Proceedings of the Workshop on Multilingual Language Resources and Interoperability, pages 17–24,
Sydney, July 2006. c©2006 Association for Computational Linguistics
Towards Agent-based Cross-lingual Interoperability of Distributed    
Lexical Resources 
Claudia Soria
*
Maurizio Tesconi
°
Andrea Marchetti
°
Francesca Bertagna
*
Monica Monachini
*
Chu-Ren Huang
§    
Nicoletta Calzolari
*
*
CNR-ILC and °CNR-IIT 
Via Moruzzi 1, 56024 Pisa 
Italy 
{firstname.lastname@ilc.cnr.it} 
{firstname.lastname@iit.cnr.it} 
§
Academia Sinica  
Nankang, Taipei  
Taiwan 
churen@gate.sinica.edu.tw 
 
 
 
Abstract 
In this paper we present an application 
fostering the integration and interopera-
bility of computational lexicons, focusing 
on the particular case of mutual linking 
and cross-lingual enrichment of two wor-
dnets, the ItalWordNet and Sinica BOW 
lexicons. This is intended as a case-study 
investigating the needs and requirements 
of semi-automatic integration and inter-
operability of lexical resources. 
1 Introduction 
In this paper we present an application fostering 
the integration and interoperability of computa-
tional lexicons, focusing on the particular case of 
mutual linking and cross-lingual enrichment of 
two wordnets. The development of this applica-
tion is intended as a case-study and a test-bed for 
trying out needs and requirements posed by the 
challenge of semi-automatic integration and en-
richment of practical, large-scale multilingual 
lexicons for use in computer applications. While 
a number of lexicons already exist, few of them 
are practically useful, either since they are not 
sufficiently broad or because they don’t cover 
the necessary level of detailed information. 
Moreover, multilingual language resources are 
not as widely available and are very costly to 
construct: the work process for manual develop-
ment of new lexical resources or for tailoring 
existing ones is too expensive in terms of effort 
and time to be practically attractive.  
The need of ever growing lexical resources for 
effective multilingual content processing has 
urged the language resource community to call 
for a radical change in the perspective of lan-
guage resource creation and maintenance and the 
design of a “new generation” of LRs: from static, 
closed and locally developed resources to shared 
and distributed language services, based on open 
content interoperability standards. This has often 
been called a “change in paradigm” (in the sense 
of Kuhn, see Calzolari and Soria, 2005; Calzolari 
2006). Leaving aside the tantalizing task of 
building on-site resources, the new paradigm 
depicts a scenario where lexical resources are 
cooperatively built as the result of controlled co-
operation of different agents, adopting the para-
digm of accumulation of knowledge so success-
ful in more mature disciplines, such as biology 
and physics (Calzolari, 2006).  
According to this view (or, better, this vision), 
different lexical resources reside over distributed 
places and can not only be accessed but choreo-
graphed by agents presiding the actions that can 
be executed over them. This implies the ability to 
build on each other achievements, to merge re-
sults, and to have them accessible to various sys-
tems and applications. 
At the same time, there is another argument in 
favor of distributed lexical resources: language 
resources, lexicons included, are inherently dis-
tributed because of the diversity of languages 
distributed over the world. It is not only natural 
that language resources to be developed and 
maintained in their native environment. Since 
language evolves and changes over time, it is not 
possible to describe the current state of the lan-
17
guage away from where the language is spoken. 
Lastly, the vast range of diversity of languages 
also makes it impossible to have one single uni-
versal centralized resource, or even a centralized 
repository of resources. 
Although the paradigm of distributed and in-
teroperable lexical resources has largely been 
discussed and invoked, very little has been made 
in comparison for the development of new meth-
ods and techniques for its practical realization. 
Some initial steps are made to design frame-
works enabling inter-lexica access, search, inte-
gration and operability. An example is the Lexus 
tool (Kemps-Snijders et al., 2006), based on the 
Lexical Markup Framework (Romary et al., 
2006), that goes in the direction of managing the 
exchange of data among large-scale lexical re-
