Knowledge Graph Question Answering for Materials Science (KGQA4MAT): Developing Natural Language Interface for Metal-Organic Frameworks Knowledge Graph (MOF-KG)

no code implementations • 20 Sep 2023 • Yuan An, Jane Greenberg, Alex Kalinowski, Xintong Zhao, Xiaohua Hu, Fernando J. Uribe-Romo, Kyle Langlois, Jacob Furst, Diego A. Gómez-Gualdrón

To evaluate the benchmark, we have developed a systematic approach for utilizing ChatGPT to translate natural language questions into formal KG queries.

Graph Question Answering Knowledge Graphs +1

Building Open Knowledge Graph for Metal-Organic Frameworks (MOF-KG): Challenges and Case Studies

no code implementations • 10 Jul 2022 • Yuan An, Jane Greenberg, Xintong Zhao, Xiaohua Hu, Scott McCLellan, Alex Kalinowski, Fernando J. Uribe-Romo, Kyle Langlois, Jacob Furst, Diego A. Gómez-Gualdrón, Fernando Fajardo-Rojas, Katherine Ardila

Metal-Organic Frameworks (MOFs) are a class of modular, porous crystalline materials that have great potential to revolutionize applications such as gas storage, molecular separations, chemical sensing, catalysis, and drug delivery.

Text to Insight: Accelerating Organic Materials Knowledge Extraction via Deep Learning

no code implementations • 27 Sep 2021 • Xintong Zhao, Steven Lopez, Semion Saikin, Xiaohua Hu, Jane Greenberg

Given the extensive and growing volume of literature, the common approach of reading and manually extracting knowledge is too time consuming, creating a bottleneck in the research cycle.

named-entity-recognition Named Entity Recognition +1

HIVE-4-MAT: Advancing the Ontology Infrastructure for Materials Science

no code implementations • 20 Jan 2021 • Jane Greenberg, Xintong Zhao, Joseph Adair, Joan Boone, Xiaohua Tony Hu

Introduces HIVE-4-MAT - Helping Interdisciplinary Vocabulary Engineering for Materials Science, an automatic linked data ontology application.

named-entity-recognition Named Entity Recognition +3