The WebNLG challenge consists in mapping sets of RDF triples to text. It provides a
common benchmark on which to train, evaluate and compare “microplanners”, ie generation …

The problem of AMR-to-text generation is to recover a text representing the same meaning
as an input AMR graph. The current state-of-the-art method uses a sequence-to-sequence …

Data-to-text generation can be conceptually divided into two parts: ordering and structuring
the information (planning), and generating fluent language describing the information …

In this report we summarize the results of the 2017 AMR SemEval shared task. The task
consisted of two separate yet related subtasks. In the parsing subtask, participants were …

Generating text from structured data is challenging because it requires bridging the gap
between (i) structure and natural language (NL) and (ii) semantically underspecified input …

A Portable Grammar-based NLG System for Verbalization of Structured Data Page 1 A portable
grammar-based NLG system for verbalization of structured data Simon Mille Universitat Pompeu …

We present a generic deep realizer called GenDR, which takes as input an abstract
semantic representation of predicate-argument relations, and produces corresponding …

Dialogue‐based systems often consist of several components, such as communication
analysis, dialogue management, domain reasoning, and language generation. In this paper …

According to urban planner Kevin Lynch, imageability is the ability of a physical object to
evoke a strong image in any viewer, making it memorable. The concept of imageability is …

Today, one of the most widely used natural language representation methods is meaning
representation for text processing in different systems. Meaning representation methods …