A92-1024 be solved by similarly focussed fact extraction applications . The information
D15-1031 in practice . For example , in fact extraction , a candidate value may be just
A92-1024 technology is also central to JASPER 's fact extraction technology . The network-based
A92-1024 selection of relevant releases and fact extraction . Results are reported below
D14-1115 represent an intriguing resource for fact extraction , providing a useful complement
D14-1038 composed of four stages . Seed fact extraction : We begin by extracting a small
A92-1024 patterns and procedures used for fact extraction . In analyzing the relevant texts
D14-1115 Hasegawa et al. , 2004 ) , and fact extraction in particular . Indeed , the
D09-1025 information extraction tasks such as fact extraction and event extraction . <title>
A92-1024 By corresponding measures for fact extraction , the system is over 84 % accurate
A92-1024 use two measures of accuracy for fact extraction : completeness and correctness
A92-1024 -RSB- , the only major deployed fact extraction system before JASPER , is the
D14-1207 scope from text , at the time of fact extraction ; ii ) methods that infer temporal
A92-1024 system : JASPER . JASPER is a fact extraction system recently developed and
D14-1089 James R Abstract State-of-the-art fact extraction is heavily constrained by recall
D14-1167 provide a prior score to help fact extraction on the benchmark data set of
D09-1025 entities or facts . Examples include fact extraction systems such as ( Cafarella et
D10-1035 et al. 's ( 2006 ) largescale fact extraction system . For simplicity , we
A92-1024 business problems can be solved by fact extraction applications which involve locating
D15-1031 missing facts in a KB and helping facts extraction ( Bordes et al. , 2011 ; Bordes
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