CAJ | 학술논문

针对篇章隐式关系检测较难的问题，提出了一种基于语义场景匹配的平行推理方法。该方法利用框架语义学，将论元抽象为概念一级的语义描述（简称语义场景），实现描述形式的压缩。基于大规模静态数据，通过语义场景的匹配挖掘可比较论元辅助关系推理。该方法能够在保证检测精度的同时，提升检测效率。利用宾州篇章树库（penn discourse tree bank，PDTB）对这一检测方法进行评测，检测精度为55.26％。
침대편장은식관계검측교난적문제，제출료일충기우어의장경필배적평행추리방법。해방법이용광가어의학，장론원추상위개념일급적어의묘술（간칭어의장경），실현묘술형식적압축。기우대규모정태수거，통과어의장경적필배알굴가비교론원보조관계추리。해방법능구재보증검측정도적동시，제승검측효솔。이용빈주편장수고（penn discourse tree bank，PDTB）대저일검측방법진행평측，검측정도위55.26％。
The implicit discourse relation detection has a higher difficulty.For this,a method was proposed to detect im-plicit discourse relation based on semantics scenario.The compression of description form was realized by frame semantics that abstract argument as conceptual semantic description (semantics scenario),and then mine the comparable argument pairs through semantics scenario from large-scale static data.It can ensure accuracy while improve detection efficiency. The discourse relation was detected in Penn Discourse Treebank (PDTB).The accuracy can reach to 55.26%.