Terminological Knowledge Base Research Articles

Phraseology and Culture in Terminological Knowledge Bases: The Case of Pollution and Environmental Law

Despite its importance, environmental law has largely been ignored in environmental knowledge bases. This may be due to the fact that legal issues may not, strictly speaking, be considered scientific knowledge in environmental knowledge resources, which may in turn relate to the complexity of reflecting the cultural component (which includes different legal systems) in the description of terms and concepts. The terminological knowledge base EcoLexicon has recently begun to include information on environmental law. This paper takes the methodological perspective of frame-based terminology to analyze typical verb collocations in environmental law that will be added to the phraseology module of EcoLexicon. Corpus analysis was used to compare the behavior of verbs collocating with pollution in environmental science and environmental law. Verbs were classified based on lexical domains and semantic classes through definition factorization, as described in the Lexical Grammar Model. The differences were mostly based on the specificity of the arguments and the emphasis on the polluter in environmental law. This resulted in a proposal for the inclusion and configuration of environmental law phraseology in EcoLexicon, showing sociocultural differences across environmental subdomains.

Semantic Representation of Context for Description of Named Rivers in a Terminological Knowledge Base.

The description of named entities in terminological knowledge bases has never been addressed in any depth in terminology. Firm preconceptions, rooted in philosophy, about the only referential function of proper names have presumably led to disparage their inclusion in terminology resources, despite the relevance of named entities having been highlighted by prominent figures in the discipline of terminology. Scholars from different branches of linguistics depart from the conservative stance on proper names and have foregrounded the need for a novel approach, more linguistic than philosophical, to describing proper names. Therefore, this paper proposed a linguistic and terminological approach to the study of named entities when used in scientific discourse, with the purpose of representing them in EcoLexicon, an environmental knowledge base designed according to the premises of Frame-based Terminology. We focused more specifically on named rivers (or potamonyms) mentioned in a coastal engineering corpus. Inclusion of named entities in terminological knowledge bases requires analyzing the context that surrounds them in specialized texts because these contexts convey specialized knowledge about named entities. For the semantic representation of context, this paper thus analyzed the local syntactic and semantic contexts that surrounded potamonyms in coastal engineering texts and described the semantic annotation of the predicate-argument structure of sentences where a potamonym was mentioned. The semantic variables annotated were the following: (1) semantic category of the arguments; (2) semantic role of the arguments; (3) semantic relation between the arguments; and (4) lexical domain of the verbs. This method yielded valuable insight into the different semantic roles that named rivers played, the entities and processes that participated in the events educed by potamonyms through verbs, and how they all interacted. Furthermore, since arguments are specialized terms and verbs are relational constructs, the analysis of argument structure led to the construction of semantic networks that depicted specialized knowledge about named rivers. These conceptual networks were then used to craft the thematic description of potamonyms. Accordingly, the semantic network and the thematic description not only constituted the representation of a potamonym in EcoLexicon, but also allowed the geographic contextualization of specialized concepts in the terminological resource.

Cultural Context and Multimodal Knowledge Representation: Seeing the Forest for the Trees.

Context, especially cultural context, has long been neglected in Terminology. Even though recent approaches have acknowledged the relevance of culture in specialized communication, the development of culture in Terminology is still marginal. Culture is also underrepresented in terminological resources, which may respond to the complexity of reflecting the cultural component in the description of terms and concepts. However, conceptualization is dynamic and changes from culture to culture and, for that reason, an in-depth study on how the nature of human perception and cultural cognition influences the representation of concept systems and terms in specialized knowledge contexts is needed. Furthermore, to facilitate knowledge acquisition, contextual and conceptual information should go together with multimodal information, as the combination of textual and visual material improves understanding. This study integrates different types of context (i.e., semantic relations, frames, and culture) to describe a methodology for the selection and representation of multimodal information for culturally bound concepts such as forest in terminological knowledge bases, based on the theoretical premises of Frame-Based Terminology. Different ideas of forest in European countries were analyzed and represented by means of culturally adapted images, which are best suited to disseminate knowledge and foreground the role of culture in specialized communication.

Pollution in Environmental Law: Comparative Corpus Analysis

Abstract Environmental Law has been mostly ignored in terminological knowledge bases (TKBs) on the environment. EcoLexicon, a multilingual and multimodal TKB on the environment, has recently begun to include information on this transversal domain. In this study, comparative corpus analysis is carried out in Sketch Engine (Kilgarriff et al. 2014) to analyse the differences between Environmental Law and Environmental Science from the theoretical and methodological perspective of Frame-Based Terminology (Faber 2012, 2015). More specifically, the focus is on multidimensionality: how concepts change their behaviour according to the context in which they participate. The results show that different facets of the Pollution frame are highlighted and its participants change in the Environmental Law domain as compared to Environmental Science. Finally, the complex multidimensional nature of the Pollution frame is represented in EcoLexicon with a combination of graphical and linguistic expression in conceptual networks and definitions.

