The multilingual entity task (MET) overview

Conference-6 (MUC-6) evaluation of named entity identification demonstrated that systems are approach-ing human performance onEnglish language t xts [10]. Informal and anonymous, the MET provided a new opportunity to assess progress on the same task in Span-ish, Japanese, and Chinese. Preliminary results indicate that MET systems in all three languages performed comparably to those of the MUC-6 evaluatien in English. Based upon the Named Entity Task Guidelines [ 11], the task was to locate and tag with SGML named entity expressions (people, organizations, and locations), time expressions (time and date), and numeric expressions (percentage and money) in Spanish texts from Agence France Presse, in Japanese texts from Kyodo newswire, or in Chinese texts from Xinhua newswkel. Across lan-guages the keywords "press conference " retrieved a rich subcorpus of texts, covering awide spectrum of topics. Frequency and types of expressions vary in the three language sets [2] [8] [9]. The original task guidelines were modified so that he core guidelines were language independent with language specific rules appended. The schedule was quite abbreviated. In the fall, Government language teams retrieved training and test texts with multilingual software for the Fast Data Finder (FDF), refined the MUC-6 guidelines, and manually tagged 100 training texts using the SRA Named Entity Tool. In January, the training texts were released along with 200 sample unannotated training texts to the partic-ipating sites. A dry run was held in late March and early April and in late April the official test on 100 texts was. The language t xts were supplied by the Linguistic Data Consortium (LDC) at the University of Pennsylvania. performed anonymously. SAIC created language ver-sions of the scoring program and provided technical support throughout. Both commercial and academic groups partici-pated. Two groups, New Mexico State University/Com

COSPO/CENDI Industry Day Conference

The conference's objective was to provide a forum where government information managers and industry information technology experts could have an open exchange and discuss their respective needs and compare them to the available, or soon to be available, solutions. Technical summaries and points of contact are provided for the following sessions: secure products, protocols, and encryption; information providers; electronic document management and publishing; information indexing, discovery, and retrieval (IIDR); automated language translators; IIDR - natural language capabilities; IIDR - advanced technologies; IIDR - distributed heterogeneous and large database support; and communications - speed, bandwidth, and wireless

Independent- Feb. 18, 2003

https://neiudc.neiu.edu/independent/1287/thumbnail.jp

The BG News August 23, 2010

The BGSU campus student newspaper August 23, 2010. Volume 101 - Issue 2https://scholarworks.bgsu.edu/bg-news/9266/thumbnail.jp

Ilium 2006

The 2006 yearbook of Taylor University in Upland, Indiana. Theme: Destinationshttps://pillars.taylor.edu/yearbooks/1008/thumbnail.jp

Mustang Daily, April 28-29, 1989

Student newspaper of California Polytechnic State University, San Luis Obispo, CA.https://digitalcommons.calpoly.edu/studentnewspaper/5012/thumbnail.jp

BGSU 1993-1994-1995 Undergraduate Catalog

Bowling Green State University undergraduate catalog for 1993-1994-1995.https://scholarworks.bgsu.edu/catalogs/1013/thumbnail.jp

Financial information extraction using pre-defined and user-definable templates in the Lolita system

Financial operators have today access to an extremely large amount of data, both quantitative and qualitative, real-time or historical and can use this information to support their decision-making process. Quantitative data are largely processed by automatic computer programs, often based on artificial intelligence techniques, that produce quantitative analysis, such as historical price analysis or technical analysis of price behaviour. Differently, little progress has been made in the processing of qualitative data, which mainly consists of financial news articles from financial newspapers or on-line news providers. As a result the financial market players are overloaded with qualitative information which is potentially extremely useful but, due to the lack of time, is often ignored. The goal of this work is to reduce the qualitative data-overload of the financial operators. The research involves the identification of the information in the source financial articles which is relevant for the financial operators' investment decision making process and to implement the associated templates in the LOLITA system. The system should process a large number of source articles and extract specific templates according to the relevant information located in the source articles. The project also involves the design and implementation in LOLITA of a user- definable template interface for allowing the users to easily design new templates using sentences in natural language. This allows user-defined information extraction from source texts. This differs from most of existing information extraction systems which require the developers to code the templates directly in the system. The results of the research have shown that the system performed well in the extraction of financial templates from source articles which would allow the financial operator to reduce his qualitative data-overload. The results have also shown that the user-definable template interface is a viable approach to user-defined information extraction. A trade-off has been identified between the ease of use of the user-definable template interface and the loss of performance compared to hand- coded templates

Redbook: 1997

Advice compiled by Boston University School of Medicine students for incoming first year students and third or fourth year students preparing for clinical rotations