Details
| Original language | English |
|---|---|
| Title of host publication | The Web Conference 2021 |
| Subtitle of host publication | Companion of the World Wide Web Conference, WWW 2021 |
| Pages | 678-679 |
| Number of pages | 2 |
| ISBN (electronic) | 9781450383134 |
| Publication status | Published - 19 Apr 2021 |
| Event | World Wide Web Conference (WWW 2021) - Ljubljana, Slovenia Duration: 19 Apr 2021 → 23 Apr 2021 Conference number: 30 |
Abstract
Information Extraction (IE) tasks are commonly studied topics in various domains of research. Hence, the community continuously produces multiple techniques, solutions, and tools to perform such tasks. However, running those tools and integrating them within existing infrastructure requires time, expertise, and resources. One pertinent task here is triples extraction and linking, where structured triples are extracted from a text and aligned to an existing Knowledge Graph (KG). In this paper, we present Plumber , the first framework that allows users to manually and automatically create suitable IE pipelines from a community-created pool of tools to perform triple extraction and alignment on unstructured text. Our approach provides an interactive medium to alter the pipelines and perform IE tasks. A short video to show the working of the framework for different use-cases is available online1.
Keywords
- Information Extraction, NLP Pipelines, Semantic Web, Software Reusability
ASJC Scopus subject areas
- Computer Science(all)
- Computer Networks and Communications
- Computer Science(all)
- Software
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
The Web Conference 2021 : Companion of the World Wide Web Conference, WWW 2021. 2021. p. 678-679.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Plumber
T2 - World Wide Web Conference (WWW 2021)
AU - Jaradeh, Mohamad Yaser
AU - Singh, Kuldeep
AU - Stocker, Markus
AU - Auer, Sören
N1 - Conference code: 30
PY - 2021/4/19
Y1 - 2021/4/19
N2 - Information Extraction (IE) tasks are commonly studied topics in various domains of research. Hence, the community continuously produces multiple techniques, solutions, and tools to perform such tasks. However, running those tools and integrating them within existing infrastructure requires time, expertise, and resources. One pertinent task here is triples extraction and linking, where structured triples are extracted from a text and aligned to an existing Knowledge Graph (KG). In this paper, we present Plumber , the first framework that allows users to manually and automatically create suitable IE pipelines from a community-created pool of tools to perform triple extraction and alignment on unstructured text. Our approach provides an interactive medium to alter the pipelines and perform IE tasks. A short video to show the working of the framework for different use-cases is available online1.
AB - Information Extraction (IE) tasks are commonly studied topics in various domains of research. Hence, the community continuously produces multiple techniques, solutions, and tools to perform such tasks. However, running those tools and integrating them within existing infrastructure requires time, expertise, and resources. One pertinent task here is triples extraction and linking, where structured triples are extracted from a text and aligned to an existing Knowledge Graph (KG). In this paper, we present Plumber , the first framework that allows users to manually and automatically create suitable IE pipelines from a community-created pool of tools to perform triple extraction and alignment on unstructured text. Our approach provides an interactive medium to alter the pipelines and perform IE tasks. A short video to show the working of the framework for different use-cases is available online1.
KW - Information Extraction
KW - NLP Pipelines
KW - Semantic Web
KW - Software Reusability
UR - http://www.scopus.com/inward/record.url?scp=85107643199&partnerID=8YFLogxK
U2 - 10.48550/arXiv.2206.01442
DO - 10.48550/arXiv.2206.01442
M3 - Conference contribution
AN - SCOPUS:85107643199
SP - 678
EP - 679
BT - The Web Conference 2021
Y2 - 19 April 2021 through 23 April 2021
ER -