The modern computational lexical semantics reached a point in its development when it has become necessary to define the premises and goals of each of its several trends. This paper proposes ten choices in terms of which these premises and goals can be discussed. It is argued that the central questions include the use of lexical rules for generating word senses; the role of syntax, pragmatics, and formal semantics in the specification of lexical meaning; the use of a world model, or ontology, as the organizing principle for lexical-semantic descriptions; the use of rules with limited scope; the relation between static and dynamic resources; the commitment to descriptive coverage; the trade-off between generalization and idiosyncracy; and, finally, the adherence to the "supply-side" (method-oriented) or "demand-side" (task-oriented) ideology of research. The discussion is inspired by, but not limited to, the comparison between the generative lexicon approach and the ontologi...

We present an approach to automatic classification of adjectives in German with respect to a range functional categories. The approach makes use of the grammatical evidence that (i) the functional category of an adjectival modifier determines its relative ordering in an NP, and (ii) only modifiers that belong to the same category may appear together in a coordination. The coordination context algorithm is discussed in detail. Experiments carried out with this algorithm are described and an evaluation of the experiments is presented.

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Adjectives constitute a challenging issue for NLP applications. From a syntactic viewpoint, they can be predicative or attributive. From a semantic viewpoint, their sense can vary depending on the context in which they appear. In this paper we present an overview on the lexical semantics of adjectives in Natural Language Processing, followed by the presentation of the papers included in this proceeding.

The fact that human readers can learn about the physical world from textual descriptions leads to a number of interesting questions about the connections between our conceptual understanding of the physical world and how it is reflected in natural language. This thesis investigates some forms in which information about physical phenomena is typically expressed in natural language and how this knowledge can be used to construct models of the underlying physical processes. Based on an analysis of the representations of physical quantities in natural language and common, reoccurring syntactic patterns, we implemented a system that uses Qualitative Process (QP) Theory to guide the semantic interpretation process to capture information about physical phenomena found in natural language text. We have recast QP Theory in terms of frame semantics as FrameNet-compatible representations (QP frames) and use an extendable, controlled subset of English to capture QP specific information from natural language descriptions. In addition to general background knowledge based on a subset of the Cyc knowledge base and the lexical information supplied by a syntactic parser, the semantics of QP Theory are used in rules that guide the semantic interpretation process and the construction of QP Frames. The thesis illustrates that QP Theory, as an established theoretical framework for handling continuous parameters and causation, can provide an essential component of

In this paper, we propose a fine grained classification of english adjectives geared at modeling the distinct inference patterns licensed by each adjective class. We show how it can be implemented in description logic and illustrate the predictions made by a series of examples. The proposal has been implemented using Description logic as a semantic representation language and the prediction verified using the DL theorem prover RACER.

In this report, we present the automatic acquisition of a lexicon involving the use of morphosemantic lexical rules on a core lexicon which was acquired semi-automatically. The process of large-scale dictionary making, as we de ned it to build Spanlex, a Spanish lexicon, for Mikrokosmos, amachine translation (MT) system based on semantics, is at the centre of this report. Our aim in this one-year project has been to acquire a lexicon of about 35,000 word meanings within a computational semantics approach. This implied to automate the task of acquisition as much as possible by developing and implementing tools to help and guide acquisition. Using this approach, we acquired one- fth of Spanlex. The other four- fths were acquired entirely automatically. This paper focuses on the way we acquired this large-scale high quality lexicon by using derivational morpho-semantic rules. In particular, we deal with the discovery, representation, and use of morphosemantic lexical rules (MSLRs) for the automatic acquisition of a large-scale computational lexicon. The analysis is based on a set of MSLRs implemented and tested on the basis of Spanish businessand nance-related corpora. First, we provide the reader with the methodology to build a computational lexicon in the Ecology of Acquisition � second, we present the MSLRs which helped automate the process of acquisition in From Submit to Submitted via Submission: On Lexical

This thesis discusses the automatic acquisition of conceptual distinctions using empirical methods, with an emphasis on semantic relations. The goal is to improve semantic lexicons for computational linguistics, but the work can be applied to general-purpose knowledge bases as well.

As shown in the formal semantics literature, adjectives can display very different inferential patterns depending on whether they are intersective, privative, subsective or plain non-subsective. Moreover, many of these classes are often described using second order constructs. In this paper, we adopt Hobbs’s ontologically promiscuous approach and present a first order treatment of adjective semantics which opens the way for a sophisticated treatment of adjectival inference. The approach was implemented and tested using first order automated reasoners. 1

Introduction Our approach to the lexicon has been driven by both theoretical and practical concerns. From a theoretical viewpoint, we are interested in capturing the core meanings of texts. We believe that lexical semantics is a crucial knowledge component of text meaning derivation, as it describes lexical meanings in their composition and combination 1 properties. A major tenet of our methodology is a separation of what is language-dependent and what is universal in semantic speci#cations. To help in determining this, our research methodology centrally includes a cross-linguistic perspective. From a practical standpoint, our lexicons are designed to support machine translation #MT# systems, in which the issue of multilinguality is clearly central. Theoretical and practical concerns are combined into the Mikrokosmos # #K # approach, where, within the paradigm of knowledge-based machine translation #KBMT#, we build lexicons for di#erent natural l