Extraction of Terms Semantically Related to Colponyms: Evaluationin a Small Specialized Corpus

This research was carried out as part of project PID2020-118369GB-I00, Transversal Integration of Culture in a Terminological Knowledge Base on Environment (TRANSCULTURE), funded by the Spanish Ministry of Science and Innovation.

Handling inconsistency in partially preordered ontologies: the Elect method

Abstract We focus on the problem of handling inconsistency in lightweight ontologies. We assume that the terminological knowledge base (TBox) is specified in DL-Lite and that the set of assertional facts (ABox) is partially preordered and may be inconsistent with respect to the TBox. One of the main contributions of this paper is the provision of an efficient and safe method, called Elect, to restore the consistency of the ABox with respect to the TBox. In the case where the assertional base is flat (i.e. no priorities are associated with the ABox) or totally preordered, we show that our method collapses with the well-known intersection ABox repair semantics and the non-defeated semantics, respectively. The semantic justification of the Elect method is obtained by first viewing a partially preordered ABox as a family of totally preordered ABoxes and then applying non-defeated inference to each of the totally preordered ABoxes. We introduce the notion of elected assertions which allows us to provide an equivalent characterization of the Elect method without explicitly generating all the totally preordered ABoxes. We show that computing the set of elected assertions is done in polynomial time with respect to the size of the ABox. The second part of the paper discusses how to go beyond the Elect method. In particular, we discuss to what extent the Elect method can be generalized to description logics that are more expressive than DL-Lite.

EcoLexicon and by-products

Abstract Reutilization and interoperability are major issues in the fields of knowledge representation and extraction, as reflected in initiatives such as the Semantic Web and the Linked Open Data Cloud. This paper shows how terminological resources can be integrated and reused within different types of application. EcoLexicon is a multilingual terminological knowledge base (TKB) on environmental science that integrates conceptual, linguistic and visual information. It has led to the following by-products: (i) the EcoLexicon English Corpus; (ii) EcoLexiCAT, a terminology-enhanced translation tool; and (iii) Manzanilla, an image annotation tool. This paper explains EcoLexicon and its by-products, and shows how the latter exploit and enhance the data in the TKB.

Frame-based terminology applied to military science: transforming a glossary into a knowledge resource

This paper describes a Frame-Based Terminology approach to the military terminology of the Spanish Armed Forces. The alphabetically organized (PD0-000) glossary of military terms of the Spanish Armed Forces was transformed into MiliMarco [MiliFrame], a bilingual terminological knowledge base in which each concept appears within a hierarchy of conceptual categories and a semantic network. Frame-based resources enhance access to domain knowledge in a contextualized way, since embedding concepts in a knowledge structure activates associative information in semantic memory and promotes context availability. The design and population of MiliMarco involved the analysis and transformation of the content in the glossary entries as well as the extraction of new information. For this purpose, specialized knowledge structures were elaborated from the definitions in the glossary and from the lexicalization of semantic relations in the corpus. New concepts were added to fill the gaps in the glossary and additional data categories were included, such as images, collocations, and contexts. Previous work on military ontologies, usually in the form of controlled, structured vocabularies, is limited to a specific domain (e.g., military intelligence). MiliMarco has the advantage of providing an expanded view of the military domain in the form of conceptual networks combined with linguistic contexts that go far beyond simple hierarchies. Although still an ongoing project, the resulting knowledge base is currently a concept-oriented resource where users can browse through the conceptual hierarchy and semantic networks based on their cognitive and communicative needs.

Extraction of Terms Related to Named Rivers

EcoLexicon is a terminological knowledge base on environmental science, whose design permits the geographic contextualization of data. For the geographic contextualization of landform concepts, this paper presents a semi-automatic method for extracting terms associated with named rivers (e.g., Mississippi River). Terms were extracted from a specialized corpus, where named rivers were automatically identified. Statistical procedures were applied for selecting both terms and rivers in distributional semantic models to construct the conceptual structures underlying the usage of named rivers. The rivers sharing associated terms were also clustered and represented in the same conceptual network. The results showed that the method successfully described the semantic frames of named rivers with explanatory adequacy, according to the premises of Frame-Based Terminology.

