In this paper, we introduce a large-scale test collection for multiple document summarization, the Text Summarization Challenge 3 (TSC3) corpus. We detail the corpus construction and evaluation measures. The significant feature of the corpus is that it annotates not only the important sentences in a document set, but also those among them that have the same content. Moreover, we define new evaluation metrics taking redundancy into account and discuss the effectiveness of redundancy minimization.
We report the outline of Text Summarization Challenge 2 (TSC2 hereafter), a sequel text summarization evaluation conducted as one of the tasks at the NTCIR Workshop 3. First, we describe briefly the previous evaluation, Text Summarization Challenge (TSC1) as introduction to TSC2. Then we explain TSC2 including the participants, the two tasks in TSC2, data used, evaluation methods for each task, and brief report on the results. Lastly we describe plans for the next evaluation, TSC3.
We are aiming to acquire named entity (NE) translation knowledge from nonparallel, content-aligned corpora, by utilizing NE extraction techniques. For this research, we are constructing a Japanese-English broadcast news corpus with NE tags. The tags represent not only NE class information but also coreference information within the same monolingual document and between corresponding Japanese-English document pairs. Analysis of about 1,100 annotated article pairs has shown that if NE occurrence information, such as classes, number of occurrence and occurrence order, is given for each language, it may provide a good clue for corresponding NEs across languages.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.