Conceptual metaphor and scripts in Recognizing Textual Entailment

被引:0
|
作者
Murray, William R. [1 ]
机构
[1] Boeing Phamton Works, Seattle, WA 98124 USA
关键词
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The power and pervasiveness of conceptual metaphor can be harnessed to expand the class of textual entailments that can be performed in the Recognizing Textual Entailment (RTE) task and thus improve our ability to understand human language and make the kind of textual inferences that people do. RTE is a key component for question understanding and discourse understanding. Although extensive lexicons, such as WordNet, can capture some word senses of conventionalized metaphors, a more general capability is needed to handle the considerable richness of lexical meaning based on metaphoric extensions that is found in common news articles, where writers routinely employ and extend conventional metaphors. We propose adding to RTE systems an ability to recognize a library of common conceptual metaphors, along with scripts. The role of the scripts is to allow entailments from the source to the target domain in the metaphor by describing activities in the source domain that map onto elements of the target domain. An example is the progress of an activity, such as a career or relationship, as measured by the successful or unsuccessful activities in a journey towards its destination. In particular we look at two conceptual metaphors: IDEAS AS PHYSICAL OBJECTS, which is part of the Conduit Metaphor of Communication, and ABSTRACT ACTIVITIES AS JOURNEYS. The first allows inferences that apply to physical objects to (partially) apply to ideas and communication acts (e.g., "he lobbed jibes to the comedian"). The second allows the progress of an abstract activity to be assessed by comparing it to a journey (e.g., "his career was derailed"). We provide a proof of concept where axioms for actions on physical objects, and axioms for how physical objects behave compared to communication objects, are combined to make correct RTE inferences in Prover9 for example text-hypothesis pairs. Similarly, axioms describing different states in a journey are used to infer the current progress of an activity, such as whether it is succeeding (e.g., "steaming ahead"), in trouble (e.g., "off course"), recovering (e.g., "back on track"), or irrevocably failed (e.g., "hijacked").
引用
收藏
页码:127 / 136
页数:10
相关论文
共 50 条
  • [1] AORTE for Recognizing Textual Entailment
    Siblini, Reda
    Kosseim, Leila
    COMPUTATIONAL LINGUISTICS AND INTELLIGENT TEXT PROCESSING, 2009, 5449 : 245 - 255
  • [2] Recognizing Textual Entailment with Statistical Methods
    Gaona, Miguel Angel Rios
    Gelbukh, Alexander
    Bandyopadhyay, Sivaji
    ADVANCES IN PATTERN RECOGNITION, 2010, 6256 : 372 - +
  • [3] Figurative Language in Recognizing Textual Entailment
    Chakrabarty, Tuhin
    Ghosh, Debanjan
    Poliak, Adam
    Muresan, Smaranda
    FINDINGS OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, ACL-IJCNLP 2021, 2021, : 3354 - 3361
  • [4] Applying Textual Entailment to the Interpretation of Metaphor
    Mohler, Michael
    Tomlinson, Marc
    Bracewell, David
    2013 IEEE SEVENTH INTERNATIONAL CONFERENCE ON SEMANTIC COMPUTING (ICSC 2013), 2013, : 118 - 125
  • [5] Paraphrase substitution for recognizing textual entailment
    Bosma, Wauter
    Callison-Burch, Chris
    EVALUATION OF MULTILINGUAL AND MULTI-MODAL INFORMATION RETRIEVAL, 2007, 4730 : 502 - +
  • [6] Recognizing Textual Entailment based on WordNet
    Feng, Jin
    Zhou, Yiming
    Martin, Trevor
    2008 INTERNATIONAL SYMPOSIUM ON INTELLIGENT INFORMATION TECHNOLOGY APPLICATION, VOL II, PROCEEDINGS, 2008, : 27 - +
  • [7] Recognizing Textual Entailment: Models and Applications
    Magnini, Bernardo
    COMPUTATIONAL LINGUISTICS, 2015, 41 (01) : 157 - 160
  • [8] Recognizing Textual Entailment: Models and Applications
    Dagan, Ido
    Roth, Dan
    Sammons, Mark
    Zanzotto, Fabio
    Synthesis Lectures on Human Language Technologies, 2013, 6 (04): : 1 - 222
  • [9] Recognizing Textual Entailment: Models and Applications
    Grabar, Natalia
    TRAITEMENT AUTOMATIQUE DES LANGUES, 2013, 54 (02): : 142 - 146
  • [10] Recognizing Textual Entailment and Paraphrases in Portuguese
    Rocha, Gil
    Cardoso, Henrique Lopes
    PROGRESS IN ARTIFICIAL INTELLIGENCE (EPIA 2017), 2017, 10423 : 868 - 879