The Natural Language Group


AMR: Abstract Meaning Representation

The AMR Bank is a set of English sentences paired with simple, readable semantic representations.  We hope that it will spur new research in natural language understanding, generation, and translation.  Please visit the AMR page for details. Thanks to NSF (IIS-0908532) for funding the initial design of AMR, and to DARPA MRP (FA-8750-09-C-0179) for supporting a group to construct consensus annotations and the AMR Editor. The initial AMR bank was built under DARPA DEFT FA-8750-13-2-0045 (PI: Stephanie Strassel; co-PIs: Kevin Knight, Daniel Marcu, and Martha Palmer) and DARPA BOLT HR0011-12-C-0014 (PI: Kevin Knight).

CWIC: Communicating Intelligently with Computers

In this project, we work on human/robot communication, and on creative language generation.This work is supported by Contract W911NF-15-1-0543 with the US Defense Advanced Research Projects Agency (DARPA).


DECODE: Deciphering Historical Manuscripts

In collaboration with colleagues at Uppsala University (Sweden), we are collecting enciphered manuscripts from the European modern era (1600-1800) and developing software to automatically decipher them. This work is supported by the Swedish Research Council and a gift from Google, Inc.

DIG: Domain-Specific Insight Graphs

DIG is a domain-specific indexing, search and analysis system. The DIG system harnesses state-of-the-art open source software combined with an open architecture and flexible set of APIs to facilitate the integration of a variety of extraction and analysis tools.  Please visit the DIG page for more details.  This research is supported in part by the Defense Advanced Research Projects Agency (DARPA) and the Air Force Research Laboratory (AFRL) under contract number FA8750-14-C-0240, and in part by the National Science Foundation under Grant No. 1117913.

ELISA: Exploiting Language Information for Situational Awareness

Today's automatic parsers, translators, extractors, and dictionaries cover a tiny fraction of the world's languages. Can we use general knowledge of how language works to extend the reach of natural language tools?  In this project, we develop technology for rapidly constructing information extraction (IE), machine translation (MT), and topic and sentiment processing capabilities for new languages.  Our collaborators are ICSI, Brno University of Technology, University of Pennsylvania, University of Notre Dame, Rensselaer Polytechnic Institute, and Next Century, Inc.  This work is carried out with funding from DARPA (HR0011-15-C-0115).

L2K2R2: Learning to Know to Read

Scientists are overwhelmed with scientific literature. If we can build machines to read scientific papers and understand them, we can help science move faster.  This work is sponsored by DARPA Big Mechanism (W911NF-14-1-0364).