Named entity recognition aims to classify words in a document into pre-defined target entity classes. It is now considered to be fundamental for many natural language processing tasks such as information retrieval, machine translation, information extraction and question answering. This paper presents a...
解析 【答案】stick【核心短语/词汇】glue:胶水【翻译】你需要胶水来把它们粘在背景纸上。【解析】根据句意及首字母提示,可知此处填动词stick“粘贴”,stick to固定搭配,表示“坚持,粘住”,空前to是不定式符号,因此此处填动词原形,故答案是stick。 反馈 收藏 ...
However, as far as we are concerned, there was no study being conducted with a concentration on method for question generation in Vietnamese known as a low-resource language. In this paper, we evaluate different powerful question generation systems in two benchmark Vietnamese datasets: UIT-Vi...
in which the voice starts slightly above the middle of the normal speaking voice range, drops and then rises abruptly. A diacritical mark that looks like a question mark without
raised the research question and collected data; T.N.X. and H.N.T.T. analyzed the data and they wrote the paper. Corresponding authors Correspondence to Ha Thi Thu Nguyen or Trung Xuan Nguyen. Ethics declarations Ethical approval This article does not contain any studies with human ...
Paper tables with annotated results for BARTpho: Pre-trained Sequence-to-Sequence Models for Vietnamese
To solve this issue, this paper proposes a hybrid approach of Query Expansion (QE) where lexical resources and word embeddings (WEs) are combined to generate synonyms and hypernyms of relevant words extracted from the user question and... E Damiano,A Minutolo,S Silvestri,... - International ...
Training set: 6831 question and query pairs Development set: 954 question and query pairs Test set: 1906 question and query pairs ModelExact Match AccuracyPaperCodeNote IRNet (2019)53.2A Pilot Study of Text-to-SQL Semantic Parsing for VietnameseLinkUsingPhoBERTas encoder ...
Pre-train_tokenizer Load datasets Train the tokenizers with SentencePiece models Save tokenizers Pre-train_model Load datasets Load tokenizers Pre-train DeBERTa-v3 Model Fine-tuning Code architecture POS tagging and NER (POS_NER) Question Answering (QA and QA2) ...
结果1 题目 ese opera C. Chinese knot B. Chinese paper-cutting Neither John nor his father was able to D. Chinese kung fu A. stay up early enough to catch the morning train.6The B. turm up C. wake up D. give up 相关知识点: 试题来源: 解析 答案见上 反馈 收藏 ...