Phraseology in specialized resources: an approach to complex nominals

In English, the international language of communication (Tono in Lexicography 1(1):1–5, 2014), complex nominals (CNs) are frequently used to convey specialized concepts (Sager et al. in English special languages. Principles and practice in science and technology. Brandstetter Verlag, Wiesbaden, 1980; Nakov in Natural Language Engineering 19(03):291–330, 2013). These phraseological units have a nominal head that is modified by another element (e.g., hydropower production). Problems can arise in relation to their identification, their bracketing or internal structure disambiguation, their meaning access, and their translation or production in another language. Although they are not marginal phenomena in specialized language, they are rarely included in specialized resources. Even when they are included, their treatment is not systematic (Cabezas-Garcia and Faber in Computational and corpus-based phraseology. Springer, Cham, pp 145–159, 2017a). This article describes the representation of CNs in EcoLexicon ( http://www.ecolexicon.ugr.es ), a terminological knowledge base, whose new phraseological module will include verb collocations (e.g., a volcano spews lava) as well as CNs. For that purpose, we used a wind power corpus in English and Spanish for term extraction, semantic analysis, establishment of interlinguistic correspondences, and definition crafting. We propose different access points to information (Kwary in International Journal of Lexicography 25(1):30–49, 2012), such as the CNs formed from a given term, a bilingual view in English and Spanish, or the syntactic–semantic combinations in CNs. The structure of the CN module is based on the semantics of these phraseological units, which facilitates the specification of mapping rules as well as knowledge acquisition (Faber in A cognitive linguistics view of terminology and specialized language. De Gruyter Mouton, Berlin, 2012).

Recent Advances in EcoLexicon

EcoLexicon is a multilingual terminological knowledge base concerning the environment. It is the practical application of Frame-based Terminology, a cognitive approach to the representation of specialized knowledge. Recent enhancements include the EcoLexicon English corpus, a phraseological module, and a flexible approach to terminological definitions.

Supervized machine learning: Computer-aided development of a specialized dictionary

This paper presents a software complex for the computer-aided modeling of a term system. The project is implemented as an expert system that consists of a research team, a terminological knowledge base, a developer interface (the Semograf information system), and a user interface (TSBuilder and TSReader). Computer-aided design of a term system was achieved using data-mining methods, namely, decision-making trees and a modification of Rosenblatt's perceptron.

Image selection and annotation for an environmental knowledge base

Images play an important role in the representation and acquisition of specialized knowledge. Not surprisingly, terminological knowledge bases (TKBs) often include images as a way to enhance the information in concept entries. However, the selection of these images should not be random, but rather based on specific guidelines that take into account the type and nature of the concept being described. This paper presents a proposal on how to combine the features of images with the conceptual propositions in EcoLexicon, a multilingual TKB on the environment. This proposal is based on the following: (1) the combinatory possibilities of concept types; (2) image types, such as photographs, drawings and flow charts; (3) morphological features or visual knowledge patterns (VKPs), such as labels, colours, arrows, and their effect on the functional nature of each image type. Currently, images are stored in association with concept entries according to the semantic content of their definitions, but they are not described or annotated according to the parameters that guided their selection, which would undoubtedly contribute to the systematization and automatization of the process. First, the images included in EcoLexicon were analyzed in terms of their adequateness, the semantic relations expressed, the concept types and their VKPs. Then, with these data, guidelines for image selection and annotation were created. The final aim is twofold: (1) to systematize the selection of images and (2) to start annotating old and new images so that the system can automatically allocate them in different concept entries based on shared conceptual propositions.

Term extraction and management based on event templates

The paper examines the possible usage of event templates derived from Frame-Based Terminology (Faber et al. 2005, 2006, 2007) as an aid to the extraction and management of legal terminology embedded in the multi-level legal system of the European Union. The method proposed here, which combines semi-automatic term extraction and a simplified event template containing six categories, is applied to an English corpus of EU texts focusing on victims of crime and their rights. Such a combination allows for the extraction of category-relevant terminological units and additional information, which can then be used for populating a terminological knowledge base organised on the basis of the same event template, but which also employs additional classification criteria to account for the multidimensionality encountered in the corpus.

Corpora as a Source of Biomedical Information: Building a Technological Knowledge Base

The versatility of linguistic corpora makes them an excellent conceptual and terminological resource. For their part, knowledge bases are rapidly gathering momentum in the field of terminology, since they allow for the creation of multidimensional conceptual systems, a significant leap forward from the traditional hierarchical or tree framework. In this paper we propose the use of a Spanish and French comparable corpus to extract terminological and conceptual information on galactosemia, a disorder belonging to the medical sub-domain of rare diseases, followed by the construction of an ontology to create a terminological knowledge base on this pathology11This research project was partially funded by the Department of Culture, Education and Universities of the Regional Government of Galicia (Spain) through grants awarded for the Consolidation and Structuring of Competitive Research Units within the Galician University System (ref. CN2012/317).. The purpose of this study is to further the development of resources that provide a satisfactory description of rare diseases, enabling translators, specialised authors, medical professionals and other users to accurately and properly understand and write texts on the topic.

