Language engineering for syntactic knowledge transfer

Language engineering for syntactic knowledge transfer

In this paper we present a method for an English-Romanian treebank construction, together with the obtained evaluation results. The treebank is built upon a parallel English-Romanian corpus word-aligned and annotated at the morphological and syntactic level. The syntactic trees of the Romanian texts are generated by considering the syntactic phrases of the English parallel texts automatically r...

Generative Knowledge Transfer for Neural Language Models

In this paper, we propose a generative knowledge transfer technique that trains an RNN based language model (student network) using text and output probabilities generated from a previously trained RNN (teacher network). The text generation can be conducted by either the teacher or the student network. We can also improve the performance by taking the ensemble of soft labels obtained from multi...

Knowledge Transfer with Medical Language Embeddings

Identifying relationships between concepts is a key aspect of scientific knowledge synthesis. Finding these links often requires a researcher to laboriously search through scientific papers and databases, as the size of these resources grows ever larger. In this paper we describe how distributional semantics can be used to unify structured knowledge graphs with unstructured text to predict new ...

Precision engineering for optical applications: knowledge transfer into UK industry

Overcoming the Knowledge Engineering Bottleneck for Understanding Student Language Input

In this paper we present Carmel-Tools, a new set of authoring tools for overcoming the knowledge engineering bottleneck for building tutorial dialogue systems that can accept natural language text input from students. Carmel-Tools provides the facilities for speeding up and simplifying the task of creating domain specific knowledge sources for sentence level language understanding. Carmel-Tools...