| 1 |
Understanding Multimodal Procedural Knowledge by Sequencing Multimodal Instructional Manuals ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 6 |
OntoNotes Release 3.0
|
|
Weischedel, Ralph; Pradhan, Sameer; Ramshaw, Lance; Kaufman; Franchini, Michelle; El-Bachouti, Mohammed; Xue, Nianwen; Palmer, Martha; Marcus, Mitchell; Taylor, Ann; Greenberg, Craig; Hovy, Eduard; Belvin, Robert; Houston, Ann. - : Linguistic Data Consortium, 2009. : https://www.ldc.upenn.edu, 2009
|
|
Abstract:
*Introduction* The OntoNotes project is a collaborative effort between BBN Technologies, the University of Colorado, the University of Pennsylvania, and the University of Southern California's Information Sciences Institute. The goal of the project is to annotate a large corpus comprising various genres of text (news, conversational telephone speech, weblogs, use net, broadcast, talk shows) in three languages (English, Chinese, and Arabic) with structural information (syntax and predicate argument structure) and shallow semantics (word sense linked to an ontology and coreference). OntoNotes Release 3.0 is a continuation of the OntoNotes project and is supported by the Defense Advanced Research Projects Agency, GALE Program Contract No. HR0011-06-C-0022. OntoNotes Release 1.0 (LDC2007T21) contains 400k words of Chinese newswire data (from Xinhua News Agency and Sinorama Magazine) and 300k words of English newswire data (from the Wall Street Journal). OntoNotes Release 2.0 (LDC2008T04) added the following to the corpus: 274k words of Chinese broadcast news data (from China Broadcasting System, China Central TV, China National Radio, China Television System and Voice of America); and 200k words of English broadcast news data (from ABC, CNN, NBC, Public Radio International and Voice of America). OntoNotes Release 3.0 incorporates the following new material: 250k words of English newswire data (from the Wall Street Journal and Xinhua News Agency), 200k of English broadcast news data (from ABC, CNN, NBC, Public Radio International and Voice of America); 200k words of English broadcast conversation material (translated from China Central TV and Phoenix TV); 250k words of Chinese newswire data (from Xinhua News Agency and Sinorama Magazine); 250k words of Chinese broadcast news material (from China Broadcasting System, China Central TV, China National Radio, China Television System and Voice of America); 150k words of Chinese broadcast conversation data (from China Central TV and Phoenix TV); and 200k words of Arabic newswire material (from An Nahar). Natural language applications like machine translation, question answering and summarization currently are forced to depend on impoverished text models like bags of words or n-grams, while the decisions that they are making ought to be based on the meanings of those words in context. That lack of semantics causes problems throughout the applications. Misinterpreting the meaning of an ambiguous word results in failing to extract data, incorrect alignments for translation, and ambiguous language models. Incorrect coreference resolution results in missed information (because a connection is not made) or incorrectly conflated information (due to false connections). OntoNotes builds on two time-tested resources, following the Penn Treebank for syntax and the Penn PropBank for predicate-argument structure. Its semantic representation will include word sense disambiguation for nouns and verbs, with each word sense connected to an ontology, and coreference. The current goals call for annotation of over a million words each of English and Chinese, and half a million words of Arabic over five years. *Data* Each data directory has been stored as a Gnu Zipped Tar File (.tgz) due to the complexity and depth of each directory and the limitations of the ISO CD9660 file system for CD and DVD media. These directories may be easily unpacked using the Unix command line or using utilities such as StuffIt or WinZip under Windows. *Samples* * Arabic * Chinese * English *Sponsorship* This work is supported in part by the Defense Advanced Research Projects Agency, GALE Program Grant No. HR0011-06-1-0003. The content of this publication does not necessarily reflect the position or policy of the Government, and no official endorsement should be inferred. The World is a co-production of Public Radio International and the British Broadcasting Corporation and is produced at WGBH Boston.
|
|
URL: https://catalog.ldc.upenn.edu/LDC2009T24
|
|
BASE
|
|
Hide details
|
|
|
| 14 |
Extracting Dynamic Evidence Networks
|
|
|
|
In: DTIC AND NTIS (2004)
|
|
BASE
|
|
Show details
|
|
|
| 15 |
Challenges in Information Retrieval and Language Modeling
|
|
|
|
In: R. Manmatha (2003)
|
|
BASE
|
|
Show details
|
|
|
| 16 |
Challenges in Information Retrieval and Language Modeling
|
|
|
|
In: Andrew McCallum (2003)
|
|
BASE
|
|
Show details
|
|
|
| 18 |
Algorithms That Learn to Extract Information BBN: Description of the Sift System as Used for MUC-7
|
|
|
|
In: DTIC (1998)
|
|
BASE
|
|
Show details
|
|
|
| 20 |
BBN: Description of the PLUM System as Used for MUC-6
|
|
|
|
In: DTIC (1995)
|
|
BASE
|
|
Show details
|
|
|
|
|
