A New Semantic Theory of Natural Language

Formal Semantics and Distributional Semantics are two important semantic frameworks in Natural Language Processing (NLP). Cognitive Semantics belongs to the movement of Cognitive Linguistics, which is based on contemporary cognitive science. Each framework could deal with some meaning phenomena, but none of them fulfills all requirements proposed by applications. A unified semantic theory characterizing all important language phenomena has both theoretical and practical significance; however, although many attempts have been made in recent years, no existing theory has achieved this goal yet. This article introduces a new semantic theory that has the potential to characterize most of the important meaning phenomena of natural language and to fulfill most of the necessary requirements for philosophical analysis and for NLP applications. The theory is based on a unified representation of information, and constructs a kind of mathematical model called cognitive model to interpret natural language expressions in a compositional manner. It accepts the empirical assumption of Cognitive Semantics, and overcomes most shortcomings of Formal Semantics and of Distributional Semantics. The theory, however, is not a simple combination of existing theories, but an extensive generalization of classic logic and Formal Semantics. It inherits nearly all advantages of Formal Semantics, and also provides descriptive contents for objects and events as fine-gram as possible, descriptive contents which represent the results of human cognition

On Yao's method of translation

Machine Translation, i.e., translating one kind of natural language to another kind of natural language by using a computer system, is a very important research branch in Artificial Intelligence. Yao developed a method of translation that he called ``Lexical-Semantic Driven". In his system he introduced 49 ``relation types" including case relations, event relations, semantic relations, and complex relations. The knowledge graph method is a new kind of method to represent an interlingua between natural languages. In this paper, we will give a comparison of these two methods. We will translate one Chinese sentence cited in Yao�s book by using these two methods. Finally, we will use the relations in knowledge graph theory to represent the ``relations" in Lexical-Semantic Driven, and partition the relations in Lexical-Semantic Driven into groups according to the relations in knowledge graph theory

The Mapping Of Action Verbs In The Teaching Of English For Food Production

This study is focused on the procedure of verbs' translation in English (source language) into Indonesian language (target language), and how the mapping of action verb meanings in the procedural text. The research uses qualitative method, employing a cooking book recipe “Step by Step Cooking Balinese Delightful for Everyday” as its data source and its Indonesian translation. The theory used in this research is the theory of Vinay and Darbelnet (in Venuti, 2000) about translation procedures that include borrowing, calque, literal translation, transposition, modulation, equivalence, and adaptation. The theory of applying the natural semantic metalanguage approach (NSM) proposed by Wierzbicka (1996) is used to discuss the mapping of English action verbs. The theory is applied in order to explain how the Indonesian action verb meanings are mapped into English, with the exponential mapping technique. The description of the mapping meanings including the exponential mapping to the action verb of the Indonesian language has produced a new dimension. This new dimension turns out to be able to explore the meaning of the lexical item including the one that has even a subtle difference, therefore there is no more swirling of meaning. Keywords: translation procedure, action verb, mapping of meanin

Genitive quantifiers in Japanese as reverse partitives

Quantificational determiners in Japanese can be marked with genitive case. Current analyses (for example by Watanabe, Natural Language and Linguistic Theory, to appear) treat the genetive case marker in these cases as semantically vacuous, but we show that it has semantic effects. We propose a new analysis as reverse partitives. Following Jackendoff (MIT-Press, 1977), we assume that partitives always contain two NPs one of which is phonologically deleted. We claim that, while in normal partitives the higher noun is deleted, in reverse partitives the lower noun is deleted

THE MAPPING OF MOVEMENT VERBS FOUND IN THE GOOD EARTH

This study aimed at focussing the translation of movement verbs in The Good Earth written by Pearl S. Buck. The Natural Semantic Metalanguage (NSM) is applied in translation process. The novel The Good Earth was chosen as data source because it has two texts which have different language types. This study has the purpose to describe the application of translation procedures that is proposed by Vinay and Darlbener and it is applied to examine the mapping of Action Verbs by the NSM (Natural Semantic Metalanguage) theory. The analysis was shown as the mapping between Indonesian and English action verbs which was presented into the subtype of the verbs based on the classification. This study attempts to apply that theory in solving the problem of the different language.  Semantic mapping (SM) is a method in statistics for dimensionality reduction that can be used in a set of multidimensional vectors of features to extract a few new features that preserves the main data characteristics. Translation is very important in various areas which are used to translate from one language into another language. However, it is not all the references written in Indonesian as they are coming from different countries and use different languages.  