Dynamism and context in specialized knowledge

EcoLexicon is a terminological knowledge base (TKB) on the environment which seeks to enhance both cognitive and communicative needs of different users. In order to achieve this, TKBs should reflect conceptual structures in a similar way to how concepts relate in the human mind (Meyer et al. 1992). Categorization itself is a dynamic context-dependent process. Therefore, representation and acquisition of specialized knowledge should certainly focus on contextual variation. In EcoLexicon, such contextualization takes the form of dynamic information modules, such as conceptual networks, images, textual information, and terminological variance. Recontextualization provides a way of representing the dynamic and multidimensional nature of conceptualization processes in the mind. On the one hand, it offers a qualitative criterion for the representation of specialized concepts in line with the workings of the human conceptual system. On the other hand, it provides a quantitative solution to the problem of information overload, as it significantly reduces irrelevant context-free information.

Type-elimination-based reasoning for the description logic SHIQbs using decision diagrams and disjunctive datalog

We propose a novel, type-elimination-based method for reasoning in the description logic SHIQbs including DL-safe rules. To this end, we first establish a knowledge compilation method converting the terminological part of an ALCIb knowledge base into an ordered binary decision diagram (OBDD) which represents a canonical model. This OBDD can in turn be transformed into disjunctive Datalog and merged with the assertional part of the knowledge base in order to perform combined reasoning. In order to leverage our technique for full SHIQbs, we provide a stepwise reduction from SHIQbs to ALCIb that preserves satisfiability and entailment of positive and negative ground facts. The proposed technique is shown to be worst case optimal w.r.t. combined and data complexity and easily admits extensions with ground conjunctive queries.

Terminological resources for text mining over biomedical scientific literature

We present a combined terminological resource for text mining over biomedical literature. The purpose of the resource is to allow the detection of mentions of specific biological entities in scientific publications, and their grounding to widely accepted identifiers. This is an essential process, useful in itself, and necessary as an intermediate step for almost every type of complex text mining application. We discuss some of the properties of the terminology for this domain, in particular the degree of ambiguity, which constitutes a peculiar problem for text mining applications. Without a correct recognition and disambiguation of the domain entities no reliable results can be produced. We also discuss an application that makes use of the resulting terminological knowledge base. We annotate an existing corpus of sentences about protein interactions. The annotation consists of a normalization step that matches the terms in our resource with their actual representation in the corpus, and a disambiguation step that resolves the ambiguity of matched terms. In this paper we present a large terminological resource, compiled through the aggregation of a number of different manually curated sources. We discuss the lexical properties of such resources, specifically the degree of ambiguity of the terms, and we inspect the causes of such ambiguity, in particular for protein names. This information is of vital importance for the implementation of an efficient term normalization and grounding algorithm.

Ontodomo: um modelo de base de conhecimentos terminológicos

In this article, we present some results of our Ph.D. thesis research in which we proposed to build a model of a Terminological Knowledge Base (TKB) based on a specialized corpus (Domo corpus). The main purpose of our research was the definition of the theoretical and methodological foundations, as well the experimentation of different Natural Language Processing (NLP) tools and techniques for the acquisition of terms and conceptual relationships, which are necessary both for the terminological structuring, the corpus and the domain modelling. In these few pages, we intend only to show the main features of our TBK model, implemented in an integrated computer system – OntoDomo.

Contextual information in terminological knowledge bases: A multimodal approach

Abstract In Lexicology and Terminology, the notion of context often refers to a textual excerpt selected according to syntactic criteria, leaving aside any semantic and pragmatic analysis. For the creation of terminological knowledge bases (TKBs), this notion is too simplistic. Contexts must be studied from an integrated approach, such as Frame Semantics and Frame-Based Terminology. These theoretical and methodological frameworks do not separate the semantic and pragmatic components of language. Meaning is acquired in context, more specifically, within a frame including a semantic and pragmatic background. Within the domain of the environment, we select and manipulate multimodal information to offer two kinds of contexts to the end-user: (1) FrameNet-like contexts, more specifically, sentences showing the different syntactic constructions of the frame elements and the target predicate; (2) combined contexts, including knowledge-rich linguistic contexts coupled with knowledge-rich visual contexts, which provide a comprehensive view of related processes and specialized lexical units. In the TKB EcoLexicon, the resulting multimodal contexts are structured in terms of specific frames and general events. Thus, the end-users have the possibility to find both cognitive and communicative information, which is selected according to the user's level of expertise.