# Wikidata Support in the Creation of Rich Semantic Metadata for Historical Archives
###### Abstract
Referring to such a domain, we selected 200 documents from the Istituto Gramsci's collections, mainly newspaper/review articles and typewritten leaflets, often with handwritten annotations (see Figure 1). Moreover, we developed an  
Figure 1: A document from the archives of the Gramsci Institute, talking about the FIAT company (Copyright: Fondazione Istituto piemontese Antonio Gramsci onlus). ontology-driven prototype web platform, enabling users to annotate such documents (see Section 2). However, ontology-based annotation is a very challenging task, also for expert users, especially since it is extremely time-consuming. For this reason, we implemented a double support for the users of the PRiSMHA annotation platform, exploiting both automatic Information Extraction techniques, namely Named Entity Recognition (NER), when full text is available, and entity linking to Linked Open Data (LOD) sets (see [6] for details about this double support). In particular, as regards the support provided by external datasets, the first step has been the integration of a functionality enabling Wikidata [7] search. This functionality provides users with (a) the possibility of linking an entity (i.e., a person, an organization, or a place) belonging to the PRiSMHA knowledge base to a Wikidata entity; (b) the suggestion of values for the _category_ and _label_ fields in the form the user has to fill in to characterize the new entity (see Section 2). We evaluated the double support with users, and the results showed that NER and entity linking to LOD actually support users in the annotation activity in an effective way; in particular, users appreciated the pre-filling of _category_ and _label_ fields in the form for creating a new entity (see [6]). Moreover, in the free comments, some users asked for more effective help, i.e., for suggestions about other properties characterizing the entity in focus. In the same study, some participants provided us with another reason to offer a better support when building semantic metadata: some of them claimed that the task was quite complex, since typically, several entities need to be characterized in order to describe the content of a text fragment. For example, when describing an event (e.g., a protest march) mentioned in a document, users may need to characterize all the single involved entities (such as place, time, people, organizations, etc. ), and gathering information about such entities can be time consuming and even distracting from the original task (i.e., the description of the event itself). On the basis of these suggestions we designed, implemented, and tested a new version of the support system which involved the following when characterizing a new entity (e.g., a person): (a) more properties, besides _category_ and _label_, are automatically pre-filled in; (b) more complex semantic representations are suggested, for example the creation of one or more events, in which the entity in focus is involved with a specific role (see Sections 3 and 4 for details). In the proof-of-concept prototype of this new version of the annotation platform, both kinds of suggestions are based on information retrieved from Wikidata. Two main issues have to be faced in order to reach this goal: (a) the alignment of the semantic model underlying Wikidata with the ontology used in the PRiSMHA system (described in Section 3); (b) on the basis of such an alignment, an effective process to extract useful information from Wikidata and a User Interface to provide users with suggestions (described in Section 4).