semantic role
Semantic Role Labelling of Prepositional Phrases
... the semantic tag- ging of prepositions is somewhat ...with semantic roles is small – around 57,000 PPs out of the million-word Treebank ...preposition semantic roles were tagged only in cer- tain ...
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Polyglot Semantic Role Labeling
... Ammar et al. (2016a) found that using train- ing data from multiple languages annotated with Universal Dependencies (Nivre et al., 2016), and represented using multilingual word vectors, out- performed monolingual ...
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Semi Supervised Semantic Role Labeling
... as training data for semantic role labeling sys- tems. However, the applicability of these sys- tems is limited to those words for which labeled data exists, and their accuracy is strongly corre- lated with ...
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Multi Predicate Semantic Role Labeling
... to Semantic Role Labeling (SRL) usually perform role clas- sification for each predicate separately and the interaction among individual predi- cate’s role labeling is ignored if there is more ...
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Collective Semantic Role Labeling on Open News Corpus by Leveraging Redundancy
... Semantic Role Labeling (SRL, Màrquez, 2009) is generally understood as the task of identifying the arguments of a given predicate and assigning them semantic labels describing the roles they ...
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Revisiting Arabic Semantic Role Labeling using SVM Kernel Methods
... As a critical language, there is huge potential for the usefulness of an Arabic Semantic Role Labeling (SRL) system. This task involves two subtasks: predicate argument boundary detection and argument ...
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Syntax for Semantic Role Labeling, To Be, Or Not To Be
... Semantic role labeling was pioneered by Gildea and Jurafsky (2002). Most traditional SRL models rely heavily on feature templates (Pradhan et al., 2005; Zhao et al., 2009b; Bj¨orkelund et al., 2009). Among ...
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Vietnamese Semantic Role Labelling
... In a second step, each argument candidate is labelled with a semantic role. Every SRL system has a classification model which can be classified into two types, independent model or joint model. While an ...
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Romanian Semantic Role Resource
... Annotated language resources have became a must in natural language processing, especially for supervised learning (training and evaluation), unsupervised learning (evaluation), hand-crafted systems (evaluation), etc. ...
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Grounded Semantic Role Labeling
... grounded semantic role labeling. Besides semantic roles ex- plicitly mentioned in language descriptions, our ap- proach also grounds implicit roles which are not explicitly ...mantic role ...
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Towards Robust Semantic Role Labeling
... Most semantic role labeling (SRL) research has been focused on training and evaluating on the same corpus. This strategy, although appropriate for initiating research, can lead to over- training to the ...
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Selectional Preferences for Semantic Role Classification
... as semantic relations, similar to those of semantic role ...extended semantic role labeling in which they show that determining the sense of the preposition is mutually related to the ...
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Tree Kernels for Semantic Role Labeling
... of semantic role annotations, they provide an easy way to engineer new features which enhance the state-of-the-art in ...recognition, role classification, and re-ranking stages are presented in ...
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Chinese Semantic Role Labeling using High quality Syntactic Knowledge
... The CoNLL-2009 shared task (Hajiˇc et al., 2009) features a substantial number of studies on SRL that used Propbank as one of the resources. These work can be categorized into two types: joint learning of syntactic ...
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Semantic Mapping Using Automatic Word Alignment and Semantic Role Labeling
... For semantic role labeling (SRL), we built our own system using a fairly standard approach: SRL is posed as a multi-class classification problem requir- ing the identification of argument candidates for ...
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Exploring Multilingual Semantic Role Labeling
... Semantic role labeling, which aims at computa- tionally identifying and labeling arguments of predicate words, has become a leading research problem in computational linguistics with the ad- vent of various ...
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Semantic Role Labeling of Chinese Using Transductive SVM and Semantic Heuristics
... Traditional semantic research is mainly concerned with deep analysis, which pro- vides a representation of the sentence in predicate logic or other formal ...low semantic parsing is becoming a hotspot in ...
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Improving Implicit Semantic Role Labeling by Predicting Semantic Frame Arguments
... Implicit semantic role labeling (iSRL) is the task of predicting the semantic roles of a predicate that do not appear as explicit ar- guments, but rather regard common sense knowledge or are ...
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Semantic Role Tagging for Chinese at the Lexical Level
... The study reported in this paper has thus tackled the unknown constituent boundary condition in semantic role labelling for Chinese, by attempting to locate the corre- sponding headwords first. We ...
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Enhancing Opinion Role Labeling with Semantic Aware Word Representations from Semantic Role Labeling
... Opinion role labeling (ORL) is an important task for fine-grained opinion mining, which identifies important opinion arguments such as holder and target for a given opinion ...with semantic role ...
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