Named entity recognition (NER) on the Bengali split of WikiANN. The goal of this task is to classify each token in the input text into one of the following categories: person, organization, location, or none of them. News Category Classification (NCC) on the Soham articles datas...
For more information visit www.intechopen.com ProvisionaClhcahpatpetre4r AAddvvaanncceedd EEcchhooccaarrddiiooggrraapphhyy ffoorr tthhee DDiiaaggnnoossiiss aanndd MMaannaaggeemmeenntt ooff IInnffeeccttiivvee EEnnddooccaarrddiittiiss John F. Sedgwick and Gregory M. Scalia John F. Sedgwick...
It really ticks me off that i have to log on-lineagain and go through the hassle of reaching the site i was at just to finish doing what I was doing-but the 2nd time around i'm not told about illegal operations-the worst part about the whole thing is when you go to the explanatio...
Conducted through live video chatting through a certain platform or software, the dentist may suggest an in-person visit for further evaluation only when they see a certain issue. Aside from being cost-efficient, it can save time and effort for both patients and practitioners alike. Thus, the ...
For "each age is a dream that is dying, or one that is coming to birth." Many voices are heard as we face a great decision. Comfort says, "Tarry a while." Opportunism says, "This is a good spot." Timidity asks, "How difficult is the road ahead?" True, we have come far from...
16.(30.00 分)When most of us get a text message on our cell phone from an unknown person,we usually say"sorry,(1) number!" and move on. But when Dennis William(s 2) a text that clearly wasn't intended for him,he did something (3) . On March 19, Dennis got a group text (4...
地区2010年有关经济发展的综合统计资料如下： 农、林、牧、渔业总产出为12亿元，其中间投入为4亿元； 工业总产出为35亿元，其中间投入为25亿元； 建筑业总产出为15亿元，其中间投入为10亿元； 批发和零售业总产出为10亿元，其中间投入为5亿元； 其他行业营业总产出为12亿元，其中间投入为6亿元； 根据上述所给...
So, we decided to use Prodigy to label the dataset for another task: named entity recognition.Once you have Prodigy installed, you can simply run:$ prodigy ner.manual bbc blank:en BBC_News_Train.csv --label PERSON,ORG,PRODUCT,LOCATION ...
Named entity recognition (NER) on the Bengali split of WikiANN. The goal of this task is to classify each token in the input text into one of the following categories: person, organization, location, or none of them. News Category Classification (NCC) on the Soham arti...
Named entity recognition (NER) on the Bengali split of WikiANN. The goal of this task is to classify each token in the input text into one of the following categories: person, organization, location, or none of them. News Category Classification (NCC) on the Soham articles d...