CogALex-V Shared Task: LOPE
Automatic discovery of semantically-related words is one of the most important NLP tasks, and has great impact on the theoretical psycholinguistic modeling of the mental lexicon. In this shared task, we employ the word embeddings model to testify two thoughts explicitly or implicitly assumed by the NLP community: (1). Word embedding models can reflect syntagmatic similarities in usage between words to distances in projected vector space. (2). Word embedding models can reflect paradigmatic relationships between words.
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CogALex-V Shared Task: Mach5 -- A traditional DSM approach to semantic relatedness
This contribution provides a strong baseline result for the CogALex-V shared task using a traditional {``}count{''}-type DSM (placed in rank 2 out of 7 in subtask 1 and rank 3 out of 6 in subtask 2). Parameter tuning exp…
The CogALex-V Shared Task on the Corpus-Based Identification of Semantic Relations
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CogALex-VI Shared Task: Transrelation - A Robust Multilingual Language Model for Multilingual Relation Identification
We describe our submission to the CogALex-VI shared task on the identification of multilingual paradigmatic relations building on XLM-RoBERTa (XLM-R), a robustly optimized and multilingual BERT model. In spite of several…
Hypernym DiscoveryLanguage ModelingLanguage ModellingMultilingual text classification+3