Search Results for author: Lucia Donatelli

Found 14 papers, 3 papers with code

Aligning Actions Across Recipe Graphs

1 code implementation EMNLP 2021 Lucia Donatelli, Theresa Schmidt, Debanjali Biswas, Arne Köhn, Fangzhou Zhai, Alexander Koller

Recipe texts are an idiosyncratic form of instructional language that pose unique challenges for automatic understanding.

A Continuation Semantics for Abstract Meaning Representation

1 code implementation DMR (COLING) 2020 Kenneth Lai, Lucia Donatelli, James Pustejovsky

Abstract Meaning Representation (AMR) is a simple, expressive semantic framework whose emphasis on predicate-argument structure is effective for many tasks.

Translation

Representing Implicit Positive Meaning of Negated Statements in AMR

no code implementations EMNLP (LAW, DMR) 2021 Katharina Stein, Lucia Donatelli

Abstract Meaning Representation (AMR) has become popular for representing the meaning of natural language in graph structures.

Spanish Abstract Meaning Representation: Annotation of a General Corpus

no code implementations15 Apr 2022 Shira Wein, Lucia Donatelli, Ethan Ricker, Calvin Engstrom, Alex Nelson, Nathan Schneider

The Abstract Meaning Representation (AMR) formalism, designed originally for English, has been adapted to a number of languages.

AMR Parsing

Compositional Generalization Requires Compositional Parsers

no code implementations24 Feb 2022 Pia Weißenhorn, Yuekun Yao, Lucia Donatelli, Alexander Koller

A rapidly growing body of research on compositional generalization investigates the ability of a semantic parser to dynamically recombine linguistic elements seen in training into unseen sequences.

A Two-Level Interpretation of Modality in Human-Robot Dialogue

no code implementations COLING 2020 Lucia Donatelli, Kenneth Lai, James Pustejovsky

We analyze the use and interpretation of modal expressions in a corpus of situated human-robot dialogue and ask how to effectively represent these expressions for automatic learning.

Dialogue-AMR: Abstract Meaning Representation for Dialogue

no code implementations LREC 2020 Claire Bonial, Lucia Donatelli, Mitchell Abrams, Stephanie M. Lukin, Stephen Tratz, Matthew Marge, Ron artstein, David Traum, Clare Voss

This paper describes a schema that enriches Abstract Meaning Representation (AMR) in order to provide a semantic representation for facilitating Natural Language Understanding (NLU) in dialogue systems.

Natural Language Understanding

Normalizing Compositional Structures Across Graphbanks

1 code implementation COLING 2020 Lucia Donatelli, Jonas Groschwitz, Alexander Koller, Matthias Lindemann, Pia Weißenhorn

The emergence of a variety of graph-based meaning representations (MRs) has sparked an important conversation about how to adequately represent semantic structure.

Multi-Task Learning Semantic Parsing

Saarland at MRP 2019: Compositional parsing across all graphbanks

no code implementations CONLL 2019 Lucia Donatelli, Meaghan Fowlie, Jonas Groschwitz, Alex Koller, er, Matthias Lindemann, Mario Mina, Pia Wei{\ss}enhorn

We describe the Saarland University submission to the shared task on Cross-Framework Meaning Representation Parsing (MRP) at the 2019 Conference on Computational Natural Language Learning (CoNLL).

Augmenting Abstract Meaning Representation for Human-Robot Dialogue

no code implementations WS 2019 Claire Bonial, Lucia Donatelli, Stephanie M. Lukin, Stephen Tratz, Ron artstein, David Traum, Clare Voss

We detail refinements made to Abstract Meaning Representation (AMR) that make the representation more suitable for supporting a situated dialogue system, where a human remotely controls a robot for purposes of search and rescue and reconnaissance.

Annotation of Tense and Aspect Semantics for Sentential AMR

no code implementations COLING 2018 Lucia Donatelli, Michael Regan, William Croft, Nathan Schneider

Although English grammar encodes a number of semantic contrasts with tense and aspect marking, these semantics are currently ignored by Abstract Meaning Representation (AMR) annotations.

Entity Typing

Towards a Computational Lexicon for Moroccan Darija: Words, Idioms, and Constructions

no code implementations COLING 2018 Jamal Laoudi, Claire Bonial, Lucia Donatelli, Stephen Tratz, Clare Voss

In this paper, we explore the challenges of building a computational lexicon for Moroccan Darija (MD), an Arabic dialect spoken by over 32 million people worldwide but which only recently has begun appearing frequently in written form in social media.

Machine Translation

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