Probing Semantic Relations
Exploration and identification in specialized texts
Semantic relations are at the core of any representational system, and are keys to enable the next generation of information processing systems with semantic and reasoning capabilities. Acquisition, description, and formalization of semantic relations are fundamentals in computer-based systems where natural language processing is required. Probing Semantic Relations provides a state of the art of current research trends in the area of knowledge extraction from text using linguistic patterns. First published as a Special Issue of Terminology 14:1 (2008), the current book emphasizes how definitional knowledge is conveyed by conceptual and semantic relations such as synonymy, causality, hypernymy (generic–specific), and meronymy (part–whole). Showing the difficulties and successes of pattern-based approaches, the book illustrates current and future challenges in knowledge acquisition from text. This book provides new perspectives to researchers and practitioners in terminology, knowledge engineering, natural language processing, and semantics.
Table of Contents
Pattern-based approaches to semantic relation extraction: A state-of-the-artAlain Auger and Caroline Barrière | pp. 1–18
Web-based extraction of semantic relation instances for terminology workJakob Halskov and Caroline Barrière | pp. 19–42
Designing and evaluating patterns for relation acquisition from texts with CaméléonNathalie Aussenac-Gilles and Marie-Paule Jacques | pp. 43–71
Definitional verbal patterns for semantic relation extractionGerardo Sierra, Rodrigo Alarcón, César Aguilar and Carme Bach | pp. 73–96
Patrones léxicos para la extracción de conceptos vinculados por la relación parte-todo en españolVictoria Soler and Amparo Alcina | pp. 97–120
Expressions of uncertainty in candidate knowledge-rich contexts: A comparison in English and French specialized textsElizabeth Marshman | pp. 121–148
Index | pp. 149–156
Cited by 1 other publications
This list is based on CrossRef data as of 6 september 2023. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.