an extrinsic evaluation of the predicted levels of MWE compositionality on the task of MWE identification. Our results suggest that the proper choice of distributional model and corpus parameters can produce compositionality predictions that are comparable to the state of the art.

In addition to individual learning mechanisms, the thesis further explores the effects of cultural transmission, social and semantic structures on language evolution. First, it simulates some major forms of cultural transmission, and discusses the role of conventionalization during horizontal transmission in language evolution. Second, it traces the emergence and maintenance of language in some stable social structures, and explores the role of popular agents in language evolution, the relationship between mutual understanding and social hierarchy, and the effect of exoteric communications on the convergence of communal languages. Finally, it studies language maintenance given different semantic spaces, and illustrates that the semantic structure may cause bias in the constituent word order, which can help to predict the word order bias in human languages. These explorations examine the role of self-organization in language evolution, provide some reconsideration on the bottleneck effect during cultural transmission, and shed light on the study of the social structure effects on language evolution. / The thesis presents a multi-agent computational model to explore a key question in language emergence, i.e., whether syntactic abilities result from innate, species-specific competences, or they evolve from domain-general abilities through gradual adaptations. The model simulates a process of coevolutionary emergence of two linguistic universals (compositionality, in the form of lexical items; and regularity, in the form of constitute word orders) in human language, i.e., the acquisition and conventionalization of these features coevolve during the transition from a holistic signaling system to a compositional language. It also traces a "bottom-up" process of syntactic development, i.e., agents, by reiterating local orders between two lexical items, can gradually form global order(s) to regulate multiple lexical items in sentences. These results suggest that compositionality, regularity, and correlated linguistic abilities could have emerged as a result of some domain-general abilities, such as pattern extraction and sequential learning. / Gong, Tao. / "May 2007." / Adviser: William S-Y. Wang. / Source: Dissertation Abstracts International, Volume: 69-01, Section: A, page: 0200. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (p. 317-346). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.

Thesis (M.A.)--University of North Texas, August, 2009. / Title from title page display. Includes bibliographical references.

Sistemas de processamento de linguagem natural baseiam-se com frequência na hipótese de que a linguagem humana é composicional, ou seja, que o significado de uma entidade linguística pode ser inferido a partir do significado de suas partes. Essa expectativa falha no caso de expressões multipalavras (EMPs). Por exemplo, uma pessoa caracterizada como pão-duro não é literalmente um pão, e também não tem uma consistência molecular mais dura que a de outras pessoas. Técnicas computacionais modernas para inferir o significado das palavras com base na sua distribuição no texto vêm obtendo um considerável sucesso em múltiplas tarefas, especialmente após o surgimento de abordagens de word embeddings. No entanto, a representação de EMPs continua a ser um problema em aberto na área. Em particular, não existe um método consolidado que prediga, com base em corpora, se uma determinada EMP deveria ser tratada como unidade indivisível (por exemplo olho gordo) ou como alguma combinação do significado de suas partes (por exemplo tartaruga marinha). Esta tese propõe um modelo de predição de composicionalidade de EMPs com base em representações de semântica distribucional, que são instanciadas no contexto de uma variedade de parâmetros. Também é apresentada uma avaliação minuciosa do impacto desses parâmetros em três novos conjuntos de dados que modelam a composicionalidade de EMP, abrangendo EMPs em inglês, francês e português. Por fim, é apresentada uma avaliação extrínseca dos níveis previstos de composicionalidade de EMPs, através da tarefa de identificação de EMPs. Os resultados obtidos sugerem que a escolha adequada do modelo distribucional e de parâmetros de corpus pode produzir predições de composicionalidade que são comparáveis às observadas no estado da arte. / Natural language processing systems often rely on the idea that language is compositional, that is, the meaning of a linguistic entity can be inferred from the meaning of its parts. This expectation fails in the case of multiword expressions (MWEs). For example, a person who is a sitting duck is neither a duck nor necessarily sitting. Modern computational techniques for inferring word meaning based on the distribution of words in the text have been quite successful at multiple tasks, especially since the rise of word embedding approaches. However, the representation of MWEs still remains an open problem in the field. In particular, it is unclear how one could predict from corpora whether a given MWE should be treated as an indivisible unit (e.g. nut case) or as some combination of the meaning of its parts (e.g. engine room). This thesis proposes a framework of MWE compositionality prediction based on representations of distributional semantics, which we instantiate under a variety of parameters. We present a thorough evaluation of the impact of these parameters on three new datasets of MWE compositionality, encompassing English, French and Portuguese MWEs. Finally, we present an extrinsic evaluation of the predicted levels of MWE compositionality on the task of MWE identification. Our results suggest that the proper choice of distributional model and corpus parameters can produce compositionality predictions that are comparable to the state of the art.