Deep Knowledge Representation based on Compositional Semantics for Chinese Geography

Elementary education resources for geography contain a wealth of knowledge that is a collection of information with various relationships. It is of vital importance to further develop human like intelligent technology for extracting deep semantic information to effectively understand the questions. In this paper, we propose a novel directed acyclic graph (DAG) deep knowledge representation built upon the theorem of combinational semantics. Knowledge is decomposed into nodes and edges which are then inserted into the ontology knowledge base. Experimental results demonstrate the superiority of the proposed method on question answering, especially when the syntax of question is complex, and its representation is fuzzy.

[1]  Raymond J. Mooney,et al.  Learning Synchronous Grammars for Semantic Parsing with Lambda Calculus , 2007, ACL.

[2]  Dan Klein,et al.  Learning Dependency-Based Compositional Semantics , 2011, CL.

[3]  Tiejun Zhao,et al.  Knowledge-Based Question Answering as Machine Translation , 2014, ACL.

[4]  Jeffrey Dean,et al.  Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.

[5]  James R. Curran,et al.  The Importance of Supertagging for Wide-Coverage CCG Parsing , 2004, COLING.

[6]  Alexander Yates,et al.  Large-scale Semantic Parsing via Schema Matching and Lexicon Extension , 2013, ACL.

[7]  Xuanjing Huang,et al.  Overview of the NLPCC 2015 Shared Task: Chinese Word Segmentation and POS Tagging for Micro-blog Texts , 2015, NLPCC.

[8]  Dan Klein,et al.  A* Parsing: Fast Exact Viterbi Parse Selection , 2003, NAACL.

[9]  Mark Steedman,et al.  Combinatory Categorial Grammar , 2011 .

[10]  Qiang Zhou.  Evaluation Reportof the third Chinese Parsing Evaluation: CIPS-SIGHAN-ParsEval-2012 , 2012, CIPS-SIGHAN.

[11]  Geoffrey Zweig,et al.  Linguistic Regularities in Continuous Space Word Representations , 2013, NAACL.

[12]  Harold L. Somers,et al.  Review Article: Example-based Machine Translation , 1999, Machine Translation.

[13]  Raymond J. Mooney,et al.  Learning Semantic Grammars with Constructive Inductive Logic Programming , 1993, AAAI.

[14]  Jun Zhao,et al.  Question Answering over Linked Data Using First-order Logic , 2014, EMNLP.