sources. A similar tool, but more tailored to the 
collaborative creation of lexicons for endangered 
language, is SHAWEL (Gulrajani and Harrison, 
2002). However, the general impression is that 
little has been made towards the development of 
new methods and techniques for attaining a con-
crete interoperability among lexical resources. 
Admittedly, this is a long-term scenario requiring 
the contribution of many different actors and ini-
tiatives (among which we only mention stan-
dardisation, distribution and international coop-
eration).  
Nevertheless, the intent of our project is to 
contribute to fill in this gap, by exploring in a 
controlled way the requirement and implications 
posed by new generation multilingual lexical 
resources. The paper is organized as follows: 
section 2 describes the general architectural de-
sign of our project; section 3 describes the mod-
ule taking care of cross-lingual integration of 
lexical resources, by also presenting a case-study 
involving an Italian and Chinese lexicons. Fi-
nally, section 4 presents our considerations and 
lessons learned on the basis of this exploratory 
testing. 
2 An Architecture for Integrating Lexi-
cal Resources 
 LeXFlow (Soria et al., 2006) was developed 
having in mind the long-term goal of lexical re-
source interoperability. In a sense, LeXFlow is 
intended as a proof of concept attempting to 
make the vision of an infrastructure for access 
and sharing of linguistic resources more tangible. 
LeXFlow is an adaptation to computational 
lexicons of XFlow, a cooperative web applica-
tion for the management of document workflows 
(DW, Marchetti et al., 2005). A DW can be seen 
as a process of cooperative authoring where a 
document can be the goal of the process or just a 
side effect of the cooperation. Through a DW, a 
document life-cycle is tracked and supervised, 
continually providing control over the actions 
leading to document compilation. In this envi-
ronment a document travels among agents who 
essentially carry out the pipeline receive-process-
send activity.  
There are two types of agents: external agents 
are human or software actors performing activi-
ties dependent from the particular Document 
Workflow Type; internal agents are software 
actors providing general-purpose activities useful 
for many DWTs and, for this reason, imple-
mented directly into the system. Internal agents 
perform general functionalities such as creat-
ing/converting a document belonging to a par-
ticular DW, populating it with some initial data, 
duplicating a document to be sent to multiple 
agents, splitting a document and sending portions 
of information to different agents, merging du-
plicated documents coming from multiple agents, 
aggregating fragments, and finally terminating 
operations over the document. External agents 
basically execute some processing using the 
document content and possibly other data; for 
instance, accessing an external database or 
launching an application.  
LeXFlow was born by tailoring XFlow to 
management of lexical entries; in doing so, we 
have assumed that each lexical entry can be 
modelled as a document instance, whose behav-
iour can be formally specified by means of a 
lexical workflow type (LWT). A LWT describes 
the life-cycle of a lexical entry, the agents al-
lowed to act over it, the actions to be performed 
by the agents, and the order in which the actions 
are to be executed. Embracing the view of coop-
erative workflows, agents can have different 
rights or views over the same entry: this nicely 
suits the needs of lexicographic work, where we 
can define different roles (such as encoder, anno-
tator, validator) that can be played by either hu-
man or software agents. Other software modules 
can be inserted in the flow, such as an automatic 
acquirer of information from corpora or from the 
web. Moreover, deriving from a tool designed 
for the cooperation of agents, LeXFlow allows to 
manage workflows where the different agents 
can reside over distributed places.  
LeXFlow thus inherits from XFlow the gen-
eral design and architecture, and can be consid-
ered as a specialized version of it through design 
18
of specific Lexical Workflow Types and plug-in 
of dedicated external software agents. In the next 
section we briefly illustrate a particular Lexical 
Workflow Type and the external software agents 
developed for the purpose of integrating different 
lexicons belonging to the same language. Since it 
allows the independent and coordinated sharing 
