As the basis of machine translation, anaphora aims to let the machine determine the entity or event to which the sentence refers by exploring the anaphora relationship between sentences. Prior to this, the research on anaphora resolution mainly focused on the resolution of entity anaphora. Through unremitting efforts, the elimination of entity-reference relationship has achieved great success, but the equally important event reference has been stagnant. This means that we can promote the development of machine translation by enhancing event reference. In this paper, a new method is proposed, which uses the latest machine learning algorithm to eliminate English event pronouns. Through feature extraction, data preprocessing, and the introduction of end-to-end double-loop neural network and attention mechanism, the network’s ability to acquire contextual features is improved, and finally, the purpose of eliminating English event pronouns is achieved. In the experimental part, this paper also conducts training and testing on the latest data set KBP. It is found that the model algorithm proposed in this paper can perform the task of experimental setup well, and the value of 40.3% F1 is given under CONLL evaluation index. This proves that the model can understand semantic information very effectively and extract relevant information from the given semantic information.
In recent years, due to the epidemic, the country is vigorously developing online teaching, which further promotes the development of hybrid English teaching. Online and offline hybrid teaching combines face-to-face classroom and online teaching. Offline traditional classroom and online auxiliary teaching can complement each other. However, in actual teaching, mixed teaching still suffers some defects, which can undermine the learning outcomes. In this paper, the Internet of Things information technology is used to study hybrid teaching. Firstly, relevant core concepts are clarified. After that, this paper designs an English online hybrid teaching model based on Internet of Things information technology and verifies the feasibility and effectiveness of this model through experiments. The results show that, compared with the simple mixed teaching, the average score of students’ final evaluation under this mode increased by 5.11 points. And the proportion of students with classroom interaction and autonomous learning also rose by 12.1%. This shows that under the promotion of Internet of Things information technology, the online hybrid teaching mode has great guiding significance for middle school English teaching.
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