janardhan: Semantic Textual Similarity using Universal Networking Language graph matching
نویسندگان
چکیده
Sentences that are syntactically quite different can often have similar or same meaning. The SemEval 2012 task of Semantic Textual Similarity aims at finding the semantic similarity between two sentences. The semantic representation of Universal Networking Language (UNL), represents only the inherent meaning in a sentence without any syntactic details. Thus, comparing the UNL graphs of two sentences can give an insight into how semantically similar the two sentences are. This paper presents the UNL graph matching method for the Semantic Textual Similarity(STS) task.
منابع مشابه
CFILT-CORE: Semantic Textual Similarity using Universal Networking Language
This paper describes the system that was submitted in the *SEM 2013 Semantic Textual Similarity shared task. The task aims to find the similarity score between a pair of sentences. We describe a Universal Networking Language (UNL) based semantic extraction system for measuring the semantic similarity. Our approach combines syntactic and word level similarity measures along with the UNL based se...
متن کاملCFILT-CORE: Finding Semantic Textual Similarity using UNL
Semantic Textual Similarity is the task of finding the degree of similarity between a pair of sentences through semantics extraction. This is motivated by the fact that syntactically diverse sentences often convey the same meaning. This paper describes the approach that was used in the *SEM Shared Task 2013. The approach combines semantic, syntactic and lexical similarity measures for finding s...
متن کاملSemantic Answer Validation using Universal Networking Language
we present a rule-based answer validation (AV) system based on textual entailment (TE) recognition mechanism that uses semantic features expressed in the Universal Networking Language (UNL). We consider the question as the TE hypothesis (H) and the supporting text as TE text (T). Our proposed TE system compares the UNL relations in both T and H in order to identify the entailment relation as ei...
متن کاملSemantic Textual Entailment Recognition using UNL
A two-way textual entailment (TE) recognition system that uses semantic features has been described in this paper. We have used the Universal Networking Language (UNL) to identify the semantic features. UNL has all the components of a natural language. The development of a UNL based textual entailment system that compares the UNL relations in both the text and the hypothesis has been reported. ...
متن کاملActive Learning-based Local Graph Matching for Textual Entailment
This paper presents a robust textual entailment system using the principle of just noticeable difference in psychology, which we call a local graph matching-based system with active learning. First, although an early textual entailment task often involved two rather simple sentences of T (“Text”) and H (“Hypothesis”), the recent textual entailment task often involves multiple / complex / compou...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2012