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The paper is dedicated to applying a hybrid approach based on rules and machine learning for anaphora resolution in the Russian language. The model combines formal rules, the Extra Trees machine learning algorithm and the Balance Cascade algorithm for working with imbalanced learning sets. A number of features were obtained from the rules or were generated from other features; in addition, the syntactic...
Anaphora is one of the mostly attractive phenomenons in computational linguistics for resolving anaphora with preceding and succeeding referent. The ability to perform Anaphora Resolution is important in NLP application. Traditional research focus on resolving particular type of anaphora only, no one integrates methods or procedure to resolve all type of anaphora. In this paper, we identify all type...
This paper aims to lay the foundations of an anaphora resolution framework able to process all types of hypertexts and treat all types of anaphors for the English language. To this end, we provide a linguistically unambiguous and extensive definition and categorization of the concept of anaphora. We introduce a new corpus, and use our proposed categorization to statistically analyze it. Finally, we...
This paper presents an approach to automatically identify potentially nocuous ambiguities, which occur when text is interpreted differently by different readers of requirements written in natural language. We extract a set of anaphora ambiguities from a range of requirements documents, and collect multiple human judgments on their interpretations. The judgment distribution is used to determine if...
A number of computational models simulate the grounded learning of units of language in the early learner. But can this initial lexical knowledge be used to acquire complex grammatical notions such as anaphora? We build on earlier work, where we simulate a language learner with perceptual attention and learn, in an unsupervised manner, a set of action models along with the participating agents, and...
A contextual analysis processing technique, consisting in determining the context understanding together with coherences in sentences, of concepts and phenomena related to each others, must be able to simultaneously interpret accurately a sequence of multiple semantic representations. A word frequently carries different meanings according to the context. For example, having a ldquobig heartrdquo is...
The rationale behind anaphora resolution in Pashto language is to make it easier for computer to comprehend and further process Pashto text accurately. This paper is focused on the implementation of the algorithm (Ali et al., 2007) and modifying few of its rules. It also adds some new rules and eliminates an undesirable one to enhance the accuracy and efficiency. The algorithm uses a rule-based approach...
This paper defines and relates several important concepts in data fusion and natural language understanding: situation, relation, relationship and context. In data fusion - as in other problem-solving applications - contextual reasoning involves inferring desired information (ldquoproblem variablesrdquo) on the basis of other available information (ldquocontext variablesrdquo). Relevant contexts are...
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