Search Results for author: Jennifer D'Souza

Found 12 papers, 6 papers with code

Easy Semantification of Bioassays

no code implementations30 Nov 2021 Marco Anteghini, Jennifer D'Souza, Vitor A. P. Martins dos Santos, Sören Auer

Biological data and knowledge bases increasingly rely on Semantic Web technologies and the use of knowledge graphs for data integration, retrieval and federated queries.

Knowledge Graphs

Ranking Facts for Explaining Answers to Elementary Science Questions

no code implementations18 Oct 2021 Jennifer D'Souza, Isaiah Onando Mulang', Soeren Auer

In multiple-choice exams, students select one answer from among typically four choices and can explain why they made that particular choice.

Interpretable Machine Learning Learning-To-Rank +1

Pattern-based Acquisition of Scientific Entities from Scholarly Article Titles

1 code implementation1 Sep 2021 Jennifer D'Souza, Soeren Auer

We describe a rule-based approach for the automatic acquisition of salient scientific entities from Computational Linguistics (CL) scholarly article titles.

Automated Mining of Leaderboards for Empirical AI Research

1 code implementation31 Aug 2021 Salomon Kabongo, Jennifer D'Souza, Sören Auer

In this regard, the Leaderboards facet of information organization provides an overview on the state-of-the-art by aggregating empirical results from various studies addressing the same research challenge.

Knowledge Graphs Scientific Results Extraction

SemEval-2021 Task 11: NLPContributionGraph -- Structuring Scholarly NLP Contributions for a Research Knowledge Graph

1 code implementation10 Jun 2021 Jennifer D'Souza, Sören Auer, Ted Pedersen

Being the first-of-its-kind in the SemEval series, the task released structured data from NLP scholarly articles at three levels of information granularity, i. e. at sentence-level, phrase-level, and phrases organized as triples toward Knowledge Graph (KG) building.

Sentence, Phrase, and Triple Annotations to Build a Knowledge Graph of Natural Language Processing Contributions -- A Trial Dataset

no code implementations9 Oct 2020 Jennifer D'Souza, Sören Auer

To this end, specifically, care was taken in the adjudication annotation stage to reduce annotation noise while formulating the guidelines for our proposed novel NLP contributions structuring and graphing scheme.

SciBERT-based Semantification of Bioassays in the Open Research Knowledge Graph

1 code implementation16 Sep 2020 Marco Anteghini, Jennifer D'Souza, Vitor A. P. Martins dos Santos, Sören Auer

As a novel contribution to the problem of semantifying biological assays, in this paper, we propose a neural-network-based approach to automatically semantify, thereby structure, unstructured bioassay text descriptions.

NLPContributions: An Annotation Scheme for Machine Reading of Scholarly Contributions in Natural Language Processing Literature

1 code implementation23 Jun 2020 Jennifer D'Souza, Sören Auer

We describe an annotation initiative to capture the scholarly contributions in natural language processing (NLP) articles, particularly, for the articles that discuss machine learning (ML) approaches for various information extraction tasks.

Machine Translation Named Entity Recognition +4

Improving Scholarly Knowledge Representation: Evaluating BERT-based Models for Scientific Relation Classification

no code implementations13 Apr 2020 Ming Jiang, Jennifer D'Souza, Sören Auer, J. Stephen Downie

With the rapid growth of research publications, there is a vast amount of scholarly knowledge that needs to be organized in digital libraries.

Classification General Classification +1

Open Research Knowledge Graph: Next Generation Infrastructure for Semantic Scholarly Knowledge

no code implementations30 Jan 2019 Mohamad Yaser Jaradeh, Allard Oelen, Kheir Eddine Farfar, Manuel Prinz, Jennifer D'Souza, Gábor Kismihók, Markus Stocker, Sören Auer

In this paper, we present the first steps towards a knowledge graph based infrastructure that acquires scholarly knowledge in machine actionable form thus enabling new possibilities for scholarly knowledge curation, publication and processing.

Knowledge Graphs

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