반응형 분류 전체보기599 [2022-09-01] 오늘의 자연어처리 Efficient and Interpretable Neural Models for Entity Tracking What would it take for a natural language model to understand a novel, such as The Lord of the Rings? Among other things, such a model must be able to: (a) identify and record new characters (entities) and their attributes as they are introduced in the text, and (b) identify subsequent references to the characters previously introduce.. 2022. 9. 1. [2022-09-01] 오늘의 자연어처리 A Spanish dataset for Targeted Sentiment Analysis of political headlines Subjective texts have been studied by several works as they can induce certain behaviours in their users. Most work focuses on user-generated texts in social networks, but some other texts also comprise opinions on certain topics and could influence judgement criteria during political decisions. In this work, we address the.. 2022. 9. 1. [2022-08-31] 오늘의 자연어처리 NEAR: Named Entity and Attribute Recognition of clinical concepts Named Entity Recognition (NER) or the extraction of concepts from clinical text is the task of identifying entities in text and slotting them into categories such as problems, treatments, tests, clinical departments, occurrences (such as admission and discharge) and others. NER forms a critical component of processing and leveragi.. 2022. 8. 31. [2022-08-31] 오늘의 자연어처리 On Unsupervised Training of Link Grammar Based Language Models In this short note we explore what is needed for the unsupervised training of graph language models based on link grammars. First, we introduce the ter-mination tags formalism required to build a language model based on a link grammar formalism of Sleator and Temperley [21] and discuss the influence of context on the unsupervised lea.. 2022. 8. 31. 이전 1 ··· 131 132 133 134 135 136 137 ··· 150 다음 반응형