Refer-to-as Relations as Semantic Knowledge

被引:0
|
作者
Feng, Song [1 ,2 ]
Ravi, Sujith [3 ]
Kumar, Ravi [3 ]
Kuznetsova, Polina [4 ]
Liu, Wei [5 ]
Berg, Alexander C. [5 ]
Berg, Tamara L. [5 ]
Choi, Yejin [6 ]
机构
[1] IBM TJ Watson Res Ctr, Yorktown Hts, NY 10598 USA
[2] SUNY Stony Brook, Stony Brook, NY 11794 USA
[3] Google, Mountain View, CA USA
[4] SUNY Stony Brook, Comp Sci Dept, Stony Brook, NY 11794 USA
[5] Univ N Carolina, Dept Comp Sci, Chapel Hill, NC USA
[6] Univ Washington, Comp Sci & Engn, Seattle, WA 98195 USA
基金
美国国家科学基金会;
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
We study Refer-to-as relations as a new type of semantic knowledge. Compared to the much studied Is-a relation, which concerns factual taxonomic knowledge, Refer-to-as relations aim to address pragmatic semantic knowledge. For example, a "penguin" is a "bird" from a taxonomic point of view, but people rarely refer to a "penguin" as a "bird" in vernacular use. This observation closely relates to the entry-level categorization studied in Psychology. We posit that Refer-to as relations can be learned from data, and that both textual and visual information would be helpful in inferring the relations. By integrating existing lexical structure knowledge with language statistics and visual similarities, we formulate a collective inference approach to map all object names in an encyclopedia to commonly used names for each object. Our contributions include a new labeled data set, the collective inference and optimization approach, and the computed mappings and similarities.
引用
收藏
页码:2160 / 2166
页数:7
相关论文
共 50 条
  • [1] A Corpus to Learn Refer-to-as Relations for Nominals
    Ahmad, Wasi Uddin
    Chang, Kai-Wei
    PROCEEDINGS OF THE ELEVENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION (LREC 2018), 2018, : 406 - 411
  • [2] Semantic Relations in Knowledge Organization Systems
    Braescher, Marisa
    KNOWLEDGE ORGANIZATION, 2014, 41 (02): : 175 - 180
  • [3] A System for Specifying Semantic Relations for Knowledge Representation
    Maia, Lucineia Souza
    de Lima, Gercina Angela
    KNOWLEDGE ORGANIZATION AT THE INTERFACE: PROCEEDINGS OF THE SIXTEENTH INTERNATIONAL ISKO CONFERENCE, 2020, 2020, 17 : 245 - 253
  • [4] Extracting Semantic Relations for Scholarly Knowledge Base Construction
    Al-Zaidy, Rabah A.
    Giles, C. Lee
    2018 IEEE 12TH INTERNATIONAL CONFERENCE ON SEMANTIC COMPUTING (ICSC), 2018, : 56 - 63
  • [5] Principles for organizing semantic relations in large knowledge bases
    Stephens, LM
    Chen, YF
    IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 1996, 8 (03) : 492 - 496
  • [6] GeoSR: Geographically Explore Semantic Relations in World Knowledge
    Hecht, Brent
    Raubal, Martin
    EUROPEAN INFORMATION SOCIETY: TAKING GEOINFORMATION SCIENCE ONE STEP FURTHER, 2009, : 95 - 113
  • [7] Extraction method of multiple semantic relations in domain knowledge
    Li Q.
    Zhong J.
    Li L.-L.
    Zhang J.
    Li Q.
    Kongzhi yu Juece/Control and Decision, 2021, 36 (01): : 52 - 60
  • [8] A Semantic Filter Based on Relations for Knowledge Graph Completion
    Liang, Zongwei
    Yang, Junan
    Liu, Hui
    Huang, Keju
    2021 CONFERENCE ON EMPIRICAL METHODS IN NATURAL LANGUAGE PROCESSING (EMNLP 2021), 2021, : 7920 - 7929
  • [9] Statistical feature-based semantic relations, not knowledge type, govern speed of semantic computation
    Le, Ada
    Rondina, Renante
    Amsel, Ben
    Cree, George
    CANADIAN JOURNAL OF EXPERIMENTAL PSYCHOLOGY-REVUE CANADIENNE DE PSYCHOLOGIE EXPERIMENTALE, 2009, 63 (04): : 345 - 345
  • [10] An Exploration of Semantic Relations in Neural Word Embeddings Using Extrinsic Knowledge
    Chen, Zhiwei
    He, Zhe
    Liu, Xiuwen
    Bian, Jiang
    2017 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM), 2017, : 1246 - 1251