Pular para o conteúdo principal

kgtk lexicalize

 Fonte https://kgtk.readthedocs.io/en/latest/transform/lexicalize/

kgtk lexicalize builds English sentences from KGTK edge files.

The primary purpose of this command is to construct inputs for text-based distance vector analysis. However, it may also prove useful for explaining the contents of local subsets of Knowledge Graphs.

Geração das sentenças para o grafo RDF@KGTK da base do lattes

conda activate kgtk-env

kgtk lexicalize --input-file lattes-prof4.tsv --add-entity-labels-from-input \
--label-properties foaf:name dc:title skos:prefLabel geo:name \
--description-properties foaf:citationName bio:biography bibo:presentedAt dcterms:subject geo:countrycode \
--isa rdf:type \
--property-value foaf:identifier foaf:homepage foaf:topic_interest dc:creator dc:language dcterms:isPartOf dcterms:isReferencedBy dcterms:issued \
--verbose > lattes-prof4-text.tsv  2> lattes-prof4-text.log  &

Exemplos

lattes:0088939094557856#P466    sentence    "\"Campanhas online e democracia: as mídias digitais nas eleições de 2016 nos Estados Unidos e 2018 no Brasil\", Comunicação e Política, is a bibo:Chapter dc:creator Arthur Cezar de Araujo Ituassu Filho and dc:creator Letícia Capone and dc:creator Sergio Lifschitz and dc:creator Vivian Mannheimer and dc:language Português and dcterms:isPartOf O Brasil vai às urnas: as campanhas eleitorais para presidente na TV e internet and dcterms:isReferencedBy CV Lattes de Arthur Cezar de Araujo Ituassu Filho and dcterms:issued 2019."


lattes:0088939094557856#author-idm45742451754928    sentence    "\"Sergio Lifschitz\", LIFSCHITZ, S., is a foaf:Person foaf:identifier 8164403687403639."
lattes:0088939094557856#author-idm45742452173232    sentence    "\"Sergio Lifschitz\", LIFSCHITZ, S., is a foaf:Person foaf:identifier 8164403687403639."
lattes:0088939094557856#author-idm45742452256816    sentence    "\"Sergio Lifschitz\", LIFSCHITZ, S., is a foaf:Person foaf:identifier 8164403687403639."

lattes:1095304607841635#author-idm45584827724496    sentence    "\"Sergio Lifschitz\", LIFSCHITZ, S., is a foaf:Person."
lattes:1095304607841635#author-idm45584827776128    sentence    "\"Sergio Lifschitz\", LIFSCHITZ, S., is a foaf:Person."
lattes:1095304607841635#author-idm45584827846384    sentence    "\"Sergio Lifschitz\", LIFSCHITZ, S., is a foaf:Person."
lattes:1095304607841635#author-idm45584827975008    sentence    "\"Sergio Lifschitz\", LIFSCHITZ, S., is a foaf:Person."

lattes:8164403687403639#author-idm45713126051216    sentence    "\"Sergio Lifschitz\", LIFSCHITZ, S.;LIFSCHITZ, Sergio;LIFSCHITZ, SÉRGIO, is a foaf:Person foaf:identifier 8164403687403639."
lattes:8164403687403639#author-idm45713126060592    sentence    "\"Sergio Lifschitz\", LIFSCHITZ, S.;LIFSCHITZ, Sergio;LIFSCHITZ, SÉRGIO, is a foaf:Person foaf:identifier 8164403687403639."
lattes:8164403687403639#author-idm45713126069392    sentence    "\"Sergio Lifschitz\", LIFSCHITZ, S.;LIFSCHITZ, Sergio;LIFSCHITZ, SÉRGIO, is a foaf:Person foaf:identifier 8164403687403639."

