In this short paper, we discuss a straight-forward approach for the identification of noun phrases denoting actors (agents). We use a multilayer perceptron applied to the word embeddings of the head nouns in order to learn a model. A list of 9,000 actors together with 11,000 non-actors generated from a newspaper corpus are used as a silver standard. An evaluation of the results seems to indicate that the model generalises well on unseen data
In general, the task of Named Entity Recognition (NER) is an information extraction subtask which se...
A system for recognition and morphological classification of unknown German words is described. Giv...
Corpus data is often structurally and lexically ambiguous; corpus extraction methodologies thus must...
In this short paper, we discuss a straight-forward approach for the identification of noun phrases d...
In this paper, we discuss work that strives to measure the degree of negativity - the negative polar...
In this paper, we introduce a gold standard for animacy detection comprising almost 14,500 German no...
International audienceWe introduce a generative model for learning person and costume specific detec...
This paper presents a simple distributional method for acquiring event-denoting and object-denoting ...
The thesis describes and analyzes the possible translation counterparts of the German pronoun man wh...
In the latest decades, machine learning approaches have been intensively experimented for natural la...
It is clear that no language exists in isolation and through personal encounters, contact between la...
This paper presents an analysis of semantic association norms for German nouns. In contrast to prior...
We introduce a generative model for learning person and costume specific detectors from labeled exam...
In this paper, we will present a first attempt to classify commonly confused words in German by cons...
The ICEWS dictionaries contain both named individuals or groups, known as actors, and generic indivi...
In general, the task of Named Entity Recognition (NER) is an information extraction subtask which se...
A system for recognition and morphological classification of unknown German words is described. Giv...
Corpus data is often structurally and lexically ambiguous; corpus extraction methodologies thus must...
In this short paper, we discuss a straight-forward approach for the identification of noun phrases d...
In this paper, we discuss work that strives to measure the degree of negativity - the negative polar...
In this paper, we introduce a gold standard for animacy detection comprising almost 14,500 German no...
International audienceWe introduce a generative model for learning person and costume specific detec...
This paper presents a simple distributional method for acquiring event-denoting and object-denoting ...
The thesis describes and analyzes the possible translation counterparts of the German pronoun man wh...
In the latest decades, machine learning approaches have been intensively experimented for natural la...
It is clear that no language exists in isolation and through personal encounters, contact between la...
This paper presents an analysis of semantic association norms for German nouns. In contrast to prior...
We introduce a generative model for learning person and costume specific detectors from labeled exam...
In this paper, we will present a first attempt to classify commonly confused words in German by cons...
The ICEWS dictionaries contain both named individuals or groups, known as actors, and generic indivi...
In general, the task of Named Entity Recognition (NER) is an information extraction subtask which se...
A system for recognition and morphological classification of unknown German words is described. Giv...
Corpus data is often structurally and lexically ambiguous; corpus extraction methodologies thus must...