Exploiting Cross-Dialectal Gold Syntax for Low-Resource Historical Languages: Towards a Generic Parser for Pre-Modern Slavic
원문 초록
This paper explores the possibility of improving the performance of specialized parsers for pre-modern Slavic by training them on data from different related varieties. Because of their linguistic heterogeneity, pre-modern Slavic varieties are treated as low-resource historical languages, whereby cross-dialectal treebank data may be exploited to overcome data scarcity and attempt the training of a variety-agnostic parser. Previous experiments on early Slavic dependency parsing are discussed, particularly with regard to their ability to tackle different orthographic, regional and stylistic features. A generic pre-modern Slavic parser and two specialized parsers -- one for East Slavic and one for South Slavic -- are trained using jPTDP (Nguyen & Verspoor 2018), a neural network model for joint part-of-speech (POS) tagging and dependency parsing which had shown promising results on a number of Universal Dependency (UD) treebanks, including Old Church Slavonic (OCS). With these experiments, a new state of the art is obtained for both OCS (83.79\% unlabelled attachment score (UAS) and 78.43\% labelled attachement score (LAS)) and Old East Slavic (OES) (85.7\% UAS and 80.16\% LAS).
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
FiLLM -- A Filipino-optimized Large Language Model based on Southeast Asia Large Language Model (SEALLM)
A Comparative Analysis of Static Word Embeddings for Hungarian
POS-tagging to highlight the skeletal structure of sentences
How Does A Text Preprocessing Pipeline Affect Ontology Syntactic Matching?
J2N -- Nominal Adjective Identification and its Application
Open-Source Web Service with Morphological Dictionary-Supplemented Deep Learning for Morphosyntactic Analysis of Czech
토론
이 논문과 연결된 포럼 글이 아직 없습니다.