Ontology-Based Interpretation of Natural Language (Paperback)

For humans, understanding a natural language sentence or discourse is so effortless that we hardly ever think about it. For machines, however, the task of interpreting natural language, especially grasping meaning beyond the literal content, has proven extremely difficult and requires a large amount of background knowledge. This book focuses on the interpretation of natural language with respect to specific domain knowledge captured in ontologies. The main contribution is an approach that puts ontologies at the center of the interpretation process. This means that ontologies not only provide a formalization of domain knowledge necessary for interpretation but also support and guide the construction of meaning representations.

We start with an introduction to ontologies and demonstrate how linguistic information can be attached to them by means of the ontology lexicon model lemon. These lexica then serve as basis for the automatic generation of grammars, which we use to compositionally construct meaning representations that conform with the vocabulary of an underlying ontology. As a result, the level of representational granularity is not driven by language but by the semantic distinctions made in the underlying ontology and thus by distinctions that are relevant in the context of a particular domain. We highlight some of the challenges involved in the construction of ontology-based meaning representations, and show how ontologies can be exploited for ambiguity resolution and the interpretation of temporal expressions. Finally, we present a question answering system that combines all tools and techniques introduced throughout the book in a real-world application, and sketch how the presented approach can scale to larger, multi-domain scenarios in the context of the Semantic Web.

Table of Contents: List of Figures / Preface / Acknowledgments / Introduction / Ontologies / Linguistic Formalisms / Ontology Lexica / Grammar Generation / Putting Everything Together / Ontological Reasoning for Ambiguity Resolution / Temporal Interpretation / Ontology-Based Interpretation for Question Answering / Conclusion / Bibliography / Authors' Biographies

對於人類來說，理解自然語言的句子或篇章是如此輕鬆，以至於我們幾乎從不去思考它。然而，對於機器來說，解釋自然語言的任務，尤其是理解超越字面內容的意義，已被證明非常困難，需要大量的背景知識。本書專注於根據本體論中捕捉的特定領域知識來解釋自然語言。主要貢獻是一種將本體論置於解釋過程中心的方法。這意味著本體論不僅提供了解釋所需的領域知識的形式化，還支持並指導意義表示的構建。

我們首先介紹本體論，並演示如何通過本體論詞典模型lemon將語言信息附加到本體論中。然後，這些詞典作為自動生成語法的基礎，我們使用這些語法來組合構建符合底層本體論詞彙的意義表示。因此，表示的細粒度水平不是由語言驅動，而是由底層本體論中所做的語義區別以及在特定領域上相關的區別所決定。我們強調了在基於本體論的意義表示構建中涉及的一些挑戰，並展示了如何利用本體論來解決歧義和解釋時間表達式。最後，我們提出了一個問答系統，將本書中介紹的所有工具和技術結合在一個實際應用中，並概述了所提出的方法如何在語義網的更大、多領域場景中擴展。

目錄：圖表清單 / 前言 / 致謝 / 引言 / 本體論 / 語言形式 / 本體論詞典 / 語法生成 / 將一切結合在一起 / 基於本體論的歧義解決 / 時間解釋 / 基於本體論的問答解釋 / 結論 / 參考文獻 / 作者簡介