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[PDF] Top 20 Problems in Evaluating Grammatical Error Detection Systems

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Problems in Evaluating Grammatical Error Detection Systems

Problems in Evaluating Grammatical Error Detection Systems

... (for error detection, Errors) over those of the majority class ...classification problems in which it is more important to correctly classify the minority rather than the majority ...class.” ... See full document

18

Addressing Class Imbalance in Grammatical Error Detection with Evaluation Metric Optimization

Addressing Class Imbalance in Grammatical Error Detection with Evaluation Metric Optimization

... low error rate (number of errors per token) in the corpus (Chodorow et ...the error rates are less than 3% for noun-number, arti- cle and preposition errors in the NUCLE annotated learner corpus (Dahlmeier ... See full document

9

GenERRate: Generating Errors for Use in Grammatical Error Detection

GenERRate: Generating Errors for Use in Grammatical Error Detection

... of error detection systems, in evaluating the robustness of NLP tools and as negative evidence in unsupervised ...between grammatical and ungrammatical ...synthetic error corpus ... See full document

9

Automatic Grammatical Error Detection for Chinese based on Conditional Random Field

Automatic Grammatical Error Detection for Chinese based on Conditional Random Field

... have grammatical errors due to negative migration of their native ...of grammatical errors is not mature enough. Based on the evaluating task ---- CGED2016, we select and analyze the classification ... See full document

6

Grammatical Error Detection and Correction using a Single Maximum Entropy Model

Grammatical Error Detection and Correction using a Single Maximum Entropy Model

... PEOPLE⊕ PROBLEMS BUT MEANS THEREFORE HOWEVER BE- ING : UP PROBLEM ’⊕ THE⊕LEMMA IN⊕ADDITION HOWEVER⊕,⊕ AMONG ;⊕ WHERE THUS ONLY HEALTH HAS⊕PAST FUNDING EXTENT ALSO⊕ TECHNOLOGICAL ” OR HAD WOULD⊕ VERY ... See full document

9

Creating a manually error tagged and shallow parsed learner corpus

Creating a manually error tagged and shallow parsed learner corpus

... manually error-tagged or shallow-parsed, is still ...manually error-tagged and shallow- ...toward evaluating the performance of existing POS- tagging/chunking techniques on learner cor- pora using ... See full document

10

Precision Isn’t Everything: A Hybrid Approach to Grammatical Error Detection

Precision Isn’t Everything: A Hybrid Approach to Grammatical Error Detection

... for detection of each error ...the detection subtask in terms of F-score (labeled ...n-gram systems ap- pear to complement each other well for this task: the base system achieved ...two ... See full document

9

Overview of NLPTEA 2018 Share Task Chinese Grammatical Error Diagnosis

Overview of NLPTEA 2018 Share Task Chinese Grammatical Error Diagnosis

... 2017. Detection-level evaluations are designed to detect whether a sentence contains grammatical errors or ...all systems performed above the ...best detection accuracy of ...the ... See full document

10

Context is Key: Grammatical Error Detection with Contextual Word Representations

Context is Key: Grammatical Error Detection with Contextual Word Representations

... and error grammars ...from error-annotated cor- pora using feature engineering approaches and of- ten utilizing maximum entropy-based classifiers ...of systems targeting specific error types, ... See full document

13

They Can Help: Using Crowdsourcing to Improve the Evaluation of Grammatical Error Detection Systems

They Can Help: Using Crowdsourcing to Improve the Evaluation of Grammatical Error Detection Systems

... two systems, the procedure is general enough to allow two systems to be compared on two dif- ferent datasets by simply examining the two ...the error rates (the proportion of instances that are ... See full document

6

Evaluating performance of grammatical error detection to maximize learning effect

Evaluating performance of grammatical error detection to maximize learning effect

... writing, error detection, and ...the error detection method (Nagata et ...the detection itself takes only a few sec- onds, five minutes are assigned to this step for two purposes: to ... See full document

7

Evaluating the Impact of Morphosyntactic Ambiguity in Grammatical Error Detection

Evaluating the Impact of Morphosyntactic Ambiguity in Grammatical Error Detection

... of error detection ...in grammatical error detection is un- ...precise error detection”. In local syntac- tic error detection the best results have been ... See full document

6

Reference based Metrics can be Replaced with Reference less Metrics in Evaluating Grammatical Error Correction Systems

Reference based Metrics can be Replaced with Reference less Metrics in Evaluating Grammatical Error Correction Systems

... In grammatical error correction (GEC), automatically evaluating system outputs requires gold-standard references, which must be created manually and thus tend to be both expensive and limited in ... See full document

6

Condition Random Fields based Grammatical Error Detection for Chinese as Second Language

Condition Random Fields based Grammatical Error Detection for Chinese as Second Language

... the grammatical structure based on the doc- ument type definiti ...correcting grammatical verb mis- ...verb error correction ...detect grammatical er- rors in sentences written by CFL ...of ... See full document

6

Cross Sentence Grammatical Error Correction

Cross Sentence Grammatical Error Correction

... Automatic grammatical error correction (GEC) research has made remarkable progress in the past decade. However, all existing ap- proaches to GEC correct errors by considering a single sentence alone and ... See full document

11

Grammatical Error Detection Based on Machine Learning for Mandarin as Second Language Learning

Grammatical Error Detection Based on Machine Learning for Mandarin as Second Language Learning

... In this section, The processing flow is illustrated here. There are distinguish two phases: training phase and testing phase. In training phase, we were doing word segmentation and part-of-speech (POS) by CKIP ( Chinese ... See full document

8

A Hybrid Model For Grammatical Error Correction

A Hybrid Model For Grammatical Error Correction

... (Nn) problems while rule-based methods are proposed for subject-verb agreement (SVA) and verb form (Vform) ...sub problems the results of which are combined through a result combination ...interacting ... See full document

8

Corpora Generation for Grammatical Error Correction

Corpora Generation for Grammatical Error Correction

... the Grammatical Error Correc- tion (GEC) task can be credited to approaching the problem as a translation task (Brockett et ...a grammatical target ... See full document

11

System Combination for Grammatical Error Correction

System Combination for Grammatical Error Correction

... The classification approach has been used to deal with the most common grammatical mistakes made by ESL learners, such as article and prepo- sition errors (Han et al., 2006; Chodorow et al., 2007; Tetreault and ... See full document

12

Minimally Augmented Grammatical Error Correction

Minimally Augmented Grammatical Error Correction

... All unsupervised systems benefit from domain- adaptation via fine-tuning on authentic labelled data (Miceli Barone et al., 2017). The more au- thentic high-quality and in-domain training data is used, the greater ... See full document

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