of actions over portions of lexicons, LeXFlow 
naturally lends itself as a tool for the manage-
ment of distributed lexical resources. 
Due to its versatility, LeXFlow is both a gen-
eral framework where ideas on automatic lexical 
resource integration can be tested and an infra-
structure for proving new methods for coopera-
tion among lexicon experts. 
2.1 Using LeXFlow for Lexicon Enrichment 
In previous work (Soria et al., 2006),  the LeX-
Flow framework has been tested for integration 
of lexicons with differently conceived lexical 
architectures and diverging formats. It was 
shown how interoperability is possible between 
two Italian lexicons from the SIMPLE and 
WordNet families, respectively, namely the 
SIMPLE/CLIPS (Ruimy et al., 2003) and Ital-
WordNet (Roventini et al., 2003) lexicons.  
In particular, a Lexical Workflow Type was 
designed where the two different monolingual 
semantic lexicons interact by reciprocally enrich-
ing themselves and moreover integrate informa-
tion coming from corpora. This LWT, called 
“lexicon augmentation”, explicitly addresses dy-
namic augmentation of semantic lexicons. In this 
scenario, an entry of a lexicon A becomes en-
riched via basically two steps. First, by virtue of 
being mapped onto a corresponding entry be-
longing to a lexicon B, the entry
A
 inherits the 
semantic relations available in the mapped en-
try
B
. Second, by resorting to an automatic appli-
cation that acquires information about semantic 
relations from corpora, the acquired relations are 
integrated into the entry and proposed to the hu-
man encoder. 
B
An overall picture of the flow is shown in 
Figure 1, illustrating the different agents partici-
pating in the flow. Rectangles represent human 
actors over the entries, while the other figures 
symbolize software agents: ovals are internal 
agents and octagons external ones. The two ex-
ternal agents involved in this flow are the “rela-
tion calculator” and the “corpora extractor”. The 
first is responsible for the mapping between the 
sets of semantic relations used by the different 
lexicons. The “corpora extractor” module in-
vokes an application that acquires information 
about part-of relations by identifying syntactic 
constructions in a vast Italian corpus. It then 
takes care of creating the appropriate candidate 
semantic relations for each lemma that is pro-
posed by the application. 
Figure 1. Lexicons Augmentation Workflow 
Type. 
A prototype of LeXFlow has been imple-
mented with an extensive use of XML technolo-
gies (XML Schema, XSLT, XPath, XForms, 
SVG) and open-source tools (Cocoon, Tomcat, 
mySQL). It is a web-based application where 
human agents interact with the system through 
an XForms browser that displays the document 
to process as a web form whereas software 
agents interact with the system via web services. 
3 Multilingual WN Service 
In the Section above we have illustrated the gen-
eral architecture of LeXFlow and showed how a 
Lexical Workflow Type can be implemented in 
order to enrich already existing lexicons belong-
ing to the same language but realizing different 
models of lexicon encoding. In this section we 
move to a cross-lingual perspective of lexicon 
integration. We present a module that similarly 
addresses the issue of lexicon augmentation or 
enrichment focusing on mutual enrichment of 
two wordnets in different languages and residing 
at different sites. 
This module, named “multilingual WN Ser-
vice” is responsible for the automatic cross-
lingual fertilization of lexicons having a Word-
19
Net-like structure. Put it very simply, the idea 
behind this module is that a monolingual word-
net can be enriched by accessing the semantic 
information encoded in corresponding entries of 
other monolingual wordnets.  
Since each entry in the monolingual lexicons 
is linked to the Interlingual Index (ILI, cf. Sec-
tion 3.1), a synset of a WN(A) is indirectly 
linked to another synset in another WN(B). On 
the basis of this correspondence, a synset(A) can 
be enriched by importing the relations that the 
corresponding synset(B) holds with other syn-
sets(B), and vice-versa. Moreover, the enrich-
ment of WN(A) will not only import the relations 
found in WN(B), but it will also propose target 
synsets in the language(A) on the basis of those 
found in language(B). 
The various WN lexicons reside over distrib-
uted servers and can be queried through web ser-
vice interfaces. The overall architecture for mul-
tilingual wordnet service is depicted in Figure 2. 
 
