Add to ORKGMany exciting things happened since I left the ExtrAns project at the University of Zurich. In this paper I present a very brief journal of the research that derived from my work at Zurich. My work combined a study of several representations of questions and answer sentences with the development of procedures to and the answer. The culmination of this work was the definition of the Logical Graphs (LGs), which are graph representations derived from ExtrAns' original Minimal Logical Forms (MLFs), and the development of a method for the automatic learning of question-answer patterns based on LGs. I hope the reader will enjoy reading this journey of ideas.8 page(s
Due to the rapid growth of knowledge graphs (KG) as representational learning methods in recent year...
The problem of answering complex First-order Logic queries over incomplete knowledge graphs is recei...
Question Answering (QA) systems over Knowledge Graphs (KGs) (KGQA) automatically answer natural lang...
In this paper we present a graph-based approach to question answering. The method assumes a graph re...
In this paper we present a graph-based approach to question answering. The method assumes a graph re...
The shortcomings of traditional Information Retrieval are most evident when users require exact info...
Abstract. The shortcomings of traditional Information Retrieval are most evident when users require ...
This paper presents an Answer Extraction system which works by transforming documents and queries in...
Machine reading comprehension has aroused wide concerns, since it explores the potential of model fo...
Answer Extraction (AE) systems retrieve phrases in textual documents that directly answer natural la...
The role of machine learning algorithms in natural language processing (NLP) tasks has become increa...
The goal of Question-Answering (QA) systems is to find short and correct answers to open-domain ques...
Elementary-level science exams pose sig-nificant knowledge acquisition and rea-soning challenges for...
Kowalski's connection graph method provides a representation for logic programs which allows for the...
Simple questions are the most common type of questions used for evaluating a knowledge graph questio...
Due to the rapid growth of knowledge graphs (KG) as representational learning methods in recent year...
The problem of answering complex First-order Logic queries over incomplete knowledge graphs is recei...
Question Answering (QA) systems over Knowledge Graphs (KGs) (KGQA) automatically answer natural lang...
In this paper we present a graph-based approach to question answering. The method assumes a graph re...
In this paper we present a graph-based approach to question answering. The method assumes a graph re...
The shortcomings of traditional Information Retrieval are most evident when users require exact info...
Abstract. The shortcomings of traditional Information Retrieval are most evident when users require ...
This paper presents an Answer Extraction system which works by transforming documents and queries in...
Machine reading comprehension has aroused wide concerns, since it explores the potential of model fo...
Answer Extraction (AE) systems retrieve phrases in textual documents that directly answer natural la...
The role of machine learning algorithms in natural language processing (NLP) tasks has become increa...
The goal of Question-Answering (QA) systems is to find short and correct answers to open-domain ques...
Elementary-level science exams pose sig-nificant knowledge acquisition and rea-soning challenges for...
Kowalski's connection graph method provides a representation for logic programs which allows for the...
Simple questions are the most common type of questions used for evaluating a knowledge graph questio...
Due to the rapid growth of knowledge graphs (KG) as representational learning methods in recent year...
The problem of answering complex First-order Logic queries over incomplete knowledge graphs is recei...
Question Answering (QA) systems over Knowledge Graphs (KGs) (KGQA) automatically answer natural lang...