Designing Statistical Language Learners: Experiments on Noun Compounds

The goal of this thesis is to advance the exploration of the statistical language learning design space. In pursuit of that goal, the thesis makes two main theoretical contributions: (i) it identifies a new class of designs by specifying an architecture for natural language analysis in which probabilities are given to semantic forms rather than to more superficial linguistic elements; and (ii) it explores the development of a mathematical theory to predict the expected accuracy of statistical language learning systems in terms of the volume of data used to train them. The theoretical work is illustrated by applying statistical language learning designs to the analysis of noun compounds. Both syntactic and semantic analysis of noun compounds are attempted using the proposed architecture. Empirical comparisons demonstrate that the proposed syntactic model is significantly better than those previously suggested, approaching the performance of human judges on the same task, and that the proposed semantic model, the first statistical approach to this problem, exhibits significantly better accuracy than the baseline strategy. These results suggest that the new class of designs identified is a promising one. The experiments also serve to highlight the need for a widely applicable theory of data requirements.Comment: PhD thesis (Macquarie University, Sydney; December 1995), LaTeX source, xii+214 page

Cooperative answers in database systems

A major concern of researchers who seek to improve human-computer communication involves how to move beyond literal interpretations of queries to a level of responsiveness that takes the user's misconceptions, expectations, desires, and interests into consideration. At Maryland, we are investigating how to better meet a user's needs within the framework of the cooperative answering system of Gal and Minker. We have been exploring how to use semantic information about the database to formulate coherent and informative answers. The work has two main thrusts: (1) the construction of a logic formula which embodies the content of a cooperative answer; and (2) the presentation of the logic formula to the user in a natural language form. The information that is available in a deductive database system for building cooperative answers includes integrity constraints, user constraints, the search tree for answers to the query, and false presuppositions that are present in the query. The basic cooperative answering theory of Gal and Minker forms the foundation of a cooperative answering system that integrates the new construction and presentation methods. This paper provides an overview of the cooperative answering strategies used in the CARMIN cooperative answering system, an ongoing research effort at Maryland. Section 2 gives some useful background definitions. Section 3 describes techniques for collecting cooperative logical formulae. Section 4 discusses which natural language generation techniques are useful for presenting the logic formula in natural language text. Section 5 presents a diagram of the system

The SP theory of intelligence: benefits and applications

This article describes existing and expected benefits of the "SP theory of intelligence", and some potential applications. The theory aims to simplify and integrate ideas across artificial intelligence, mainstream computing, and human perception and cognition, with information compression as a unifying theme. It combines conceptual simplicity with descriptive and explanatory power across several areas of computing and cognition. In the "SP machine" -- an expression of the SP theory which is currently realized in the form of a computer model -- there is potential for an overall simplification of computing systems, including software. The SP theory promises deeper insights and better solutions in several areas of application including, most notably, unsupervised learning, natural language processing, autonomous robots, computer vision, intelligent databases, software engineering, information compression, medical diagnosis and big data. There is also potential in areas such as the semantic web, bioinformatics, structuring of documents, the detection of computer viruses, data fusion, new kinds of computer, and the development of scientific theories. The theory promises seamless integration of structures and functions within and between different areas of application. The potential value, worldwide, of these benefits and applications is at least $190 billion each year. Further development would be facilitated by the creation of a high-parallel, open-source version of the SP machine, available to researchers everywhere.Comment: arXiv admin note: substantial text overlap with arXiv:1212.022

The Semantic Annotation of the Quran Corpus Based on Hierarchical Network of Concepts Theory

This Quran as the central religious text of Islam is widely regarded as the finest work in classical Arabic literature and plays an important role in Islam world. This paper studied and analyzed the Quran Chinese and English data, built the Quran Chinese and English words semantic knowledge base in which the grammar and semantic information of the Quranic words were described based on HNC theory, built the Quran semantic annotation corpus in which the part of speech and semantic description were annotated. The corpus with semantic annotation can help us identify the same meaning with different word forms. This paper proposed a new method of semantic analysis to solve the semantic similarity problem of natural language processing, which will benefit both the research on the semantic analysis in Natural Language Processing and the development of the Islamic Cultures

Spanish Resource Grammar version 2023

We present the latest version of the Spanish Resource Grammar (SRG). The new SRG uses the recent version of Freeling morphological analyzer and tagger and is accompanied by a manually verified treebank and a list of documented issues. We also present the grammar's coverage and overgeneration on a small portion of a learner corpus, an entirely new research line with respect to the SRG. The grammar can be used for linguistic research, such as for empirically driven development of syntactic theory, and in natural language processing applications such as computer-assisted language learning. Finally, as the treebanks grow, they can be used for training high-quality semantic parsers and other systems which may benefit from precise and detailed semantics.Comment: 10 pages, 4 figure