Towards a Lexicon of XIXth Century SloveneTomaž Erjavec1, Christoph Ringlstetter2, Maja Žorga3, Annette Gotscharek2
1

Department for Knowledge Technologies, Jožef Stefan InstituteJamova cesta 39, 1000 Ljubljana
tomaz.erjavec@ijs.si
2
Centre for Language and Information Processing, University of Münich
Schellingstrasse 10, 80799 Münich
kristof@cis.uni-muenchen.de, annette@cis.uni-muenchen.de
3
maja.zorga@gmail.com
Abstract
Historical Slovene texts are being increasingly digitized and made available on the internet in the scope of digital libraries, but so far
no language-technology support is offered for processing, searching and reading such materials. Appropriate lexical resources forhistorical Slovene language could significantly increase such support, by enabling better automatic OCR correction, full-text searching
and by modernizing archaic language. This paper describes the first steps in creating a historical lexicon of Slovene, which will map
archaic word-forms into modern word-forms and lemmas. The process of lexicon acquisition relies on a proof-read corpus of Slovene
books from the XIXth century, a large lexicon of contemporary Slovene language, and LeXtractor, a tool to map historical forms totheir contemporary equivalents via a set of rewrite rules, and to provide an editing environment for lexicon construction. The
envisioned lexicon should not only help in making digital libraries more accessible but also provide a quantitative basis for linguistic
explorations of historical Slovene texts.

Prvi koraki v izdelavi leksikona slovenščine devetnajstega stoletjaČedalje več slovenskih historičnih besedil je digitaliziranih in dostopnih na spletu v okviru digitalnih knjižnic, vendar zaenkrat še ni na
voljo jezikovnotehnološke podpore za obdelavo, iskanje in branje takšnih gradiv. Ustrezni leksikalni viri za historično slovenščino bi
lahko z omogočanjem popravkov avtomatsko prepoznanega besedila, iskanja po celotnem besedilu in modernizacijo arhaičnega jezika
občutno izboljšali tako podporo. Članek opiše prve korake v razvoju historičnega leksikona slovenščine, ki bo pripisal arhaičnim
besednim oblikam sodobne besedne oblike in leme. Proces gradnje slovarja se naslanja na korigirani korpus slovenskih knjig 19.
stoletja, obsežen leksikon sodobnega slovenskega jezika in orodje, ki omogoča tako preslikavo historičnih oblik v njihove sodobne
ustreznice s pomočjo prepisovalnih pravil kot urejevalno okolje za gradnjo slovarja. Tako zastavljeni leksikon ne bo le omogočil večjo
dostopnost digitalnih knjižnic, temveč bo predstavljal tudi kvantitativno osnovo za jezikoslovne raziskave historičnih slovenskih
besedil.

1. Introduction
In the context of digital libraries human language
technology support can bring increased functionality esp.
for full-text search and information retrieval. The mostobvious task is automatic lemmatisation of text, which
abstracts away from the morphological variationencountered in heavily inflecting languages, such as
Slovene. The user can thus query for e.g. mati (mother)and receives portions of text containing this word in anyof its inflected forms (matere, materi, materjo, etc.).
Support for lemmatisation, as well as morphosyntactic
tagging is well-advanced for modern-day Slovene(Erjavec & Džeroski, 2004). However, the situation isvery different for historical Slovene, where no suchdetailed research has yet been carried out for the language.
Historical Slovene language1 brings with it a numberof problems related to automatic processing:• due to the low print quality, optical character
recognition (OCR) produces much worse results thanfor modern day texts; currently, such texts must be
hand-corrected to arrive at acceptable quality levels;• full-text search is difficult, as the texts are notlemmatised and use different orthographic

conventions with different archaic spellings, typicallynot familiar to the user;• comprehension of the texts for most users can also be
problematic, esp. with texts older than 1850 which
use the Bohoričica alphabet.2
The above problems would be alleviated by using alarge lexicon of historical Slovene language giving the
mapping of historical word-forms into their modern-day
equivalents with associated lemmas. OCR engines could
make use of such a lexicon to guide the recognition
process; texts could be lemmatised enabling better search;and the texts could be transcribed using modern day
equivalents of the word-forms to facilitate reading.
Developing a lexicon of historical Slovene is a very
timely undertaking, as a large number of books andperiodicals from the XIXth century are being madeavailable on the internet, e.g. in the context of the dLib.si
digital library3 (Krstulović and Šetinc, 2005) and the
Slovene literary classics in WikiSource4 – Hladnik (2009)
gives an overview of digitisation efforts and availability of
Slovene texts on the internet.
The lexicon we are developing has a simple structure,
where each entry contains the following fields:

2

1

In this paper we concentrate on the Slovene language from the
XIXth century; the problems are, of course, worse going further
back in time, but even here, due to the late development of thewritten Slovene word and its spelling standardisation, there aresubstantial differences to contemporary Slovene.

