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The Parallel Meaning Bank: Towards a Multilingual Corpus of Translations Annotated with Compositional Meaning Representations
TLDR
The approach is based on cross-lingual projection: automatically produced (and manually corrected) semantic annotations for English sentences are mapped onto their word-aligned translations, assuming that the translations are meaning-preserving. Expand
Evaluating Scoped Meaning Representations
TLDR
This work presents a semantically annotated parallel corpus for English, German, Italian, and Dutch where sentences are aligned with scoped meaning representations in order to capture the semantics of negation, modals, quantification, and presupposition triggers. Expand
Exploring Neural Methods for Parsing Discourse Representation Structures
TLDR
This work presents a sequence-to-sequence neural semantic parser that is able to produce Discourse Representation Structures (DRSs) for English sentences with high accuracy, outperforming traditional DRS parsers. Expand
HELP: A Dataset for Identifying Shortcomings of Neural Models in Monotonicity Reasoning
TLDR
A new dataset, called HELP, is introduced for handling entailments with lexical and logical phenomena and it is found that some types of inferences can be improved by the data augmentation while others are immune to it. Expand
Towards Universal Semantic Tagging
TLDR
The paper presents the initial version of the semantic tagset and shows that (a) the tags provide semantically fine-grained information, and (b) they are suitable for cross-lingual semantic parsing. Expand
Can Neural Networks Understand Monotonicity Reasoning?
TLDR
The Monotonicity Entailment Dataset (MED) is introduced, and analysis using a monotonicity-driven data augmentation method showed that state-of-the-art NLI models might be limited in their generalization ability in upward and downward reasoning. Expand
MRP 2020: The Second Shared Task on Cross-Framework and Cross-Lingual Meaning Representation Parsing
The 2020 Shared Task at the Conference for Computational Language Learning (CoNLL) was devoted to Meaning Representation Parsing (MRP) across frameworks and languages. Extending a similar setup fromExpand
LangPro: Natural Language Theorem Prover
TLDR
LangPro is an automated theorem prover for natural language that is able to prove semantic relations between them given a set of premises and a hypothesis, and achieves high results comparable to state-of-the-art. Expand
A Tableau Prover for Natural Logic and Language
TLDR
A theorem prover for Natural Logic, a logic whose terms resemble natural language expressions based on an analytic tableau method and employs syntactically and semantically motivated schematic rules is designed. Expand
The First Shared Task on Discourse Representation Structure Parsing
TLDR
The paper presents the IWCS 2019 shared task on semantic parsing where the goal is to produce Discourse Representation Structures (DRSs) for English sentences and displayed improvements over the existing state-of-the-art parser. Expand
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