Add to ORKGInternational audienceWe introduce an error mining technique for automatically detecting errors in resources that are used in parsing systems. We applied this technique on parsing results produced on several million words by two distinct parsing systems, which share the syntactic lexicon and the pre-parsing processing chain. We were thus able to identify missing and erroneous information in these resources
Syntactic parsing is vital for semantic treatment by many applications related to natural language p...
While the corpus-based research relies on human annotated corpora, it is often said that a non-negli...
In an investigation of the use of a novelty detection algorithm for identifying inapprop...
International audienceWe introduce an error mining technique for automatically detecting errors in r...
In recent years, error mining approaches were developed to help identify the most likely sources of ...
Shortage of available training data is holding back progress in the area of automated error detectio...
AbstractThis paper describes a two-level error repair and recovery scheme applicable to table- drive...
Thesis (Ph.D.)--University of Washington, 2015Automatic speech recognition (ASR), the transcription ...
International audienceThe coverage of a parser depends mostly on the quality of the underlying gramm...
International audienceSuccessful parsing depends on the quality of the underlying grammar but also o...
In this thesis, we investigate methods for automatic detection, and to some extent correction, of gr...
The amount of data being collected is growing exponentially, both in academics as well as in busines...
PEst-OE/EEI/LA0021/2013 SFRH/BD/85737/2012In this paper we describe a corpus of automatic translatio...
We describe Hjerson, a tool for automatic classification of errors in machine translation out-put. T...
International audienceThis research investigates the collocational errors made by English learners i...
Syntactic parsing is vital for semantic treatment by many applications related to natural language p...
While the corpus-based research relies on human annotated corpora, it is often said that a non-negli...
In an investigation of the use of a novelty detection algorithm for identifying inapprop...
International audienceWe introduce an error mining technique for automatically detecting errors in r...
In recent years, error mining approaches were developed to help identify the most likely sources of ...
Shortage of available training data is holding back progress in the area of automated error detectio...
AbstractThis paper describes a two-level error repair and recovery scheme applicable to table- drive...
Thesis (Ph.D.)--University of Washington, 2015Automatic speech recognition (ASR), the transcription ...
International audienceThe coverage of a parser depends mostly on the quality of the underlying gramm...
International audienceSuccessful parsing depends on the quality of the underlying grammar but also o...
In this thesis, we investigate methods for automatic detection, and to some extent correction, of gr...
The amount of data being collected is growing exponentially, both in academics as well as in busines...
PEst-OE/EEI/LA0021/2013 SFRH/BD/85737/2012In this paper we describe a corpus of automatic translatio...
We describe Hjerson, a tool for automatic classification of errors in machine translation out-put. T...
International audienceThis research investigates the collocational errors made by English learners i...
Syntactic parsing is vital for semantic treatment by many applications related to natural language p...
While the corpus-based research relies on human annotated corpora, it is often said that a non-negli...
In an investigation of the use of a novelty detection algorithm for identifying inapprop...