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freesunshine0316 / semantic-nmt

Code corresponding to our paper "Semantic Neural Machine Translation using AMR"
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how to generate the semantic graphs based on my own dataset? #5

Open zhao1402072392 opened 4 years ago

zhao1402072392 commented 4 years ago

Thanks for your sharing , it's really helpful.But could I know how to generate the semantic graphs based on my own dataset?thanks in advance！

freesunshine0316 commented 4 years ago

Since I don't know which type of semantic graphs you use, I can't provide much constructive help. For AMR data, you may refer to the data processing section of our AMR-to-text generation work.

zhao1402072392 commented 4 years ago

Sorry, It's my fault. I wasn't clear. I mean how could I gain AMR from my own dataset(a group of sentences).

------------------ 原始邮件 ------------------ 发件人: "Linfeng Song"<notifications@github.com>; 发送时间: 2020年5月27日(星期三) 上午6:40 收件人: "freesunshine0316/semantic-nmt"<semantic-nmt@noreply.github.com>; 抄送: "Joshua Zhao"<1402072392@qq.com>;"Author"<author@noreply.github.com>; 主题: Re: [freesunshine0316/semantic-nmt] how to generate the semantic graphs based on my own dataset? (#5)

Since I don't know which type of semantic graphs you use, I can't provide much constructive help. For AMR data, you may refer to the data processing section of our AMR-to-text generation work.

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freesunshine0316 commented 4 years ago

You can take a AMR parser to do that. There are a bunch of them, like stog.

zhao1402072392 commented 4 years ago

Thanks for your reply^_^.

------------------ 原始邮件 ------------------ 发件人: "Linfeng Song"<notifications@github.com>; 发送时间: 2020年5月27日(星期三) 中午11:35 收件人: "freesunshine0316/semantic-nmt"<semantic-nmt@noreply.github.com>; 抄送: "Joshua Zhao"<1402072392@qq.com>;"Author"<author@noreply.github.com>; 主题: Re: [freesunshine0316/semantic-nmt] how to generate the semantic graphs based on my own dataset? (#5)

You can take a AMR parser to do that. There are a bunch of them, like stog.

— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub, or unsubscribe.