First Attempt to Automatically Generate Hungarian Semantic Verb Classes
نویسندگان
چکیده
Aiming to create verb paraphrases to lay the foundation of sentence paraphrases I automatically created Hungarian semantic verb classes with k-means algorithm. The vector representation of verbs was special: dimensions were cases and values were sets of lemmas that can fill the verb frame position defined by the case. I clustered 900 frequent verbs, from which 243 got into 71 smaller clusters, which tend to be semantically coherent. I evaluated the method intuitively, and verified the good classes by contrasting them with a machine readable synonym dictionary, and also by contrasting them with the new Hungarian WordNet.
منابع مشابه
Clustering Hungarian Verbs on the Basis of Complementation Patterns
Our paper reports an attempt to apply an unsupervised clustering algorithm to a Hungarian treebank in order to obtain semantic verb classes. Starting from the hypothesis that semantic metapredicates underlie verbs’ syntactic realization, we investigate how one can obtain semantically motivated verb classes by automatic means. The 150 most frequent Hungarian verbs were clustered on the basis of ...
متن کاملرشد جنبه معنایی فعل در کودک فارسیزبان: مطالعه طولی
Objective Learning “verb” as one of the main components of sentence, has been always a debatable topics in the process of language learning. One of the important issues in “verb” learning is determining its meaning using syntactic clues and learning its semantic aspects. Therefore, the main objective of this study was to examine the development of the semantic aspect of ...
متن کاملLinking Reflexive Verb Structure to Verb Meaning in a Cross-Lingual Lexical Setting
Language typology studies have shown that reflexive verb structures are widely represented in diverse languages. In this paper reflexive verb constructs in Bulgarian, French and Hungarian are compared and described on a paradigmatic level. A classification is provided where key Bulgarian reflexive verb constructs, distributed in semantic classes, are used as a seed data set for defining corresp...
متن کاملA Step-wise Usage-based Method for Inducing Polysemy-aware Verb Classes
We present an unsupervised method for inducing verb classes from verb uses in gigaword corpora. Our method consists of two clustering steps: verb-specific semantic frames are first induced by clustering verb uses in a corpus and then verb classes are induced by clustering these frames. By taking this step-wise approach, we can not only generate verb classes based on a massive amount of verb use...
متن کاملMapping Ontologies Using Ontologies: Cross-lingual Semantic Role Information Transfer
This paper presents the process of enriching the verb frame database of a Hungarian natural language parser to enable the assignment of semantic roles. We accomplished this by linking the parser’s verb frame database to existing linguistic resources such as VerbNet and WordNet, and automatically transferring back semantic knowledge. We developed OWL ontologies that map the various constraint de...
متن کامل