 
Figure 2. Multilingual Wordnet Service Archi-
tecture. 
 
Put in the framework of the general LeXFlow 
architecture, the Multilingual wordnet Service 
can be seen as an additional external software 
agent that can be added to the augmentation 
workflow or included in other types of lexical 
flows. For instance, it can be used not only to 
enrich a monolingual lexicon but to bootstrap a 
bilingual lexicon. 
3.1 Linking Lexicons through the ILI  
The entire mechanism of the Multilingual WN 
Service is based on the exploitation of Interlin-
gual Index (Peters et al., 1998), an unstructured 
version of WordNet used in EuroWordNet 
(Vossen et al., 1998) to link wordnets of different 
languages; each synset in the language-specific 
wordnet is linked to at least one record of the ILI 
by means of a set of equivalence relations 
(among which the most important is the 
EQ_SYNONYM, that expresses a total, perfect 
equivalence between two synsets).  
Figure 6 describes the schema of a WN lexical 
entry. Under the root “synset” we find both in-
ternal relations (“synset relations”) and ILI Rela-
tions, which link to ILI synsets. 
Figure 3 shows the role played by the ILI as 
set of pivot nodes allowing the linkage between 
concepts belonging to different wordnets.  
 
 
Figure 3. Interlingual Linking of Language-
specific Synsets. 
 
In the Multilingual WN Service, only equiva-
lence relations of type EQ_SYNONYM and 
EQ_NEAR_SYNONYM have been taken into ac-
count, being them the ones used to represent a 
translation of concepts and also because they are 
the most exploited (for example, in IWN, they 
cover about the 60% of the encoded equivalence 
relations). The EQ_SYNONYM relation is used to 
realize the one-to-one mapping between the lan-
guage-specific synset and the ILI, while multiple 
EQ_NEAR_SYNONYM relations (because of their 
nature) might be encoded to link a single lan-
guage-specific synset to more than one ILI re-
cord. In Figure 4 we represented the possible 
relevant combinations of equivalence relations 
that can realize the mapping between synsets 
belonging to two languages. In all the four cases, 
a synset “a” is linked via the ILI record to a syn-
set “b” but a specific procedure has been fore-
seen in order to calculate different “plausibility 
scores” to each situation. The procedure relies on 
different rates assigned to the two equivalence 
relations (rate “1” to EQ_NEAR_SYNONYM rela-
tion and rate “0” to the EQ_SYNONYM). In this 
way we can distinguish the four cases by assign-
ing respectively a weight of “0”, “1”, “1” and 
“2”. 
20
 
 
Figure 4. Possible Combinations of Relations 
between two Lexicons A and B and the ILI. 
 
The ILI is a quite powerful yet simple method 
to link concepts across the many lexicons be-
longing to the WordNet-family. Unfortunately, 
no version of the ILI can be considered a stan-
dard and often the various lexicons exploit dif-
ferent version of WordNet as ILI
1
. This is a 
problem that is handled at web-service level, by 
incorporating the conversion tables provided by 
(Daudé et al., 2001). In this way, the use of dif-
ferent versions of WN does not have to be taken 
into consideration by the user who accesses the 
system but it is something that is resolved by the 
system itself
2
. This is why the version of the ILI 
is a parameter of the query to web service (see 
Section below). 
3.2 Description of the Procedure 
On the basis of ILI linking, a synset can be en-
riched by importing the relations contained in the 
corresponding synsets belonging to another 
wordnet. 
In the procedure adopted, the enrichment is 
performed on a synset-by-synset basis. In other 
words, a certain synset is selected from a word-
net resource, say WN(A). The cross-lingual mod-
ule identifies the corresponding ILI synset, on 
the basis of the information encoded in the syn-
set. It then sends a query to the WN(B) web ser-
vice providing the ID of ILI synset together with 
the ILI version of the starting WN. The WN(B) 
web service returns the synset(s) corresponding 
to the WN(A) synset, together with reliability 
scores. If WN(B) is based on a different ILI ver-
sion, it can carry out the mapping between ILI 
versions (for instance by querying the ILI map-
ping web service). The cross-lingual module then 
analyzes the synset relations encoded in the 
                                                 
