This study aimed to enhance third and fourth graders' text comprehension at the situation model level. Therefore, we tested a reading strategy training developed to target inference making skills, which are widely considered to be pivotal to situation model construction. The training was grounded in contemporary literature on situation model-based inference making and addressed the source (text...

We combine state-of-the-art techniques from computational linguistics and theorem proving to build an engine for playing text adventures, computer games with which the player interacts purely through natural language. The system employs a parser for dependency grammar and a generation system based on TAG, and has components for resolving and generating referring expressions. Most of these modul...

We present a new gene prioritization method that learns a probabilistic knowledge model from a knowledge base and free text research documents and exploits it to prioritize candidate genes. The knowledge model is represented by a network of associations among the domain entities (e.g., genes) and is extracted from a domain knowledge base (e.g., protein-protein interaction database) or a corpus ...

________________ One of the most common findings of recent reading research is that drawing inferences is an essential part of the comprehension process, even among young children (Anderson & Pearson, 1984). Dole et al (1991) argues that inference is at the heart of comprehension process. As they construct their own models of meaning for a given text, readers and listeners alike use inferencing...

The vast amounts of on-line text now available have led to renewed interest in information extraction (IE) systems that analyze unrestricted text, producing a structured representation of selected information from the text. This paper presents a novel approach that uses machine learning to acquire knowledge for some of the higher level IE processing. Wrap-Up is a trainable IE discourse componen...

The vast amounts of on-line text now available have led to renewed interest in information extraction (IE) systems that analyze unrestricted text, producing a structured representation of selected information from the text. This paper presents a novel approach that uses machine learning to acquire knowledge for some of the higher level IE processing. Wrap-Up is a trainable IE discourse componen...

In the last decade, members of the computational linguistics community have adopted a perspective on discourse based primarily on either Rhetorical Structure Theory or Grosz and Sidner’s Theory. However, only recently, researchers have started to investigate the relationship between the two perspectives. In this paper, we use Moser and Moore’s (1996) work as a departure point for extending Marc...

This paper describes the PASCAL Network of Excellence Recognising Textual Entailment (RTE) Challenge benchmark 1 . The RTE task is defined as recognizing, given two text fragments, whether the meaning of one text can be inferred (entailed) from the other. This applicationindependent task is suggested as capturing major inferences about the variability of semantic expression which are commonly n...