Still, their annotation schemes are designed for individual languages that have language-dependent features. ![]() Several semantic approaches are proposed for parsing natural language sentences in semantic representation, such as Groningen Meaning Bank (GMB) and abstract meaning representation (AMR). Typically, a semantic parser labels each word in the original sentence according to its semantic role or represents each compound component based on its meaning. Semantic parsing is an essential process and has attracted great attention in multilingual semantic representation and NLP research over the last few decades. The process of parsing a natural language sentence to its semantic representation is called semantic parsing, which parses the sentences without representing the syntactic classification of the components of the sentence. It has been applied in several areas, such as machine translation, question answering, and document representation. ![]() Multilingual semantic representation presents words, phrases, texts, or documents in heterogeneous parties (e.g., English and Chinese) to achieve semantic consistency. The evaluation results demonstrate that the proposed MParser shows higher compatibility with human intuitions. In addition, 154 non-expert participants evaluated the sentences’ semantic expressiveness. To evaluate the annotator agreement of MParser outputs that generates a list of English sentences under a common multilingual word sense, three expert participants manually and semantically annotated 75 sentences (505 words in total) in English. ![]() In addition, it provides a human and computer-readable and -understandable interaction concept to resolve the semantic shift problems and guarantees consistent information understanding among heterogeneous sentence-level contexts. By leveraging a semantic input method for sharing common atomic concepts, MParser represents any simple English sentence as a bag of unique and universal concepts via case grammar of an explainable machine natural language. This paper proposes a Machine Natural Language Parser (MParser) to address the semantic interoperability problem between users and computers. In multilingual semantic representation, the interaction between humans and computers faces the challenge of understanding meaning or semantics, which causes ambiguity and inconsistency in heterogeneous information.
0 Comments
Leave a Reply. |