Question generation is the parallel task of question answering, where given an input context and, optionally, answer, goal to generate a relevant and fluent natural language question. Although recent works on have experienced success by utilizing sequence-to-sequence models, there need for models handle increasingly complex contexts produce detailed questions. Multi-hop more challenging that ai...

Evolutionary processes depend on both selection—how fit any given individual may be, and on evolvability—how and how effectively new and fitter individuals are generated over time. While genetic algorithms typically represent the selection process explicitly by the fitness function and the information in the genomes, factors affecting evolvability are most often implicit in and distributed thro...

This paper presents research work performed on the development and the verification of dependable reflective systems based on MetaObject Protocols (MOPs). We describe our experience, we draw the lessons learnt from both a design and a validation viewpoint, and we discuss some possible future trends on this topic. The main originality of this work relies on the combination of both design and val...

As students read expository text, comprehension is improved by pausing to answer questions that reinforce the material. We describe an automatic question generator that uses semantic pattern recognition to create questions of varying depth and type for self-study or tutoring. Throughout, we explore how linguistic considerations inform system design. In the described system, semantic role labels...

With recent advancements in Semantic Web technologies, a new trend in MCQ item generation has emerged through the use of ontologies. Ontologies are knowledge representation structures that formally describe entities in a domain and their relationships, thus enabling automated inference and reasoning. Ontology-based MCQ item generation is still in its infancy, but substantial research efforts ar...

Ontologies provide a structured representation of concepts and the relationships which connect them. This work investigates how a pre-existing educational Biology ontology can be used to generate useful practice questions for students by using the connectivity structure in a novel way. It also introduces a novel way to generate multiple-choice distractors from the ontology, and compares this to...

We present a fresh approach to automatic question generation that significantly increases the percentage of acceptable questions compared to prior state-of-the-art systems. In our evaluation of the top 20 questions, our system generated 71% more acceptable questions by informing the generation process with Natural Language Understanding techniques. The system also introduces our DeconStructure ...

This paper presents a technique to generate distractors for cloze questions in the context of a Computer-Assisted Language Learning tutoring system. The document will focus on an evaluation process used to measure the quality of the distractors that were automatically generated. The main goal of the present study is to be able to include this feature in the tutoring system.

When designing the natural language question asking interface for a formal knowledge base, managing and scoping the user expectations regarding what questions the system can answer is a key challenge. Allowing users to type ask arbitrary English questions will likely result in user frustration, because the system may be unable to answer many questions even if it correctly understands the natura...

We address the problem of automatically generating concise factual questions from linguistically complex sentences in reading materials. We discuss semantic and pragmatic issues that appear in complex sentences, and then we present an algorithm for extracting simplified sentences from appositives, subordinate clauses, and other constructions. We conjecture that our method is useful as a prelimi...