scholarly journals A FRAMEWORK FOR STRUCTURED KNOWLEDGE EXTRACTION AND REPRESENTATION FROM NATURAL LANGUAGE THROUGH DEEP SENTENCE ANALYSIS

2011 ◽  
Keyword(s):  
Natural Language ◽  
Knowledge Extraction ◽  
Structured Knowledge

scholarly journals Legal Knowledge Extraction for Knowledge Graph Based Question-Answering

2020 ◽  
Author(s):  
Francesco Sovrano ◽  
Monica Palmirani ◽  
Fabio Vitali
Keyword(s):  
Natural Language ◽  
Language Processing ◽  
Design Patterns ◽  
Question Answering ◽  
Knowledge Extraction ◽  
Knowledge Graph ◽  
Legal Knowledge ◽  
Legal Information ◽  
Event Time ◽  
Legal Domain

This paper presents the Open Knowledge Extraction (OKE) tools combined with natural language analysis of the sentence in order to enrich the semantic of the legal knowledge extracted from legal text. In particular the use case is on international private law with specific regard to the Rome I Regulation EC 593/2008, Rome II Regulation EC 864/2007, and Brussels I bis Regulation EU 1215/2012. A Knowledge Graph (KG) is built using OKE and Natural Language Processing (NLP) methods jointly with the main ontology design patterns defined for the legal domain (e.g., event, time, role, agent, right, obligations, jurisdiction). Using critical questions, underlined by legal experts in the domain, we have built a question answering tool capable to support the information retrieval and to answer to these queries. The system should help the legal expert to retrieve the relevant legal information connected with topics, concepts, entities, normative references in order to integrate his/her searching activities.

scholarly journals Finding Answers to Questions, in Text Collections or Web, in Open Domain or Specialty Domains

2012 ◽  
pp. 344-370
Author(s):  
Brigitte Grau
Keyword(s):  
Natural Language ◽  
Information Management ◽  
Question Answering ◽  
Target Language ◽  
Open Domain ◽  
Text Collections ◽  
Factual Question ◽  
Structured Knowledge ◽  
Answering Questions ◽  
The Web

This chapter is dedicated to factual question answering, i.e., extracting precise and exact answers to question given in natural language from texts. A question in natural language gives more information than a bag of word query (i.e., a query made of a list of words), and provides clues for finding precise answers. The author first focuses on the presentation of the underlying problems mainly due to the existence of linguistic variations between questions and their answerable pieces of texts for selecting relevant passages and extracting reliable answers. The author first presents how to answer factual question in open domain. The author also presents answering questions in specialty domain as it requires dealing with semi-structured knowledge and specialized terminologies, and can lead to different applications, as information management in corporations for example. Searching answers on the Web constitutes another application frame and introduces specificities linked to Web redundancy or collaborative usage. Besides, the Web is also multilingual, and a challenging problem consists in searching answers in target language documents other than the source language of the question. For all these topics, this chapter presents main approaches and the remaining problems.

Chinese Natural Language Oriented Dynamic Knowledge Extraction: A Case Study of Intelligent Design

2001 ◽  
Author(s):  
Renbin Xiao ◽  
Ming Chang ◽  
Hongbin Zhan ◽  
Mu Su
Keyword(s):  
Natural Language ◽  
Intelligent Systems ◽  
Intelligent Design ◽  
Knowledge Extraction ◽  
Prototype System ◽  
Practical Case ◽  
Natural Language Text ◽  
Sentence Clustering

Abstract In view of the existed problems of knowledge acquisition in intelligent systems, a dynamic knowledge extraction method based on Chinese natural language sentence-clustering is put forward, and the corresponding software prototype system is implemented. First of all, the proposed method is introduced in the paper by the way to give its outline. In order to demonstrate an important role of the proposed method, we make a complete case study via the intelligent design of certain machine tool. The design background of such a product is presented and the implementation steps is given in detail to show the whole design process. Through the practical case, we have succeeded in extracting knowledge from natural language text and the effectiveness of the proposed method is verified.

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