A Lexicon Design for Ontology-based Question Answering
Ibrahim Soumana, Sylviane Cardey and Peter Greenfield
Centre de Recherche en Linguistique Lucien Tesnière, Université de Franche Comté,
30 rue Megevand, 25030 Besançon Cedex, Besançon, France
Keywords: Natural Language Interface for Database, NLIDB, NLI, Lexicon, Interclass Lexicon, Intraclass Lexicon,
RDF Triple, Ontology, Operator, Function, Natural Language Processing.
Abstract: Data volume growth leads to new challenges for Natural Language Interfaces (NLI). With Big Data for
example, NLI must not only be portable from one domain to another, but be operational simultaneously in
several domains. The lexicon is an important resource that improves the system performance. In this paper,
we propose an approach to design a lexicon centered on RDF (Resource Description Framework) triple. We
argue that a triple centric lexicon is reusable. The lexicon is also extended to include operations and possible
functions in which data can be involved. This allows increasing the complexity of questions a NLI can
process.
1 INTRODUCTION
A natural language interface to databases (or
ontology) allows querying a database in natural
language without using formal languages such as
SQL or SPARQL. Developed since the 70s (Woods
et al., 1972), Natural Language Interface (NLI) has
in recent years a renewed interest and new
challenges. Data produced on the Internet are more
and more structured. Government and private
organizations are also taking the initiative to publish
their publically accessible data through Open Data.
Storage models more suited to the abundance and
heterogeneity of data have been developed through
Big Data. Natural language appears to be the most
instinctive way for database querying (Chao et al.,
1999). Several studies have shown that users prefer
to formulate their queries in natural language
(Kaufmann and Bernstein, 2007). A natural
language interface to structured data can meet the
need for information in the context of local
infomediation (Soumana et al., 2012). The Growth
in data volume and their heterogeneity reduce the
performance of large scale NLI. This reduction in
the performance is due to, on the one hand the words
that are expressed in the question which do not
always correspond to the lexicon used for
understanding the concepts of database or the formal
language (in which the question is translated) and on
the other hand the systems are unable to identify
correctly the requested information in the database.
Several strategies have been used to increase the
performance and portability of NLI. In this paper,
we propose a triple centric approach to build a
reusable lexicon for NLI. The lexicon is extended to
potential operators or functions in which the data
may be involved.
The rest of the paper is structured as follows. The
following section introduces the concept of triple
and argues for the portability of its lexicon. Section
3 summarizes the literature review of NLI focusing
on how lexicon is built. Section 4 presents the
methodology and an example for cardinal numbers.
Section 5 ends with the conclusion.
2 TRIPLE AS PORTABLE
ELEMENT
The Semantic Web has developed the RDF
(Resource Description Framework) as a data model
for describing the web. An RDF triple consists of
(subject, predicate, object). RDF defines two types
of properties (predicates): object properties and
datatype properties. Object properties (example 2)
link two entities of the application (or instances)
while datatype properties (example 3) link an entity
(or instance) to data values.
170
Soumana I., Cardey S. and Greenfield P..
A Lexicon Design for Ontology-based Question Answering.
DOI: 10.5220/0004540501700175
In Proceedings of the International Conference on Knowledge Engineering and Ontology Development (KEOD-2013), pages 170-175
ISBN: 978-989-8565-81-5
Copyright
c
 2013 SCITEPRESS (Science and Technology Publications, Lda.)

subject predicate object (1)
City mayor Person (2)
City population integer (3)
Paris population 2,243,833 (4)
Example 1 is the syntax of a triple. Example 4 is an
instance of the example 3, and means that Paris has a
population of 2,243,833 inhabitants. Several NLI use
the triple to solve certain lexical ambiguities. For
example in this triple (bank, branch, string), the
subject bank is ambiguous. It can refer to a financial
institution or a geographical entity. However with
the predicate branch, we can say that it is the
financial institution rather than a geographical entity.
The triple is less ambiguous than the subject,
predicate and objects taken separately. Thus the
lexicon developed around a triple is also stable for
various domains for the same triple. The lexicon
developed from a triple can be grouped in two
categories: intraclass lexicon and interclass lexicon.
The intraclass lexicon is the lexicon that indicates
exclusively, a subject, a predicate or an object. City,
population, Paris are examples of intraclass lexicon
because they are related to one single class (city
refers to class city, population refers to the predicate
population, Paris is an instance of the class city).
