Portrait of Lucy Vanderwende

Lucy Vanderwende

Senior Researcher

About

Lucy holds a Ph.D. in Computational Linguistics from Georgetown University, in Washington D.C. Lucy worked at IBM Bethesda on natural language processing from 1988 – 1990. In 1991, she was a Visiting Scientist at the Institute for Systems Science in Singapore.  Lucy has worked at Microsoft Research since 1992.  Lucy was Program Co-Chair for NAACL in 2009 and General Chair for NAACL in 2013. Since 2011, Lucy is also Affiliate Associate Faculty at University of Washington Department of Biomedical Health Informatics, a member of the UW BioNLP group, who are using NLP technology to extract critical information from patient reports.

Research Interests

MindNet: automated acquisition of semantic knowledge
Summarization, focusing on summary generation and evaluation
Making reading more effective
Question Generation
Computer-Assisted Grading
NLPwin, robust, broad-coverage language analysis at Microsoft
NLP and Healthcare

 

Projects

Data-Driven Conversation

This project aims to enable people to converse with their devices. We are trying to teach devices to engage with humans using human language in ways that appear seamless and natural to humans. Our research focuses on statistical methods by…

NLPwin parses AMR

Established: March 17, 2015

The Logical Form analysis produced by the NLPwin parser is very close in spirit to the level of semantic representation defined in AMR, Abstract Meaning Representation. The "NLPwin parses AMR" project is a conversion from LF to AMR in order…

NLPwin

Established: October 3, 2014

An introduction by Lucy Vanderwende* * on behalf of everyone who contributed to the development of NLPwin NLPwin is a software project at Microsoft Research that aims to provide Natural Language Processing tools for Windows (hence, NLPwin). The project was started…

MSR SPLAT

Established: April 4, 2012

Statistical Parsing and Linguistic Analysis Toolkit is a linguistic analysis toolkit. Its main goal is to allow easy access to the linguistic analysis tools produced by the Natural Language Processing group at Microsoft Research. The tools include both traditional linguistic…

Microsoft Research ESL Assistant

Established: May 9, 2008

The Microsoft Research ESL Assistant is a web service that provides correction suggestions for typical ESL (English as a Second Language) errors. Such errors include, for example, the choice of determiners (the/a) and the choice…

MindNet

Established: December 19, 2001

Overview MindNet is a knowledge representation project that uses our broad-coverage parser to build semantic networks from dictionaries, encyclopedias, and free text. MindNets are produced by a fully automatic process that takes the input text, sentence-breaks it, parses each sentence…

Publications

2016

Visual Storytelling
Ting-Hao (Kenneth) Huang, Francis Ferraro, Nasrin Mostafazadeh, Ishan Misra, Aishwarya Agrawal, Jacob Devlin, Ross Girshick, Xiaodong He, Pushmeet Kohli, Dhruv Batra, C. Lawrence Zitnick, Devi Parikh, Lucy Vanderwende, Michel Galley, Margaret Mitchell, in Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL HLT), 2016, ACL – Association for Computational Linguistics, June 13, 2016, View abstract, Download PDF, View external link

2015

2014

2013

2012

2011

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Projects

Commonsense and World Knowledge Link description

Commonsense and World Knowledge

Date

July 24, 2015

Speakers

Benjamin Van Durme, Dan Roth, Lucy Vanderwende, Margaret Mitchell, and Raymond J. Mooney

Affiliation

Microsoft Research, University of Texas at Austin, University of Illinois at Urbana-Champaign, Johns Hopkins University

UW/MS symposium Link description

UW/MS symposium

Date

June 6, 2008

Speakers

Danyel Fisher, Douglas Downey, Chris Quirk, Scott Drellishak, Kelly O'Hara, Emily M. Bender, Sumit Basu, Matthew Hurst, Arnd Christian König, Michael Gamon, Chris Brockett, Dmitriy Belenko, Bill Dolan, Jianfeng Gao, and Lucy Vanderwende

Other

Lucy’s research focuses on text understanding. She is deeply involved with developing MindNet, a method for automatically acquiring semantic information. All types of semantic information can be identified in and extracted from text. Dictionaries can provide the semantic information, for example, that a sheep is an animal; encyclopedias provide specific knowledge, for example, that Armstrong landed on the moon. Specialized data sets provide information on a given topic, for example, that Microsoft Research was founded in 1991. Common sense information can also be extracted from web-scale resources. Such information can be extracted in a variety of ways, from rule-based to completely unsupervised.

Lucy’s focus is to work with applications that demonstrate how the information in a knowledge resource can be used to improve human understanding and productivity.  In particular, she has been involved in several projects in Healthcare that are aimed at understanding and structuring the information contained in unstructured text such as a patient’s clinical records (e.g., for phenotype prediction) or biomedical scientific publications. Understanding the author’s commitment to the reliability of the statement (sometimes called, assertion detection) is key to providing a robust understanding of the text.

Lucy is also excited to be working on ways to make reading more effective. One avenue is to support a reader’s mastery of the text by using Question Generation to create quizzes for arbitrary selections of text. With such quizzes, the reader can see for themselves which part(s) of the text they know and which they should re-read.  The value of open-response questions to support learning is well-known. She is also working on enabling teachers to pose open-response questions by creating a workflow called Powergrading, where the teacher grades clusters of answers simultaneously, identifies answers that don’t belong in the cluster, and provides rich feedback while gaining insight into how well the students are doing in class.