Group items tagged

The Spanish FrameNet Project is creating an online lexical resource for Spanish, based on frame semantics and supported by corpus evidence. The "starter lexicon" is available to the public, and contains more than 1,000 lexical items (verbs, predicative nouns, and adjectives, adverbs, prepositions and entities) representative of a wide range of semantic domains. The aim is to document the range of semantic and syntactic combinatory possibilities (valences) of each word in each of its senses, through: * human approved and automatic annotated example sentences and * automatic capture and organization of the annotation results. The Spanish FrameNet database will be in a platform-independent format, and it is able to be displayed and queried via the web and other interfaces.

TAGARELA is an intelligent computer-assisted language learning (ICALL) system designed to be fully integrated into the Portuguese Individualized Instruction Program at The Ohio State University. It can be viewed as an intelligent automatic workbook that provides students with opportunities to practice their reading, listening, and writing skills. Because it is a web-based system, it can be used anywhere there is a computer with internet access. TAGARELA uses state-of-the-art Natural Language Processing (NLP) technology to analyze students' input, and detect spelling, morphological, syntactic and semantic errors. Its NLP components allow the system to handle activities that go beyond the usual multiple choice or fill-in-the-blanks used by regular CALL systems. Its exercise types are similar to the ones typically found in current workbooks, such as: * listening and reading comprehension * picture description * vocabulary practice * phrasing and re-writing TAGARELA has a student model that keeps track of each student's individual performance, and an instructor model that carries information about activity and error types. Together the student and instructor models allow the system to choose the best feedback strategy to use with each individual learner based on the level of the activity, type of task, characteristics of error, and learner profile.

Beyond those trillion pages lies an even vaster Web of hidden data: financial information, shopping catalogs, flight schedules, medical research and all kinds of other material stored in databases that remain largely invisible to search engines.

Media Cloud is a system that lets you see the flow of the media. The Internet is fundamentally altering the way that news is produced and distributed, but there are few comprehensive approaches to understanding the nature of these changes. Media Cloud automatically builds an archive of news stories and blog posts from the web, applies language processing, and gives you ways to analyze and visualize the data. The system is still in early development, but we invite you to explore our current data and suggest research ideas. This is an open-source project, and we will be releasing all of the code soon.