Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Shared Task 1 of SemEval-2014 comprised two subtasks on the same dataset of sentence pairs: recognizing textual entailment and determining textual similarity.  used an existing system based on formal semantics and logical inference to participate in the first subtask, reaching an accuracy of 82%, ranking in the top 5 of more than tnty participating systems. For determining semantic similarity  took a supervised approach using a variety of features, the majority of which was produced by our system for recognizing textual entailment. In this subtask our system achieved a mean squared error of 0.322, the best of all participating systems.
['Johannes Bjerva', 'Johan Bos', 'Rob van der Goot', 'Malvina Nissim']
I am writing a research paper on a idea The Meaning Factory: Formal Semantics for Recognizing Textual Entailment and Determining Semantic Similarity
[{"from": "human", "value": "I am writing a research paper on a idea The Meaning Factory: Formal Semantics for Recognizing Textual Entailment and Determining Semantic Similarity"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Shared Task 1 of SemEval-2014 comprised two subtasks on the same dataset of sentence pairs: recognizing textual entailment and determining textual similarity.  used an existing system based on formal semantics and logical inference to participate in the first subtask, reaching an accuracy of 82%, ranking in the top 5 of more than tnty participating systems. For determining semantic similarity  took a supervised approach using a variety of features, the majority of which was produced by our system for recognizing textual entailment. In this subtask our system achieved a mean squared error of 0.322, the best of all participating systems."}]