=Paper=
{{Paper
|id=Vol-1676/paper7
|storemode=property
|title=Re-designing Online Terminology Resources for German Grammar
|pdfUrl=https://ceur-ws.org/Vol-1676/paper7.pdf
|volume=Vol-1676
|authors=Karolina Suchowolec,Christian Lang,Roman Schneider
|dblpUrl=https://dblp.org/rec/conf/ercimdl/SuchowolecLS16
}}
==Re-designing Online Terminology Resources for German Grammar==
https://ceur-ws.org/Vol-1676/paper7.pdf
Re-designing Online Terminology Resources for
German Grammar
Project Report
Karolina Suchowolec, Christian Lang, and Roman Schneider
Institut für Deutsche Sprache (IDS), Mannheim, Germany
{suchowolec, lang, schneider}@ids-mannheim.de
Abstract The compilation of terminological vocabularies plays a cen-
tral role in the organization and retrieval of scientific texts. Both simple
keyword lists as well as sophisticated modellings of relationships between
terminological concepts can make a most valuable contribution to the
analysis, classification, and finding of appropriate digital documents, ei-
ther on the Web or within local repositories. This seems especially true
for long-established scientific fields with various theoretical and histor-
ical branches, such as linguistics, where the use of terminology within
documents from different origins is sometimes far from being consistent.
In this short paper, we report on the early stages of a project that aims at
the re-design of an existing domain-specific KOS for grammatical content
grammis. In particular, we deal with the terminological part of grammis
and present the state-of-the-art of this online resource as well as the key
re-design principles. Further, we propose questions regarding ramifica-
tions of the Linked Open Data and Semantic Web approaches for our
re-design decisions.
1 State of the Art
Grammis is a specialized hypertext resource hosted by the Institute for German
Language (IDS) in Mannheim.1 It brings together terminological, lexicographi-
cal, and bibliographic information about German grammar. Initiated more than
two decades ago, it combines the traditional description of grammatical struc-
tures with the results of corpus-based studies. From a technical point of view,
all primary data and meta data is coded within more than one thousand semi-
structured XML instances that are composed of semantical markup element
types (title, header, example, link anchor, etc.).
From the user’s perspective, grammis consists of several components. The
core component uses comprehensive reference texts, which describe grammatical
phenomena in great detail. In contrast, the terminological component is meant
to be a short reference, where each entry concisely describes a grammar concept
and, therefore, gives just the basic notion of it. It also (statically) points the user
to relevant entries in the core component for further reference.
1
http://hypermedia.ids-mannheim.de/
As of now, the intended user of grammis needs a sound knowledge in the
field of grammar. This means that he or she needs to be a professional lin-
guist, most likely a grammar scholar. However, there are other online resources
on German grammar hosted by IDS that target at different user groups; for
instance, ProGr@mm is dedicated to teaching and explaining grammar to non-
scholars, such as students of linguistics.2 It mirrors the structure of grammis,
i.e. has similar components such as comprehensive references texts and termi-
nological reference. These components, however, may or may not have the same
content as corresponding grammis entries. Also, there are other, more special-
ized, resources, for example on so-called connectors, which are results of different
research projects at IDS.
Finally, there is a separate terminological resource called grammatische On-
tologie [9].3 It is, in fact, a taxonomy of regular hierarchical relations such as
broader/narrower term (both generic and partitive) (BT/NT), related term (RT)
as well as synonym relation. No other information on terms and concepts such as
scope notes or definitions is given. This resource, which has been developed and
maintained independently of grammis, is implemented in an object-relational
database management system (ORDBMS). It also serves a different purpose—it
(dynamically) generates a list of references to other terminological, lexicograph-
ical, and bibliographic resources by IDS on a given topic, and uses the hierarchy
to generate more relevant hits.
To sum it up, the landscape of online terminology resources at IDS is het-
erogeneous. Above all, it is a result of different research projects, with different
goals, scopes, scholarly traditions, and persons involved. Therefore, it covers
different areas of grammar with different degrees of specialization. Moreover,
terminology is currently managed within different tools, depending on whether
it is used in the grammis dictionaries, ontology, or bibliography. Further, the
content often reflects needs of heterogeneous user groups. And finally, different
resources were designed with different purposes in mind—to serve as a concise
grammar reference or a repository for enhancing information retrieval.
In addition, there is a broad spectrum of terminology that is yet to be covered
by terminology resources. To deal with these heterogeneities, distributions, and
unsatisfactory coverage of terminology resources, IDS has launched a project for
re-designing the current terminology management.
2 Re-Design Principles
To address the above-mentioned issues of heterogeneity, distribution, and cover-
age of the current terminology resources, we propose the following work packages
for the re-design of the terminology management, which are described in more
detail below.
– Combining distributed terminology resources into one resource;
2
http://hypermedia.ids-mannheim.de/programm/
3
http://hypermedia.ids-mannheim.de/call/public/termwb.html
– Updating the content using automated keyword extraction techniques;
– Ensuring interoperability of the new resource with other projects;
– Implementing a new backend for terminology management.
2.1 Combining Resources into one Resource
One way of improving the current terminology management for both, the user
and the (terminology) author, is to unite the scattered terminology resources
into one global resource. The new resource should first incorporate not only
the descriptions of single concepts and terms, but also the relations between
them. In other words, it should contain both—the hierarchy and the descriptive
information about terms and concepts within this hierarchy.
