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Accession Number:
AD1044902
Title:
Deep Reading and Learning
Corporate Author:
OREGON STATE UNIV CORVALLIS CORVALLIS United States
Report Date:
2017-10-01
Abstract:
Our project made significant progress on several subtasks of natural language processing NLP including, part of speech tagging, chunking, named entity recognition, co-reference resolution, linking, event detection, event-argument extraction, and script learning. The unifying theme is an algorithmic framework based on search-based structured prediction. Almost all tasks in NLP can be formulated as mapping a structured input, e.g., a sentence or a document, into a structured output, e.g., a knowledge base. The problem of learning this mapping from supervisory training data is called structured prediction. In search-based structured prediction, this mapping is constructed incrementally via heuristic search. We adapted several variations of heuristic search algorithms including greedy search, beam search, and limited discrepancy search to structured prediction, achieving state of the art results in multiple subtasks of NLP. We published our work in conferences such as ICML, AAAI, EMNLP and ACL and journals such as JAIR and JMLR.
Descriptive Note:
Technical Report,01 Oct 2012,30 Jun 2017
Pages:
0017
Distribution Statement:
Approved For Public Release;
Contract Number:
FA8750-13-2-0033
File Size:
0.65MB
