Semantic parsing as an energy minimization problem

被引:0
|
作者
Chan, SWK [1 ]
机构
[1] City Univ Hong Kong, Dept Comp Sci, Hong Kong, Peoples R China
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Language understanding is not just a matter of knowing the language, but to a considerable degree of logical inference with the world knowledge. Pure linguistic approach cannot interpret any natural language utterances. They can only constrain their interpretation and the rest must leave to semantic parsing. To discriminate senses in any semantic parsing, a reader should consider a diversity of information, including syntactic tags and restriction, word frequencies collocations, semantic context and role-related expectations. However, current approaches make use of only small subsets of this information. In this paper, we show how semantic parsing can be formulated as a sequence of processes in which multiple sources of knowledge are incorporated. A resolution-based inference procedure will be shown to determine semantic meanings from the analyzed utterances. They are on the basis that language technology has to employ cost-efficient solutions with respect to the phenomena occurring in the real world language understanding.
引用
收藏
页码:1118 / 1122
页数:5
相关论文
共 50 条
  • [21] Semantic Parsing of Textual Requirements
    Holter, Ole Magnus
    [J]. SEMANTIC WEB: ESWC 2020 SATELLITE EVENTS, 2020, 12124 : 240 - 249
  • [22] Energy Minimization via Graph Cuts for Semantic Place Labeling
    Fazl-Ersi, Ehsan
    Tsotsos, John K.
    [J]. IEEE/RSJ 2010 INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2010), 2010,
  • [23] Energy minimization via graph cuts for semantic place labeling
    Department of Computer Science and Engineering, York University, Toronto, ON M3J 1P3, Canada
    [J]. IEEE/RSJ Int. Conf. Intelligent Rob. Syst., IROS - Conf. Proc., (5947-5952):
  • [24] Constrained Semantic Forests for Improved Discriminative Semantic Parsing
    Lu, Wei
    [J]. PROCEEDINGS OF THE 53RD ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL) AND THE 7TH INTERNATIONAL JOINT CONFERENCE ON NATURAL LANGUAGE PROCESSING (IJCNLP), VOL 2, 2015, : 737 - 742
  • [25] Deep Hierarchical Parsing for Semantic Segmentation
    Sharma, Abhishek
    Tuzel, Oncel
    Jacobs, David W.
    [J]. 2015 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2015, : 530 - 538
  • [26] Semantic Parsing with Neural Hybrid Trees
    Susanto, Raymond Hendy
    Lu, Wei
    [J]. THIRTY-FIRST AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2017, : 3309 - 3315
  • [27] Semantic Parsing Using Construction Categorization
    Gao, Yi
    Hong, Caifu
    Wu, Xihong
    [J]. INTELLIGENCE SCIENCE AND BIG DATA ENGINEERING: BIG DATA AND MACHINE LEARNING TECHNIQUES, ISCIDE 2015, PT II, 2015, 9243 : 576 - 584
  • [28] Evaluating Ambiguous Questions in Semantic Parsing
    Papicchio, Simone
    Papotti, Paolo
    Cagliero, Luca
    [J]. 2024 IEEE 40TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING WORKSHOP, ICDEW, 2024, : 338 - 342
  • [29] Unsupervised Semantic Parsing of Video Collections
    Sener, Ozan
    Zamir, Amir R.
    Savarese, Silvio
    Saxena, Ashutosh
    [J]. 2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV), 2015, : 4480 - 4488
  • [30] On WordNet Semantic Classes and Dependency Parsing
    Bengoetxea, Kepa
    Agirre, Eneko
    Nivre, Joakim
    Zhang, Yue
    Gojenola, Koldo
    [J]. PROCEEDINGS OF THE 52ND ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, VOL 2, 2014, : 649 - 655