Update README.md

README.md

@@ -23,26 +23,41 @@ task_ids:
 - text-scoring
 - dialogue-modeling
 ---
-#### SPOLIN is provided in JSON format
+
+# SPOLIN
 [![CC BY-NC 4.0][cc-by-nc-shield]][cc-by-nc]
 
 
-**First level keys:**
-* `yesands`
-* `non-yesands`
+This is the repo for the paper ["Grounding Conversations with Improvised Dialogues"](https://aclanthology.org/2020.acl-main.218/) (ACL2020). 
+The _Selected Pairs of Learnable ImprovisatioN_ (SPOLIN) corpus is a collection of more than 68,000 "Yes, and" type dialogue pairs extracted from the Spontaneanation podcast by Paul F. Tompkins, the Cornell Movie-Dialogs Corpus, and the SubTle corpus. For more information, refer to our [paper](https://arxiv.org/abs/2004.09544) or our [project page](https://justin-cho.com/spolin).
+
+
+### Available SPOLIN versions:
+The core dataset that was used for the experiments in the paper only includes _yes-ands_ and non-_yes-ands_ from Spontaneanation and most of what is provided in those extracted from the Cornell Movie-Dialogs Corpus. After the submitting the paper, we continued our iterative data augmentation process, repeating another iteration with the Cornell Movie-Dialogs Corpus and extracting from the SubTle corpus. This expanded version is also included in this repository [here](/data). This latest version of SPOLIN was used to train the model used in our [demo](https://spolin.isi.edu). 
+
+
+In the `data` folder, we provide two versions of the SPOLIN training set: 
+1. Version used for experiments in the ACL paper: `data/spolin-train-acl.csv` 
+2. Expanded version: `data/spolin-train.csv`
 
-**Second level keys:**
-* `spont`: shorthand for Spontaneanation
-* `cornell`: shorthand for Cornell Movie-Dialogs Corpus 
-* `subtle`: (not present in `spolin-valid.json`) shorthand for  SubTle Corpus 
+### Relevant links: 
 
-Each second level item is a list of _yes-ands_ or non-_yes-ands_. Each item contains the following: 
-* `id`: dataset ID
-* `prompt`: Utterance that starts the dialogue turn 
-* `response`: Response to the prompt
+* Project page: https://justin-cho.com/spolin
+* Github repo: https://github.com/wise-east/spolin 
+* SpolinBot Demo: https://spolin.isi.edu
+* ACL2020 Paper: https://aclanthology.org/2020.acl-main.218/
 
+**Fiels**
+* `id`: unique identifier
+* `prompt`: first utterance in utterance pair
+* `response`: second utterance in utterance pair 
+* `label`: yesand = 1, non-yesand = 0 
+* `source`: the source for the sample 
+* `split`: whether the sample belongs to the training set or the validation set 
+  
+### Dataset Statistics 
 
-##### `spolin-train.json`:  
+##### `spolin-train.csv`:  
 || yesands| non-yesands|
 |--|---:|---:|
 |Spontaneanation|10,459|5,587*|
@@ -51,7 +66,7 @@ Each second level item is a list of _yes-ands_ or non-_yes-ands_. Each item cont
 |Total|67,188|43,409|
 
 
-##### `spolin-train-acl.json`: 
+##### `spolin-train-acl.csv`: 
 
 || yesands| non-yesands|
 |--|---:|---:|
@@ -59,7 +74,7 @@ Each second level item is a list of _yes-ands_ or non-_yes-ands_. Each item cont
 |Cornell|14,976|17,851|
 |Total|25,435|23,438|
 
-##### `spolin-valid.json`: 
+##### `spolin-valid.csv`: 
 
 || yesands| non-yesands|
 |--|---:|---:|
@@ -69,6 +84,25 @@ Each second level item is a list of _yes-ands_ or non-_yes-ands_. Each item cont
 
 \*Artificially collected by mix & matching positive Spontaneanation samples to balance dataset for training classifier
 
+### ACL Presentation 
+
+[Video recording](https://slideslive.com/38928948/grounding-conversations-with-improvised-dialogues)
+
+
+### Citation
+
+If you use our data for your work, please cite our ACL2020 paper: 
+```
+@inproceedings{cho2020spolin,
+    title={Grounding Conversations with Improvised Dialogues},
+    author={Cho, Hyundong and May, Jonathan},
+    booktitle ={Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics},
+    publisher = {Association for Computational Linguistics}, 
+    location =  {Seattle, Washington, USA},
+    year={2020}
+}  
+```
+
 
 ### License