=Paper=
{{Paper
|id=Vol-100/paper-9
|storemode=property
|title=OntoTag: A Semantic Web Page Linguistic Annotation Model
|pdfUrl=https://ceur-ws.org/Vol-100/Guadalupe_Aguado_de_Cea-et-al.pdf
|volume=Vol-100
|dblpUrl=https://dblp.org/rec/conf/ecai/CeaRPP02
}}
==OntoTag: A Semantic Web Page Linguistic Annotation Model==
https://ceur-ws.org/Vol-100/Guadalupe_Aguado_de_Cea-et-al.pdf
OntoTag: A Semantic Web Page
Linguistic Annotation Model
Guadalupe Aguado de Cea1, Inmaculada Álvarez de Mon2, Antonio Pareja-Lora3,
Rosario Plaza-Arteche4
Abstract. Although with the Semantic Web initiative much this context, the semantic annotation of texts, since it makes
research on web page semantic annotation has already been done meaning explicit, has become a relevant topic and, therefore,
by AI researchers, linguistic text annotation, including the advanced design and application of models and formalisms for the
semantic one, was originally developed in Corpus Linguistics and semantic annotation of web pages are needed.
its results have been somehow neglected by AI. The purpose of
Lately, much research has already been carried out by
the research presented in this proposal is to prove that integration
of results in both fields is not only possible, but also highly useful ontologists on the semantic annotation of web pages [3], [10], [11],
in order to make Semantic Web pages more machine-readable. A [12]. However, such works have somehow neglected the results
multi-level (possibly multi-purpose and multi-language) obtained on corpus annotation in the field of Corpus Linguistics,
annotation model based on EAGLES standards and Ontological not only in the semantic level, but also in other linguistic levels.
Semantics, implemented with last generation Semantic Web These other linguistic levels, whilst not being intrinsically
languages is being developed to fit the needs of both semantic, can add extra semantic information to help a computer
communities.1 2 3 4 understand a text or, in our case, web pages.
The goal of this paper is to present the results of our research in
which special efforts are being devoted to finding a way of
1. INTRODUCTION. bringing together and identifying complementarities between the
All of us are by now used to making extensive use of the so-called semantic annotation models from AI and the annotations proposed
World Wide Web (WWW) which we might consider a great source by Corpus Linguistics.
of information, accessible through computers but, hitherto, only This paper is organised as follows: firstly, an introduction to
understandable to human beings. In its beginning, web pages were the state of the art in semantic annotation in corpus linguistics is
hand made, intended and oriented to the exchange of information presented (section 2). In section 3, some brief notes on the use of
among human beings. All of these documents contained a huge ontologies in semantic annotation are sketched. In section 4, an
amount of text, images and even sounds, meaningless to a example of the integration of both paradigms (AI’s and Corpus
computer. In this way, they put the burden of extracting and Linguistics’) is presented in the scope of our project goals. The
interpreting the relevant information on the reader. Due to the main advantages of this integration are then analysed –section 5–
astonishing growth of Internet use, new technologies emerged and, and, finally, further work to be done is included –section 6–.
with them, machine-aided web page generation appeared.
Currently, web page presentation in the WWW is being handled
independently from its content, mainly through the use of XML [1] 2. SEMANTIC ANNOTATION IN CORPUS
or other resource-oriented languages as XOL [2], SHOE [3], OML LINGUISTICS.
[4], RDF [5], RDF Schema [6], OIL [7] or DAML+OIL [8]. But The idea of text annotation was originally developed in Corpus
even though the automatic process of information is being eased, Linguistics. Traditionally, linguists have defined corpus as "a body
still the above-mentioned tasks –relevant information access, of naturally occurring (authentic) language data which can be used
extraction and interpretation– cannot be wholly performed by as a basis for linguistic research" [13]. From this point of view,
computers. Hence, the goal of enabling computers to understand Corpus Linguistics [14] may not be considered a branch of
the meaning (the semantics) of written texts and web pages is the Linguistics in itself, like syntax or semantics. The latter are focused
main pillar sustaining the development of the Semantic Web [9]. In on describing or explaining an aspect of language use; the former is
–––––––––––––––––––––––––––––––––––––––––––––––––––––– rather a methodology or an approach which can be taken by these
1
Department of Applied Linguistics to Science and Technology (DLACT), branches to explain or describe their particular aspect of language
Computer Science Faculty, UPM, Madrid, Spain. lupe@fi.upm.es. use. Following the same authors, Corpus Linguistics was first
2
DLACT, Telecommunications Engineering College, UPM, Madrid, Spain. applied to research on language acquisition, to the teaching of a
ialvarez@euitt.upm.es. second language, to the elaboration of descriptive grammars, etc..
