UW-Stanford System Description for AESW 2016 Shared Task on Grammatical Error Detection

نویسندگان

  • Dan Flickinger
  • Michael Goodman
  • Woodley Packard
چکیده

This is a report on the methods used and results obtained by the UW-Stanford team for the Automated Evaluation of Scientific Writing (AESW) Shared Task 2016 on grammatical error detection. This team developed a symbolic grammar-based system augmented with manually defined mal-rules to accommodate and identify instances of highfrequency grammatical errors. System results were entered both for the probabilistic estimation track, where we ranked second, and for the Boolean decision track, where we ranked fourth.

برای دانلود 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

Sentence-Level Grammatical Error Identification as Sequence-to-Sequence Correction

We demonstrate that an attention-based encoder-decoder model can be used for sentence-level grammatical error identification for the Automated Evaluation of Scientific Writing (AESW) Shared Task 2016. The attention-based encoder-decoder models can be used for the generation of corrections, in addition to error identification, which is of interest for certain end-user applications. We show that ...

متن کامل

Feature-Rich Error Detection in Scientific Writing Using Logistic Regression

The goal of the Automatic Evaluation of Scientific Writing (AESW) Shared Task 2016 is to identify sentences in scientific articles which need editing to improve their correctness and readability or to make them better fit within the genre at hand. We encode many different types of errors occurring in the dataset by linguistic features. We use logistic regression to assign a probability indicati...

متن کامل

Overview of NLP-TEA 2016 Shared Task for Chinese Grammatical Error Diagnosis

This paper presents the NLP-TEA 2016 shared task for Chinese grammatical error diagnosis which seeks to identify grammatical error types and their range of occurrence within sentences written by learners of Chinese as foreign language. We describe the task definition, data preparation, performance metrics, and evaluation results. Of the 15 teams registered for this shared task, 9 teams develope...

متن کامل

CoNLL-2013 Shared Task: Grammatical Error Correction NTHU System Description

Grammatical error correction has been an active research area in the field of Natural Language Processing. This paper describes the grammatical error correction system developed at NTHU in participation of the CoNLL-2013 Shared Task. The system consists of four modules in a pipeline to correct errors related to determiners, prepositions, verb forms and noun number. Although more types of errors...

متن کامل

KUNLP Grammatical Error Correction System For CoNLL-2013 Shared Task

This paper describes an English grammatical error correction system for CoNLL2013 shared task. Error types covered by our system are article/determiner, preposition, and noun number agreement. This work is our first attempt on grammatical error correction research. In this work, we only focus on reimplementing the techniques presented before and optimizing the performance. As a result of the im...

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

برای دانلود 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

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2016