The Bohoričica alphabet had different conventions in writing
various Slovene sounds, e.g. »shaloſt« is the modern-day»žalost«, which makes it confusing for today’s readers.
3
http://www.dlib.si/
4
http://sl.wikisource.org/wiki/Wikivir:Slovenska_leposlovna_kla
sika

•

a word-form that has been witnessed in a proof-readhistorical text
• the equivalent word-form from contemporary Slovene• the contemporary lemma of the word-form• the lexical morphosyntactic properties of the lemmaCompiling such a lexicon with sufficient coverage is a
non-trivial process: a representative corpus of proof-readhistorical texts must be compiled, a comprehensive
modern-day lexicon must be obtained, and the word-stockof the former must be matched against the latter. Problems
arise in methodological issues (not all historical wordforms even have a modern day equivalent) as well as
technological ones (having a good software environment
for lexicon construction).
The rest of this paper is structured as follows: in
Section 2 we present the language resources we currently
use for lexicon construction, in particular the AHLib
historical corpus and FidaPLUS contemporary language
lexicon; in Section 3 we introduce the LeXtractor softwareenvironment used for lexicon construction; Section 4
discusses the main issues so far discovered in building thelexicon; and Section 5 gives some conclusions anddirections for further work.

each word was automatically annotated with its
morphosyntactic description (MSD) and lemma. The
MSDs are compact strings that give the morphosyntactic
features of the word form, and can be decomposed intofeatures, e.g. the MSD Ncmsn is equivalent to the feature
set Noun, Type = common, Gender = masculine,
Number = singular, Case = nominative.
The lexicon was gathered from the corpus by
extracting all the triplets consisting of the word-form,
lemma and MSD. The word-forms were lowercased, andthe word-boundary symbol added to the start and end of
the word (c.f. next section). Using regular expressions,entries with anomalous “words” were removed, and only
those lexical items with a frequency greater than 4 wereretained. The MSDs were also reduced to the lexicalfeatures, e.g. from Ncmsan to Ncm, which simplifies thetask of the lexicographer when adding new words to thelexicon. With this we arrived at a lexicon, which is large
enough to serve as a reference lexicon of modern wordforms. The lexicon contains about 600,000 word-forms
and 200,000 lemmas.

2. The corpus and lexicon

This section first explains the general ideas andprinciples guiding our corpus-based construction of lexica
for historical language and then describes a web tool forcollaborative construction of historical lexica, initiallyconceptualized for German (Gotscharek et al., 2009), andits adaptation for the Slovenian lexicon project.

For the historical lexicon of Slovene to be built using
the envisaged methodology, three language resources areneeded: a proof-read reference corpus of historical texts, alarge lexicon of modern-day Slovene, and the patterns ofhistorical spelling variation. In this section we detail thefirst two resources, and leave the third for the discussion
in the next section.

2.1.

The AHLib corpus

The corpus we currently use was compiled in thescope of the project Deutsch-slowenische / kroatischeÜbersetzung 1848–1918 (Prunč, 2007). The projectaddressed the linguistic study of Slovene books translated
from German in the period 1848–1918, where a large
portion of the effort went towards building a digital library(compiling a corpus) of these translations. To this end, thebooks were first scanned and OCRed, and then, for a
portion of the corpus, the transcription was handcorrected, marked-up with structural information, and, fora few books, lemmatised; this process was supported by a
web interface (Erjavec, 2007).
The subcorpus chosen for building the historicallexicon includes all the AHLib proof-read books written
before the year 1900, where the oldest one was publishedin 1847. There are all together 71 such books, of which
the majority (56) are fiction (mostly novels) while 15 arenon-fiction (from self-help books for farmers, to textbooks on astronomy, chemistry, etc.). All together the
corpus contains approximately 2.2 million running words.
While certainly small compared to most corpora ofcontemporary language, it is large and varied enough toenable us to start building the lexicon.

