Biaffine Dependency and Semantic Graph Parsing for EnhancedUniversal Dependencies

no code implementations • ACL (IWPT) 2021 • Giuseppe Attardi, Daniele Sartiano, Maria Simi

This paper presents the system used in our submission to the IWPT 2021 Shared Task.

Dependency Parsing Lemmatization +2

Linear Neural Parsing and Hybrid Enhancement for Enhanced Universal Dependencies

no code implementations • WS 2020 • Giuseppe Attardi, Daniele Sartiano, Maria Simi

To accomplish the shared task on dependency parsing we explore the use of a linear transition-based neural dependency parser as well as a combination of three of them by means of a linear tree combination algorithm.

Dependency Parsing

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

no code implementations • SEMEVAL 2017 • Giuseppe Attardi, Antonio Carta, Federico Errica, Andrea Madotto, Ludovica Pannitto

In this paper we present ThReeNN, a model for Community Question Answering, Task 3, of SemEval-2017.

Community Question Answering Dependency Parsing +3

Question Dependent Recurrent Entity Network for Question Answering

1 code implementation • 25 Jul 2017 • Andrea Madotto, Giuseppe Attardi

Question Answering is a task which requires building models capable of providing answers to questions expressed in human language.

Memorization Question Answering +1

UniPI at SemEval-2016 Task 4: Convolutional Neural Networks for Sentiment Classification

no code implementations • SEMEVAL 2016 • Giuseppe Attardi, Daniele Sartiano

General Classification Sentiment Analysis +2

Adapting the TANL tool suite to Universal Dependencies

no code implementations • LREC 2016 • Maria Simi, Giuseppe Attardi

TANL is a suite of tools for text analytics based on the software architecture paradigm of data driven pipelines.

Non-projective Dependency-based Pre-Reordering with Recurrent Neural Network for Machine Translation

no code implementations • WS 2015 • Antonio Valerio Miceli-Barone, Giuseppe Attardi

Combinatorial Optimization Machine Translation +1

DeepNL: a Deep Learning NLP pipeline

no code implementations • WS 2015 • Giuseppe Attardi

Constituency Parsing Dependency Parsing +3

UniPi: Recognition of Mentions of Disorders in Clinical Text

no code implementations • SEMEVAL 2014 • Giuseppe Attardi, Vittoria Cozza, Daniele Sartiano

Named Entity Recognition (NER) Word Embeddings

Pre-Reordering for Machine Translation Using Transition-Based Walks on Dependency Parse Trees

no code implementations • WS 2013 • Antonio Valerio Miceli-Barone, Giuseppe Attardi

Machine Translation Translation

Dependency Parsing Domain Adaptation using Transductive SVM

no code implementations • WS 2012 • Antonio Valerio Miceli-Barone, Giuseppe Attardi

Dependency Parsing Domain Adaptation