TY - GEN

T1 - Falcon 2.0

T2 - 29th ACM International Conference on Information and Knowledge Management, CIKM 2020

AU - Sakor, Ahmad

AU - Singh, Kuldeep

AU - Patel, Anery

AU - Vidal, Maria Esther

N1 - Funding Information: This work has received funding from the EU H2020 Project No. 727658 (IASIS).

PY - 2020/10/19

Y1 - 2020/10/19

N2 - The Natural Language Processing (NLP) community has significantly contributed to the solutions for entity and relation recognition from a natural language text, and possibly linking them to proper matches in Knowledge Graphs (KGs). Considering Wikidata as the background KG, there are still limited tools to link knowledge within the text to Wikidata. In this paper, we present Falcon 2.0, the first joint entity and relation linking tool over Wikidata. It receives a short natural language text in the English language and outputs a ranked list of entities and relations annotated with the proper candidates in Wikidata. The candidates are represented by their Internationalized Resource Identifier (IRI) in Wikidata. Falcon 2.0 resorts to the English language model for the recognition task (e.g., N-Gram tiling and N-Gram splitting), and then an optimization approach for the linking task. We have empirically studied the performance of Falcon 2.0 on Wikidata and concluded that it outperforms all the existing baselines. Falcon 2.0 is open source and can be reused by the community; all the required instructions of Falcon 2.0 are well-documented at our GitHub repository (https://github.com/SDM-TIB/falcon2.0). We also demonstrate an online API, which can be run without any technical expertise. Falcon 2.0 and its background knowledge bases are available as resources at https://labs.tib.eu/falcon/falcon2/.

AB - The Natural Language Processing (NLP) community has significantly contributed to the solutions for entity and relation recognition from a natural language text, and possibly linking them to proper matches in Knowledge Graphs (KGs). Considering Wikidata as the background KG, there are still limited tools to link knowledge within the text to Wikidata. In this paper, we present Falcon 2.0, the first joint entity and relation linking tool over Wikidata. It receives a short natural language text in the English language and outputs a ranked list of entities and relations annotated with the proper candidates in Wikidata. The candidates are represented by their Internationalized Resource Identifier (IRI) in Wikidata. Falcon 2.0 resorts to the English language model for the recognition task (e.g., N-Gram tiling and N-Gram splitting), and then an optimization approach for the linking task. We have empirically studied the performance of Falcon 2.0 on Wikidata and concluded that it outperforms all the existing baselines. Falcon 2.0 is open source and can be reused by the community; all the required instructions of Falcon 2.0 are well-documented at our GitHub repository (https://github.com/SDM-TIB/falcon2.0). We also demonstrate an online API, which can be run without any technical expertise. Falcon 2.0 and its background knowledge bases are available as resources at https://labs.tib.eu/falcon/falcon2/.

KW - background knowledge

KW - dbpedia

KW - english morphology

KW - entity linking

KW - nlp

KW - relation linking

KW - wikidata

UR - http://www.scopus.com/inward/record.url?scp=85095866274&partnerID=8YFLogxK

U2 - 10.1145/3340531.3412777

DO - 10.1145/3340531.3412777

M3 - Conference contribution

AN - SCOPUS:85095866274

T3 - International Conference on Information and Knowledge Management, Proceedings

SP - 3141

EP - 3148

BT - CIKM 2020

PB - Association for Computing Machinery (ACM)

Y2 - 19 October 2020 through 23 October 2020

ER -