The nature of the relationship between (computational) linguistics and natural language processing remains a hot topic in the field. There is at this point a substantial history of workshops focused on how to get the most out of this interaction, including at least:
- An invited plenary symposium on Computational Linguistics in Support of Linguistic Analysis at the 2009 meeting of the Linguistic Society of America and the associated special issue of Linguistic Issues in Language Technology
- The EACL 2009 Workshop on the Interaction between Linguistics and Computational Linguistics: Virtuous, Vicious or Vacuous? and the associated special issue of Linguistic Issues in Language Technology
- The ACL 2010 Workshop on NLP and Linguistics: Finding the Common Ground
- The Workshops on the Use of Computational Methods in the Study of Endangered Languages at ACL 2014 and ICLDC 2017
- The EMNLP 2017 Workshop on Building Linguistically Generalizable NLP Systems
- The Workshop Perceptrons and Syntactic Structures at Sixty, held jointly with the inaugural meeting of the Society for Computational in Linguistics
- The ACL 2018 Workshop on the Relevance of Linguistic Structure in Neural NLP
[There are undoubtedly more! Please let us know what we’ve missed in the comments and we’ll add them to this list.]
The interaction between the fields also tends to be a hot-button topic on Twitter, leading to very long and sometimes informative discussions, such as the NLP/CL Megathread of April 2017 (as captured by Sebastian Mielke) or the November 2017 discussion on linguistics, NLP, and interdisciplinarity, summarized in blog posts by Emily M. Bender and Ryan Cotterell.
It is very important to us as PC co-chairs of COLING 2018 to continue the COLING tradition of providing a venue that encourages interdisciplinary work. COLING as a venue should host both computationally-aided linguistic analysis and linguistically informed work on natural language processing. Furthermore, it should provide a space for authors of each of these kinds of papers to provide feedback to each other.
Actions we have taken so far to support this vision include recruiting area chairs whose expertise spans the two fields as well as in the design of our paper types and associated review forms.
We’d like to see even more discussion of how interdiscipinarity works/can work in our field. What do you consider to be best practices for carrying out such interdisciplinary work? What role do you see for linguistics in NLP/how do computational methods inform your linguistic research? How do you build and maintain collaborations? When you read (or review) in this field, what kind of features of a paper stand out for you as particularly good approaches to interdisciplinary work? Finally, how can COLING further support such best practices?