Towards a Multi-Level Annotation Format for the Interoperability of Automatic Term Extraction Corpora
Authors: Nicola Cirillo, Daniela Vellutino (Università di Salerno, 2023)
Topic: Lexical and Semantic Resources and Analysis

Abstract
The main corpora used as benchmarks in Automatic Term Extraction are represented in different formats. Unfortunately, none of these formats covers the wide range of linguistic phenomena related to terminology. To address this issue, we propose to encode Automatic Term Extraction corpora in RDF using the OntoLex-Lemon and the NLP Interchange Format ontologies. Furthermore, we developed a small Italian corpus on waste management legislation to provide an example of the proposed formalization.

Introduction
Automatic Term Extraction - ATE is an NLP task that involves recognizing terms in specialized corpora. As with most NLP tasks, ATE research benefits from annotated corpora that are employed as training data and evaluation benchmarks. Nevertheless, existing term annotation schemata are far from capturing the complex organization that characterizes the terminology of specialized languages [1, 2, 3]. Most ATE studies, with a few exceptions [4, 5, 6], overlook the complex organization of terms in specialized languages assuming that the terms contained in a corpus belong to a single domain. At best, they draw a difference between domain terms (that belong to the investigated domain) and out-of-domain terms (that belong to different domains). Unfortunately, this assumption is too simplistic since every specialized corpus contains terms from different subject fields. Moreover, in the interest of reusability, researchers who use terminology corpora in their work must be able to define the subject fields of interest according to their needs. Furthermore, ATE corpora do not adhere to standard formats used to encode terminological data like TermBase eXchange, an ISO standard [7], and OntoLex-Lemon, a W3C standard. This lack of standardization poses interoperability issues and hinders the evaluation of ATE tools. The adoption of a standard format will provide at least three main benefits: • It will grant the interoperability of termbases. Therefore if a term is already present in an existing termbase, it could be imported. • It will grant the interoperability of corpora, meaning that multiple corpora could be combined to cover different languages and subject fields. • It will ease the effort made to evaluate ATE tools from both sides developers and users. In this paper, we propose a custom form design of multilevel annotation to formalize ATE corpora in RDF format by using the OntoLex-Lemon1 and the NLP Interchange Format - NIF2 ontologies to represent termbases and corpora, respectively. Moreover, we develop a small annotated corpus to provide a proof-of-concept. The corpus and the code employed in its formalization are publicly available on GitHub3 The remainder of this paper is organized as follows. Section 2 lays out the main feature of terms. Section 3 gives an overview of the main ATE corpora. Section 4 illustrates the proposed formalization schema. In Section 5 we describe the corpus annotation experiment. Finally, Section 6 provides conclusions.

Conclusion
The lack of standardization in the representation of ATE corpora constitutes a bottleneck for the evaluation of ATE tools. To address this issue, we proposed an RDF-based formalization that employs OntoLex-Lemon to represent termbases and NIF to represent corpora. We showed that these formats are able to represent the wide range of linguistic and conceptual phenomena that characterize terminology. In addition, we developed a small corpus about waste management legislation in order to provide an example of the proposed formalization. In future, we plan to convert the major ATE corpora into the proposed format, to further improve ATE standardization. Moreover, we intend to increase the size and quality of the small ATE corpus we developed.