Longtonotes: OntoNotes with Longer Coreference Chains

Ontonotes has served as the most important benchmark for coreference resolution. However, for ease of annotation, several long documents in Ontonotes were split into smaller parts. In this work, we build a corpus of coreference-annotated documents of significantly longer length than what is currently available. We do so by providing an accurate, manually-curated, merging of annotations from documents that were split into multiple parts in the original Ontonotes annotation process. The resulting corpus, which we call LongtoNotes contains documents in multiple genres of the English language with varying lengths, the longest of which are up to 8x the length of documents in Ontonotes, and 2x those in Litbank. We evaluate state-of-the-art neural coreference systems on this new corpus, analyze the relationships between model architectures/hyperparameters and document length on performance and efficiency of the models, and demonstrate areas of improvement in long-document coreference modeling revealed by our new corpus. Our data and code is available at: https://github.com/kumar-shridhar/LongtoNotes

An NLP-based Reading Tool for Aiding Non-native English Readers

This paper describes a text-reading tool that makes extensive use of widely available NLP tools and resources to aid non-native English speakers overcome language related hindrances while reading a text. It is a web-based tool, that can be accessed from browsers running on PCs or tablets, and provides the reader with an intelligent e-book functionalit

Individual Differences and Instructed Second Language Acquisition: Insights from Intelligent Computer Assisted Language Learning

The present dissertation focuses on the role of cognitive individual difference factors in the acquisition of second language vocabulary in the context of intelligent computer assisted language learning (ICALL). The aim was to examine the association between working memory and declarative memory and the learning of English phrasal verbs in a web-based ICALL-mediated experiment. Following a pretest-posttest design, 127 adult learners of English were assigned to two instructional conditions, namely meaning-focused and form-focused conditions. Learners in both conditions read news texts on the web for about two weeks; learners in the form-focused condition additionally interacted with the texts via selecting multiple-choice options. The results showed that both working memory and declarative memory were predictive of vocabulary acquisition. However, only the working memory effect was modulated by the instructional context, with the effect being found exclusively in the form-focused condition, and thus suggesting the presence of an aptitude-treatment interaction. Finally, findings also revealed that learning during treatment in the form-focused group was nonlinear, and that paying attention to form and meaning simultaneously impeded global reading comprehension for intermediate, not advanced learners. From a theoretical perspective, the findings provide evidence to suggest that individual differences in both working memory and declarative memory affect the acquisition of lexical knowledge in ICALL-supported contexts. Methodologically, the current study illustrates the advantages of conducting interdisciplinary work between ICALL and second language acquisition by allowing for the collection of experimental data through a web-based, all-encompassing ICALL system. Overall, the present dissertation represents an initial attempt at characterizing who is likely to benefit from ICALL-based interventions