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  1. ; ; ; ; ; ; ; ; (, LREC proceedings)
    Calzolari, Nicoletta; Bechet, Frederic; Blache, Philippe; Choukri, Khalid; Cieri, Christopher; Declerck, Thierry; Goggi, Thierry; Isahara, Hitoshi; Maegaard, Bente; Mariani, Joseph (Ed.)
    This paper provides an overview of the xDD/LAPPS Grid framework and provides results of evaluating the AskMe retrieval engine using datasets included in the BEIR benchmark. Our primary goal is to determine a solid baseline of performance to guide further development of our retrieval capabilities. Beyond this, we aim to dig deeper to determine when and why certain approaches perform well (or badly) on both in-domain and out-of-domain data, an issue that has to date received relatively little attention. 
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    Accepted Manuscript Full Text Available
  2. ; ; ; ; (, Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020)
    Karin Verspoor, Kevin Bretonnel (Ed.)
    In a recent project, the Language Applications Grid was augmented to support the mining of scientific publications. The results of that effort have now been repurposed to focus on Covid-19 literature, including modification of the LAPPS Grid “AskMe” query and retrieval engine. We describe the AskMe system and discuss its functionality as compared to other query engines available to search covid-related publications. 
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    Full Text Available 
  3. ; ; ; ; (, Proceedings of the 13th Linguistic Annotation Workshop)
    This paper describes an ecosystem consisting of three independent text annotation platforms. To demonstrate their ability to work in concert, we illustrate how to use them to address an interactive domain adaptation task in biomedical entity recognition. The platforms and the approach are in general domain-independent and can be readily applied to other areas of science. 
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    Full Text Available