46 citations · 144 across the 21 of their papers we have counts for
24 papers
Contextual Augmentation for Entity Linking using Large Language Models
Daniel Vollmers, Hamada M. Zahera, Diego Moussallem +1
Entity Linking involves detecting and linking entity mentions in natural language texts to a knowledge graph. Traditional methods use a two-step process with separate models for en…
LOLA -- An Open-Source Massively Multilingual Large Language Model
Nikit Srivastava, Denis Kuchelev, Tatiana Moteu Ngoli +5
This paper presents LOLA, a massively multilingual large language model trained on more than 160 languages using a sparse Mixture-of-Experts Transformer architecture. Our architect…
MST5 -- Multilingual Question Answering over Knowledge Graphs
Nikit Srivastava, Mengshi Ma, Daniel Vollmers +3
Knowledge Graph Question Answering (KGQA) simplifies querying vast amounts of knowledge stored in a graph-based model using natural language. However, the research has largely conc…
Convolutional Hypercomplex Embeddings for Link Prediction
Caglar Demir, Diego Moussallem, Stefan Heindorf +1
Knowledge graph embedding research has mainly focused on the two smallest normed division algebras, and . Recent results suggest that trilinear products of…
Knowledge Graph Question Answering using Graph-Pattern Isomorphism
Daniel Vollmers, Rricha Jalota, Diego Moussallem +3
Knowledge Graph Question Answering (KGQA) systems are based on machine learning algorithms, requiring thousands of question-answer pairs as training examples or natural language pr…
A shallow neural model for relation prediction
Caglar Demir, Diego Moussallem, Axel-Cyrille Ngonga Ngomo
Knowledge graph completion refers to predicting missing triples. Most approaches achieve this goal by predicting entities, given an entity and a relation. We predict missing triple…
NABU Multilingual Graph-based Neural RDF Verbalizer
Diego Moussallem, Dwaraknath Gnaneshwar, Thiago Castro Ferreira +1
The RDF-to-text task has recently gained substantial attention due to continuous growth of Linked Data. In contrast to traditional pipeline models, recent studies have focused on n…
Knowledge Graphs for Multilingual Language Translation and Generation
Diego Moussallem
The Natural Language Processing (NLP) community has recently seen outstanding progress, catalysed by the release of different Neural Network (NN) architectures. Neural-based approa…
Where is Linked Data in Question Answering over Linked Data?
Tommaso Soru, Edgard Marx, André Valdestilhas +3
We argue that "Question Answering with Knowledge Base" and "Question Answering over Linked Data" are currently two instances of the same problem, despite one explicitly declares to…
A Holistic Natural Language Generation Framework for the Semantic Web
Axel-Cyrille Ngonga Ngomo, Diego Moussallem, Lorenz Bühmann
With the ever-growing generation of data for the Semantic Web comes an increasing demand for this data to be made available to non-semantic Web experts. One way of achieving this g…
Semantic Web for Machine Translation: Challenges and Directions
Diego Moussallem, Matthias Wauer, Axel-Cyrille Ngonga Ngomo
A large number of machine translation approaches have recently been developed to facilitate the fluid migration of content across languages. However, the literature suggests that m…
Augmenting Neural Machine Translation with Knowledge Graphs
Diego Moussallem, Mihael Arčan, Axel-Cyrille Ngonga Ngomo +1
While neural networks have been used extensively to make substantial progress in the machine translation task, they are known for being heavily dependent on the availability of lar…
Neural Machine Translation for Query Construction and Composition
Tommaso Soru, Edgard Marx, André Valdestilhas +3
Research on question answering with knowledge base has recently seen an increasing use of deep architectures. In this extended abstract, we study the application of the neural mach…
Entity Linking in 40 Languages using MAG
Diego Moussallem, Ricardo Usbeck, Michael Röder +1
A plethora of Entity Linking (EL) approaches has recently been developed. While many claim to be multilingual, the MAG (Multilingual AGDISTIS) approach has been shown recently to o…
NeuralREG: An end-to-end approach to referring expression generation
Thiago Castro Ferreira, Diego Moussallem, Ákos Kádár +2
Traditionally, Referring Expression Generation (REG) models first decide on the form and then on the content of references to discourse entities in text, typically relying on featu…
Expeditious Generation of Knowledge Graph Embeddings
Tommaso Soru, Stefano Ruberto, Diego Moussallem +4
Knowledge Graph Embedding methods aim at representing entities and relations in a knowledge base as points or vectors in a continuous vector space. Several approaches using embeddi…
RDF2PT: Generating Brazilian Portuguese Texts from RDF Data
Diego Moussallem, Thiago Castro Ferreira, Marcos Zampieri +4
The generation of natural language from Resource Description Framework (RDF) data has recently gained significant attention due to the continuous growth of Linked Data. A number of…
LIDIOMS: A Multilingual Linked Idioms Data Set
Diego Moussallem, Mohamed Ahmed Sherif, Diego Esteves +2
In this paper, we describe the LIDIOMS data set, a multilingual RDF representation of idioms currently containing five languages: English, German, Italian, Portuguese, and Russian.…
Machine Translation using Semantic Web Technologies: A Survey
Diego Moussallem, Matthias Wauer, Axel-Cyrille Ngonga Ngomo
A large number of machine translation approaches have recently been developed to facilitate the fluid migration of content across languages. However, the literature suggests that m…
BENGAL: An Automatic Benchmark Generator for Entity Recognition and Linking
Axel-Cyrille Ngonga Ngomo, Michael Röder, Diego Moussallem +2
The manual creation of gold standards for named entity recognition and entity linking is time- and resource-intensive. Moreover, recent works show that such gold standards contain…
TANKER: Distributed Architecture for Named Entity Recognition and Disambiguation
Sandro A. Coelho, Diego Moussallem, Gustavo C. Publio +1
Named Entity Recognition and Disambiguation (NERD) systems have recently been widely researched to deal with the significant growth of the Web. NERD systems are crucial for several…
SPARQL as a Foreign Language
Tommaso Soru, Edgard Marx, Diego Moussallem +4
In the last years, the Linked Data Cloud has achieved a size of more than 100 billion facts pertaining to a multitude of domains. However, accessing this information has been signi…
MAG: A Multilingual, Knowledge-base Agnostic and Deterministic Entity Linking Approach
Diego Moussallem, Ricardo Usbeck, Michael Röder +1
Entity linking has recently been the subject of a significant body of research. Currently, the best performing approaches rely on trained mono-lingual models. Porting these approac…
Using Ontology-Based Context in the Portuguese-English Translation of Homographs in Textual Dialogues
Diego Moussallem, Ricardo Choren
This paper introduces a novel approach to tackle the existing gap on message translations in dialogue systems. Currently, submitted messages to the dialogue systems are considered…