1
 For example, the Chinese and the Italian wordnets consid-
ered as our case-study use respectively versions 1.6 and 1.5. 
2
 It should be noted, however, that the conversion between 
different WN versions could not be accurate so the mapping 
is always proposed with a probability score.
WN(B) synset and for each of them creates a 
new synset relation for the WN(A) synset. 
If the queried wordnets do not use the same set 
of synset relations, the module must take care of 
the mapping between different relation sets. In  
our case-study no mapping was needed, since the 
two sets were completely equivalent.   
Each new relation is obtained by substituting 
the target WN(B)  synset  with the corresponding 
synset WN(A), which again is found by querying 
back the WN(A) web service (all these steps 
through the ILI). The procedure is formally de-
fined by the following formula: 
 
 
 
 
 
Figure 5. Finding New Relations. 
 
Every local wordnet has to provide a web ser-
vice API  with the following methods: 
 
1. GetWeightedSynsetsByIli(ILIid, ILIversion) 
2. GetSynsetById(sysnsetID) 
3. GetSynsetsByLemma(lemma) 
 
21
The returned synsets of each method must be 
formatted in XML following the schema de-
picted in Figure 6: 
 
Figure 6. Schema of Wordnet Synsets Returned 
by WN Web Services. 
 
The scores returned by the method “Get-
WeightedSynsetsByIli” are used by our module 
to calculate the reliability rating for each new 
proposed relation. 
3.3 A Case Study: Cross-fertilization be-
tween Italian and Chinese Wordnets. 
We explore this idea with a case-study involving 
the ItalianWordNet (Roventini et al., 2003) and 
the Academia Sinica Bilingual Ontological 
Wordnet (Sinica BOW, Huang et al., 2004).  
The BOW integrates three resources: Word-
Net, English-Chinese Translation Equivalents 
Database (ECTED), and SUMO (Suggested Up-
per Merged Ontology). With the integration of 
these three key resources, Sinica BOW functions 
both as an English-Chinese bilingual wordnet 
and a bilingual lexical access to SUMO. Sinica 
Bow currently has two bilingual versions, corre-
sponding to WordNet 1.6. and 1.7. Based on 
these bootstrapped versions, a Chinese Wordnet 
(CWN, Huang et al. 2005) is under construction 
with handcrafted senses and lexical semantic re-
lations. For the current experiment, we have used 
the version linking to WordNet 1.6. 
ItalWordNet was realized as an extension of 
the Italian component of EuroWordNet. It com-
prises a general component consisting of about 
50,000 synsets and terminological wordnets 
linked to the generic wordnet by means of a spe-
cific set of relations. Each synset of ItalWordNet 
is linked to the Interlingual-Index (ILI). 
The two lexicons refer to different versions of 
the ILI (1.5 for IWN and 1.6 for BOW), thus 
making it necessary to provide a mapping be-
tween the two versions. On the other hand, no 
mapping is necessary for the set of synset rela-
tions used, since both of them adopt the same set. 
For the purposes of evaluating the cross-
lingual module, we have developed two web-
services for managing a subset of the two re-
sources.  
The following Figure shows a very simple ex-
ample where our procedure discovers and pro-
poses a new meronymy relation for the Italian 
synset {passaggio,strada,via}. This synset is 
equivalent to the ILI “road,route” that is ILI-
connected with BOW synset “道路,道 ,路” (da-
o_lu, dao, lu) (Figure 7, A) . The Chinese synset 
has a meronymy relation with the synset “十字
路口” (wan)  (B). This last  synset is equivalent 
to the ILI “bend, crook, turn” that is ILI-
connected with Italian WordNet synset “curva-
tura, svolta, curva” (C). Therefore the procedure 
will propose a new candidate meronymy relation 
between the two Italian WordNet synsets (D). 
 
