We present Charagram embeddings, a simple approach for learning character-based
compositional models to embed textual sequences. A word or sentence is represented using …

The Parallel Meaning Bank is a corpus of translations annotated with shared, formal
meaning representations comprising over 11 million words divided over four languages …

The goal of the Groningen Meaning Bank (GMB) is to obtain a large corpus of English texts
annotated with formal meaning representations. Since manually annotating a …

In this paper, we present a rule-based sentence boundary disambiguation Python package
that works out-of-the-box for 22 languages. We aim to provide a realistic segmenter which …

Neural methods have had several recent successes in semantic parsing, though they have
yet to face the challenge of producing meaning representations based on formal semantics …

We propose a novel semantic tagging task, sem-tagging, tailored for the purpose of
multilingual semantic parsing, and present the first tagger using deep residual networks …

Tweets often contain a large proportion of abbreviations, alternative spellings, novel words
and other non-canonical language. These features are problematic for standard language …

We combine character-level and contextual language model representations to improve
performance on Discourse Representation Structure parsing. Character representations can …

Semantic parsing offers many opportunities to improve natural language understanding. We
present a semantically annotated parallel corpus for English, German, Italian, and Dutch …

Modern OCR engines incorporate some form of error correction, typically based on
dictionaries. However, there are still residual errors that decrease performance of natural …