IJCNLP-2017 Task 5: Multi-choice Question Answering in Examinations

نویسندگان

  • Shangmin Guo
  • Kang Liu
  • Shizhu He
  • Cao Liu
  • Jun Zhao
  • Zhuoyu Wei
چکیده

The IJCNLP-2017 Multi-choice Question Answering(MCQA) task aims at exploring the performance of current Question Answering(QA) techniques via the realworld complex questions collected from Chinese Senior High School Entrance Examination papers and CK12 website1. The questions are all 4-way multi-choice questions writing in Chinese and English respectively that cover a wide range of subjects, e.g. Biology, History, Life Science and etc. And, all questions are restrained within the elementary and middle school level. During the whole procedure of this task, 7 teams submitted 323 runs in total. This paper describes the collected data, the format and size of these questions, formal run statistics and results, overview and performance statistics of different methods.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

MappSent at IJCNLP-2017 Task 5: A Textual Similarity Approach Applied to Multi-choice Question Answering in Examinations

In this paper we present MappSent, a textual similarity approach that we applied to the multi-choice question answering in exams shared task. MappSent has initially been proposed for question-toquestion similarity (Hazem et al., 2017). In this work, we present the results of two adaptations of MappSent for the question answering task on the English dataset.

متن کامل

JU NITM at IJCNLP-2017 Task 5: A Classification Approach for Answer Selection in Multi-choice Question Answering System

The present task describes the participation of the JU NITM team in IJCNLP2017 Shared Task 5: ”Multi-choice Question Answering in Examinations”. One of the main aims of this shared task is to choose the correct option for each of the multi-choice questions. We represent each of the questions and its corresponding answer in vector space and find the cosine similarity between two vectors. Our pro...

متن کامل

ADAPT Centre Cone Team at IJCNLP-2017 Task 5: A Similarity-Based Logistic Regression Approach to Multi-choice Question Answering in an Examinations Shared Task

We describe the work of a team from the ADAPT Centre in Ireland in addressing automatic answer selection for the Multichoice Question Answering in Examinations shared task. The system is based on a logistic regression over the string similarities between question, answer, and additional text. We obtain the highest grade out of six systems: 48.7% accuracy on a validation set (vs. a baseline of 2...

متن کامل

ALS at IJCNLP-2017 Task 5: Answer Localization System for Multi-Choice Question Answering in Exams

Multi-choice question answering in exams is a typical QA task. To accomplish this task, we present an answer localization method to locate answers shown in web pages, considering structural information and semantic information both. Using this method as basis, we analyze sentences and paragraphs appeared on web pages to get predictions. With this answer localization system, we get effective res...

متن کامل

YNUDLG at IJCNLP-2017 Task 5: A CNN-LSTM Model with Attention for Multi-choice Question Answering in Examinations

“Multi-choice Question Answering in Exams” is a typical question answering task, which aims to test how accurately the participants could answer the questions in exams. Most of the existing QA systems typically rely on handcrafted features and rules to conduct question understanding and/or answer ranking. In this paper, we perform convolutional neural networks (CNN) to learn the joint represent...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2017