Note: This is a historical document (from 2007!) that describes the original motivations for the development of OLiA in the context of the project “Sustainability of Linguistic Data” (funded by DFG, 2005-2008 at U Tübingen, U Hamburg, U Potsdam; Germany). Subsequently, novel fields of application have emerged.
Concentrating on the more elementary levels of linguistic analysis such as parts of speech and morphology, a generalization over different terminologies applied for the annotation of the corpora hosted by three collaborative research centers SFB 441 (Tübingen), SFB 538 (Hamburg) and SFB 632 (Potsdam/Berlin) was developed, and later extended for NLP tools and corpora beyond these resources. As a result, an ontology was developed which specifies reference terminology, and the tags of the original annotated data are linked with this reference terminology. Besides its function in annotation documentation, the ontology can be applied for the formulation of tag-set neutral corpus queries. For this purpose, I developed the OntoClient, a JAVA-based query pre-processor which translates formal ontology-based specifications into disjunctions of concrete tags. The OntoClient serves as a pre-processor for corpus querying languages such as ANNIS-QL and CQP, furthermore, it was applied in the specification of tag-set independent corpus processing scripts. The current developmental stage of the OLiA ontologies is available here.
The OLiA ontologies were initially developed in the context of the project "Sustainability of Linguistic Resources", a collaborative project between three German Collaborative Research Centers (SFBs), The Collaborative Research Centres involved in the project are the SFB 538 'Multilingualism'at the University of Hamburg, the SFB 632 'Information Structure' at the University of Potsdam and the Humboldt University Berlin, and the SFB 441 'Linguistic Data Structures' at the Eberhard Karls University Tübingen.
The project aimed at preparing language resources to assure an accessible dissemination and sustainable storage of linguistic corpora. One of the main goals of the project was a practical one: resources acquired in long-term projects situated in the three Collaborative Research Centres have to be converted in either one or multiple formats to be sustainably usable by researchers and applications. Furthermore, the project developed unified methods of access for the heterogeneous data acquired in the projects.
The linguistic resources dealt by the project are highly heterogeneous:
See here for a general description of the project in Tübingen.
One of the tasks addressed by the sustainability project was the integration of heterogeneous terminology, especially those applied for the annotation of existing corpora. Examples for such differences range from minor variation in the choice of tag names (which often go unrealized and thus, affect the reliability of broad-scale corpus studies) to fundamental conceptual differences.
All these problems are taken from the seemingly most elementary domain, the domain of part of speech tags, however, more problems arise as soon as morphology, syntax, or discourse phenomena are addressed.
In order to overcome such problems, terminological integration is necessary, i.e.
To provide an integrated access to terminologically heterogeneous resources, it is also necessary to provide an abstract model of linguistic reference terminology to which individual annotations refer, a so-called "terminological backbone".
Classical solutions are the standardization approach and the interlingua approach:
Both solutions are limited in flexibility and scalability, and hence, both approaches are applicable only within a limited domain. The standardization approach relies on the existence of common grammatical categories and features found in the languages for which standard-conformant tag sets are to be developed. Otherwise, it results in projection of complexity (e.g. the standard entails predictions for grammatical categories for a standard-conformant tagset which are absent in a language). However, even the sheer existence of universal morphosyntactic categories has been questioned in typologic research, and hence, the EAGLES-based standardization approach is unlikely to extend beyond "Standard Average European" languages.
The interlingua approach, however, involves the process to construct an interlingua between existing schemes, and is less statically than the standardization process. However, the complexity of the interlingua grows monotonically with every new language/tag set considered, and, hence, the general applicability of the interlingua approach is restricted by its limited scalability.
Therefore, the project is currently developing an ontology of linguistic annotations as a more flexible representation of a "terminological backbone".
So far, we have developed an ontology of linguistic annotations with special consideration of part of speech and morphological annotations existing the participating Collaborative Research Centers (Schmidt et al. 2006, Chiarcos 2006c, Chiarcos 2006d, Chiarcos 2007).
The approach relies on the ontological reconstruction of annotation schemes based on guidelines and additional documentation in so-called "annotation models" (or "domain models").
Every annotation model represents one tag set or annotation scheme, with nonterminal nodes (concepts) representing conceptual categories as mentioned in the documentation or indicated in the document structure of the annotation guidelines, and terminal nodes (instances) representing concrete annotation values, or tags.
As an illustration, prototypes for the following annotation models are available in an HTML serialization:
With respect to morphosyntactic annotations, the OLiA annotation models currently comprise 16 annotation schemes applied to 42 languages (5 annotation models for English, 5 annotation models for German, 2 annotation models for Russian, one annotation model for Tibetan, one for Old High German, the Connexor annotation model for 10 European languages, one annotation model for a typologically-oriented annotation scheme applied to 29 languages). Annotation models for syntax and information structure/anaphora are currently under construction.
The concepts of these annotation models are linked to a common "reference model" which is based on the EAGLES recommendations for morphosyntax, and extended according to the needs of the participating annotation models, hence it is also referred to as "E(xtended)-EAGLES" ontology.
The annotation models are then mapped onto the categories specified in the reference model by means of conceptual subsumption (rdfs:subClassOf, rdfs:subPropertyOf). This mapping is specified in separate "linking files", thus making both the reference model and the annotation models independent and self-contained ontologies.
The "reference model", however, does not specify authoritative definitions for existing terminology, but only a fairly traditional view on it. Hence, its primary function is not to provide prescriptive definitions of terms, but only to provide a reference point for the participating annotation models. Whenever a more reliable ontology of linguistic terminology will be developed (e.g. revised versions of the General Ontology of Linguistic Description (GOLD) or the grammis ontology), the reference model can be linked with it in the same way as the annotation models are linked with the reference model, and thus mediate between such an external reference model and the annotation models. In this sense, the reference model serves as an interface to the annotation model, and it could be better termed "interface model".
Besides the purely documentation function of the ontologies, the specifications in the ontology can be used for tag-set neutral corpus querying. In essence, this means that expressions from the ontology can be directly used for corpus queries. As an example, a user may enter the query
PossessivePronoun and hasNumber(Singular) and hasGender(Neuter) and hasCase(Genitive)
instead of the SUSANNE tag
APPGh1 is shorter, but it is a cryptic and idiosyncratic
abbreviation, and knowing about the function of
APPGh1 in SUSANNE
helps nothing when searching for the corresponding items in, say, the
Uppsala corpus, where the same query expands to
pronomen_pos_1p_gen_sg_neut_opl \| pronomen_pos_2p_gen_sg_neut_opl [\| \...]
Especially, this kind of ontology-based corpus querying can thus allow researchers unfamiliar with a certain resource to take a first glance at a corpus with an unknown tag set without having to spend to much efforts in locating and consuming the annotation documentation. Hence, the bias for re-usability of existing resources is substantially lowered.
For ontology-based corpus querying, the OntoClient is developed, a JAVA-package that works as a pre-processor for corpus queries. Given a certain string, the OntoClient replaces ontology-sensitive sub-strings with the disjunction of tags retrieved as instances which satisfy the criteria specified in the ontology-sensitive sub-string.
The output of the OntoClient is highly configurable, and thus, it can be easily applied to practically any kind of existing corpus query interface.