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Auflistung nach Schlagwort "Lexical semantics"

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  • Zeitschriftenartikel
    Dissertation Abstract:Learning High Precision Lexical Inferences
    (KI - Künstliche Intelligenz: Vol. 35, No. 0, 2021) Shwartz, Vered
    The fundamental goal of natural language processing is to build models capable of human-level understanding of natural language. One of the obstacles to building such models is lexical variability , i.e. the ability to express the same meaning in various ways. Existing text representations excel at capturing relatedness (e.g. blue / red ), but they lack the fine-grained distinction of the specific semantic relation between a pair of words. This article is a summary of a Ph.D. dissertation submitted to Bar-Ilan University in 2019, under the supervision of Professor Ido Dagan of the Computer Science Department. The dissertation explored methods for recognizing and extracting semantic relationships between concepts ( cat is a type of animal ), the constituents of noun compounds (baby oil is oil for babies), and verbal phrases (‘X died at Y’ means the same as ‘X lived until Y’ in certain contexts). The proposed models outperform highly competitive baselines and improve the state-of-the-art in several benchmarks. The dissertation concludes in discussing two challenges in the way of human-level language understanding: developing more accurate text representations and learning to read between the lines.
  • Zeitschriftenartikel
    Draw mir a Sheep: A Supersense-based Analysis of German Case and Adposition Semantics
    (KI - Künstliche Intelligenz: Vol. 35, No. 0, 2021) Prange, Jakob; Schneider, Nathan
    Adpositions and case markers are ubiquitous in natural language and express a wide range of meaning relations that can be of crucial relevance for many NLP and AI tasks. However, capturing their semantics in a comprehensive yet concise, as well as cross-linguistically applicable way has remained a challenge over the years. To address this, we adapt the largely language-agnostic SNACS framework to German, defining language-specific criteria for identifying adpositional expressions and piloting a supersense-annotated German corpus. We compare our approach with prior work on both German and multilingual adposition semantics, and discuss our empirical findings in the context of potential applications.