irc-disentanglement

This repository contains data and code for disentangling conversations on IRC, as described in:

Conversation disentanglement is the task of identifying separate conversations in a single stream of messages. For example, the image below shows two entangled conversations and an annotated graph structure (indicated by lines and colours). The example includes a message that receives multiple responses, when multiple people independently help BurgerMann, and the inverse, when the last message responds to multiple messages. We also see two of the users, delire and Seveas, simultaneously participating in two conversations.

Image of an IRC message log with conversations marked

This work:

  1. Introduces a new dataset, with disentanglement for 77,563 messages of IRC.
  2. Introduces a new model, which achieves significantly higher results than prior work.
  3. Re-analyses prior work, identifying issues with data and assumptions in models.

To get our code and data, download this repository in one of these ways:

This repository contains:

Note: this data is being used as part of a task at DSTC 8. We will add the test annotations to this repository once the shared task is complete. After the shared task we will also add a link to a set of 496,469 disentangled conversations.

If you use the data or code in your work, please cite our work as:

@InProceedings{acl19disentangle,
  author    = {Jonathan K. Kummerfeld and Sai R. Gouravajhala and Joseph Peper and Vignesh Athreya and Chulaka Gunasekara and Jatin Ganhotra and Siva Sankalp Patel and Lazaros Polymenakos and Walter S. Lasecki},
  title     = {A Large-Scale Corpus for Conversation Disentanglement},
  booktitle = {Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics},
  location  = {Florence, Italy},
  month     = {July},
  year      = {2019},
  doi       = {10.18653/v1/P19-1374},
  pages     = {3846--3856},
  url       = {https://aclweb.org/anthology/papers/P/P19/P19-1374/},
  arxiv     = {https://arxiv.org/abs/1810.11118},
  software  = {https://jkk.name/irc-disentanglement},
  data      = {https://jkk.name/irc-disentanglement},
}

Questions

If you have a question please either:

Contributions

If you find a bug in the data or code, please submit an issue, or even better, a pull request with a fix. I will be merging fixes into a development branch and only infrequently merging all of those changes into the master branch (at which point this page will be adjusted to note that it is a new release). This approach is intended to balance the need for clear comparisons between systems, while also improving the data.

Acknowledgments

This material is based in part upon work supported by IBM under contract 4915012629. Any opinions, findings, conclusions or recommendations expressed are those of the authors and do not necessarily reflect the views of IBM.