Elements in Semantics – serie

Addresses the role of structure in semantic analysis from the perspective of theories of meaning using rich theories of types. Also relates the theory of frames to these type theories as introducing, to some extent, similar structure into semantic analysis. The authors show how a structured approach is necessary to appropriately analyse phenomena in areas as diverse as lexical semantics and the semantics of attitudinal constructions referring to psychological states. In particular, these are: polysemy taken together with copredication, and attitudes such as belief and knowledge. The authors argue that the very same structure required to define a rich system of types enables them to adequately analyse both of these phenomena, thus revealing similarities in two otherwise apparently unrelated topics in semantics. They also argue that such theories facilitate a semantic theory oriented towards a psychological and contextually situated view of meaning. This title is also available as open access on Cambridge Core.

Computer programs are often factored into pure components - simple, total functions from inputs to outputs - and components that may have side effects - errors, changes to memory, parallel threads, abortion of the current loop, and so on. In this Element, the authors make the case that human languages are similarly organized around the give and pull of pure values and impure processes, and show how denotational techniques from computer science can be leveraged to support elegant and illuminating analyses of semantic composition in natural language.

This Element gives an introduction to the emerging discipline of natural language ontology. Natural language ontology is an area at the interface of semantics, metaphysics, and philosophy of language that is concerned with which kinds of objects are assumed by our best semantic theories. The Element reviews different strategies for identifying a language's ontological commitments. It observes that, while languages share a large number of their ontological commitments (such as to individuals, properties, events, and kinds), they differ in other commitments (for example, to degrees). The Element closes by relating different language and theory-specific ontologies, and by pointing out the merits and challenges of identifying inter-category relations within a single ontology.

This Element gives an introduction to the emerging discipline of natural language ontology. Natural language ontology is an area at the interface of semantics, metaphysics, and philosophy of language that is concerned with which kinds of objects are assumed by our best semantic theories. The Element reviews different strategies for identifying a language's ontological commitments. It observes that, while languages share a large number of their ontological commitments (such as to individuals, properties, events, and kinds), they differ in other commitments (for example, to degrees). The Element closes by relating different language and theory-specific ontologies, and by pointing out the merits and challenges of identifying inter-category relations within a single ontology.

This Element covers the interaction of two research areas: linguistic semantics and deep learning. It focuses on three phenomena central to natural language interpretation: reasoning and inference; compositionality; extralinguistic grounding. Representation of these phenomena in recent neural models is discussed, along with the quality of these representations and ways to evaluate them (datasets, tests, measures). The Element closes with suggestions on possible deeper interactions between theoretical semantics and language technology based on deep learning models.

This Element covers the interaction of two research areas: linguistic semantics and deep learning. It focuses on three phenomena central to natural language interpretation: reasoning and inference; compositionality; extralinguistic grounding. Representation of these phenomena in recent neural models is discussed, along with the quality of these representations and ways to evaluate them (datasets, tests, measures). The Element closes with suggestions on possible deeper interactions between theoretical semantics and language technology based on deep learning models.

Semantic theories for natural language assume many different kinds of objects, including (among many others) individuals, properties, events, degrees, and kinds. Formal type-theoretic semantics tames this 'zoo' of objects by assuming only a small number of ontologically primitive categories and by obtaining the objects of all other categories through constructions out of these primitives. This Element surveys arguments for this reduction of semantic categories. It compares the ontological commitments of different such reductions and establishes relations between competing foundational semantic ontologies. In doing so, it yields insights into the requirements on minimal semantic ontologies for natural language and the challenges for semantic ontology engineering.

Semantic theories for natural language assume many different kinds of objects, including (among many others) individuals, properties, events, degrees, and kinds. Formal type-theoretic semantics tames this 'zoo' of objects by assuming only a small number of ontologically primitive categories and by obtaining the objects of all other categories through constructions out of these primitives. This Element surveys arguments for this reduction of semantic categories. It compares the ontological commitments of different such reductions and establishes relations between competing foundational semantic ontologies. In doing so, it yields insights into the requirements on minimal semantic ontologies for natural language and the challenges for semantic ontology engineering.

Addresses the role of structure in semantic analysis from the perspective of theories of meaning using rich theories of types. Also relates the theory of frames to these type theories as introducing, to some extent, similar structure into semantic analysis. The authors show how a structured approach is necessary to appropriately analyse phenomena in areas as diverse as lexical semantics and the semantics of attitudinal constructions referring to psychological states. In particular, these are: polysemy taken together with copredication, and attitudes such as belief and knowledge. The authors argue that the very same structure required to define a rich system of types enables them to adequately analyse both of these phenomena, thus revealing similarities in two otherwise apparently unrelated topics in semantics. They also argue that such theories facilitate a semantic theory oriented towards a psychological and contextually situated view of meaning. This title is also available as open access on Cambridge Core.