This is the first study that empirically investigates preposition placement across all clause types. The study compares first-language (British English) and second-language (Kenyan English) data and will therefore appeal to readers interested in world Englishes. Over 100 authentic corpus examples are discussed in the text, which will appeal to those who want to see 'real data'
Date: Tue, 17 May 2005 13:50:43 +0200 From: Petra Gieselmann <firstname.lastname@example.org> Subject: Ontological Semantics
AUTHORS: Nirenburg, Sergei; Raskin, Victor TITLE: Ontological Semantics SERIES: Language, Speech, and Communication PUBLISHER: MIT Press YEAR: 2004
Petra Gieselmann, Interactive Systems Lab, University of Karlsruhe
DESCRIPTION / SUMMARY
This book aims to describe a comprehensive approach called ontological semantics to the treatment of text meaning by various NLP-applications, such as machine translation, information extraction, etc. Ontological semantics consists of an integrated complex of different theories and methodologies. It is built on microtheories covering such diverse areas as specific language phenomena, processing heuristics, and implementation system architecture. All these theories are coordinated at the level of knowledge acquisition and runtime system architecture implementation.
The book is divided in two parts: The first part describes ontological semantics and explains its main theoretical points in relation to other fields, such as cognitive science and the AI paradigm, the philosophy of science, linguistic semantics and the philosophy of language, computational lexical semantics, and studies in formal ontology. The second part deals with the content of ontological semantics. It discusses text-meaning representation, static knowledge sources, the processes involved in text analysis, and the acquisition of static knowledge.
Chapter 1 gives an introduction to ontological semantics. The approach is centered around the metaphor of an intelligent agent. Therefore, two intelligent agents are necessary at least: The discourse producer and the discourse consumer. The model consists of the following dynamic knowledge sources: an analyzer, a generator, and a module for world knowledge maintenance and reasoning. Furthermore, the static knowledge sources consist of an ontology, a fact repository, a lexicon, an onomasticon (a lexicon of proper names), a text-meaning representation formalism and some knowledge for semantic processing (structural mappings, knowledge supporting treatment of reference, etc.). Since a single comprehensive theory covering all these different aspects seems not feasible, the authors introduce the concept of microtheories which are bunched according to the phenomena they can deal with. In addition, the authors explain different architectures, such as the stratified model, the flat model and the constraint-satisfaction model; the latter being largely adopted in ontological semantics. Also the relations of ontological semantics to the non-semantic components of an NLP system and the development of ontological semantics over the last years are briefly outlined.
Chapter 2 is a very theoretical and philosophical description of ontological semantics compared to other theories. The first section explains the need for philosophical discussions in general and in the field of computational linguistics in particular. Then the authors give definitions for the main components in scientific theories, such as purview, premises, body, and justification. The conceptual space within which all linguistic semantic theories can be positioned is composed of diverse parameters. The authors also explain the relation between theories and methodologies associated with them. In addition, this chapter discusses practical applications of theories and their influence on relations between theories and methodologies. Finally, the authors describe how this philosophical approach can be used to characterize and analyze ontological semantics. Therefore, they concentrate on one example parameter: Explicitness.
Chapter 3 deals with the history of semantics and different philosophical and linguistic traditions. First, the chapter briefly describes the roots of linguistic semantics starting already with Plato. The authors explain the different semantic traditions covering also diachronic semantics and examinations on the historical meaning change. They explain different semantic approaches from Ogden, Richards and Bar Hillel up to contemporary approaches in detail. In addition, the chapter summarizes the ideas on compositional semantics and their influence on ontological semantics. The authors also discuss key ideas from other semantic traditions and evaluate them against ontological semantics.