Moreover, we are exploring the question, to what extent we can further unify
this resource to globally serve for different target groups and for results from
different research projects. These considerations have implications for the content
of the entries, but also for their structure and, derived from that, for the data
modelling. Therefore, we are currently evaluating the style and the structure
of the existing terminology entries in order to find a common and hence more
consistent way of authoring them.
2.2 Automated Keyword Extraction
To enhance the coverage of the new resource, we use automatic keyword ex-
traction on the core component’s entries. Topic Rank [1], an algorithm based
on Page Rank [2], is applied to each entry of grammis, ProGr@mm and the
specialized resources. In addition to standard linguistic preprocessing we opti-
mize the algorithm’s input by excluding non-domain-specific (loglikelihood [7]
and weirdness ratio [3] against DeReKo corpus [cf. 6]) and non-characteristic
candidate words (TF-IDF [10], Gries DP [4]). As a plus, we exploit the semantic
markup of heterogeneous text sections, coded with XML element types. In a pre-
liminary study, we compare recall and precision performance of the automatized
extraction against a human annotated gold standard.
2.3 Interoperability
The end-user of the new resource will be provided, as with the current resource,
with an online interface. However, we also want to ensure that our data is trans-
parent as well as easily accessible, exchangeable, and reusable within different
(scientific) contexts and applications. In particular, we want to make it available
to the communities that provide the scientific backbone of our project i.e. the
terminology community and the taxonomy and thesaurus community. Therefore,
we implement standard exchange formats for our data.
For the terminology community, such standard is TBX [5]. As of now, we are
evaluating data categories available in TBX and mapping them to our current
data categories. Implementing TBX without information loss would possibly
mean flattening our current meta model [cf. 8], hence reducing the number of
available relation types to fit into the three-level TBX meta model.
For the taxonomy community, we identified SKOS as a possible format [11].
We also would like to look into Lemon as an alternative format with more lin-
guistic power [12]. We are exploring the implications of these formats on our
meta model and section 3 deals with our first considerations on SKOS.
2.4 New Backend for Terminology Management
From all of the above follows that the current terminology backend tools need to
be reconsidered in order to account for the changes in the terminology man-
agement. After specifying the requirements, we are now evaluating different
options for the new tool, looking into commercial native terminology, native
thesaurus, and hybrid solutions, but also considering a re-design of our own
tools. Most importantly, the new tool should manage both the hierarchy and
the descriptive information on concepts and terms within this hierarchy. Since
no language management for grammatical terminology is intended, it also needs
to efficiently manage quasi-synonyms, i.e. partially-equivalent terms, accounting
for different schools of linguistics. Further features comprise the support of the
above-mentioned exchange formats and the interoperability with other in-house
applications. Finally, visualizing data as a graph is a desirable, but an optional
feature.
3 Sematic Web and Linked Open Data Ramifications
As of now, we are still in the early stages of our project and there are some
questions we would like to discuss. As mentioned above, we are assessing the
implications of SKOS for our project, which can be summarized by the following
questions:
– What are the challenges when converting data into SKOS?
– What implications does SKOS have for our meta model?
– Taking it further, what implications for our meta model would becoming a
part of Semantic Web and Linked Open Data have?
References
1. Bougouin, A., Boudin, F., Daille, B.: TopicRank: Graph-based topic ranking for
keyphrase extraction. In: International Joint Conference on Natural Language Pro-
cessing. pp. 543–551 (2013)
2. Brin, S., Page, L.: The anatomy of a large-scale hypertextual search engine. Com-
puter Networks and ISDN Systems 30(1-7), 107–117 (1998)
3. Gillam, L., Tariq, M., Ahmad, K.: Terminology and the construction of ontology.
Terminology 11(1), 55–81 (2005)
4. Gries, S.T.: Dispersions and adjusted frequencies in corpora. International Journal
of Corpus Linguistics 13(4), 403–437 (2008)
5. ISO 30042: Systems to manage terminology, knowledge and content – TermBase
eXchange TBX. First edition (2008)
6. Kupietz, M., Keibel, H.: The Mannheim German Reference Corpus (DeReKo) as
a basis for empirical linguistic research. In: Minegishi, M., Kawaguchi, Y. (eds.)
Working Papers in Corpus-based Linguistics and Language Education, pp. 53–59.
No. 3, Tokyo University of Foreign Studies, Tokyo (2009)
7. Rayson, P., Garside, R.: Comparing corpora using frequency profiling. In: Proceed-
ings of the workshop on Comparing Corpora, 38th annual meeting of the Associa-
tion for Computational Linguistics (ACL). pp. 1–6. Hong Kong (2000)
8. Schneider, R., Gottron, T.: A hybrid approach to statistical and semantical analy-
sis of Web documents. In: Proceedings of the IASTED International Conference
Internet and Multimedia Systems and Applications (EuroImsa). pp. 115–120 (2009)
9. Sejane, I.: Wissensrepräsentation Linguistik. Modellierung, Potenzial und Gren-
zen am Beispiel der Ontologie zur deutschen Grammatik im GRAMMIS-
Informationssystem des IDS, Mannheim. phdthesis, Ruprecht-Karls-Universität
Heidelberg (2010)
10. Spärck Jones, K.: A statistical interpretation of term specifity and its application
in retrieval. Journal of Documentation 28(1), 11–21 (1972)
11. W3C: SKOS Simple Knowledge Organization System reference (2009), https://
www.w3.org/TR/2009/REC-skos-reference-20090818/, 2009-08-18
12. W3C Ontology Lexicon Community Group: Final model specification (2016),
https://www.w3.org/community/ontolex/wiki/Final_Model_Specification