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Found 5 papers, 0 papers with code
HITSZ-HLT at SemEval-2022 Task 10: A Span-Relation Extraction Framework for Structured Sentiment Analysis
This paper describes our system that participated in the SemEval-2022 Task 10: Structured Sentiment Analysis, which aims to extract opinion tuples from texts. A full opinion tuple generally contains an opinion holder, an opinion target, the sentiment expression, and the corresponding polarity. The complex structure of the opinion tuple makes the task challenging. To address this task, we formalize it as a span-relation extraction problem and propose a two-stage extraction framework accordingly. In the first stage, we employ the span module to enumerate spans and then recognize the type of every span. In the second stage, we employ the relation module to determine the relation between spans. Our system achieves competitive results and ranks among the top-10 systems in almost subtasks.
Argument Pair Extraction with Mutual Guidance and Inter-sentence Relation Graph
In this paper, we tackle the APE task by a mutual guidance framework, which could utilize the information of an argument in one passage to guide the identification of arguments that can form pairs with it in another passage.
Ranked #1 on
Argument Pair Extraction (APE)
on RR
Benchmarking Large Language Models with Augmented Instructions for Fine-grained Information Extraction
Information Extraction (IE) is an essential task in Natural Language Processing.
HITSZ-HLT at SemEval-2021 Task 5: Ensemble Sequence Labeling and Span Boundary Detection for Toxic Span Detection
This paper presents the winning system that participated in SemEval-2021 Task 5: Toxic Spans Detection.
CN-HIT-IT.NLP at SemEval-2020 Task 4: Enhanced Language Representation with Multiple Knowledge Triples
For this task, it is obvious that external knowledge, such as Knowledge graph, can help the model understand commonsense in natural language statements.