Chapter 4, together with chapter 3, relates ontological semantics to other important semantic approaches and issues. Chapter 4 concentrates on lexical semantics and focusses on four central issues already raised in the lexical semantics of the late 80's to early 90's. First, the advantages and disadvantages of generative vs. enumerative lexicons are discussed and the authors explain why they think that every good lexicon, including ontological semantic ones, should be capable of accommodating novel meanings and therefore be generative. The next section discusses the complicated relationship between semantics and syntax and explains why the authors do not believe that there is a complete isomorphism between the two and that such a simplifying assumption cannot be hold in practice. Furthermore, the chapter discusses sentential meaning and the relation to the meaning of the words in detail. In ontological semantics, semantic meaning is defined as a text-meaning expression obtained through the application of rules for syntactic analysis, for linking syntactic and semantic dependencies and for establishing the meaning of lexical units. Therefore, a formal world model, namely the ontology, is crucial.
Chapter 5 discusses the differences between ontological semantics and other ontological efforts. The first section places ontology in the context of metaphysics. The authors discuss formal ontology and its contributions to ontological semantics as far as theoretical and also practical issues are concerned. As an example of practical issues the semantic web initiative is explained. The chapter explains the differences between ontology and natural language giving some examples of crosslinguistic semantic divergences which result in problems for multilingual ontologies.
Chapter 6 is the first chapter of the second part. It deals with meaning representation in ontological semantics. The first section discusses the problems of meaning proper and possible inferences. Then the authors explain the text meaning representation (TMR) giving different examples. The TMR includes the lexical information and the results of morphological and syntactic analysis of the input text. Therefore, the text meaning representation uses two basic means: instantiation of ontological concepts and instantiation of semantic parameters not connected to the ontology. The Backus Naur Form specifies the syntax of TMR which consists of a set of propositions connected through text-level discourse relations, such as modality, coreference, time dependencies and style. The propositions are units of semantic representation corresponding to single predications in context (typically realized as clauses). This means that the TMR results above all from the process of disambiguation by the analyzer. Therefore, ontological semantics uses semantic selectional restrictions stored in the lexicon and the ontology described in detail in chapter 8. The authors give different examples of TMR specifications. In addition, they discuss possibilities to represent synonyms and paraphrases in TMR.
Chapter 7 explains the different static knowledge sources, such as the ontology, the fact repository and the lexicons and their relations. The ontology consists of definitions of concepts representing classes of objects or events in the real world. It is language-independent and uses a collection of property-value pairs. Inheritance mechanisms are available and also multiple inheritance is allowed, although seldom used in real applications until now. Semantic properties describe the nature of objects and events in the ontology, such as physical properties, inherent properties, is-a-properties, and also properties specifying the semantic arguments (i.e. case roles for predicates). In addition, the ontology also contains complex events instantiated from the text input to provide expectations for further sentence processing in the text (similar to 'scripts' explained by Schank and Abelson 1977 for example.) Last but not least, an axiomatic definition of the ontology is given. The fact repository includes records of past experience. Therefore, you can find in the fact repository instances of ontological concepts. The lexicon contains a collection of entries indexed with their citation form in the languages available in the system. Every entry includes all the lexemes with the same base form, regardless of pronunciation, sense or syntactic information. Each entry contains information on the lexical category, the orthography, phonology, morphology, syntax, etc. In the onomasticon, proper nouns can be found.
