arXiv:1608.06111
공식 코드 · Papers with Code
An Incremental Parser for Abstract Meaning Representation
원문 초록
Meaning Representation (AMR) is a semantic representation for natural language that embeds annotations related to traditional tasks such as named entity recognition, semantic role labeling, word sense disambiguation and co-reference resolution. We describe a transition-based parser for AMR that parses sentences left-to-right, in linear time. We further propose a test-suite that assesses specific subtasks that are helpful in comparing AMR parsers, and show that our parser is competitive with the state of the art on the LDC2015E86 dataset and that it outperforms state-of-the-art parsers for recovering named entities and handling polarity.
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Selecting and Merging: Towards Adaptable and Scalable Named Entity Recognition with Large Language Models
Label-Guided In-Context Learning for Named Entity Recognition
Named Entity Recognition in Historical Italian: The Case of Giacomo Leopardi's Zibaldone
Reassessing Graph Linearization for Sequence-to-sequence AMR Parsing: On the Advantages and Limitations of Triple-Based Encoding
A Comparative Analysis of Static Word Embeddings for Hungarian
Methods for Recognizing Nested Terms
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