Add to ORKGWe demonstrate that the bidirectionality of deep grammars, allowing them to generate as well as parse sentences, can be used to automatically and effectively identify errors in the grammars. The system is tested on two implemented HPSG grammars: Jacy for Japanese, and the ERG for English. Using this system, we were able to increase generation coverage in Jacy by 18% (45% to 63%) with only four weeks of grammar development.Accepted versio
This work focuses on designing a grammar detection system that understands both structural and conte...
In this dissertation, I investigate valencies and syntactically relevant semantic categories in Nort...
This paper compares a deep and a shallow processing approach to the problem of classifying a sentenc...
We demonstrate that the bidirectionality of deep grammars, allowing them to generate as well as pars...
One of the advantages of deep grammars, such as those based on HPSG, is that they can be used for ge...
Abstract. This article presents the central algorithm of an open system for grammar checking, based ...
This paper explores the issue of automatically generated ungrammatical data and its use in error det...
In this thesis, I show the advantages of using symbolic parsers for Grammatical Error Detection and ...
Shortage of available training data is holding back progress in the area of automated error detectio...
Traditionally, English grammatical error checking is done by English language professionals. However...
Grammar checking is one of the most widely used tools within natural language processing. Many word ...
Typical grammar checking software use some form of natural language parsing to determine if errors e...
Abstract — Applications like word processors and other writing tools typically include a grammar che...
Most state-of-the-art parsers aim to produce an analysis for any input despite errors. However, smal...
We investigate grammatical error detec-tion in spoken language, and present a data-driven method to ...
This work focuses on designing a grammar detection system that understands both structural and conte...
In this dissertation, I investigate valencies and syntactically relevant semantic categories in Nort...
This paper compares a deep and a shallow processing approach to the problem of classifying a sentenc...
We demonstrate that the bidirectionality of deep grammars, allowing them to generate as well as pars...
One of the advantages of deep grammars, such as those based on HPSG, is that they can be used for ge...
Abstract. This article presents the central algorithm of an open system for grammar checking, based ...
This paper explores the issue of automatically generated ungrammatical data and its use in error det...
In this thesis, I show the advantages of using symbolic parsers for Grammatical Error Detection and ...
Shortage of available training data is holding back progress in the area of automated error detectio...
Traditionally, English grammatical error checking is done by English language professionals. However...
Grammar checking is one of the most widely used tools within natural language processing. Many word ...
Typical grammar checking software use some form of natural language parsing to determine if errors e...
Abstract — Applications like word processors and other writing tools typically include a grammar che...
Most state-of-the-art parsers aim to produce an analysis for any input despite errors. However, smal...
We investigate grammatical error detec-tion in spoken language, and present a data-driven method to ...
This work focuses on designing a grammar detection system that understands both structural and conte...
In this dissertation, I investigate valencies and syntactically relevant semantic categories in Nort...
This paper compares a deep and a shallow processing approach to the problem of classifying a sentenc...