Chapter 8 outlines the basic processing mechanisms in ontological semantic text analysis. The workflow consists of the following steps: Preprocessing, building semantic dependencies, processing meaning beyond basic semantic dependencies which includes the treatment of phenomena such as aspect, modality and time and finally processing at the suprapositional level. Thereby, processes at the suprapositional level consists of reference and coreference phenomena, temporal ordering within TMRs and discourse relations. The preprocessing is again divided into different phases: tokenization and morphological analysis, lexical lookup, syntactic analysis. After that, basic semantic dependencies are created based on a propositional structure which is established first by means of a basic selectional-restriction matching procedure. Sometimes, the basic selectional-restriction matching procedure cannot completely disambiguate the word senses of a given lexeme. In this case, the authors present different back-up strategies, such as dynamic tightening of selectional restrictions or comparing distances in ontological space. On the other hand, it is also possible that a selectional restriction fails to find any candidate for filling the value of property. The reasons for this case can be twofold: There is no recognizable candidate in the input which might be due to ellipsis or unexpected words or phrases in the input; on the other hand, the given lexeme is available in the lexicon, but has no sense which matches the selectional restriction which can be caused by non-literal language for example. Therefore, relaxation of selectional restrictions in the ontology is possible so that sentences such as 'The baby ate a piece of paper.' or non-literal meanings such as 'The pianist played Bach.' can be resolved. In addition, ontological semantics can also process unattested inputs (i.e. words or phrases which are not covered by the lexicons or onomasticons at the moment). Therefore, proper names are already discovered by a preprocessing component of the analyser. Other unattested input is processed by the available morphological, syntactic and semantic analyzers to assign as many features to it as possible given the fact that no lexicon entry is available. Out of that and by means of the semantic dependencies and the selectional restrictions of the other concepts in the input, a new lexicon entry can be generated on the fly.
Chapter 9 deals with the acquisition of static knowledge sources for ontological semantics. The authors explain the immense effort necessary to develop such natural language resources, both in time and in trained human resources. Therefore, automatic knowledge acquisition is desirable. The acquisition of the ontology involves the decisions, whether a new concept is necessary, where it should be integrated exactly and which properties are crucial for this concept. This cannot be done automatically at the moment, but requires trained people to work on this task. The lexicon can at least be acquired by some automatic support. Therefore, the authors explain the rapid propagation: A single sample entry for a whole class of lexical entries is used to copy most of its properties to the whole class with only slight changes (i.e. English adjectives of size can be rapidly propagated in this way.) In addition, ontological semantics uses lexical rules to derive the properties of some deverbal adjectives from their corresponding verbs for example, such as 'abhorrent' from 'abhor'. The authors stress the importance of the grain size of the lexicon and its practical effability. Furthermore, they discuss the relationship between ontological matching and lexical constrains. The fact repository can be semi-automatically acquired by means of information extraction techniques used on web pages.
Finally Chapter 10 gives a short conclusion and an outlook on future work areas.
"Ontological semantics" is an interesting and valuable contribution to the NLP community. It offers a clear outline of the theory of ontological semantics and explains the differences to other theories and traditions. Especially the first part of the book is very theoretical and might not be easy to read, especially for beginners in semantics. In my opinion, it would be interesting to see how this ontological semantics is used in some more practical examples, such as an MT application for example. The book only briefly mentions some examples, but a complete workflow is missing and would be interesting to get a general impression of the power of this approach. Another interesting application for ontological semantics might be dialogue processing which is only very briefly mentioned in this book. Furthermore, the acquisition of language resources is very expensive in time and human resources as already mentioned by the authors. Still they did not explain any completely automatic methods for acquiring them, but only some tools to facilitate the whole process for the linguist a little bit. It might be interesting to see what other methods could fit here into the theory of ontological semantics to gain an easier acquisition of new resources and save time and money for new applications.
Raskin, V. and S. Nirenburg. 1996. Adjectival Modification in Text Meaning Representation. Proceedings of COLING 96. 842-847
Schank, R. and R. Abelson. 1977. Scripts, Plans, Goals and Understanding. Hillsdale. NJ: Erlbaum.
Searle, J. (1969) Speech Acts: An Essay in the Philosophy of Language. Cambridge: Cambridge University Press.
ABOUT THE REVIEWER:
ABOUT THE REVIEWER
Petra Gieselmann has a M.A. in Computational Linguistics. Currently, she works at the university of Karlsruhe in the Interacitve Systems Lab towards her PhD. Her research interest lies in the field of dialogue management and speech understanding. She is especially interested in semantics and pragmatics in dialogue systems and error recovery by means of resolution of anaphora and elliptical expressions.