lattes:0964031559829384#P9    sentence    "\"Skew handling for parallel BLAST processing\", Bancos de Dados, is a bibo:Article dc:creator Rogério Luís de Carvalho Costa and dc:creator Sergio Lifschitz and dc:language Inglês and dcterms:isPartOf Anais. SBC and dcterms:isReferencedBy CV Lattes de Rogério Luís de Carvalho Costa and dcterms:issued 2003."


lattes:8164403687403639#masterthesis3    sentence    "\"Um Algoritmo Linear para o Cálculo de Algumas Funções Distância entre Polígonos Convexos\", Matemática da Computação, is a bibo:Thesis dc:creator lattes:8164403687403639#author-idm45713129642576 and dcterms:isReferencedBy CV Lattes de Sergio Lifschitz and dcterms:issued 1990."


lattes:8164403687403639#phdthesis7    sentence    "\"Stratégies d\'Evaluation Parallèle de Requêtes Datalog Récursives\", Banco de Dados, is a bibo:Thesis dc:creator lattes:8164403687403639#author-idm45713129642576 and dcterms:isReferencedBy CV Lattes de Sergio Lifschitz and dcterms:issued 1994."

Mas ainda não consegui gerar os text embeddings com essa base de dados

Comentários

Postagens mais visitadas deste blog

Connected Papers: Uma abordagem alternativa para revisão da literatura

Durante um projeto de pesquisa podemos encontrar um artigo que nos identificamos em termos de problema de pesquisa e também de solução. Então surge a vontade de saber como essa área de pesquisa se desenvolveu até chegar a esse ponto ou quais desdobramentos ocorreram a partir dessa solução proposta para identificar o estado da arte nesse tema. Podemos seguir duas abordagens:  realizar uma revisão sistemática usando palavras chaves que melhor caracterizam o tema em bibliotecas digitais de referência para encontrar artigos relacionados ou realizar snowballing ancorado nesse artigo que identificamos previamente, explorando os artigos citados (backward) ou os artigos que o citam (forward)  Mas a ferramenta Connected Papers propõe uma abordagem alternativa para essa busca. O problema inicial é dado um artigo de interesse, precisamos encontrar outros artigos relacionados de "certa forma". Find different methods and approaches to the same subject Track down the state of the art rese...

Knowledge Graph Embedding with Triple Context - Leitura de Abstract

  Jun Shi, Huan Gao, Guilin Qi, and Zhangquan Zhou. 2017. Knowledge Graph Embedding with Triple Context. In Proceedings of the 2017 ACM on Conference on Information and Knowledge Management (CIKM '17). Association for Computing Machinery, New York, NY, USA, 2299–2302. https://doi.org/10.1145/3132847.3133119 ABSTRACT Knowledge graph embedding, which aims to represent entities and relations in vector spaces, has shown outstanding performance on a few knowledge graph completion tasks. Most existing methods are based on the assumption that a knowledge graph is a set of separate triples, ignoring rich graph features, i.e., structural information in the graph. In this paper, we take advantages of structures in knowledge graphs, especially local structures around a triple, which we refer to as triple context. We then propose a Triple-Context-based knowledge Embedding model (TCE). For each triple, two kinds of structure information are considered as its context in the graph; one is the out...

KnOD 2021

Beyond Facts: Online Discourse and Knowledge Graphs A preface to the proceedings of the 1st International Workshop on Knowledge Graphs for Online Discourse Analysis (KnOD 2021, co-located with TheWebConf’21) https://ceur-ws.org/Vol-2877/preface.pdf https://knod2021.wordpress.com/   ABSTRACT Expressing opinions and interacting with others on the Web has led to the production of an abundance of online discourse data, such as claims and viewpoints on controversial topics, their sources and contexts . This data constitutes a valuable source of insights for studies into misinformation spread, bias reinforcement, echo chambers or political agenda setting. While knowledge graphs promise to provide the key to a Web of structured information, they are mainly focused on facts without keeping track of the diversity, connection or temporal evolution of online discourse data. As opposed to facts, claims are inherently more complex. Their interpretation strongly depends on the context and a vari...