#5073. Few-Shot Relation Extraction Towards Special Interests

July 2026publication date
Proposal available till 15-05-2025
4 total number of authors per manuscript0 $

The title of the journal is available only for the authors who have already paid for
Journal’s subject area:
Management Information Systems;
Information Systems and Management;
Information Systems;
Computer Science Applications;
Places in the authors’ list:
place 1place 2place 3place 4
FreeFreeFreeFree
2510 $1340 $1170 $1000 $
Contract №5073.1 Contract №5073.2 Contract №5073.3 Contract №5073.4
1 place - free (for sale)
2 place - free (for sale)
3 place - free (for sale)
4 place - free (for sale)

More details about the manuscript: Arts & Humanities Citation Index or/and Science Citation Index Expanded or/and Social Sciences Citation Index
Abstract:
With the continuous development of natural language processing, Relation extraction (RE) has been intensively studied and well performed in extracting relations from unstructured texts in both English and modern Chinese. In this paper, we study to extract relations from a special type of text, that is, Chinese textual description of Han Dynasty Stone Reliefs (HanDSR). We aim to develop an efficient relation extractor for special interests with a small number of samples. To exploit the representation of dependency trees, we design five dependency semantic path patterns(DSPPs) to extract relation triples of special interests. Besides, we build the HanDSR Treebank that includes 4190 sentences, 28124 dependency trees, following the annotation format of the Penn Chinese Treebank 8.0, which addresses the lack of domain-specific corpus and could be used in extract relations from such texts. The experimental results illustrate that our proposal significantly outperforms the rule-based relation extraction model in both effectiveness and efficiency.
Keywords:
Dependency parsing; Few-shot; Relation extraction; Special interests

Contacts :
0