2.2.

The FidaPLUS lexicon

The lexicon of contemporary Slovene used was
extracted from the FidaPLUS corpus5 (Arhar and Gorjanc,2007), a large corpus of contemporary Slovene, where5

http://www.fidaplus.net/

3. LeXtractor and approximate string
matching

3.1 Corpus based lexicon construction
Given a sufficiently large historical corpus, we ignore
all words found in a contemporary lexicon of the language
processed, as well as special contemporary vocabularysuch as names, geographic expressions, etc. The
remaining words are analyzed by their frequency ofoccurrence in the historical corpus. This frequency-based
construction ensures that the lexicon soon enables areasonable recall over the word tokens that represent
historical variants of contemporary words.
In order to minimize the cognitive load of thelexicographers, we employ a number of advanced NLP
techniques. Our intention is the following ideal division ofwork: it is the role of the machine to produce meaningful
suggestions of what to include into the lexicon; thelexicographers are enabled to concentrate on the linguistic
decision according to the corpus material; they can justconfirm or reject the suggestions. In the real production
process (cf. Section 4), difficult cases where more
complex actions and unsupported input of thelexicographers is needed also occur. In what follows wedescribe the resources that are used to come close to theidealistic goal.
Word lists for contemporary vocabulary. To separate
between contemporary words and historical spellings, acollection of word lists of contemporary vocabulary isused. We use special lists for names and geographic
expressions, as well as a large list Dmod that covers thecontemporary standard vocabulary of the processedlanguage.
List of patterns. For Slovene as well as for otherlanguages, many historical spelling variants can be traced
back to a set of rewrite rules or “patterns” that locallyexplain the difference between contemporary andhistorical spelling. The most prominent pattern forSlovene is r→er as exemplified by the pair brž→berž.
Based on corpus inspection and as a side result of lexicon
construction, we currently collected a list P of 57 patterns
for Slovene; of these, 26 are for transliteration (e.g., e→ê
or š→ſh), and the rest for “proper” changes in spelling. It
should be noted that our patters can also be sensitive to theword boundary, as some spelling changes occur only at
the start or the end of the word, e.g. žganjem→žganjam,
where the inflectional ending -am has changed intomodern-day -em. To enable this functionality, the words
in Dmod are embedded in a special character (@), e.g.
@žganjem@, and the appropriate patterns make use ofthis symbol, e.g. em@→am@.
Matching modulo patterns. We employ a tool formatching modulo patterns. The tool uses the word list Dmodand the list of patterns P as background resources. Given
an input token w’ occurring in the historical corpus, allentries w in Dmod are computed where w′ can be obtained
from w by applying one or several patterns. The output list
is ranked, preferring candidates w where a small numberof pattern applications are needed to rewrite w into w′.
With each suggestion w the tool also outputs the set ofpatterns that are used to rewrite w into w′. The tool isimplemented as a finite-state device. The lexicon Dmod isrepresented as a deterministic finite-state automaton. For
traversal of the automaton, a special procedure has been
implemented that takes pattern variation into account,using the list of patterns P.
Lemmatizing contemporary word-forms. The output of
the above process are one or several contemporary wordforms w which correspond to a given historical token w’.
It remains to assign the correct lemma(s) and part-ofspeech (lexical category) to the word-form(s) w. A
lemmatiser for the processed language is used to map acontemporary inflected word-form w to all possible
corresponding lemmas. In the case of Slovene,“lemmatizing” of w is implemented by the modern
Slovene lexicon. The lexicon holds full forms with thelemma and morphological information attached. This
enables us to add linguistic features like part-of-speech
and morpho-syntactic information to the entry of w’.

database consist of the historical string as found in the
corpus, the corresponding contemporary word-form andlemma, the part-of-speech category, pointers toconcordances6 in the historical corpus which serve as
attestations for the given interpretation, and the name ofthe person who created the entry. Note that a historicalstring can be associated with several entries of thedatabase. The database also contains “non-standard”
entries such as named entities, abbreviations, andhistorical words that do not have a corresponding
contemporary lemma.
The graphical user interface visualizes the different
workflows to create lexicon entries of the words in the
corpus. Figure 1 shows the frequency list mode with thepattern based strings on the left and the non-derivablestrings on the right hand side. If the user selects a token wof the left list, she is taken to a new screen that visualizes
the possible interpretations of w. By an interpretation wemean a pattern based derivation of w from a valid
contemporary word-form (cf. Figure 2). The user now
confirms or rejects the proposed interpretations. For eachconfirmed interpretation, the linguistic readings in termsof the corresponding lemma(s) have to be determined.

