AMR Parsing
49 papers with code • 8 benchmarks • 6 datasets
Each AMR is a single rooted, directed graph. AMRs include PropBank semantic roles, within-sentence coreference, named entities and types, modality, negation, questions, quantities, and so on. See.
Benchmarks
These leaderboards are used to track progress in AMR Parsing
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Bio
Groningen Meaning Bank
Latest papers with no code
Slide, Constrain, Parse, Repeat: Synchronous SlidingWindows for Document AMR Parsing
We evaluate our oracle and parser using the Abstract Meaning Representation (AMR) parsing 3. 0 corpus.
AMR Parsing with Instruction Fine-tuned Pre-trained Language Models
Instruction fine-tuned language models on a collection of instruction annotated datasets (FLAN) have shown highly effective to improve model performance and generalization to unseen tasks.
Strictly Breadth-First AMR Parsing
AMR parsing is the task that maps a sentence to an AMR semantic graph automatically.
Transition-based Abstract Meaning Representation Parsing with Contextual Embeddings
We study a way of combing two of the most successful routes to meaning of language--statistical language models and symbolic semantics formalisms--in the task of semantic parsing.
Spanish Abstract Meaning Representation: Annotation of a General Corpus
The Abstract Meaning Representation (AMR) formalism, designed originally for English, has been adapted to a number of languages.
AMRize, then Parse! Enhancing AMR Parsing with PseudoAMR Data
As Abstract Meaning Representation (AMR) implicitly involves compound semantic annotations, we hypothesize auxiliary tasks which are semantically or formally related can better enhance AMR parsing.
Sequence-to-sequence AMR Parsing with Ancestor Information
AMR parsing is the task that maps a sentence to an AMR semantic graph automatically.
Graph Pre-training for AMR Parsing and Generation
To our knowledge, we are the first to consider pre-training on AMR graphs.
Incorporating EDS Graph for AMR Parsing
AMR (Abstract Meaning Representation) and EDS (Elementary Dependency Structures) are two popular meaning representations in NLP/NLU.
Dependency Patterns of Complex Sentences and Semantic Disambiguation for Abstract Meaning Representation Parsing
Abstract Meaning Representation (AMR) is a sentence-level meaning representation based on predicate argument structure.
