%0 %0 Book Section %A Waldinger, Richard; Appelt, Douglas E.; Fry, John; Israel, David J.; Jarvis, Peter; Martin, David; Riehemann, Susanne; Stickel, MArk E.; Tyson, Mabry; Hobbs, Jerry & Dungan, Jennifer L. %D 2004 %T Deductive Question Answering from Multiple Resources %E Maybury, Mark %B New Directions in Question Answering %C Menlo Park, CA %I AAAI %V %6 %N %P %& 20 %Y %S %7 %8 %9 %? %! %Z %@ %( %) %* %L %M %1 %2 %3 incollection %4 %# %$ %F Waldinger:2004 %K question_answering flat_semantics %X Questions in natural language are answered by consulting multiple sources and inferring answers from information they provide. An automated deduction system, equipped with an axiomatic application-domain theory, serves as the coordinator for the process. Sources include data bases, Web pages, programs, and unstructured text. Answers may contain text or visualizations. Although the approach is domain-independent, many of our experiments have dealt with geographic questions. %Z %U http://www.ai.sri.com/pubs/full.php?id=986 %+ %^ %0 %0 Conference Proceedings %A Moll\'a,, Diego %D 2001 %T Ontologically Promiscuous Flat Logical Forms for NLP %E Bunt, Harry; van der Sluis, Ielka & Thijsse, Elias %B Proceedings of IWCS-4 %C %I %V %6 %N %P 249-265 %& %Y Tilburg University %S %7 %8 %9 %? %! %Z %@ %( %) %* %L %M %1 %2 %3 inproceedings %4 %# %$ %F Molla:IWCS4 %K flat_semantics molla_publication %X %Z %U %+ %^ %0 %0 Conference Proceedings %A Moll\'a,, Diego %D 2001 %T Towards Incremental Semantic Annotation %E %B Proc. First International Workshop on Multimedia Annotation (MMA-2001) %C Tokyo %I %V %6 %N %P %& %Y %S %7 %8 %9 %? %! %Z %@ %( %) %* %L %M %1 %2 %3 inproceedings %4 %# %$ %F Molla:MMA2001 %K flat_semantics molla_publication %X %Z %U http://www.ics.mq.edu.au/\~{}diego/publications/papers.html %+ %^ %0 %0 Conference Proceedings %A Katz, Boris & Lin, Jimmy %D 2000 %T REXTOR: A System for Generating Relations from Natural Language %E %B Proc. ACL'2000 Workshop on Recent Advances in Natural Language Processing and Information Retrieval %C %I %V %6 %N %P %& %Y Hong-Kong University of Science and Technology %S %7 %8 %9 %? %! %Z %@ %( %) %* %L %M %1 %2 %3 inproceedings %4 %# %$ %F Katz:2000 %K flat_semantics inf_retrieval %X This paper argues that a finite-state language model with a ternary expression representation is currently the most practical and suitable bridge between natural language processing and information retrieval... %Z %U http://sensei.ieec.uned.es/IRNLP-2000/papers/ %+ %^ %0 %0 Conference Proceedings %A Kay, Martin %D 1996 %T Chart Generation %E %B Proc. 34th Annual Meeting of the {ACL} %C Santa Cruz, CA %I %V %6 %N %P 200-204 %& %Y %S %7 %8 %9 %? %! %Z %@ %( %) %* %L %M %1 %2 %3 inproceedings %4 %# %$ %F Kay:1996 %K parsers flat_semantics generation %X Charts constitute a natural uniform architecture for parsing and generation provided string position is replaced by a notion more appropriate to logical forms and that measures are taken to curtail generation paths containing semantically incomplete phrases. %Z %U %+ %^