Alessandro Moschitti

Amazon, University of Trento
0000-0003-2216-8034
http://disi.unitn.it/moschitti/
Publications327
h-index50
Citations10,958
Highly Influential Citations1,059
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CoNLL-2012 Shared Task: Modeling Multilingual Unrestricted Coreference in OntoNotes
TLDR
The OntoNotes annotation (coreference and other layers) is described and the parameters of the shared task including the format, pre-processing information, evaluation criteria, and presents and discusses the results achieved by the participating systems.
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Towards Robust Linguistic Analysis using OntoNotes
TLDR
An analysis of the performance of publicly available, state-of-the-art tools on all layers and languages in the OntoNotes v5.0 corpus should set the benchmark for future development of various NLP components in syntax and semantics, and possibly encourage research towards an integrated system that makes use of the various layers jointly to improve overall performance.
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Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks
TLDR
This paper presents a convolutional neural network architecture for reranking pairs of short texts, where the optimal representation of text pairs and a similarity function to relate them in a supervised way from the available training data are learned.
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Efficient Convolution Kernels for Dependency and Constituent Syntactic Trees
TLDR
A new convolution kernel, namely the Partial Tree (PT) kernel, is proposed, to fully exploit dependency trees and an efficient algorithm for its computation is proposed which is futhermore sped-up by applying the selection of tree nodes with non-null kernel.
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Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)
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Making Tree Kernels Practical for Natural Language Learning
TLDR
This paper provides a simple algorithm to compute tree kernels in linear average running time and a study on the classification properties of diverse tree kernels show that kernel combinations always improve the traditional methods.
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Twitter Sentiment Analysis with Deep Convolutional Neural Networks
TLDR
A comparison between the results of the approach and the systems participating in the challenge on the official test sets, suggests that the model could be ranked in the first two positions in both the phrase-level subtask A and the message- level subtask B on Twitter Sentiment Analysis.
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A Study on Convolution Kernels for Shallow Statistic Parsing
TLDR
Novel convolution kernels for automatic classification of predicate arguments are designed and experiments on FrameNet data have shown that SVMs are appealing for the classification of semantic roles even if the proposed kernels do not produce any improvement.
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SemEval-2017 Task 3: Community Question Answering
TLDR
SemEval–2017 Task 3 on Community Question Answering reran the four subtasks from SemEval-2016, providing all the data from 2015 and 2016 for training, and fresh data for testing, and added a new subtask E in order to enable experimentation with Multi-domain Question Duplicate Detection in a larger-scale scenario, using StackExchange subforums.
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BART: A Modular Toolkit for Coreference Resolution
TLDR
B BART is presented, a highly modular toolkit for developing coreference applications that was used to extend a reimplementation of the Soon et al. (2001) proposal with a variety of additional syntactic and knowledge-based features, and experiment with alternative resolution processes, preprocessing tools, and classifiers.
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