The interclass lexicon is related to at least two
elements of the triple (subject, predicate or object).
For example the word megacity has the notion of
city, population and a restriction on the size of the
population. So megacity refers to the subject, the
predicate and the object of the triple. These
conditions should be taken into account when the
question is translated into formal language. Words
from the interclass lexicon need additional
processing over and above just string matching (as
an intraclass lexicon).
3 LITERATURE REVIEW
The extension of the lexicon of NLI can increase the
portability and recall. Several methods are used to
build the lexicon. The initial lexicon and the
adaptation (to a new domain) lexicon can be built
automatically or manually. The lexicon can be
generated automatically from the database (Cardey
et al., 2001), PRECISE (Popescu et al., 2004). Some
systems like PANTO (Wang et al., 2007) and
Aqualog (Lopez and Motta, 2004) use Wordnet
(Fellbaum, 1998) to extend the lexicon. Aqualog, in
addition to Wordnet, uses machine learning
techniques to augment the lexicon. The single use of
Wordnet does not allow adequate coverage of the
lexicon because it is a general resource. In a
database (or ontology), labels are sometimes coded,
absent or not meaningful. Automatic recognition
using Wordnet is not sufficient. A lexicon engineer
is required to extend the lexicon for a new domain
ORAKEL (Cimiano et al., 2008) to have a good
quality and coverage of the lexicon. In ORAKEL the
lexicon is built so that the parse tree of the question
can match the ontology concepts. In TEAM (Grosz
et al., 1987), the adaptation to a new domain is done
by the database administrator.
The lexicon can also be acquired by a set of
named entity annotators implemented as a web
service (Ou et al., 2008; Soumana, 2010). The
annotators are used to identify the concepts of the
ontology. FREyA (Damljanovic et al., 2011) and
QUERIX (Kaufmann et al., 2006) use user feedback
in case of ambiguity. Some systems consider the
web as a lexical resource. Online resources like
LOD (Linked Open Data) are used to identify the
concepts of database (Lopez et al., 2011; Yahya et
al., 2012).
Most of the research on lexicon design consists
in identifying directly the database concepts (values,
properties, entities) in the question. Natural language
does not always express the concepts as a bijection
from the lexicon to database concepts (classes,
properties or values). Except for some fuzzy
quantifiers which can be part of the interclass
lexicon, the main work in NLI for lexicon design is
focused on building an intraclass lexicon. For
example big is a fuzzy quantifier, but it is not part of
the interclass lexicon because it does not have a
meaning of any specific predicate. Its meaning is
only scalar. The fuzzy quantifier hot can be part of
the interclass lexicon because it has not only the
notion of being scalar (object of a datatype triple)
but the notion of temperature which can be linked to
a specific part of the triple. The meaning has at least
two dimensions (scalar and temperature) which can
be linked either to the subject, the predicate or with
the object of a triple.
In the next section, we present the triple centric
model for lexicon design and an example of how it
is built with cardinal numbers (values).
4 LEXICON DESIGN
The lexicon is build from basic types up to a triple
level. For a datatype property, the object can be:
numeric, string, boolean, binary or geometric (one,
two or three dimensions for spatial database) values.
In traditional linguistics a numeric value can be
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cardinal number or ordinal number. The lexicon is
designed in the form of hierarchical classes. The
basic types (numeric, string, boolean, binary or
geometric) are subclasses of the object class.
4.1 Class Hierarchy
The vocabulary that occurs within a triple can be
divided into 4 classes:
Figure 1: class hierarchy.
 Object class
 Measure class
 Predicate class
 Subject class
The measure class is optional. It occurs when the
object is a quantity of measure (like numeric values).
The Object class contains vocabulary whose
semantics refers exclusively to the object. If the
object is a numeric value which is a cardinal, the
lexicon generated for this class contains all the
vocabulary that expresses only cardinal numbers. So
the lexicon should contain all the cardinals (0,1, 3,
etc.), as well as words such as big, little which have
exclusively the notion of number. This class also
contains words which refer to a cardinal like value,
number but without any precision. Words like long,
heavy are not parts of this class because the notion
of the measure is already included: long is related to
length and heavy is related to weight. The measure
class contains both the intraclass lexicon of measure
and the interclass lexicon object and measure. An
example of the intraclass lexicon content for
measure is: length, weight, temperature. These refer
to a measure without precision. Another example of
the interclass lexicon content is: long, heavy, hot.
