• Refine your search:
  • 
    Keyword
  • 
    Creator / Publisher:
    
    • Chang, Haw-Shiuan (2)
    • Birle, Ian (1)
    • Flanigan, Jeffrey (1)
    • Hough, Alfred (1)
    • Huang, Kevin Joon-Ming (1)
    • Jensen, Zach (1)
    • Kim, Edward (1)
    • Massachusetts Institute of Technology. Department of Materials Science and Engineering (1)
    • Massachusetts Institute of Technology. Institute for Data, Systems, and Society (1)
    • McCallum, Andrew (1)
    •   more
  • 
    Year
  • 
    Medium:
    
    • Online (2)
  • 
    Type:
    
    • Article (2)
  • 
    BLLDB-Access

Search in the Catalogues and Directories

All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 2 of 2 1 Open Aspect Target Sentiment Classification with Natural Language Prompts ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Birle, Ian; Chang, Haw-Shiuan. - : Underline Science Inc., 2021 BASE Show details 2 The materials science procedural text corpus: Annotating materials synthesis procedures with shallow semantic structures Mysore, Sheshera; Jensen, Zach; Kim, Edward; Huang, Kevin Joon-Ming; Chang, Haw-Shiuan; Strubell, Emma; Flanigan, Jeffrey; McCallum, Andrew; Olivetti, Elsa A. In: arXiv (2020) Abstract: © 2019 Association for Computational Linguistics Materials science literature contains millions of materials synthesis procedures described in unstructured natural language text. Large-scale analysis of these synthesis procedures would facilitate deeper scientific understanding of materials synthesis and enable automated synthesis planning. Such analysis requires extracting structured representations of synthesis procedures from the raw text as a first step. To facilitate the training and evaluation of synthesis extraction models, we introduce a dataset of 230 synthesis procedures annotated by domain experts with labeled graphs that express the semantics of the synthesis sentences. The nodes in this graph are synthesis operations and their typed arguments, and labeled edges specify relations between the nodes. We describe this new resource in detail and highlight some specific challenges to annotating scientific text with shallow semantic structure. We make the corpus available to the community to promote further research and development of scientific information extraction systems. ; National Science Foundation (Awards 1534340/1534341) ; Office of Naval Research (Contract N00014-16-1-2432) URL: https://hdl.handle.net/1721.1/137710.2 BASE Hide details

Mobile view All Catalogues UB Frankfurt Linguistik 0 IDS Mannheim 0 OLC Linguistik 0 UB Frankfurt Retrokatalog 0 DNB Subject Category Language 0 Institut für Empirische Sprachwissenschaft 0 Leibniz-Centre General Linguistics (ZAS) 0 Bibliographies BLLDB 0 BDSL 0 IDS Bibliografie zur deutschen Grammatik 0 IDS Bibliografie zur Gesprächsforschung 0 IDS Konnektoren im Deutschen 0 IDS Präpositionen im Deutschen 0 IDS OBELEX meta 0 MPI-SHH Linguistics Collection 0 MPI for Psycholinguistics 0 Linked Open Data catalogues Annohub 0 Online resources Link directory 0 Journal directory 0 Database directory 0 Dictionary directory 0 Open access documents BASE 2 Linguistik-Repository 0 IDS Publikationsserver 0 Online dissertations 0 Language Description Heritage 0