3
Department of Computer Systems and Programming (DSIP), Computer With the arrival of computers, the number of potential studies to
Science Faculty, UCM, Madrid, Spain. apareja@sip.ucm.es. which corpora could be applied increased exponentially.
4
Department of Applied Linguistics to Science and Technology (DLACT),
Computer Science Faculty, UPM, Madrid, Spain. rplaza@fi.upm.es.
So, nowadays, the term corpus is being applied to "a body of decide which one must employ, simply by moving up or down
language material which exists in electronic form, and which may to the next level in the hierarchy.
be processed by computer for various purposes such as linguistic 6. It should conform to a standard, if one exists. A hard-and-fast
research and language engineering" [13]. An annotated corpus system of categories, even being the result of a consensual
"may be considered to be a repository of linguistic information [...] work, may be rejected by many researchers. However, a
made explicit through concrete annotation" [14]. The benefit of standard in this level could lay, like EAGLES standards have
such an annotation is clear: it makes retrieving and analysing done in other levels, a broad framework of principles and
information about what is contained in the corpus quicker and major categories. Such a standard would facilitate
easier. Let us now see the recommendations stated in Corpus comparability and, at the same time, could be modified as
Linguistics for text semantic annotation. necessary for individual needs7.
As asserted in [14], two broad types of semantic annotation may
be identified, related to:
1. Semantic relationships between items in the text (i.e., the 3. ONTOLOGIES AND SEMANTIC WEB
agents or patients of particular actions). This type of annotation ANNOTATIONS.
has scarcely begun to be applied. AI researchers have found in ontologies [17], [18] the ideal
2. The semantic features of words in a text, essentially the knowledge model to formally describe web resources and its
annotation of word senses in one form or another. There is no vocabulary and, hence, to make explicit in some way the
universal agreement in semantics about which features of underlying meaning of the terms included in web pages. With
words should be annotated5. Ontological Semantics [19] as a support theory8, the annotation of
Although some preliminary recommendations on lexical these web resources with ontological information should allow
semantic encoding have already been posited [15], no EAGLES intelligent access to them, should ease searching and browsing
semantic corpus annotation standard has yet been published; within them and should exploit new web inference approaches
nevertheless, for choosing or devising a corpus semantic field6 from them. Many systems and projects have been developed:
annotation system (second type of semantic annotation above SHOE [3]; the (KA)2 initiative [10]; PlanetOnto [11] and the
mentioned) a set of reference criteria has been proposed by Semantic Community Web Portals project [12]. Semantic
Schmidt and is presented in [16]. These criteria are: annotation tools have also been developed so far: COHSE [20],
1. It should make sense in linguistic or psycholinguistic terms. It MnM [21], OntoMat-Annotizer [22], SHOE Knowledge Annotator
is known from psycholinguistic experiments that certain basic [23] and AeroDAML [24].
categories exist in the mind. At present, in general, there is a
good agreement between many basic categories we already
know about from neuropsychology (for example colours, 4. INTEGRATION OF PARADIGMS: AN
body parts, topography and so on); but still an exhaustive set EXAMPLE.
