Knowledge graph construction from text
Being able to organize the massive amount of unstructured data that is produced every day would make analysis simpler and uncover trends and linkages that might not otherwise be seen. Open Information Extraction (OpenIE), a popular tool, extracts semantic triples (Subject -> Relation -> Obj...
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sg-ntu-dr.10356-1630742022-11-21T02:56:57Z Knowledge graph construction from text Lim, Yi Keong Sun Aixin School of Computer Science and Engineering AXSun@ntu.edu.sg Engineering::Computer science and engineering Being able to organize the massive amount of unstructured data that is produced every day would make analysis simpler and uncover trends and linkages that might not otherwise be seen. Open Information Extraction (OpenIE), a popular tool, extracts semantic triples (Subject -> Relation -> Object) from texts. However, it could lead to ambiguity during semantic triple extraction in information extraction. Pronouns can be thought of as apart from their subject. This project aims to resolve the aforementioned ambiguity by integrating OpenIE systems with Coreference Resolution, thereby allowing the extraction of relations between entities across the entire document. Additionally, new OpenIE systems will be explored and hyperparameter tuning will be done to find the best model. Bachelor of Engineering (Computer Science) 2022-11-21T02:56:57Z 2022-11-21T02:56:57Z 2022 Final Year Project (FYP) Lim, Y. K. (2022). Knowledge graph construction from text. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/163074 https://hdl.handle.net/10356/163074 en SCSE21-0721 application/pdf Nanyang Technological University |
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Engineering::Computer science and engineering Lim, Yi Keong Knowledge graph construction from text |
description |
Being able to organize the massive amount of unstructured data that is produced every day
would make analysis simpler and uncover trends and linkages that might not otherwise be
seen. Open Information Extraction (OpenIE), a popular tool, extracts semantic triples (Subject
-> Relation -> Object) from texts. However, it could lead to ambiguity during semantic triple
extraction in information extraction. Pronouns can be thought of as apart from their subject.
This project aims to resolve the aforementioned ambiguity by integrating OpenIE systems
with Coreference Resolution, thereby allowing the extraction of relations between entities
across the entire document. Additionally, new OpenIE systems will be explored and
hyperparameter tuning will be done to find the best model. |
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Sun Aixin |
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Sun Aixin Lim, Yi Keong |
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Final Year Project |
author |
Lim, Yi Keong |
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Lim, Yi Keong |
title |
Knowledge graph construction from text |
title_short |
Knowledge graph construction from text |
title_full |
Knowledge graph construction from text |
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Knowledge graph construction from text |
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Knowledge graph construction from text |
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knowledge graph construction from text |
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Nanyang Technological University |
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2022 |
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https://hdl.handle.net/10356/163074 |
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1751548565989097472 |