Sagan in TAC2010: A Machine Learning Approach to RTE within a Corpus
نویسنده
چکیده
This paper describes the Sagan system in the context of the Sixth Pascal Recognizing Textual Entailment (RTE6) and the RTE task within a Corpus. The system employs a Support Vector Machine classifier which uses semantic similarity metrics to sentence level using only WordNet as source of knowledge, and co-reference analysis. Additionally, we proposed a baseline to the Novelty Detection subtask.
منابع مشابه
An approach using Named Entities for Recognizing Textual Entailment
This paper describes the Sagan system in the context of the Fourth Pascal Recognizing Textual Entailment (RTE-4) Evaluation Challenge. Sagan applies a Support Vector Machine classifier to examples characterized by four features based on: edit distance, distance in WordNet and Longest Common Substring between text and hypothesis. Additionally, we created a filter applying hand-crafted rules base...
متن کاملA Machine Learning Approach for Recognizing Textual Entailment in Spanish
This paper presents a system that uses machine learning algorithms for the task of recognizing textual entailment in Spanish language. The datasets used include SPARTE Corpus and a translated version to Spanish of RTE3, RTE4 and RTE5 datasets. The features chosen quantify lexical, syntactic and semantic level matching between text and hypothesis sentences. We analyze how the different sizes of ...
متن کاملSagan in TAC2009: Using Support Vector Machines in Recognizing Textual Entailment and TE Search Pilot task
This paper describes the Sagan system in the context of the Fifth Pascal Recognizing Textual Entailment (RTE-5) Evaluation Challenge and the new Textual Entailment Search Pilot Task. The system employs a Support Vector Machine classifier with a set of 32 features, which includes lexical and semantic similarity for both two-way and three-way classification tasks. Additionally, we show an approac...
متن کاملCorpus based coreference resolution for Farsi text
"Coreference resolution" or "finding all expressions that refer to the same entity" in a text, is one of the important requirements in natural language processing. Two words are coreference when both refer to a single entity in the text or the real world. So the main task of coreference resolution systems is to identify terms that refer to a unique entity. A coreference resolution tool could be...
متن کاملPRIS at TAC2010 KBP Track
This paper describes our participation in Knowledge Base Population track at TAC2010. In the entity-linking task, we combined machine learning-based methods and rule-based methods to improve the linking results. In the slot filling task, a supervised machine learning method based on CRF model and a rule pattern method were used to select proper answers for slots.
متن کامل