{"title":"A Question Answering System Supported by Information Extraction","authors":"R. Srihari, W. Li","doi":"10.3115/974147.974170","DOIUrl":"https://doi.org/10.3115/974147.974170","url":null,"abstract":"This paper discusses an information extraction (IE) system, Textract, in natural language (NL) question answering (QA) and examines the role of IE in QA application. It shows: (i) Named Entity tagging is an important component for QA, (ii) an NL shallow parser provides a structural basis for questions, and (iii) high-level domain independent IE can result in a QA breakthrough.","PeriodicalId":103133,"journal":{"name":"Applied Natural Language Processing Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128961602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Domain-Specific Knowledge Acquisition from Text","authors":"D. Moldovan, Roxana Girju, V. Rus","doi":"10.3115/974147.974184","DOIUrl":"https://doi.org/10.3115/974147.974184","url":null,"abstract":"In many knowledge intensive applications, it is necessary to have extensive domain-specific knowledge in addition to general-purpose knowledge bases. This paper presents a methodology for discovering domain-specific concepts and relationships in an attempt to extend WordNet. The method was tested on five seed concepts selected from the financial domain: interest rate, stock market, inflation, economic growth, and employment.","PeriodicalId":103133,"journal":{"name":"Applied Natural Language Processing Conference","volume":"284 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121331152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Talk'N'Travel: A Conversational System For Air Travel Planning","authors":"D. Stallard","doi":"10.3115/974147.974157","DOIUrl":"https://doi.org/10.3115/974147.974157","url":null,"abstract":"We describe Talk'n'Travel, a spoken dialogue language system for making air travel plans over the telephone. Talk'n'Travel is a fully conversational, mixed-initiative system that allows the user to specify the constraints on his travel plan in arbitrary order, ask questions, etc., in general spoken English. The system operates according to a plan-based agenda mechanism, rather than a finite state network, and attempts to negotiate with the user when not all of his constraints can be met.","PeriodicalId":103133,"journal":{"name":"Applied Natural Language Processing Conference","volume":"67 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120899403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Aggressive Morphology for Robust Lexical Coverage","authors":"W. Woods","doi":"10.3115/974147.974177","DOIUrl":"https://doi.org/10.3115/974147.974177","url":null,"abstract":"This paper describes an approach to providing lexical information for natural language processing in unrestricted domains. A system of approximately 1200 morphological rules is used to extend a core lexicon of 39, 000 words to provide lexical coverage that exceeds that of a lexicon of 80, 000 words or 150, 000 word forms. The morphological system is described, and lexical coverage is evaluated for random words chosen from a previously unanalyzed corpus.","PeriodicalId":103133,"journal":{"name":"Applied Natural Language Processing Conference","volume":"258 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121896551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Plan-Based Dialogue Management in a Physics Tutor","authors":"Reva Freedman","doi":"10.3115/974147.974155","DOIUrl":"https://doi.org/10.3115/974147.974155","url":null,"abstract":"This paper describes an application of APE (the Atlas Planning Engine), an integrated planning and execution system at the heart of the Atlas dialogue management system. APE controls a mixed-initiative dialogue between a human user and a host system, where turns in the 'conversation' may include graphical actions and/or written text. APE has full unification and can handle arbitrarily nested discourse constructs, making it more powerful than dialogue managers based on finitestate machines. We illustrate this work by describing Atlas-Andes, an intelligent tutoring system built using APE with the Andes physics tutor as the host.","PeriodicalId":103133,"journal":{"name":"Applied Natural Language Processing Conference","volume":"282 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120987019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Javox: A Toolkit for Building Speech-Enabled Applications","authors":"Michael S. Fulkerson, A. Biermann","doi":"10.3115/974147.974162","DOIUrl":"https://doi.org/10.3115/974147.974162","url":null,"abstract":"JAVOX provides a mechanism for the development of spoken-language systems from existing desktop applications. We present an architecture that allows existing Java1 programs to be speech-enabled with no source-code modification, through the use of reflection and automatic modification to the application's compiled code. The grammars used in JAVOX are based on the Java Speech Grammar Format (JSGF); JAVOX grammars have an additional semantic component based on our JAVOX Scripting Language (JSL). JAVOX has been successfully demonstrated on real-world applications.","PeriodicalId":103133,"journal":{"name":"Applied Natural Language Processing Conference","volume":"566 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116533001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Experiments with Corpus-based LFG Specialization","authors":"Nicola Cancedda, C. Samuelsson","doi":"10.3115/974147.974175","DOIUrl":"https://doi.org/10.3115/974147.974175","url":null,"abstract":"Sophisticated grammar formalisms, such as LFG, allow concisely capturing complex linguistic phenomena. The powerful operators provided by such formalisms can however introduce spurious ambiguity, making parsing inefficient. A simple form of corpus-based grammar pruning is evaluated experimentally on two wide-coverage grammars, one English and one French. Speedups of up to a factor 6 were obtained, at a cost in grammatical coverage of about 13%. A two-stage architecture allows achieving significant speedups without introducing additional parse failures.","PeriodicalId":103133,"journal":{"name":"Applied Natural Language Processing Conference","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125892549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Answer Extraction","authors":"Steven P. Abney, Michael Collins, A. Singhal","doi":"10.3115/974147.974188","DOIUrl":"https://doi.org/10.3115/974147.974188","url":null,"abstract":"Information retrieval systems have typically concentrated on retrieving a set of documents which are relevant to a user's query. This paper describes a system that attempts to retrieve a much smaller section of text, namely, a direct answer to a user's question. The SMART IR system is used to extract a ranked set of passages that are relevant to the query. Entities are extracted from these passages as potential answers to the question, and ranked for plausibility according to how well their type matches the query, and according to their frequency and position in the passages. The system was evaluated at the TREC-8 question answering track: we give results and error analysis on these queries.","PeriodicalId":103133,"journal":{"name":"Applied Natural Language Processing Conference","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115937747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Ranking suspected answers to natural language questions using predictive annotation","authors":"Dragomir R. Radev, J. Prager, Valerie Samn","doi":"10.3115/974147.974168","DOIUrl":"https://doi.org/10.3115/974147.974168","url":null,"abstract":"In this paper, we describe a system to rank suspected answers to natural language questions. We process both corpus and query using a new technique, predictive annotation, which augments phrases in texts with labels anticipating their being targets of certain kinds of questions. Given a natural language question, our IR system returns a set of matching passages, which we then rank using a linear function of seven predictor variables. We provide an evaluation of the techniques based on results from the TREC Q&A evaluation in which our system participated.","PeriodicalId":103133,"journal":{"name":"Applied Natural Language Processing Conference","volume":"287 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122400652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Automatic construction of parallel English-Chinese corpus for cross-language information retrieval","authors":"Jiang Chen, Jian-Yun Nie","doi":"10.3115/974147.974151","DOIUrl":"https://doi.org/10.3115/974147.974151","url":null,"abstract":"A major obstacle to the construction of a probabilistic translation model is the lack of large parallel corpora. In this paper we first describe a parallel text mining system that finds parallel texts automatically on the Web. The generated Chinese-English parallel corpus is used to train a probabilistic translation model which translates queries for Chinese-English cross-language information retrieval (CLIR). We will discuss some problems in translation model training and show the preliminary CLIR results.","PeriodicalId":103133,"journal":{"name":"Applied Natural Language Processing Conference","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126879773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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