Several studies found cross-linguistic structural priming with various language combinations. Here, we investigated the role of two important domains of language variation: case marking and word order, for transitive and ditransitive structures. We varied these features in an artificial language learning paradigm, using three different artificial…

Artificial intelligence revolution becomes a trend in most aspects of life. ChatGPT, an AI chatbot, has impacted various domains, including education and language learning. Enhancing writing abilities of ESL learners requires frequent writing practice and feedback, which ChatGPT can easily provide. However, ChatGPT's accuracy in identifying and…

There is now a well-established literature showing that people anticipate upcoming concepts and words during language processing. Commonsense knowledge about typical event sequences and verbal selectional preferences can contribute to anticipating what will be mentioned next. We here investigate how temporal discourse connectives…

In this article, we describe an online English collocation explorer developed to help English L2 learners produce correct and appropriate collocations. Our tool, which is able to visually represent relevant correct/incorrect collocations on a single webpage, was designed based on the notions of collocation clusters and intercollocability proposed…

This article describes the development of a tense and aspect identifier, an online tool designed to help learners of English by harnessing a natural language processing pipeline to automatically classify verb groups into one of 12 grammatical tenses. Currently, there is no website or application that can automatically identify tense in context,…

This study investigates the relative efficacy of using linguistic micro-features, the aggregation of such features, and a combination of micro-features and aggregated features in developing automatic essay scoring (AES) models. Although the use of aggregated features is widespread in AES systems (e.g., e-rater; Intellimetric), very little…

This study investigates "of"-constructions in the predicates of two reporting verbs, "demonstrate" and "show," in academic discourse. A construction perspective is taken to examine how the two predicate constructions (["demonstrate" N1 "of" N2] and ["show" N1 "of" N2]) would…

The fundamental problem faced by automatic text understanding in Natural Language Processing (NLP) is to identify semantically related pieces of text and integrate them together to compute the meaning of the whole text. However, the principle of compositionality runs into trouble very quickly when real language is examined with its frequent…

The deep semantic understanding necessary for complex natural language processing tasks, such as automatic question-answering or text summarization, would benefit from highly accurate word sense disambiguation (WSD). This dissertation investigates what makes an appropriate and effective sense inventory for WSD. Drawing on theories and…

For over 30 years, reference resolution, the process of determining what a noun phrase including a pronoun refers to in written and spoken language, has been an important and on-going area of research. Most existing pronominal reference resolution algorithms and systems are designed to use syntactic information and surface features (e.g. number…

Natural language often contains dependencies that span words, phrases, or even sentences. Thus, language comprehension relies on recovering recently processed information from memory for subsequent interpretation. This dissertation investigates the memory operations that subserve dependency resolution through the lens of "verb-phrase ellipsis"…

A classifier which is capable of distinguishing a syntactically well formed sentence from a syntactically ill formed one has the potential to be useful in an L2 language-learning context. In this article, we describe a classifier which classifies English sentences as either well formed or ill formed using information gleaned from three different…

Since the seminal work of Gildea and Jurafsky (2000), semantic role labeling (SRL) researchers have been trying to determine the appropriate syntactic/semantic knowledge and statistical algorithms to tackle the challenges in SRL. In search of the appropriate knowledge, SRL researchers shifted from constituency grammar to dependency grammar around…

The three objectives of this dissertation were to develop a question type model for predicting linguistic features of responses to interview questions, create a tool for linguistic analysis of documents, and use lexical bundle analysis to identify linguistic differences between fraudulent and non-fraudulent financial reports. First, The Moffitt…

Although natural language appears to be largely compositional, the meanings of certain expressions cannot be straightforwardly recovered from the meanings of their parts. This study examined the online processing of one such class of expressions: "concealed questions", in which the meaning of a complex noun phrase ("the proof of the theorem")…