3.2 A web-tool for collaborative construction oflexica for historical language
A web-based tool was designed to implement theworkflow of NLP supported collaborative lexicon
construction. The main modules of the web-tool are amanaging module, which guarantees that no conflicts arise
when several lexicographers simultaneously work on the
vocabulary of the corpus, an analyzer module, and thegraphical user interface; the latter two are described in
more detail below.
Given a historical string w’ observed in the corpus, theanalyzer
modulefirstsuggests
corresponding
contemporary word-forms w from the contemporary
lexicon Dmod based on matching. Each interpretation w
comes with the set of patterns that were applied. Second,
for a given contemporary word-form w, the analyzer
computes all the lemma(s) – including part-of-speech
information – which may underlie the word-form w.
The confirmed entries for the historical lexicon are
stored in a special database. Standard entries of theFig. 1 GUI for collaborative lexicon building, corpus
mode. Unchecked word-forms derivable by patterns fromcontemporary words are presented in the left column,
ordered by frequency; the non-derivable word-forms arein the right-hand column.

6

A concordance is a text window containing an occurrence of
the word form.

Fig. 2 Selecting possible interpretations for “kerv”. The
system suggests “kirv” and “kru”. Alternatively, “kerv”
can be added to special lists visible in the lower part.
In our case, readings based on the contemporary
lexicon are suggested by the system. Each reading is
confirmed or rejected. Before the lexicographer may
confirm a reading she has to select at least one attestation,i.e. a concordance where the reading in question is thecorrect one. To this end, all concordances are showngraphically (cf. Figure 3).
For every confirmed reading, a separate lexicon entry
is created that includes the associated attestations. If a
processed string has other than pattern based mappings to
a contemporary word form or lacks a contemporary
explanation, it is included into one of the following
special sublexica: historic words without a contemporary
equivalent; historic abbreviations; historic word-forms
which lack a simple transition pattern; named entities;
missing words of the contemporary lexicon (cf. Figure 2,
lower part).
Entries of the right frequency list are more
complicated because they are not rule-based variants interms of patterns. The system can’t suggest the mappingof a historical string w’ to its contemporary equivalent w
automatically, so w has to be specified manually. If
necessary, the lexicographer can also assign these entries
to the special lexica mentioned above. If the lexicographer
sees a derivation from a contemporary word using a newpattern p she can suggest to add p to the list of patterns. In
the current version, there are no automated update
mechanisms for the list of patterns and the matchingprocedure.
Document mode. The lexicographer may also decide towork on a specific text. On the basis of the current lexicon
and the matching rules, the text is visualized with allwords marked according to their lexical explanation (cf.
Figure 3). Additional information is provided throughmouse events. We distinguish: contemporary words,
checked entries of the lexicon for historical word-forms,
entries of the left (right) frequency list shown in the
corpus mode, and non-explained strings. If a string is
activated in the document mode, the sequential processing
is the same as for the corpus mode.
The system is web based and collaborative. Bothissues are of great importance for the project. As theinvolved lexicographers do not work at the same location,
flexibility concerning their individual workplaces isneeded. Since the professional abilities of the contributors
and the complexity of certain lexical entries differ
significantly, a workflow was created that leaves morechallenging entries in the frequency list to the trained
historical linguists, whereas the other lexicographers deal
with the simple cases.
From our present perspective, corpus, matching rules,
and lexicon should be considered as a joint knowledge
base. Given a set of patterns we may use historical wordforms and corresponding contemporary word-forms stored
in the lexicon and in addition the corpus for deriving
meaningful probabilities or edit weights for the patterns.
As a matter of fact, frequency based lexicon construction
also helps to find new relevant patterns. In this sense,
lexicon and corpus provide empirical evidence for patterns(rules) and help to fine-tune approximate matching.
Conversely, we have seen above how refined matchingprocedures help to speed up lexicon construction.
Summing up, this shows that refinement of matchingprocedures and lexicon construction can be directlyinterleaved in a kind of bootstrapping procedure.

