[PDF] Top 20 Using Parse Features for Preposition Selection and Error Detection
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Using Parse Features for Preposition Selection and Error Detection
... writer’s preposition is flagged as an error by the system if its likelihood according to the model satisfied a set of criteria ...writer’s preposition is 0.8 or higher). Un- like the selection ... See full document
6
Chinese Preposition Selection for Grammatical Error Diagnosis
... English preposition error detection has attracted much attention for ...(2008), error detection of nine common prepositions is tackled with the maximum entropy ...the detection ... See full document
12
Model Combination for Correcting Preposition Selection Errors
... grammatical error detection and correction has stud- ied methods based on statistical classifiers (Tetreault and Chodorow, 2008; De Felice and Pulman, 2009; Tetreault et ...classifier using contex- ... See full document
6
Precision Isn’t Everything: A Hybrid Approach to Grammatical Error Detection
... following error types: preposition selection errors (coded “RT” in the data), extraneous prepositions (“UT”), missing prepositions (“MT”), determiner selection errors (“RD”), extraneous de- ... See full document
9
Error Detection for Statistical Machine Translation Using Linguistic Features
... to parse a sentence even when the parser can not fully interpret the entire sentence ...to parse the entire sentence, it ignores one word each time until it finds linkages for remaining ... See full document
8
Tree Kernel based Negation and Speculation Scope Detection with Structured Syntactic Parse Features
... tic parse features contain some complicated and lengthy components, and the flat features cross corpus are ...effective features for the scope detection on differ- ent ... See full document
9
Unsupervised Parse Selection for HPSG
... experimented using gold standard tags, extracted from the gold standard ...idiosyncratic features of words, such as restrictions on preposition forms, mass/count dis- tinctions and comparative versus ... See full document
11
Error Detection Using Linguistic Features
... linguistic features into error de- tection: lexical features of words, and syn- tactic features from a robust lexicalized ...guistic features alone are not as useful as word confidence ... See full document
8
Semantic Role Labeling Using Different Syntactic Views
... new features including fea- tures extracted from dependency parses, ii) performing feature selection and cali- bration and iii) combining parses obtained from semantic parsers trained using dif- ... See full document
8
The Ups and Downs of Preposition Error Detection in ESL Writing
... reported error rates for English prepositions that were as high as 10% in a Japanese learner ...correct selection (“we arrived to the station”), ex- traneous use (“he went to outside”), and omission (“we ... See full document
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Active learning for HPSG parse selection
... HPSG parse se- lection by using selective ...sample selection metrics based on tree en- tropy (Hwa, 2000) and disagreement between two differ- ent parse selection models significantly ... See full document
8
Correcting Preposition Errors in Learner English Using Error Case Frames and Feedback Messages
... called error case frames for correcting preposition ...the preposition is ...generated error case frames achieve a performance comparable to con- ventional methods; (ii) error case ... See full document
11
Software for the quantification of glistenings in intra-ocular lenses
... Before glistenings detection process, we need to specify the region of lens. This front-end includes 2 ways to identify the boundary of the lens. First, user can load lens mask by selecting lens mask image file ... See full document
6
Recognizing Implicit Discourse Relations in the Penn Discourse Treebank
... which features discourse level annotation on both explicit and implicit ...The features we used include contex- tual modeling of relation dependencies, features extracted from constituent ... See full document
9
Proposed methodology for auto error correction and detection for closed loop manufacturing using embedded system
... of features with reference to their resolutions, linearity, measuring range, measuring cycle time, cost ...measurements using above sensors are evidence in Flatness measurement using pressure sensor ... See full document
5
Experimental Investigation on Error Detection...
... OFDM is a modulation technique in that it enables user data to be modulated onto the tones. The information is modulated onto a tone by adjusting the tone's phase, amplitude, or both. In the most basic form, a tone may ... See full document
6
Boosting based Parse Reranking with Subtree Features
... (non-zero) features selected by boosting are around 8,000 and 3,000 in the WSJ parsing and shallow parsing, ...tive features might amount to millions or ... See full document
8
Verb Particle Constructions in Questions
... Verb-particle constructions have been paid con- siderable attention in natural language processing. Baldwin and Villavicencio (2002) detected verb- particle constructions in raw texts on the basis of POS-tagging, ... See full document
6
Informing Determiner and Preposition Error Correction with Hierarchical Word Clustering
... Elghafari, Meurers and Wunsch (2010) showed this surface-based approach to be competitive with published state-of-the-art machine learning ap- proaches using complex feature sets (Gamon et al., 2008; De Felice, ... See full document
8
A Contrastive Analysis of the French and EmbSí Prepositions: The Case Study of ‘Dans’ and ‘Ts’
... French preposition ‘dans’ and the Emb sí ‘tsà’ has revealed that the syntax of prepositions is more alike cross linguistically than any other grammatical ...the preposition ‘tsà’ cannot be combined with a ... See full document
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