 
Figure 7. Example of a New Proposed Mero-
nymy Relation for Italian. 
3.4 Considerations and Lessons Learned 
Given the diversity of the languages for which 
wordnets exist, we note that it is difficult to im-
plement an operational standard across all typo-
logically different languages. Work on enriching 
and merging multilingual resources presupposes 
that the resources involved are all encoded with 
the same standard. However, even with the best 
efforts of the NLP community, there are only a 
small number of language resources encoded in 
any given standard. In the current work, we pre-
suppose a de-facto standard, i.e. a shared and 
conventionalized architecture, the WordNet one. 
Since the WordNet framework is both conven-
tionalized and widely followed, our system is 
22
able to rely on it without resorting to a more sub-
stantial and comprehensive standard. In the case, 
for instance, of integration of lexicons with dif-
ferent underlying linguistic models, the availabil-
ity of the MILE (Calzolari et al., 2003) was an 
essential prerequisite of our work. Nevertheless, 
even from the perspective of the same model, a 
certain degree of standardization is required, at 
least at the format level. 
From a more general point of view, and even 
from the perspective of a limited experiment 
such as the one described in this paper, we must 
note that the realization of the new vision of dis-
tributed and interoperable language resources is 
strictly intertwined with at least two prerequi-
sites. On the one side, the language resources 
need to be available over the web; on the other, 
the language resource community will have to 
reconsider current distribution policies, and to 
investigate the possibility of developing an 
“Open Source” concept for LRs. 
4 Conclusion 
Our proposal to make distributed wordnets inter-
operable has the following applications in proc-
essing of lexical resources: 
 
• Enriching existing resources: informa-
tion is often not complete in any given 
wordnet: by making two wordnets inter-
operable, we can bootstrap semantic rela-
tions and other information from other 
wordnets. 
• Creation of new resources: multilingual 
lexicons can be bootstrapped by linking 
different language wordnets through ILI. 
• Validation of existing resources: seman-
tic relation information and other synset 
assignments can be validated when it is re-
inforced by data from a different wordnet. 
In particular, our work can be proposed as a 
prototype of a web application that would sup-
port the Global WordNet Grid initiative 
(www.globalwordnet.org/gwa/gwa_grid.htm).  
Any multilingual process, such as cross-
lingual information retrieval, must involve both 
resources and tools in a specific language and 
language pairs. For instance, a multilingual query 
given in Italian but intended for querying Eng-
lish, Chinese, French, German, and Russian 
texts, can be send to five different nodes on the 
Grid for query expansion, as well as performing 
the query itself. In this way, language specific 
query techniques can be applied in parallel to 
achieve best results that can be integrated in the 
future. As multilingualism clearly becomes one 
of the major challenges of the future of web-
based knowledge engineering, WordNet emerges 
as one leading candidate for a shared platform 
for representing a lexical knowledge model for 
different languages of the world. This is true 
even if it has to be recognized that the wordnet 
model is lacking in some important semantic in-
formation (like, for instance, a way to represent 
the semantic predicate). However, such knowl-
edge and resources are distributed. In order to 
create a shared multi-lingual knowledge base for 
cross-lingual processing based on these distrib-
uted resources, an initiative to create a grid-like 
structure has been recently proposed and pro-
moted by the Global WordNet Association, but 
until now has remained a wishful thinking. The 
success of this initiative will depend on whether 
there will be tools to access and manipulate the 
rich internal semantic structure of distributed 
multi-lingual WordNets. We believe that our 
work on LeXFlow offers such a tool to provide 
inter-operable web-services to access distributed 
multilingual WordNets on the grid. 
This allows us to exploit in a cross-lingual 
framework the wealth of monolingual lexical 
information built in the last decade. 

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