An orchestration of ontologies for linguistic knowledge

Starting from multilingual knowledge representation in ontologies and an eye on linguistic linked data and controlled natural languages, we had developed a basic ontology for the Bantu noun class system [1] to link with the lemon model [2]. The noun class system is alike gender in, e.g., German and Italian, but then a bit different. It is based on semantics of the nouns and each Bantu language has some 12-23 noun classes. For instance, noun classes 1 and 2 are for singular and plural humans, 9 and 10 for animals (singular and plural, respectively), 11 for inanimates and long thin objects (e.g., a telephone cable), and class 14 has abstract nouns (e.g., beauty). Each class has its own augment or augment+prefix to be added to the stem. None of the other linguistic resources, such as ISOcat or the GOLD ontology, dealt with them, so, lemon did not either, but we needed it. The first version of the ontology we introduced in [1] had its limitations, but it mostly did its job. Mostly, but not fully.

Lemon needs that morphology module and then some for the rules. The ontology did not fully satisfy Bantu languages other than Chichewa and isiZulu. With the knowledge of the latter only, it was more alike a merged conceptual data model, for it was tailored to the two specific languages. Also, it wasn’t aligned to other models or ontologies, thus hampering interoperability and reuse. We didn’t have any competency questions or cool inferences either, because our scope then was just to annotate the names of the classes in an ontology. Hence, it was time for an improvement.

Among others, we don’t want just to annotate, but, given that Bantu languages are underresourced, see what we can add to derive implicit information, which could help with tagging terms. For instance

• if you know abantu is a plural and in noun class 2 and umuntu is the singular of it, then umuntu is in noun class 1, or
• when it is declared that inja is in noun class 9, then so is its stem -ja (or vv), or
• language specific, which singular (plural) noun class goes with which plural (singular) noun class: while the majority neatly has a pair of successive odd and even numbers (1-2, 3-4, 5-6 etc), this is not always the case; e.g., in isiZulu, noun class 11 does not have noun class 12 as plural, but noun class 10 (which has its own augment and prefix).

Then, besides the interoperability and reuse requirements, we’d needed to distinguish between language-specific axioms and those that hold across the language family. To solve all that, we developed a framework, reusing the pyramid structure idea from BioTop [3] and the so-called “double articulation principle” of DOGMA [4], where the language-specific axioms are at the level of DOGMA’s conceptual model, for they add specific constraints.

To make a long story short, the framework/orchestration applied to the linguistic knowledge of Bantu noun classes in general, and specific to some language, looks as follows:

framework applied to some linguistics ontologies (source: [5])

More details are described in the recently accepted paper “An orchestration framework for linguistic task ontologies” [5], to be presented as the 9th Metadata and Semantics Research Conference (MTSR’15), to be held from 9 to 11 September in Manchester, UK. My co-author Catherine Chavula will be attending MTSR’15 and present our paper, hoping/assuming that all those last-minute things—like visa and money actually being transferred to buy that plane ticket—will be sorted this month. (Odd ‘checks and balances’ that make life harder and more expensive for people outside of a visa-free zone and tied to a funding benefactor is a topic for some other time.).

The set of ontologies (in OWL) is available in NCS1.zip from my ontologies directory. It contains the goldModule—a module extracted from the GOLD ontology for general linguistics knowledge and that is aligned to the foundational ontology SUMO—the NCS ontology, and three languages-specific axiomatizations for the noun classes, being Chichewa, isiXhosa, and isiZulu (more TBA). The same approach can be used for other linguistic features in other language groups or families; e.g., instead of the NCS, one could have knowledge represented about conjugation in the Romance languages (Italian, Spanish etc.), and then the more precise axiomatization (conceptual data model, if you will) for constraints unique to each language.

 

p.s.: Bantu languages is the term used in linguistics, so that’s why it’s used here. Elsewhere, they are also called African languages. They’re not synonymous, however, as the latter includes also other, non-Bantu, languages, as it can designate any language spoken in Africa that may have a wholly different grammar, hence, the difference linguists make to avoid misinterpretation.

 

References

[1] Chavula, C., Keet, C.M. Is Lemon Sufficient for Building Multilingual Ontologies for Bantu Languages? 11th OWL: Experiences and Directions Workshop (OWLED’14). Keet, C.M., Tamma, V. (Eds.). Riva del Garda, Italy, Oct 17-18, 2014. CEUR-WS vol. 1265, 61-72.

[2] McCrae, J., Aguado-de Cea, G., Buitelaar, P., Cimiano, P., Declerck, T., Gómez-Pérez, A., Gracia, J., Hollink, L., Montiel-Ponsoda, E., Spohr, D., Wunner, T.: Interchanging lexical resources on the Semantic Web. Language Resources & Evaluation, 2012, 46(4), 701-719

[3] Beißwanger, E., Schulz, S., Stenzhorn, H., Hahn, U.: Biotop: An upper domain ontology for the life sciences: A description of its current structure, contents and interfaces to obo ontologies. Applied Ontology, 2008, 3(4), 205-212

[4] Jarrar, M., Meersman, R.: Ontology Engineering The DOGMA Approach. In: Advances in Web Semantics I, LNCS, vol. 4891, pp. 7-34. Springer (2009)

[5] Chavula, C., Keet, C.M. An Orchestration Framework for Linguistic Task Ontologies. 9th Metadata and Semantics Research Conference (MTSR’15), Springer CCIS. 9-11 September, 2015, Manchester, UK. (in print)