Challenge: Existing lexicons blur senses and frames of predicates, which needs to be refined to meet word sense disambiguation and event extraction tasks.
Approach: They propose to construct a predicate lexicon for Chinese AMR corpus with 14,389 senses and 10,800 frames of 8,470 words.
Outcome: The proposed lexicon includes 14,389 senses and 10,800 frames of 8,470 words.

Similar Papers

Align-smatch: A Novel Evaluation Method for Chinese Abstract Meaning Representation Parsing based on Alignment of Concept and Relation (2022.lrec-1)

Copied to clipboard

Challenge: Abstract Meaning Representation abstracts the meaning of sentences into a single-rooted, acyclic and directed graph.
Approach: They propose to use a metric to evaluate concept alignment and relation alignment to improve Chinese AMR parsing evaluation methods.
Outcome: The proposed method is more robust and compatible with concept alignment and relation alignment and more robust in evaluating arcs.
Building a Broad Infrastructure for Uniform Meaning Representations (2024.lrec-main)

Copied to clipboard

Challenge: This paper reports the first release of the UMR data set for six languages . it includes annotations for six different languages that vary greatly in terms of their linguistic properties and resource availability.
Approach: They report the first release of the UMR data set for six languages . they describe on-going efforts to enlarge the data set and extend it to other languages - including Navajo, Navájo, and Sanapaná .
Outcome: The first release of the UMR data set includes annotations for six languages . the language dataset is available for free and can be extended to other languages if needed .
Abstract Meaning Representation of Constructions: The More We Include, the Better the Representation (L18-1)

Copied to clipboard

Challenge: Abstract Meaning Representation (AMR) uses a flexible pattern or template of multiple lexical items to provide semantic representation of certain constructions.
Approach: They propose to expand the AMR project's lexicon of predicate senses to include entries for a growing set of constructions.
Outcome: The proposed approach provides coverage for the annotation of certain types of constructions.
Abstract Meaning Representation Guided Graph Encoding and Decoding for Joint Information Extraction (2021.naacl-main)

Copied to clipboard

Challenge: Abstract Meaning Representation (IE) and Information Extraction (IE), both focus on extracting the main information from natural language texts.
Approach: They propose an AMR-guided framework for joint information extraction using a pre-trained AMR parser.
Outcome: The proposed framework achieves state-of-the-art on all IE subtasks.
A Structured Syntax-Semantics Interface for English-AMR Alignment (N18-1)

Copied to clipboard

Challenge: Abstract Meaning Representation (AMR) annotations do not require explicit mapping between elements of an AMR and the corresponding elements of the sentence that evoke them.
Approach: They devised an expressive framework to align AMR graphs to dependency graphs . their framework explains how 97% of AMR edges are evoked by words or syntax .
Outcome: The proposed framework explains how 97% of AMR edges are evoked by words or syntax.
Semantically Inspired AMR Alignment for the Portuguese Language (2020.emnlp-main)

Copied to clipboard

Challenge: Abstract Meaning Representation (AMR) parsers require alignment between nodes and words of the sentence.
Approach: They propose to use a more semantically matched word-concept pair to align graphs with words in Portuguese . they performed intrinsic and extrinsic evaluations and found it outperforms the English alignment strategies.
Outcome: The proposed method outperforms the existing methods for English and achieves competitive results with a parser designed for the Portuguese language.
Transfer of Frames from English FrameNet to Construct Chinese FrameNet: A Bilingual Corpus-Based Approach (L18-1)

Copied to clipboard

Challenge: Current publicly available Chinese FrameNet has a relatively low coverage of frames and lexical units compared with other languages.
Approach: They propose an automatic way to construct Chinese FrameNet using a sentence-aligned English-Chinese bilingual corpus.
Outcome: The proposed resource can provide frame recommendations acceptable by annotators.
DocAMR: Multi-Sentence AMR Representation and Evaluation (2022.naacl-main)

Copied to clipboard

Challenge: Abstract Meaning Representation (AMR) graphs are compared to gold graphs by the Smatch metric, but lack a well-defined representation and evaluation.
Approach: They propose an algorithm for deriving a unified graph representation using a super-sentential annotation method.
Outcome: The proposed algorithm avoids the pitfalls of over-merging and lacks coherence from under merging.
A Corpus of German Abstract Meaning Representation (DeAMR) (2024.lrec-main)

Copied to clipboard

Challenge: Abstract Meaning Representations (AMRs) are semantic graphs that abstract away from surface syntax and capture the meaning of who does what to whom in a sentence.
Approach: They propose to use German Abstract Meaning Representation (Deutsche AMR) to represent the structure and semantics of German.
Outcome: The proposed framework is based on an annotated corpus of 400 DeAMR in German and is validated through inter-annotator agreement.
AnCast++: Document-Level Evaluation of Graph-based Meaning Representations (2025.findings-acl)

Copied to clipboard

Challenge: Abstract Meaning Representation (UMR) is a cross-lingual document-level graph-based representation that extends it to document- level semantic annotations.
Approach: They propose an evaluation metric that unifies evaluation of four distinct sub-structures of UMR.
Outcome: The proposed metric is made available on Github.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations