Peter E. Clark

Exploring Markov Logic Networks for Question Answering

2015

Elementary-level science exams pose sig-nificant knowledge acquisition and rea-soning challenges for automatic question answering. We develop a system that rea-sons with knowledge derived from text-books, represented in a subset of first-order logic. Automatic extraction, while …

Declarative Question Answering over Knowledge Bases Containing Natural Language Text with Answer Set Programming

2019 · Proceedings of the AAAI Conference on Artificial Intelligence

While in recent years machine learning (ML) based approaches have been the popular approach in developing endto-end question answering systems, such systems often struggle when additional knowledge is needed to correctly answer the questions. Proposed …

Multi-class Hierarchical Question Classification for Multiple Choice Science Exams

2019 · arXiv (Cornell University)

Prior work has demonstrated that question classification (QC), recognizing the problem domain of a question, can help answer it more accurately. However, developing strong QC algorithms has been hindered by the limited size and complexity …

Learning Knowledge Graphs for Question Answering through Conversational Dialog

2015

We describe how a question-answering system can learn about its domain from conversational dialogs. Our system learns to relate concepts in science questions to propositions in a fact corpus, stores new concepts and relations in …

Combining Retrieval, Statistics, and Inference to Answer Elementary Science Questions

2016 · Proceedings of the AAAI Conference on Artificial Intelligence

What capabilities are required for an AI system to pass standard 4th Grade Science Tests? Previous work has examined the use of Markov Logic Networks (MLNs) to represent the requisite background knowledge and interpret test …

SciTaiL: A Textual Entailment Dataset from Science Question Answering

2018 · Proceedings of the AAAI Conference on Artificial Intelligence

We present a new dataset and model for textual entailment, derived from treating multiple-choice question-answering as an entailment problem. SciTail is the first entailment set that is created solely from natural sentences that already exist …

Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

2018 · arXiv (Cornell University)

We present a new question set, text corpus, and baselines assembled to encourage AI research in advanced question answering. Together, these constitute the AI2 Reasoning Challenge (ARC), which requires far more powerful knowledge and reasoning …

Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering

2018

We present a new kind of question answering dataset, OpenBookQA, modeled after open book exams for assessing human understanding of a subject. The open book that comes with our questions is a set of 1326 …

QUAREL: A Dataset and Models for Answering Questions about Qualitative Relationships

2019

Many natural la guage questions require recognizing and reasoning with qualitative relationships (e.g., in science, economics, and medicine), but are challenging to answer with corpus-based methods. Qualitative modeling provides tools that support such reasoning, but …

QuaRTz: An Open-Domain Dataset of Qualitative Relationship Questions

2019

Oyvind Tafjord, Matt Gardner, Kevin Lin, Peter Clark. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). 2019.

QASC: A Dataset for Question Answering via Sentence Composition

2020

Composing knowledge from multiple pieces of texts is a key challenge in multi-hop question answering. We present a multi-hop reasoning dataset, Question Answering via Sentence Composition (QASC), that requires retrieving facts from a large corpus …

GenericsKB: A Knowledge Base of Generic Statements

2020 · arXiv (Cornell University)

We present a new resource for the NLP community, namely a large (3.5M+ sentence) knowledge base of *generic statements*, e.g., "Trees remove carbon dioxide from the atmosphere", collected from multiple corpora. This is the first …