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Event Detection and Domain Adaptation with Convolutional Neural Networks

Python 100.00%

event-detection---convolutional-neural-networks-cnn's Introduction

Event-Detection---Convolutional-Neural-Networks

Event Detection and Domain Adaptation with Convolutional Neural Networks论文复现

------2019.6.5更新--------

加入test部分,引入ranking loss,增加最终处理好的dev整个样本。

跑的结果dev大概67%,测试62.5%,和论文仍有差距,目前不知道如何调试。


把预训练的放在这个路径下,应该可以直接运行。 数据train.txt的格式为第一行为句子分词,第二行为每个单词的trigger标签,第三行为每个单词的entity type标签(只给了一个句子的格式)

只做了在dev上,dev上原则选取效果最好的,然后保存模型,测试test(未做),与论文f1大概差距5%。 思考问题可能存在数据划分上(给的别的论文作者的划分,与原论文划分有出入!),其次两个以上的trigger词没有进行特别处理。

顺便吐槽一句 真的好坑

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