These refer to a measure with some value in the
scale of this measure. The value is the object of the
triple. For all classes, we have an intraclass lexicon
and possibly an interclass lexicon which is
semantically the intersection of the current class and
subclasses. An example of the predicate level can be
illustrated as following:
Area population integer (5)
What is the population of each area? (6)
What are the populated areas? (7)
With triple (5), we can have the question (6) and (7).
The word population is from the intraclass lexicon
of the predicate because it denotes just the predicate
without any restriction. The system should display
the population of all areas regardless the number of
habitants. In question (7), the word populated refers
to the predicate population and makes a restriction
on the object of the triple. Not all the values are
accepted. The system should not display an area
with zero habitants. So the word populated is in the
interclass lexicon of the predicate population. The
reuse of the lexicon is done by inheritance. A triple
can inherit the subclass lexicon of basic type like the
cardinals for example, the lexicon of the class
measures, the lexicon of the predicates or the lexicon
of subjects. The lexicon is developed once but can
be used by many applications according to the level
of granularity that is necessary.
4.2 Cardinal Numbers
Cardinal number is a subclass of the class object. It
has no interclass lexicon because the main class (the
object class) is the lowest class in the hierarchy. The
general approach is to determine the variables, the
instances, the data granularity, and the operations
and functions. Information is searched in all the
syntactic granularities (part of speech tag or
multiword expression). The aim of studying the
intraclass lexicon and the interclass at each level of
the triple is firstly to identify the concept in the
question. The syntactic information will be used
subsequently to compute the semantics. The
following paragraphs are more focused on
identifying the concepts than computing their
semantics.
4.2.1 Variable of Cardinal Numbers
A variable is the string used to denote a cardinal.
There is no reference to any particular value. Table 1
shows a list of the cardinal variable according their
part of speech (POS) tag in French. Lists are not
exhaustive but are given as an example. The
corresponding English word is in brackets.
Object
Subject
Measure
Predicate
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Table 1: A list of variables for cardinal number.
POS tag Variable
Noun
valeur (value), nombre (number),
chiffre (numeral), donnée
Verb
compter dénombrer chiffrer (to count),
évaluer (to evaluate,), s’élever (to rise),
calculer (to calculate), estimer (to
estimate), énumérer (to enumerate)
Adverb combien (how much/how many)
4.2.2 Instances of Cardinal Numbers
The instantiation lexicon is rich. Many adjectives
and adverbs derived from these adjectives express a
cardinal value; see Table 2.
Table 2: A list of cardinal instances.
POS tag Instance
Noun million, couple, singleton, multitude
adjective
unique, seule (alone),
grand (big), considerable
Adverb
uniquement (only)
considérablement (greatly)
Verb exceller (excel)
Determinant
determinant (singular or plural),
number (0, 1, 2,3 etc.), nul, aucun
(no)
Pronoun personne (nobody, none)
In the question which students excel in math? the
system should understand the word excel as an
instance of value linked to math.
4.2.3 Operators of Values Generation
The values generation operators allow generating
more precise intervals than those that can be found
in Table 2. We are interested in the intervals that the
natural language can express using at most one
operator. These intervals are called basic intervals.
They are usually traditional half-lines in geometry.
The other intervals can be expressed by composition
(using two or more operators). Table 3 presents the
basic interval where a is a cardinal. In the phrase
exceed a, exceed is the operator and a is the
argument, and the phrase exceed a generates an
interval.
The interval [a,b] and intervals centered around a
value such as a ±
 (e.g. around 5) where

is the
variation (amplitude) are also considered as basic
intervals according to the previous definition. The
symbol “-” can be used to express an interval (e.g. 5-
10 meaning from 5 to 10). However the analysis
must be extended to the sentence to ensure the
operator is an operator of value generation.
Table 3: Basic intervals (half-lines).
POS [a ; +∞ [ ]a ;+∞[ ]- ∞ ; a] ]-∞;a[
verb
dépasser
(exceed)
prepo-
sition
dès,
à partir de
(from)
plus de,
more than
jusqu’à
(until)
moins de,
inférieur à
(less than)
Table 4: Others basic intervals.
