Out of domain corpora in semantic role labeling (SRL) are quite rare in the literature. Frequently used corpora are CoNLL05 and CoNLL2012 as input and evaluating gold data for neural network models but they lack specialized data. We propose CTeTex SRL, the first, to our knowledge, software requirement specification (SRS) corpora annotated in SRL. We followed the Proposition Bank’s guidelines and applied new conventions to better treat linguistic features of an out of domain dataset. CTeTex SRL is composed of 196 SRS each manually annotated in SRL with an interannotator agreement of 82% for argument labeling. We hope this first gold SRS corpora can be used to evaluate neural network driven semantic role labeling models and we hope our enrich...
This paper addresses Semantic Role Labeling (SRL) within the context of English Discourse Representa...
The predicate-argument structure (PAS) of a natural language sentence is a useful representation tha...
Large-scale annotated corpora are a prerequisite to developing high-performance NLP systems. Such co...
In recent years, thanks to the relative maturity of neural network models, the task of automaticall...
© 2014 IEEE. We propose a method for adapting Semantic Role Labeling (SRL) systems from a source dom...
We present a new method for semantic role labeling in which arguments and seman-tic roles are jointl...
Semantic role labeling (SRL) is a method for the semantic analysis of texts that adds a level of sem...
The natural language processing (NLP) community has recently experienced a growing interest in seman...
Semantic role labelling (SRL) is a natural language processing (NLP) technique that maps sentences t...
We present the first experiment-based study that explicitly contrasts the three major semantic role ...
We explore the extent to which high-resource manual annotations such as tree-banks are necessary for...
We present an approach for Seman-tic Role Labeling (SRL) using Condi-tional Random Fields in a joint...
We present an approach to automatic semantic role labeling (SRL) carried out in the context of the ...
Correctly identifying semantic entities and successfully disambiguating the relations between them a...
The identication and classication of some circumstance semantic roles like Location, Time, Manner an...
This paper addresses Semantic Role Labeling (SRL) within the context of English Discourse Representa...
The predicate-argument structure (PAS) of a natural language sentence is a useful representation tha...
Large-scale annotated corpora are a prerequisite to developing high-performance NLP systems. Such co...
In recent years, thanks to the relative maturity of neural network models, the task of automaticall...
© 2014 IEEE. We propose a method for adapting Semantic Role Labeling (SRL) systems from a source dom...
We present a new method for semantic role labeling in which arguments and seman-tic roles are jointl...
Semantic role labeling (SRL) is a method for the semantic analysis of texts that adds a level of sem...
The natural language processing (NLP) community has recently experienced a growing interest in seman...
Semantic role labelling (SRL) is a natural language processing (NLP) technique that maps sentences t...
We present the first experiment-based study that explicitly contrasts the three major semantic role ...
We explore the extent to which high-resource manual annotations such as tree-banks are necessary for...
We present an approach for Seman-tic Role Labeling (SRL) using Condi-tional Random Fields in a joint...
We present an approach to automatic semantic role labeling (SRL) carried out in the context of the ...
Correctly identifying semantic entities and successfully disambiguating the relations between them a...
The identication and classication of some circumstance semantic roles like Location, Time, Manner an...
This paper addresses Semantic Role Labeling (SRL) within the context of English Discourse Representa...
The predicate-argument structure (PAS) of a natural language sentence is a useful representation tha...
Large-scale annotated corpora are a prerequisite to developing high-performance NLP systems. Such co...