tailieunhanh - Báo cáo khoa học: "An Integrated Architecture for Shallow and Deep Processing"

We present an architecture for the integration of shallow and deep NLP components which is aimed at flexible combination of different language technologies for a range of practical current and future applications. In particular, we describe the integration of a high-level HPSG parsing system with different high-performance shallow components, ranging from named entity recognition to chunk parsing and shallow clause recognition. The NLP components enrich a representation of natural language text with layers of new XML meta-information using a single shared data structure, called the text chart. . | An Integrated Architecture for Shallow and Deep Processing Berthold Crysmann Anette Frank Bernd Kiefer Stefan Miiller Giinter Neumann Jakub Piskorski Ulrich Schafer Melanie Siegel Hans Uszkoreit Feiyu Xu Markus Becker and Hans-Ulrich Krieger DFKI GmbH Stuhlsatzenhausweg 3 Saarbrucken Germany whiteboard@ Abstract We present an architecture for the integration of shallow and deep NLP components which is aimed at flexible combination of different language technologies for a range of practical current and future applications. In particular we describe the integration of a high-level HPSG parsing system with different high-performance shallow components ranging from named entity recognition to chunk parsing and shallow clause recognition. The NLP components enrich a representation of natural language text with layers of new XML meta-information using a single shared data structure called the text chart. We describe details of the integration methods and show how information extraction and language checking applications for real-world German text benefit from a deep grammatical analysis. 1 Introduction Over the last ten years or so the trend in application-oriented natural language processing . in the area of term information and answer extraction has been to argue that for many purposes shallow natural language processing SNLP of texts can provide sufficient information for highly accurate and useful tasks to be carried out. Since the emergence of shallow techniques and the proof of their utility the focus has been to exploit these technolo gies to the maximum often ignoring certain complex issues . those which are typically well handled by deep NLP systems. Up to now deep natural language processing DNLP has not played a significant role in the area of industrial NLP applications since this technology often suffers from insufficient robustness and throughput when confronted with large quantities of unrestricted text. Current information extractions IE .

• Báo cáo khoa học
• An Integrated Architecture for Shallow
• Deep Processing
• Berthold Crysmann
• báo cáo khoa học
• mô hình ngôn ngữ
• xử lý ngôn ngữ tự nhiên
• Bài giảng Xử lý ngôn ngữ tự nhiên
• Ngôn ngữ tự nhiên
• Kỹ thuật lập trình
• Xử lý nhập nhằng ngữ nghĩa
• Xử lý ngữ nghĩa
• Xử lý ngôn ngữ
• Natural Language Processing
• Ngôn ngữ lập trình
• Nhập nhằng cấu trúc
• Tri thức về ngôn ngữ
• Mô hình n gram
• Dịch máy
• Phương pháp dịch máy
• Hiểu ngôn ngữ
• Phân tích ngữ nghĩa
• Phân loại tin tự động
• Biểu diễn vị từ
• Thuộc tính về sự kiện
• Thuộc tính về sự kiện
• Mô hình ngôn ngữ Google Book N grams
• Mô hình ngôn ngữ KenLM
• Phương pháp làm mịn
• Tách từ tiếng Việt
• Gán nhãn từ loại
• Phân tích cú pháp
• Nghĩa từ vựng
• Phân giải nhập nhằng từ
• Phân loại văn bản
• Lexical chain
• Phản hồi thông tin
• Bài toán PTCP
• Cấu trúc ngữ pháp
• Phân tích cú pháp xác suất
• CKY kết hợp xác suất
• Văn phạm phi ngữ cảnh xác suất
• Hình thái học