Search Results for author: Gaetano Rossiello

Found 20 papers, 8 papers with code

Retrieval-Based Transformer for Table Augmentation

1 code implementation20 Jun 2023 Michael Glass, Xueqing Wu, Ankita Rajaram Naik, Gaetano Rossiello, Alfio Gliozzo

In this paper, we introduce a novel approach toward automatic data wrangling in an attempt to alleviate the effort of end-users, e. g. data analysts, in structuring dynamic views from data lakes in the form of tabular data.

Imputation Retrieval +1

KnowGL: Knowledge Generation and Linking from Text

no code implementations25 Oct 2022 Gaetano Rossiello, Md Faisal Mahbub Chowdhury, Nandana Mihindukulasooriya, Owen Cornec, Alfio Massimiliano Gliozzo

We propose KnowGL, a tool that allows converting text into structured relational data represented as a set of ABox assertions compliant with the TBox of a given Knowledge Graph (KG), such as Wikidata.

Navigate Sentence

KGI: An Integrated Framework for Knowledge Intensive Language Tasks

no code implementations8 Apr 2022 Md Faisal Mahbub Chowdhury, Michael Glass, Gaetano Rossiello, Alfio Gliozzo, Nandana Mihindukulasooriya

In this paper, we present a system to showcase the capabilities of the latest state-of-the-art retrieval augmented generation models trained on knowledge-intensive language tasks, such as slot filling, open domain question answering, dialogue, and fact-checking.

Fact Checking Open-Domain Question Answering +4

A Generative Model for Relation Extraction and Classification

no code implementations26 Feb 2022 Jian Ni, Gaetano Rossiello, Alfio Gliozzo, Radu Florian

Relation extraction (RE) is an important information extraction task which provides essential information to many NLP applications such as knowledge base population and question answering.

Classification Knowledge Base Population +4

Applying a Generic Sequence-to-Sequence Model for Simple and Effective Keyphrase Generation

no code implementations14 Jan 2022 Md Faisal Mahbub Chowdhury, Gaetano Rossiello, Michael Glass, Nandana Mihindukulasooriya, Alfio Gliozzo

In recent years, a number of keyphrase generation (KPG) approaches were proposed consisting of complex model architectures, dedicated training paradigms and decoding strategies.

Keyphrase Generation Language Modelling

A Two-Stage Approach towards Generalization in Knowledge Base Question Answering

no code implementations10 Nov 2021 Srinivas Ravishankar, June Thai, Ibrahim Abdelaziz, Nandana Mihidukulasooriya, Tahira Naseem, Pavan Kapanipathi, Gaetano Rossiello, Achille Fokoue

Most existing approaches for Knowledge Base Question Answering (KBQA) focus on a specific underlying knowledge base either because of inherent assumptions in the approach, or because evaluating it on a different knowledge base requires non-trivial changes.

Knowledge Base Question Answering Knowledge Graphs +3

Zero-shot Slot Filling with DPR and RAG

2 code implementations17 Apr 2021 Michael Glass, Gaetano Rossiello, Alfio Gliozzo

Recently, there has been a promising direction in evaluating language models in the same way we would evaluate knowledge bases, and the task of slot filling is the most suitable to this intent.

Knowledge Base Population Knowledge Graphs +3

Open Knowledge Graphs Canonicalization using Variational Autoencoders

1 code implementation EMNLP 2021 Sarthak Dash, Gaetano Rossiello, Nandana Mihindukulasooriya, Sugato Bagchi, Alfio Gliozzo

In this work, we propose Canonicalizing Using Variational Autoencoders (CUVA), a joint model to learn both embeddings and cluster assignments in an end-to-end approach, which leads to a better vector representation for the noun and relation phrases.

Clustering Knowledge Graphs +1

Knowledge Graph Embeddings and Explainable AI

no code implementations30 Apr 2020 Federico Bianchi, Gaetano Rossiello, Luca Costabello, Matteo Palmonari, Pasquale Minervini

Knowledge graph embeddings are now a widely adopted approach to knowledge representation in which entities and relationships are embedded in vector spaces.

Knowledge Graph Embeddings

Learning Relational Representations by Analogy using Hierarchical Siamese Networks

no code implementations NAACL 2019 Gaetano Rossiello, Alfio Gliozzo, Robert Farrell, Nicolas Fauceglia, Michael Glass

We address relation extraction as an analogy problem by proposing a novel approach to learn representations of relations expressed by their textual mentions.

Entity Embeddings Knowledge Base Population +3

Iterative Multi-document Neural Attention for Multiple Answer Prediction

no code implementations8 Feb 2017 Claudio Greco, Alessandro Suglia, Pierpaolo Basile, Gaetano Rossiello, Giovanni Semeraro

People have information needs of varying complexity, which can be solved by an intelligent agent able to answer questions formulated in a proper way, eventually considering user context and preferences.

Question Answering Recommendation Systems

Cannot find the paper you are looking for? You can Submit a new open access paper.