@inproceedings{mendes-etal-2024-application,
title = "Application of Generative {AI} as an Enterprise Wikibase Knowledge Graph {Q}{\&}{A} System",
author = "Mendes, Ren{\^e} and
Oliveira, Dimas and
Garcia, Victor",
editor = "Biswas, Russa and
Kaffee, Lucie-Aim{\'e}e and
Agarwal, Oshin and
Minervini, Pasquale and
Singh, Sameer and
de Melo, Gerard",
booktitle = "Proceedings of the 1st Workshop on Knowledge Graphs and Large Language Models (KaLLM 2024)",
month = aug,
year = "2024",
address = "Bangkok, Thailand",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.kallm-1.4",
pages = "35--42",
abstract = "Generative AI and Large Language Models are increasingly used in business contexts. One application involves natural language conversations contextualized by company data, which can be accomplished by Enterprise Knowledge Graphs, standardized representations of data. This paper outlines an architecture for implementation of an Enterprise Knowledge Graph using open-source Wikibase software. Additionally, it is presented a Knowledge Graph Q{\&}A System powered by Generative AI.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="mendes-etal-2024-application">
<titleInfo>
<title>Application of Generative AI as an Enterprise Wikibase Knowledge Graph Q&A System</title>
</titleInfo>
<name type="personal">
<namePart type="given">Renê</namePart>
<namePart type="family">Mendes</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Dimas</namePart>
<namePart type="family">Oliveira</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Victor</namePart>
<namePart type="family">Garcia</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2024-08</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 1st Workshop on Knowledge Graphs and Large Language Models (KaLLM 2024)</title>
</titleInfo>
<name type="personal">
<namePart type="given">Russa</namePart>
<namePart type="family">Biswas</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Lucie-Aimée</namePart>
<namePart type="family">Kaffee</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Oshin</namePart>
<namePart type="family">Agarwal</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Pasquale</namePart>
<namePart type="family">Minervini</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Sameer</namePart>
<namePart type="family">Singh</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Gerard</namePart>
<namePart type="family">de Melo</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Bangkok, Thailand</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>Generative AI and Large Language Models are increasingly used in business contexts. One application involves natural language conversations contextualized by company data, which can be accomplished by Enterprise Knowledge Graphs, standardized representations of data. This paper outlines an architecture for implementation of an Enterprise Knowledge Graph using open-source Wikibase software. Additionally, it is presented a Knowledge Graph Q&A System powered by Generative AI.</abstract>
<identifier type="citekey">mendes-etal-2024-application</identifier>
<location>
<url>https://aclanthology.org/2024.kallm-1.4</url>
</location>
<part>
<date>2024-08</date>
<extent unit="page">
<start>35</start>
<end>42</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Application of Generative AI as an Enterprise Wikibase Knowledge Graph Q&A System
%A Mendes, Renê
%A Oliveira, Dimas
%A Garcia, Victor
%Y Biswas, Russa
%Y Kaffee, Lucie-Aimée
%Y Agarwal, Oshin
%Y Minervini, Pasquale
%Y Singh, Sameer
%Y de Melo, Gerard
%S Proceedings of the 1st Workshop on Knowledge Graphs and Large Language Models (KaLLM 2024)
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F mendes-etal-2024-application
%X Generative AI and Large Language Models are increasingly used in business contexts. One application involves natural language conversations contextualized by company data, which can be accomplished by Enterprise Knowledge Graphs, standardized representations of data. This paper outlines an architecture for implementation of an Enterprise Knowledge Graph using open-source Wikibase software. Additionally, it is presented a Knowledge Graph Q&A System powered by Generative AI.
%U https://aclanthology.org/2024.kallm-1.4
%P 35-42
Markdown (Informal)
[Application of Generative AI as an Enterprise Wikibase Knowledge Graph Q&A System](https://aclanthology.org/2024.kallm-1.4) (Mendes et al., KaLLM-WS 2024)
ACL