In this paper we present ThReeNN, a model for Community Question Answering, Task 3, of SemEval-2017. The proposed model exploits both syntactic and semantic information to build a single and meaningful embedding space. Using a dependency parser in combination with word embeddings, the model creates sequences of inputs for a Recurrent Neural Network, which are then used for the ranking purposes of the Task. The score obtained on the official test data shows promising results.

FA3L at SemEval-2017 Task 3: A ThRee Embeddings Recurrent Neural Network for Question Answering / Attardi, Giuseppe; Carta, Antonio; Errica, Federico; Madotto, Andrea; Pannitto, Ludovica. - ELETTRONICO. - (2017), pp. 299-304. (Intervento presentato al convegno 11th International Workshop on Semantic Evaluation (SemEval-2017) tenutosi a Vancouver, Canada nel August 2017) [10.18653/v1/S17-2048].

FA3L at SemEval-2017 Task 3: A ThRee Embeddings Recurrent Neural Network for Question Answering

Pannitto, Ludovica
Co-primo
2017

Abstract

In this paper we present ThReeNN, a model for Community Question Answering, Task 3, of SemEval-2017. The proposed model exploits both syntactic and semantic information to build a single and meaningful embedding space. Using a dependency parser in combination with word embeddings, the model creates sequences of inputs for a Recurrent Neural Network, which are then used for the ranking purposes of the Task. The score obtained on the official test data shows promising results.
2017
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)
299
304
FA3L at SemEval-2017 Task 3: A ThRee Embeddings Recurrent Neural Network for Question Answering / Attardi, Giuseppe; Carta, Antonio; Errica, Federico; Madotto, Andrea; Pannitto, Ludovica. - ELETTRONICO. - (2017), pp. 299-304. (Intervento presentato al convegno 11th International Workshop on Semantic Evaluation (SemEval-2017) tenutosi a Vancouver, Canada nel August 2017) [10.18653/v1/S17-2048].
Attardi, Giuseppe; Carta, Antonio; Errica, Federico; Madotto, Andrea; Pannitto, Ludovica
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/949537
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