提供者：刘璐
这个语料库是我现在学习和工作中接触的最多的一个，所以在本次大作业中拿出来分享一些我对于这个语料库的理解，以及我在工作中做的一些笔记和一些我看过的相关的论文。
==download web：==
http://cs.rochester.edu/nlp/rocstories/
==paper for this dataset and evaluation==
https://arxiv.org/pdf/1604.01696.pdf
==introduction==
background
Representation and learning of commonsense knowledge is one of the foundational problems in the quest to enable deep language understanding;
Story understanding is an extremely challenging task in natural language understanding with a longrunning history in AI ;
This issue is particularly challenging for understanding causal and correlational relationships between events（事件之间的因果和相关关系）;
Recently, there has been a renewed interest in story and narrative understanding based on progress made in core NLP tasks.
research has been hindered（阻碍） by the lack of a proper evaluation framework.
main goals:
- The corpus contains a variety of commonsense causal and temporal relations between everyday events. 该语料库注重常识关系和因果关系的构建
- The corpus is a high quality collection of nonfictional daily short life stories.该语料库只包含真实事件（这种真实指的是不含虚构内容，比如说一只小狗踢足球等等）
example of this corpus:
| storyid | storytitle | sentence1 | sentence2 | sentence3 | sentence4 | sentence5 |
| :——– | ——–:| :–: |:–: |:–: |:–: |:–: |
|9a51198e-96f1-42c3-b09d-a3e1e067d803 | Overweight Kid |Dan’s parents were overweight .| Dan was overweight as well .| The doctors told his parents it was unhealthy .| His parents understood and decided to make a change . |They got themselves and Dan on a diet .|
617e7ada-3878-488d-bd56-40695b91f053| The Bike Accident| Carrie had just learned how to ride a bike . |She didn’t have a bike of her own .| Carrie would sneak rides on her sister’s bike . |She got nervous on a hill and crashed into a wall .| The bike frame bent and Carrie got a deep gash on her leg .|
79b0da1f-e460-4173-ba58-8c9e2553c53a| Beach| Morgan enjoyed long walks on the beach .| She and her boyfriend decided to go for a long walk .| After walking for over a mile , something happened .| Morgan decided to propose to her boyfriend .| Her boyfriend was upset he didn’t propose to her first .|
d173b7de-4611-4cdf-934c-912834755e41 |The bad customer .|Jane was working at a diner .| Suddenly , a customer barged up to the counter . |He began yelling about how long his food was taking .| Jane didn’t know how to react .| Luckily , her coworker intervened and calmed the man down .|
==the evaluation framework for this corpus==
- This system is given a four-sentence ‘context’ and two alternative endings to the story, called ‘right ending’ and ‘wrong ending’.
- Hence, in this test the fifth sentence is blank. Then the system’s task is to choose the right ending.
- 简单来说：这个评测就是给出一个故事的plot(前四句话)，让你的模型在训练之后在两个ending（只有一个正确）中选择正确的结局。算是一个二分类问题。
- examples:
- 这个评测现在有很多人在做，后面我会附上一些现有的成果paper。
==our work for this corpus:==
- 我们做的是一个故事生成的任务，旨在根据故事的plot(前4句话)，生成故事的结局（ending，最后一句）
- 现在主要用到的方法：
- seq2seq+attn
- RL
- external knowledge（还在尝试）