When information available in unstructured or semi-structured formats, e.g., tables or texts, comes in, finding links between strings appearing in these sources and the entities they refer to in some background Knowledge Graphs (KGs) is a key step to integrate, enrich and extend the data and/or KGs. This Entity Linking task is usually decomposed into Entity Retrieval and Entity Disambiguation because of the large entity search space. This paper presents an Entity Retrieval service (LamAPI) and discusses the impact of different retrieval configurations, i.e., query and filtering strategies, on the retrieval of entities. The approach is to augment the search activity with extra information, like types, associated with the strings in the original datasets. The results have been empirically validated against public datasets.

Avogadro, R., Cremaschi, M., D'Adda, F., De Paoli, F., Palmonari, M. (2022). LamAPI: A Comprehensive Tool for String-based Entity Retrieval with Type-base Filters. In 17th International Workshop on Ontology Matching, OM 2022 (pp.25-36). CEUR-WS.

LamAPI: A Comprehensive Tool for String-based Entity Retrieval with Type-base Filters

Avogadro R.;Cremaschi M.;D'Adda F.;De Paoli F.;Palmonari M.
2022

Abstract

When information available in unstructured or semi-structured formats, e.g., tables or texts, comes in, finding links between strings appearing in these sources and the entities they refer to in some background Knowledge Graphs (KGs) is a key step to integrate, enrich and extend the data and/or KGs. This Entity Linking task is usually decomposed into Entity Retrieval and Entity Disambiguation because of the large entity search space. This paper presents an Entity Retrieval service (LamAPI) and discusses the impact of different retrieval configurations, i.e., query and filtering strategies, on the retrieval of entities. The approach is to augment the search activity with extra information, like types, associated with the strings in the original datasets. The results have been empirically validated against public datasets.
paper
Entity Disambiguation; Entity Linking; Entity Retrieval; Knowledge Graph;
English
17th International Workshop on Ontology Matching, OM 2022 - 23 October 2022
2022
Shvaiko, P; Euzenat, J; Jimenez-Ruiz, E; Hassanzadeh, O; Trojahn, C
17th International Workshop on Ontology Matching, OM 2022
2022
3324
25
36
none
Avogadro, R., Cremaschi, M., D'Adda, F., De Paoli, F., Palmonari, M. (2022). LamAPI: A Comprehensive Tool for String-based Entity Retrieval with Type-base Filters. In 17th International Workshop on Ontology Matching, OM 2022 (pp.25-36). CEUR-WS.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/412695
Citazioni
  • Scopus 1
  • ???jsp.display-item.citation.isi??? ND
Social impact