Fig. 3 GUI for collaborative lexicon building: document mode with highlighting, in which different types of words arepresented in different colours.

3.3 Adapting the system to Slovene
In addition to integrate language specific backgroundresources, as for example, the rewrite pattern set and themodern lexicon into the system, internal software
adjustments were also necessary. To start lexicon
building, the tokenizer had to be enabled to cope withspecial characters, such as ſ and Ş introduced by thealphabet of historical Slovene. Furthermore, the software
had to be adapted to the specific format of the Slovene
modern lexicon that differs from the format used for theGerman variant of the lexicon building tool. Since the
Slovene rewrite patterns include word boundaries, thecontextual treatment of patterns had to be extended
accordingly. During the first round of lexicon production
a list of further issues turned up which is reported on in
the next section.

5.

6.

4. Discussion
Currently only a few hundred word-forms have been
added to the lexicon of historical Slovene; rather thangoing for quantity, we first concentrated on the various
types of issues that arise in lexicon construction. In thissection we discuss the main problems – and solutions –that we have encountered in our work so far. Below weprovide a typology of cases which arise in the constructionof the lexicon. The first five are already a part of
LeXtractor itself:
1. Historical word-forms without descendants: such is acase with pairs of similar words, of which only one
survived in modern Slovene; the other is thus
included under this category. For example, both
pervle and pervič (firstly[adv.]) existed in 19th century,
but only prvič is used in modern Slovene.
2. Problematic historical word-forms: although there issuch a proposed category in LeXtractor, we are
currently avoiding including words in it, as we arestill determining the general methodology of how todeal with such cases.
3. Named Entities: when entities are pattern-based, theypose a specific problem. Such was the case with thegiven name Ménart. Since modern Slovene (usually)
does not include diacritical marks in writing, patterns
for diacritic removal were added, so that the wordform can be found in the modern background lexicon.
The LeXtractor tool does not allow for adding theword-forms to the list of entities once a pattern has
been chosen. This leads to making a list of
attestations where a word-form is used as a name,adding the attestations under sub-lexicon Entities, andmanually adding the modern string without thediacritical mark, in our case, Menart.
4. Modern word-form missing in modern backgroundlexicon: some word-forms are still alive in modern(though not necessary standard) Slovene, but are
missing from our contemporary background lexicon.
Such is the case of the word tavžent, a deformed
German word tausend (thousand[num.]), that is missing
from the background lexicon, even though the word isvery much alive in spoken Slovene. Another example
is word-form Ogerska (Hungary[sg.,loc.]), which only
exists as an adjective in the background lexicon, and7.

8.

not as a geographical name, as is the case in historical
corpus. The proposed solution is either to add thesewords in modern background lexicon, or to have anedit option in LeXtractor, which would allow thelexicographer to add MSD information to the wordform.
Identical word-forms: in the otherwise trivial casewhen a historical word-form exactly corresponds to amodern word-form it can happen that the entry in thelexicon is a false friend; for example, serca is anarchaic form for srca (heart[sg,gen]), but at the sametime is identical to a form of the contemporary lemma
serec (horse of a gray colour). The problem is solved
when we ascribe a pattern to the word-form, r→er,
which transcribes serca into a univocal srca.
Missing readings: sometimes the correct MSD is
missing in the background lexicon, and isconsequently also missing in LeXtractor. Such was
the case with word-forms dobé and mrtve that
represent two different approaches of dealing withsuch problems. The word-form dobé was transcribed
into dobe (both they get and era[sg. gen. or pl. nom.]), but
the background lexicon only offered the latterreading, i.e. Ncf: noun, common, feminine. We
decided to change the pattern (ijo→e) and modernize
the otherwise possible, but in contemporary Slovenearchaic verb form dobe into a more common modern
form dobijo. This extracted the proper reading for
dobé from the background lexicon. The second
possible scenario of a missing MSD is much more
complicated. The possible solution for it is the same
solution we propose for modern word-forms missing
in modern background lexicon. Sometimes ahistorical word-form was used differently thanmodern word-form, which means that the modern
background lexicon cannot offer the missing MSD.
For example, the word-form mrtve, it is not only an
adjective of a feminine plural for dead, it is also anaccusative plural form for a masculine noun mrtvi(the dead), as well as a nominative plural form for afeminine noun the dead. This last use, however, isforeign to contemporary Slovene, which only uses
masculine plural noun mrtvi. An edit option, withwhich the lexicographer could manually add themissing MSD information, would again be needed.
Historical word-form corresponds to more than one
modern word-form of the same lemma: such is a casewith the word-form veči, that doesn’t only transcribe
into večji (bigger), but also into večja, večje and večjo(veči žejo/večjo žejo, veči groze/večje groze, veči
del/večji del, veči nesreča/večja nesreča etc.). The
solution to this is to first add the suggested readings
and attestations and then create additional entries
manually. The lexicographer needs to pay special
attention with such cases, because the entry proceduremust be performed in a single step: once we stop
working on the word-form veči and work on anotherword-form, the only way to return veči is to destroy
all the entries for it, recalculate and start again. Onceagain an edit option would be needed.
Change of inflection: a form of the missing reading or
MSD is an inaccurate reading. Sometimes the wordform for a specific declination has changed during

