孟加拉语Verb:在孟加拉语NLP中进行过渡性分类的句子级数据集
Zannatul Mawa Koli1, Md Jahidul Alam1, Zakia Sultana1
1Department of Computer Science and Engineering. Daffodil International University, Bangladesh.
Data in brief
|March 9, 2026
概括
本研究介绍了BanglaVerb,这是一个新的数据集,用于孟加拉语动词过渡性分类. 它提供了一个可靠的资源,以推进孟加拉语的自然语言处理.
科学领域:
- 计算语言学 计算语言学
- 自然语言处理 (NLP) 是一种自然语言处理.
- 词典写作 词典写作 词典写作
背景情况:
- 孟加拉语是一种具有丰富形态的语言,缺乏足够的以动词为中心的NLP资源.
- 现有的资源不足以支持精细的语言分析,如过渡性分类.
- 资源不足的语言在NLP开发中存在独特的挑战.
研究的目的:
- 介绍BanglaVerb,一个新的句子级数据集,用于孟加拉语动词过渡性分类.
- 为孟加拉语动词的计算分析提供语言验证的资源.
- 促进孟加拉语NLP的研究和开发,特别是与动词相关的任务.
主要方法:
- 3001个孟加拉语句子的系统策划和语言验证.
- 使用基于规则的预标签和专家验证,将动词实例作为过渡性或不过渡性的注释.
- 从各种公共来源收集,并进行标准化和清理以确保文本完整性.
- 分析词汇和结构统计数据以确认语言代表性.
主要成果:
- 孟加拉语Verb数据集包含3001个注释的孟加拉语句 (1634个过渡性,1367个不过渡性).
- 高度的注释者同意 (92%) 表示标签一致性和可靠性.
- 统计分析证实了数据集的语言代表性 (例如,Zipf的法律遵守).
- 基线机器学习模型显示出强大的过渡性分类性能.
结论:
- 孟加拉语Verb是一个高质量的,公开可访问的数据集孟加拉语动词的过渡性.
- 该数据集桥梁句子结构和动词语义,支持各种下游NLP应用程序.
- 它是推动孟加拉语NLP的宝贵资源,包括 lemmatization,解析和语言模型开发.
相关概念视频
Classification of Neurotransmitters
5.7K
Neurotransmitters play a crucial role in the communication between neurons in the autonomic nervous system. Neurons in the autonomic nervous system can be cholinergic or adrenergic depending on the neurotransmitters synthesized. Cholinergic neurons use acetylcholine as their primary neurotransmitter. This includes all the preganglionic fibers of the sympathetic and pre- and postganglionic fibers of the parasympathetic nervous systems. In addition, neurons of the somatic nervous system also use...
5.7K
Classification of Signals
1.5K
In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
1.5K
Aggregates Classification
1.1K
Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
1.1K
Classification of Systems-II
542
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
542
Cotranslational Protein Translocation
10.8K
Translocation of proteins across membranes is an ancient process that occurs even in bacteria and archaebacteria. In fact, the components of the translocation machinery are still conserved between prokaryotes and eukaryotes.
Sec61 channel partners for cotranslational translocation
During cotranslational translocation, the Sec61 channel partners with the signal recognition particle (SRP), the signal recognition particle receptor (SR), and the ribosomes to transport the nascent polypeptide chain...
Sec61 channel partners for cotranslational translocation
During cotranslational translocation, the Sec61 channel partners with the signal recognition particle (SRP), the signal recognition particle receptor (SR), and the ribosomes to transport the nascent polypeptide chain...
10.8K
Classification of Systems-I
647
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
647

