Supervised learning model for parsing Arabic language
Parsing the Arabic language is a difficult task given the specificities of this language and given the scarcity of digital resources (grammars and annotated corpora). In this paper, we suggest a method for Arabic parsing based on supervised machine learning. We used the SVMs algorithm to select the syntactic labels of the sentence. Furthermore, we evaluated our parser following the cross validation method by using the Penn Arabic Treebank. The obtained results are very encouraging.
Code (0)
등록된 구현이 없습니다.
Tasks
BIG-bench Machine LearningmodelSentenceSimilar Papers 제목 키워드 기반
Arabic Morphosyntactic Tagging and Dependency Parsing with Large Language Models
Large language models (LLMs) perform strongly on many NLP tasks, but their ability to produce explicit linguistic structure remains unclear. We evaluate instruction-tuned LLMs on two structured prediction tasks for Stand…
Structured PredictionDependency ParsingStatistical Parsing by Machine Learning from a Classical Arabic Treebank
Research into statistical parsing for English has enjoyed over a decade of successful results. However, adapting these models to other languages has met with difficulties. Previous comparative work has shown that Modern …
BIG-bench Machine LearningConstituency Parsing"Wikily" Supervised Neural Translation Tailored to Cross-Lingual Tasks
We present a simple but effective approach for leveraging Wikipedia for neural machine translation as well as cross-lingual tasks of image captioning and dependency parsing without using any direct supervision from exter…
Cross-Lingual TransferCross-Lingual Word EmbeddingsDependency ParsingImage Captioning+3“Wikily” Supervised Neural Translation Tailored to Cross-Lingual Tasks
We present a simple but effective approach for leveraging Wikipedia for neural machine translation as well as cross-lingual tasks of image captioning and dependency parsing without using any direct supervision from exter…
Cross-Lingual TransferCross-Lingual Word EmbeddingsDependency ParsingImage Captioning+3Neural Unsupervised Parsing Beyond English
Recently, neural network models which automatically infer syntactic structure from raw text have started to achieve promising results. However, earlier work on unsupervised parsing shows large performance differences bet…