of categories is to be determined. Overabstraction must be
avoided, in any case. As we have already mentioned, the goal of this paper is to
2. It should be able to account exhaustively for the vocabulary in present the complementarities of linguistic and ontological
the corpus, not just for a part of it. If a term cannot readily be annotation for the Semantic Web. The purpose of the project we
classified in the existing annotation system, then the system are presenting, ContentWeb, is the creation of an ontology-based
clearly needs to be amended. platform to enable users to query e-commerce applications by
3. It should be sufficiently flexible to allow for those using natural language, performing the automatic retrieval of
emendations that are necessary for treating a different period, information from web documents annotated with ontological and
language, register or textbase. The treatment of specialised linguistic information. ContentWeb objectives can be enunciated as
texts (such as computer-related, commerce, etc.) may require follows:
considerably more detailed subclassification of the domain in 1. Semi-automatic building of ontologies in the domains of e-
question than other texts. commerce and of entertainment, reusing existing ontologies
4. It should operate at an appropriate level of granularity (or and international e-commerce standards and joint initiatives.
delicacy of detail) –related to criteria (3). What level of 2. Elaboration of OntoTag, a model and environment for the
granularity is correct for an annotation system is an open hybrid –linguistic and ontological– annotation of web
question and depends partly on the aims of the end user. For documents.
this reason, the next criterion is posited. 3. Development of OntoConsult, a natural language interface
5. It should, where appropriate, possess a hierarchical structure. based on ontologies.
If a semantic category system has a hierarchical structure,
based on increasingly general levels of relatedness between
terms, the end user can look at all the different levels and ––––––––––––––––––––––––––––––––––––––––––––––––––––––
7
Once again the SENSEVAL initiatives [30], [31] must be mentioned: they
–––––––––––––––––––––––––––––––––––––––––––––––––––––– reveal the demand for semantic standardization in the field of word sense
5
See, for example, the controversies within the SENSEVAL initiative disambiguation.
8
meetings – [30], [31]. Ontological Semantics [19] uses a constructed world model –the
6
A semantic field (sometimes also called a conceptual field, a semantic ontology– as the central resource for extracting and representing meaning
domain or a lexical domain) is a theoretical construct which groups of natural language texts, reasoning about knowledge derived from texts
together words that are related by virtue of their being connected –at as well as generating natural language texts based on representations of
some level of generality– with the same mental concept [16]. their meaning.
be referenced in higher-level relationships or by other levels of
the annotation model (i.e. Tras cinco años de espera y después de rdf:ID="1_510">). The annotation of the phrase “la película
muchas habladurías, llega a nuestras pantallas la película más esperada de los últimos tiempos” has been included in the
más esperada de los últimos tiempos. figure.
In the semantic level (see Figure 3) some components of
lower level annotations are tagged with semantic references to
the concepts, attributes and relationships determined by our
(domain) ontology, implemented in the language DAML+OIL.
la
5. ADVANTAGES OF THE INTEGRATED
MODEL.
As shown in the example from section 4, it seems that AI and
Corpus Linguistics, far from being irreconcilable, can join
together to give birth to an integrated annotation model. This
ARTDFS
conjunct annotation scheme would be very useful and valuable
el
in the development of the Semantic Web and would benefit
from the results of both disciplines in many ways. Let us now
see the benefits at the semantic level of a hybrid annotation
TDFS0 model, first from a linguistic point of view and, then, from an
el ontological point of view.
DET
FEM
SG
la
DN> NP
los
últimos
tiempos
Figure 1: Morphosyntactic annotation of the article
“la”.
4. Creation of OntoAdvice, an ontology-based system PP
for querying and retrieving information from de
annotated web documents in the entertainment los últimos tiempos
domain.
One of the tasks performed to reach goal 2 is the
manual annotation of a Spanish sentence "Tras cinco
años de espera y después de muchas habladurías, llega
a nuestras pantallas la película más esperada de los AdjP
últimos tiempos." (“After five years of expectation and más
gossiping, here comes the most expected film for the esperada
time being.”) on the languages XML and RDF(S). The de los últimos tiempos
RDF(S) annotation of this sentence in the first three
levels is shown in Figure 1, Figure 2 and Figure 3.
