Text Annotation Graphs: Annotating Complex Natural Language Phenomena

被引:0
|
作者
Forbes, Angus G. [1 ]
Lee, Kristine [2 ]
Hahn-Powell, Gus [3 ]
Valenzuela-Escarcega, Marco A. [3 ]
Surdeanu, Mihai [3 ]
机构
[1] Univ Calif Santa Cruz, Santa Cruz, CA 95064 USA
[2] Univ Illinois, Chicago, IL USA
[3] Univ Arizona, Tucson, AZ 85721 USA
关键词
annotation; event extraction; online NLP tools; text visualization;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper introduces a new web-based software tool for annotating text, Text Annotation Graphs, or TAG. It provides functionality for representing complex relationships between words and word phrases that are not available in other software tools, including the ability to define and visualize relationships between the relationships themselves (semantic hypergraphs). Additionally, we include a visualization mode in which annotation subgraphs, or semantic summaries, are used to show relationships outside of the sequential context of the text itself. These subgraphs can be used to quickly find similar structures within the current document or external annotated documents. TAG was initially developed to support information extraction tasks on a large database of biomedical articles. However, our software is flexible enough to support a wide range of annotation tasks for many domains. Examples are provided that showcase TAG's capabilities
引用
收藏
页码:1047 / 1052
页数:6
相关论文
共 50 条
  • [1] High School Girls' Interpretations of Science Graphs: Exploring Complex Visual and Natural Language Hybrid Text
    Whitacre, Michelle P.
    Saul, E. Wendy
    INTERNATIONAL JOURNAL OF SCIENCE AND MATHEMATICS EDUCATION, 2016, 14 (08) : 1387 - 1406
  • [2] High School Girls’ Interpretations of Science Graphs: Exploring Complex Visual and Natural Language Hybrid Text
    Michelle P. Whitacre
    E. Wendy Saul
    International Journal of Science and Mathematics Education, 2016, 14 : 1387 - 1406
  • [3] Korean Time Information Analysis of Hierarchical Annotation Rules from Natural Language Text
    Lim, Chae-Gyun
    Choi, Ho-Jin
    2019 IEEE INTERNATIONAL CONFERENCE ON BIG DATA AND SMART COMPUTING (BIGCOMP), 2019, : 645 - 648
  • [4] LANGUAGE AND COMPLEX PHENOMENA
    SPENCER, J
    AUSTRALIAN AND NEW ZEALAND JOURNAL OF PSYCHIATRY, 1992, 26 (03): : 515 - 516
  • [5] Controlled Natural Language for Semantic Annotation
    Davis, Brian
    Varma, Pradeep
    Handschuh, Siegfried
    Dragan, Laura
    Cunningham, Hamish
    SEMANTIC WEB: RESEARCH AND APPLICATIONS, 2009, 5554 : 816 - +
  • [6] Annotation of Spatial Relations in Natural language
    Shen, Qijun
    Zhang, Xueying
    Jiang, Wenming
    2009 INTERNATIONAL CONFERENCE ON ENVIRONMENTAL SCIENCE AND INFORMATION APPLICATION TECHNOLOGY, VOL III, PROCEEDINGS,, 2009, : 418 - 421
  • [7] Large language models as a substitute for human experts in annotating political text
    Heseltine, Michael
    von Hohenberg, Bernhard Clemm
    RESEARCH & POLITICS, 2024, 11 (01)
  • [8] Methods of Annotating and Identifying Metaphors in the Field of Natural Language Processing
    Pticek, Martina
    Dobsa, Jasminka
    FUTURE INTERNET, 2023, 15 (06)
  • [9] UNIQORN: Unified question answering over RDF knowledge graphs and natural language text
    Pramanik, Soumajit
    Alabi, Jesujoba
    Roy, Rishiraj Saha
    Weikum, Gerhard
    JOURNAL OF WEB SEMANTICS, 2024, 83
  • [10] Best Practices for Text Annotation with Large Language Models
    Toernberg, Petter
    SOCIOLOGICA-INTERNATIONAL JOURNAL FOR SOCIOLOGICAL DEBATE, 2024, 18 (02): : 67 - 85