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Targeted IE methods are transforming into open-ended techniques.
- Michele Banko, Oren Etzioni
- ACL
- 2008
Traditional Information Extraction (IE) takes a relation name and hand-tagged examples of that relation as input. Open IE is a relationindependent extraction paradigm that is tailored to massive and… (More)
- Susan T. Dumais, Michele Banko, Eric Brill, Jimmy J. Lin, Andrew Y. Ng
- SIGIR
- 2002
This paper describes a question answering system that is designed to capitalize on the tremendous amount of data that is now available online. Most question answering systems use a wide variety of… (More)
- Michele Banko, Eric Brill
- ACL
- 2001
The amount of readily available on-line text has reached hundreds of billions of words and continues to grow. Yet for most core natural language tasks, algorithms continue to be optimized, tested and… (More)
- Eric Brill, Jimmy J. Lin, Michele Banko, Susan T. Dumais, Andrew Y. Ng
- TREC
- 2001
INTRODUCTION Data-driven methods have proven to be powerful techniques for natural language processing. It is still unclear to what extent this success can be attributed to specific techniques,… (More)
Extractive summarization techniques cannot generate document summaries shorter than a single sentence, something that is often required. An ideal summarization system would understand each document… (More)
1 3 , 8 1 0 , 0 0 0 T u p l e s ? P r i m a r y E n t i t i e s ? R e l a t i o n s F i l t e r i n g Figure 4.2: Open Extraction from Wikipedia: TextRunner extracts 32.5 million distinct assertions… (More)
Traditional information extraction systems have focused on satisfying precise, narrow, pre-specified requests from small, homogeneous corpora. In contrast, the TextRunner system demonstrates a new… (More)
- Eric Brill, Susan T. Dumais, Michele Banko
- EMNLP
- 2002
We describe the architecture of the AskMSR question answering system and systematically evaluate contributions of different system components to accuracy. The system differs from most question… (More)
- Michele Banko, Robert C. Moore
- COLING
- 2004
We present a new HMM tagger that exploits context on both sides of a word to be tagged, and evaluate it in both the unsupervised and supervised case. Along the way, we present the first comprehensive… (More)