In the morphosyntactic level (Figure 1) every word
or lexical token is given a different Uniform Resource NP
Identifier (URI). The morphosyntactic annotation of the la
article “la”, according to three different tagsets and película
systems is presented. Each tagset has been assigned a más esperada de los últimos
different class in the morphAnnot namespace: tiempos
TradAnnot (CRATER tagset), MBTAnnot (MBT tagset
[25]) and ConstrAnnot (Constraint Grammar -
CONEXOR tagset [26]). For the sake of space, just the
annotation of the article “la” has been included in the figure.
Figure 2: Syntactic annotation of the chunk “la película más
In the syntactic level (Figure 2) every syntactic relationship
esperada de los últimos tiempos” in RDF(S).
between morpho-syntactic items is given a new URI, so that it can
llega
a nuestras pantallas
película
después de muchas habladurías
Tras cinco años de espera
más esperada de los últimos tiempos
El Señor de los Anillos
El Señor de los Anillos
Figure 3: Semantic annotation of "Tras cinco años de espera y después de muchas habladurías, llega a
nuestras pantallas la película más esperada de los últimos tiempos." in RDF(S).
are more ambitious and potentially wider than the strictly ontology-
5.1. Regarding ontology-based annotations from based ones. Establishing a link between semantic annotation and
a linguistic point of view. discourse annotation and text construction following the RST
The first result of our work is that the use of ontologies as a approach, which has already been applied in text generation [29],
basis for a semantic annotation scheme fits perfectly and seems a fairly promising linguistic enhancement.
accomplishes the criteria posited by Schmidt. Clearly, its mostly
hierarchical structure fulfils by itself criterion (5) and, as a side
effect, criteria (2) and (4), since an ontology can grow horizontally
6. CONCLUSIONS AND FURTHER WORK.
(in breadth) and vertically (in depth). Criterion (3) is also satisfied This paper has shown the results of the research carried out on
by an ontology-based semantic annotation scheme, since we can how linguistic annotation can help computers understand the text
always specialise the concepts in the ontology according to specific contained in a document –a Semantic Web page– bringing together
periods, languages, registers and textbases. Ontologies are, by semantic annotation models from AI and the annotations proposed
definition, consensual and, thus, are closer to becoming a standard for every linguistic level from Corpus Linguistics.
than many other knowledge models, as criteria (6) requires. Further elements susceptible of semantic annotation are
Concerning criterion (1), quite a lot of groups developing presently being sought and research is being done towards their
ontologies are characterized by a strong interdisciplinary approach determination by the team of linguists in our project. The
that combines Computer Science, Linguistics and (sometimes) pragmatic counterpart of OntoTag has not yet been tackled at this
Philosophy; then, an ontology-based approach should also make phase of the project.
sense in linguistic terms. Still, much work must be done in order to fully specify,
implement and assess the whole model. Besides, many efforts are
being devoted to developing OntoAdvice, the ontology-based
5.2. Regarding linguistic annotations from an information retrieval system, in order to validate this model.
ontological point of view.
The main drawback for AI researchers to adopt a linguistically
ACKNOWLEDGEMENTS.
motivated annotation model would lie on the fact that (section 2)
“there is no universal agreement in semantics about which features The research described in this paper is supported by MCyT
of words should be annotated” or on Schmidt’s criterion (1): “still (Spanish Ministry of Science and Technology) under the project
an exhaustive set of categories is to be determined”. But ontology name: ContentWeb: “PLATAFORMA TECNOLÓGICA PARA
researchers are trying to fill this gap with initiatives such as the LA WEB SEMÁNTICA: ONTOLOGÍAS, ANÁLISIS DE
UNSPSC [27] or RosettaNet [28] in specific domains (i.e. e- LENGUAJE NATURAL Y COMERCIO ELECTRÓNICO” –
commerce). In any case, linguistic annotations at the semantic level TIC2001-2745 ("ContentWeb: Semantic Web Technologic
Platform: Ontologies, Natural Language Analysis and E- [18] Studer, R., Benjamins, R., Fensel, D. (1998) Knowledge
Business"). We would also like to thank Socorro Bernardos, Óscar Engineering: Principles and Methods. DKE 25(1-2): 161-197.
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