Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  describes the INAOE’s ansr validation system evaluated at the Spanish track of the AVE 2007. This system is based on a supervised learning approach that considers two kinds of attributes. On the one hand, some attributes indicating the textual entailment beten the given support text and the hypothesis constructed from the question and ansr. On the other hand, some new features denoting certain ansr restrictions as imposed by the question’s type and format. In order to extract all these attributes the system uses different tools such as a lemmatizer, a POS tagger, a NER procedure and a superficial syntactic parser. Experimental results are encouraging; they show that the proposed system achieved a 52.91% of F-measure and that it outperformed the standard baseline by 15 percentage points.
['Alberto Téllez-Valero', 'Manuel Montes-y-Gómez', 'Luis Villaseñor-Pineda']
I am writing a research paper on a idea INAOE at AVE 2007: Experiments in Spanish Answer Validation
[{"from": "human", "value": "I am writing a research paper on a idea INAOE at AVE 2007: Experiments in Spanish Answer Validation"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  describes the INAOE\u2019s ansr validation system evaluated at the Spanish track of the AVE 2007. This system is based on a supervised learning approach that considers two kinds of attributes. On the one hand, some attributes indicating the textual entailment beten the given support text and the hypothesis constructed from the question and ansr. On the other hand, some new features denoting certain ansr restrictions as imposed by the question\u2019s type and format. In order to extract all these attributes the system uses different tools such as a lemmatizer, a POS tagger, a NER procedure and a superficial syntactic parser. Experimental results are encouraging; they show that the proposed system achieved a 52.91% of F-measure and that it outperformed the standard baseline by 15 percentage points."}]