Building a Greek corpus for Textual Entailment
نویسندگان
چکیده
This paper deals with the relationship between weblog content and time. With the proposed temporal mutual information, we analyze the collocations in time dimension, and the interesting collocations related to special events. The temporal mutual information is employed to observe the strength of term-to-term associations over time. An event detection algorithm identifies the collocations that may cause an event in a specific timestamp. An event summarization algorithm retrieves a set of collocations which describe an event. We compare our approach with the approach without considering the time interval. The experimental results demonstrate that the temporal collocations capture the real world semantics and real world events over time.
منابع مشابه
Building Evaluation Dataset for Textual Entailment in Czech
Recognizing textual entailment (RTE) is a subfield of natural language processing (NLP). Currently several RTE systems exist in which some of the subtasks are language independent but some are not. Moreover, large datasets for evaluation are prepared almost exclusively for English language. In this paper we describe methods for obtaining test dataset for RTE in Czech. We have used methods for e...
متن کاملNamed Entity Relation Mining using Wikipedia
Discovering relations among Named Entities (NEs) from large corpora is both a challenging, as well as useful task in the domain of Natural Language Processing, with applications in Information Retrieval (IR), Summarization (SUM), Question Answering (QA) and Textual Entailment (TE). The work we present resulted from the attempt to solve practical issues we were confronted with while building sys...
متن کاملText Grouping using Textual Entailment
Textual Entailment is an important field in Natural Language Processing domain. Given two texts called T (Text) and H (Hypothesis), the textual entailment recognition is the task of deciding whether the meaning of H can be logically inferred from that of T. A Textual Entailment (TE) system has developed and this system has tested on various entailment standard datasets. This TE will apply to di...
متن کاملExpanding textual entailment corpora fromWikipedia using co-training
In this paper we propose a novel method to automatically extract large textual entailment datasets homogeneous to existing ones. The key idea is the combination of two intuitions: (1) the use of Wikipedia to extract a large set of textual entailment pairs; (2) the application of semisupervised machine learning methods to make the extracted dataset homogeneous to the existing ones. We report emp...
متن کاملCorpora for Learning the Mutual Relationship between Semantic Relatedness and Textual Entailment
In this paper we present the creation of a corpora annotated with both semantic relatedness (SR) scores and textual entailment (TE) judgments. In building this corpus we aimed at discovering, if any, the relationship between these two tasks for the mutual benefit of resolving one of them by relying on the insights gained from the other. We considered a corpora already annotated with TE judgment...
متن کامل