time: for example, the word-form serci (from srce,heart), was used both as the nominative andaccusative dual form, najne serci (our two hearts), as
well as the historical singular dative and locative
form, k serci, pri serci. Contemporary Slovene uses
the form srci only for the first case (and as
instrumental plural form, though no such attestations
were found in historical corpus), whereas the modern
singular dative form is srcu. The dilemma that arises
is this: should a new pattern, and hence a newreading, be added transcribing u→i, so that the fulland correct MSD can later be extracted not only forthe dual but also for the singular dative form? If thisis not done and the lexicographer just ascribes theinformation, that srci is a common neutral noun, later,
more specific MSD extraction could not recognizethat srci is also a historical singular dative form.
9. The background lexicon offers too many possible
readings: another frequent problem that needed
systematical solving is a case when a word-form,
transcribed into a modern word-form, offers more
grammatical readings (MSDs) than the historical
corpus shows are needed. For example, the word form
ravna only appeared in the historical corpus as a formof a verb ravnati (to straighten), even though it could
also be a feminine adjective form of raven (straight).
There are two possible solutions for such a case. One
is to exclude the reading for adjective because theword-form historically did not exist as an adjective,
the other is to mark that there were no attestations
found, even though the word-form ravna alreadyexisted as an adjective. We have opted to exclude thereading when the word as such doesn’t appear in
Pleteršnik’s dictionary, published in 1894—1895, andon the other hand mark that there were no attestations
found for the proposed reading, if the word does
appear in his dictionary, as was the case for ravan. In
the future, when texts before 1847 are added, it would
also be wise to include cited older dictionaries as areference.
10. Historical word-form is written separately, modern
word-form is not: sometimes, historical word-forms
are written separately, even though in modern
Slovene they are written as one word. Such is the caseof compound words najprej (firstly), historically nar
pervo, zase (for him/her/itself), historically za-se, andčezenj (over him), historically čeznj, čez-nj, and in
one instance also čes-nj. Words with the prefix nar
were sometimes written separately, like nar pervo,
and sometimes together, narbolj (mostly). Since somecompound words were written with a hyphen andothers were not, a possible solution would be tomerge the prefix with the following word, so that
LeXtractor recognizes the compound word in the
background lexicon, with or without applying
patterns. A solution more complex to implement
would be for the lexicographer having the option ofmarking that two words actually form one and ascribe
modern compound word to the unit.

5. Conclusions
The paper presented the first steps in building alexicon of XIXth century Slovene, using a historical
corpus, a contemporary lexicon of Slovene, spellingvariation patterns, and the LeXtractor software. So far wehave mostly concentrated on setting up the resource andprogram environment and methodological issues, whichhave been discussed in the present paper.
In further work we plan to intensively start adding
entries to the lexicon, extend the corpus, esp. withnewspapers and older books, as well as address theremaining methodological issues, such as tokenisation,
which, as discussed, can be different in historical words
from their contemporary equivalents.
Current work has also been exclusively empiricallydriven, i.e. we addressed only issues that directly arise outof the lexical items found in the corpus. In the future weplan to take into account the linguistic research that has
been done so far on historical Slovene language, as
discussed e.g. in Orožen (1996).
Maybe ourcomputational approach might also reveal newquantitative and qualitative linguistic insights into thelanguage as used in XIXth century Slovenia.

Acknowledgements
The work presented in this paper was supported by the
EU FP7 ICT project IMPACT, “Improving Access toText”.

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