The two models jointly offer an effective way to find more answers and better answers in the list question answering task.
文章针对列表类自动问题回答的任务要求,提出了一种基于短语检索和答案距离排序模型的列表类问题回答的方法。
Open domain question answering (QA) represents a challenge of natural language processing, aiming at returning exact answers in response to natural language questions.
开放领域的问题回答(question answering)是自然语言处理领域中具有挑战性的研究方向。
This paper presents a now method for answer ranking in question answering(QA)track.
本文描述了一种问题回答任务中答案排序的新方法。
Tom, please answer my question.
汤姆，请回答我的问题。
Jenny, please answer my questions now.
珍妮，现在请回答我的问题。
Please answer me / my question.
请回答我／回答我的问题。
Would you kindly answer my questions?
请回答我的问题好吗？
Please answer my question immediately.
请立刻回答我的问题。
Linda, please answer my questions.
琳达，请你回答我的问题。
I 'll ask someone who can answer your question to call you back .
我会请能回答您问题的人给您回电话。
Please write and I will answer your questions about America.
请回信。我将回答你关于美国的问题。
Yes, I have answered very question in the form.
是的，申请表中的所有问题我都回答了。
Please put the book aside and answer my question.
请把书放在一旁，回答我的问题。
Please answer my question in chorus.
请大家一起回答我的问题。
Please answer my questions quickly and properly, not palter with them.
请马上准备回答我的问题，不要含糊其辞。
Please excuse me if I have left any of your questions unanswered.
如果我还有什么问题没有回答你的话,请原谅。
He answered my questions patiently.
他耐心地回答我的问题。
Three questions, @ I say.
于是我就会说：“请回答三个问题。”
He used to travel by train.
现在请回答第二个问题:
Please answer the question in English.
请用英语回答问题。
As I cannot answer your question, I refer you to my secretary (to the dictionary).
因为我不能回答你的问题，请去问我的秘书(查字典)。