POS tag [a ;b]
a ± 
verb
avoisiner,
approcher,
frôler (to approach)
preposition
à, au
(to)
autour de
(around)
symbol -
In the sentence “The Russian team surprised many
observers by fighting back from 0-2 and 2-3”, the
symbol “-” does not indicate an interval.
4.2.4 Operators of Proportion
The operators of proportion can be classed in two
categories: coefficient and ratio. The operators with
a coefficient indicate the coefficient of the
proportion and the sign (multiplication or division).
For example double, triple indicates respectively the
coefficient two and three and the sign is
multiplication. Half, the quarter, the third indicate
respectively two, four and three and the sign is
division. Certain word (multiple, multiply, split,
partition) specifies only the sign of the operation.
The coefficient can be found in the context of the
word. The operators which indicate a ratio are in
general prepositions or symbols (e.g. 9 over 10 or
90%).
Table 5: Operators of proportion.
POS tag Coefficient Ratio
nom
double, triple,
moitié (half), multiple
verb
doubler (double),
tripler(triple)
adjective double, triple, quintuple
preposition
sur (over),
parmi (among),
des (of),
pour cent
(percent)
adverb
doublement
(doubling twice),
symbol %, /
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4.2.5 Comparison Operators
Comparison uses the same operators as those used to
generate intervals. In the case of interval generation
the result is an interval, for comparison, it is a
boolean. Table 6 gives a possible list for equality.
Table 6: Operators of comparison (equality).
POS tag Operators
noun égalité (equality)
verb
égaler (equal) , correspondre
(correspond), équilibrer (balance)
adjective
même (same), identique (identical),
similaire (similar), équivalent
(equivalent)
adverb exactement (exactly)
4.2.6 Logical Operators
The logical operator expresses disjunction,
conjunction and negation. Conjunction is marked by
words or expression such as and, with, like, as well
as, or the comma. Disjunction is expressed by words
such as or, otherwise. Negation is marked by not,
without.
Table 7: Logical operators.
POS conjunction disjunction negation
conj.
et (and),
aussi bien que
(as well as),
or,
soit (either..or)
prep. puis (then)
sans
(without)
adv.
autrement
(otherwise)
pas (not)
4.2.7 Set Operators
The arguments of set operators are sets. Union and
intersection can have the same operators as
conjunction and disjunction respectively.
Complement is generally marked by prepositions
such as without, except or apart from.
4.2.8 Arithmetical Operators
The arithmetical operators also allow increasing the
complexity of questions. They make it possible to
introduce into the questions elementary calculations
whose parameters are known or unknown at the time
of the question. For example in a database the
following question: “Which directors has a salary
more than 4 times the minimum salary of the
company?” requires calculations.
Table 7: Operators for addition.
POS addition
verb additionner ajouter totaliser sommer (add)
noun addition ajout totalité somme (addition)
adjective entire, total
adverb en tout, en tout et pour tout, plus (in all)
determ. tout (all)
symbol +
4.2.9 Functions
A cardinal may be involved in a function (a
sequence of elementary operations). Functions can
be of two types: general functions or functions
related to the business processes. The general
functions are functions such as powers, square root.
Functions related to the business process are domain
dependent.
5 CONCLUSIONS
In this paper, a design of the lexicon based on the
triplet is proposed. This is structured in 4
hierarchical classes: object, measurement, predicate,
and subject. The intraclass lexicon and interclass
lexicon have been defined to take into account the
specificity of each one. The class object is at the
lowest level. It contains the basic types like the
numerical type (cardinal and ordinal), string,
boolean, binary and geometric type. Apart from the
object class which has only a intraclass lexicon, all
the classes of the hierarchy can have, in addition, an
interclass lexicon. An example of the intraclass
lexicon for cardinals with their operators has been
presented. The hierarchy of classes helps to develop
the lexicon once and can be reused in as many
applications if necessary. The reusability is done by
inheritance when the classes are semantically
equivalent. A limitation of this approach is that
semantic equivalence cannot be done well
automatically. In example (5) population can refer to
humans, animals or plants. The lexicon developed
for these populations is not the same. Human
intervention can help to disambiguate as is done in
many NLI. Currently we are working on the others
basic types and higher level classes.
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