Negation is an important characteristic of language, and a major component of information
extraction from text. This subtask is of considerable importance to the biomedical domain …

In this paper I look at Natural Language Understanding, an area of Natural Language
Processing aimed at making sense of text, through the lens of a visionary future: what do we …

Automatic negation scope detection is a task that has been tackled using different classifiers
and heuristics. Most systems are however 1) highly-engineered, 2) English-specific, and 3) …

Boxer is a semantic parser for English texts with many input and output possibilities, and
various ways to perform meaning analysis based on Discourse Representation Theory. This …

In this work, we revisit Shared Task 1 from the 2012* SEM Conference: the automated
analysis of negation. Unlike the vast majority of participating systems in 2012, our approach …

We present an end-to-end neural approach to generate English sentences from formal
meaning representations, Discourse Representation Structures (DRSs). We use a rather …

The development of complex and consistent linguistic annotations over large and varied
corpora requires an approach which allows for the incremental improvement of existing …

In many domains of public discourse such as arguments about public policy, there is an
abundance of knowledge to store, query, and reason with. To use this knowledge, we must …

Uncertainty detection plays fundamental role to separate new discovering information from
those are factual information. Uncertainty texts have nonfactual information which could be …

Many language technology applications would benefit from the ability to represent negation
and its scope on top of widely-used linguistic resources. In this paper, we investigate the …