Details
| Original language | English |
|---|---|
| Title of host publication | Web Engineering |
| Subtitle of host publication | 21st International Conference, ICWE 2021Biarritz, France, May 18–21, 2021Proceedings |
| Editors | Marco Brambilla, Richard Chbeir, Flavius Frasincar, Ioana Manolescu |
| Publisher | Springer Science and Business Media Deutschland GmbH |
| Pages | 240-254 |
| Number of pages | 15 |
| ISBN (print) | 9783030742959 |
| Publication status | Published - 2021 |
| Event | 21st International Conference on Web Engineering, ICWE 2021 - Virtual, Online Duration: 18 May 2021 → 21 May 2021 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 12706 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (electronic) | 1611-3349 |
Abstract
We propose Plumber, the first framework that brings together the research community’s disjoint information extraction (IE) efforts. The Plumber architecture comprises 33 reusable components for various Knowledge Graphs (KG) information extraction subtasks, such as coreference resolution, entity linking, and relation extraction. Using these components, Plumber dynamically generates suitable information extraction pipelines and offers overall 264 distinct pipelines. We study the optimization problem of choosing suitable pipelines based on input sentences. To do so, we train a transformer-based classification model that extracts contextual embeddings from the input and finds an appropriate pipeline. We study the efficacy of Plumber for extracting the KG triples using standard datasets over two KGs: DBpedia, and Open Research Knowledge Graph (ORKG). Our results demonstrate the effectiveness of Plumber in dynamically generating KG information extraction pipelines, outperforming all baselines agnostics of the underlying KG. Furthermore, we provide an analysis of collective failure cases, study the similarities and synergies among integrated components, and discuss their limitations.
Keywords
- Information extraction, NLP pipelines, Semantic search, Semantic Web, Software reusability
ASJC Scopus subject areas
- Mathematics(all)
- Theoretical Computer Science
- Computer Science(all)
- General Computer Science
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Web Engineering : 21st International Conference, ICWE 2021Biarritz, France, May 18–21, 2021Proceedings. ed. / Marco Brambilla; Richard Chbeir; Flavius Frasincar; Ioana Manolescu. Springer Science and Business Media Deutschland GmbH, 2021. p. 240-254 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12706 LNCS).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Better Call the Plumber
T2 - 21st International Conference on Web Engineering, ICWE 2021
AU - Jaradeh, Mohamad Yaser
AU - Singh, Kuldeep
AU - Stocker, Markus
AU - Both, Andreas
AU - Auer, Sören
N1 - Funding Information: Acknowledgements. This work was co-funded by the European Research Council for the project ScienceGRAPH (Grant agreement ID: 819536) and the TIB Leibniz Information Centre for Science and Technology.
PY - 2021
Y1 - 2021
N2 - We propose Plumber, the first framework that brings together the research community’s disjoint information extraction (IE) efforts. The Plumber architecture comprises 33 reusable components for various Knowledge Graphs (KG) information extraction subtasks, such as coreference resolution, entity linking, and relation extraction. Using these components, Plumber dynamically generates suitable information extraction pipelines and offers overall 264 distinct pipelines. We study the optimization problem of choosing suitable pipelines based on input sentences. To do so, we train a transformer-based classification model that extracts contextual embeddings from the input and finds an appropriate pipeline. We study the efficacy of Plumber for extracting the KG triples using standard datasets over two KGs: DBpedia, and Open Research Knowledge Graph (ORKG). Our results demonstrate the effectiveness of Plumber in dynamically generating KG information extraction pipelines, outperforming all baselines agnostics of the underlying KG. Furthermore, we provide an analysis of collective failure cases, study the similarities and synergies among integrated components, and discuss their limitations.
AB - We propose Plumber, the first framework that brings together the research community’s disjoint information extraction (IE) efforts. The Plumber architecture comprises 33 reusable components for various Knowledge Graphs (KG) information extraction subtasks, such as coreference resolution, entity linking, and relation extraction. Using these components, Plumber dynamically generates suitable information extraction pipelines and offers overall 264 distinct pipelines. We study the optimization problem of choosing suitable pipelines based on input sentences. To do so, we train a transformer-based classification model that extracts contextual embeddings from the input and finds an appropriate pipeline. We study the efficacy of Plumber for extracting the KG triples using standard datasets over two KGs: DBpedia, and Open Research Knowledge Graph (ORKG). Our results demonstrate the effectiveness of Plumber in dynamically generating KG information extraction pipelines, outperforming all baselines agnostics of the underlying KG. Furthermore, we provide an analysis of collective failure cases, study the similarities and synergies among integrated components, and discuss their limitations.
KW - Information extraction
KW - NLP pipelines
KW - Semantic search
KW - Semantic Web
KW - Software reusability
UR - http://www.scopus.com/inward/record.url?scp=85111157954&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-74296-6_19
DO - 10.1007/978-3-030-74296-6_19
M3 - Conference contribution
AN - SCOPUS:85111157954
SN - 9783030742959
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 240
EP - 254
BT - Web Engineering
A2 - Brambilla, Marco
A2 - Chbeir, Richard
A2 - Frasincar, Flavius
A2 - Manolescu, Ioana
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 18 May 2021 through 21 May 2021
ER -