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  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Word order based analysis of given and new information in controlled synthetic languages</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Normunds Grūzītis</string-name>
          <email>normundsg@ailab.lv</email>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Institute of Mathematics and Computer Science, University of Latvia Raina bulv.</institution>
          <addr-line>29, Riga, LV-1459</addr-line>
          ,
          <country country="LV">Latvia</country>
        </aff>
      </contrib-group>
      <fpage>29</fpage>
      <lpage>34</lpage>
      <abstract>
        <p>When an OWL ontology, together with SWRL rules, is defined or verbalized in controlled natural language (CNL) it is important to ensure that the meaning of CNL statements will be unambiguously (predictably) interpreted by both human and machine. CNLs that are based on analytical languages (namely, English) impose a number of syntactic restrictions that enable the deterministic interpretation. Similar restrictions can be adapted to a large extent also for synthetic languages, however, a fundamental issue reveals in analysis of given (topic) and new (focus) information. In highly analytical CNLs, detection of which information is new and which has been already introduced is enabled by systematic use of definite and indefinite articles. In highly synthetic languages, articles are not typically used. In this paper we show that topic-focus articulation in synthetic CNLs can be reflected by systematic changes in word order that are both intuitive for a native speaker and formal for the automatic parsing.</p>
      </abstract>
      <kwd-group>
        <kwd>eol&gt;Ontology Verbalization</kwd>
        <kwd>Controlled Natural Language</kwd>
        <kwd>Synthetic Language</kwd>
        <kwd>Word Order</kwd>
        <kwd>Information Structure</kwd>
        <kwd>Topic-Focus Articulation</kwd>
        <kwd>Anaphoric References</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>1. INTRODUCTION</title>
      <p>
        One of the fundamental requirements in definition and
verbalization of ontology structure, restrictions, and implication
rules is the unambiguous interpretation (in terms of the underlying
formalism) of controlled natural language (CNL) statements, so
that the CNL user could easily predict the precise meaning of the
specification he/she is writing or reading; that also includes the
resolving of anaphoric references. To enable deterministic
construction of discourse representation structures (DRS), several
widely accepted restrictions are used in CNLs (e.g., in Attempto
Controlled English [
        <xref ref-type="bibr" rid="ref2">2</xref>
        ]): a set of interpretation rules for potentially
ambiguous syntactic constructions (an issue that is still present
even in a highly restricted syntactic subset of natural language), a
monosemous lexicon (i.e., domain-specific terminology), an
assumption that the antecedent of a definite noun phrase (NP) is
the most recent and most specific accessible NP that agrees in
gender and number, and some other limitations.
      </p>
      <p>
        There are several sophisticated CNLs that provide seemingly
informal means for bidirectional mapping between controlled
English and OWL [
        <xref ref-type="bibr" rid="ref10">10</xref>
        ]. Experiments show that the underlying
principles of English-based CNLs can be successfully adapted
also for other rather analytical languages, for example, for
Afrikaans [
        <xref ref-type="bibr" rid="ref7">7</xref>
        ]. Moreover, Ranta and Angelov [
        <xref ref-type="bibr" rid="ref8">8</xref>
        ] have shown that
the Grammatical Framework (GF), a formalism for
implementation of multilingual CNLs, provides convenient means
for writing parallel grammars that simultaneously cover similar
syntactic fragments of several natural languages. Thus, if the
abstract and concrete grammars are carefully designed, GF
provides a syntactically and semantically precise translation from
one CNL to another (again, assuming that the domain-specific
translation equivalents are monosemous). This potentially allows
exploitation of powerful tools that are already developed for one
or the other ―dialect‖ of controlled English also for non-English
CNLs. For instance, the ACE parser [
        <xref ref-type="bibr" rid="ref2">2</xref>
        ] could be used for DRS
construction, paraphrasing and mapping to OWL, and ACE
verbalizer [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ] could be used in the reverse direction, facilitating
cross-lingual ontology development, verbalization, and querying.
While it seems promising and straightforward for rather analytical
CNLs that share common fundamental characteristics, allowing
(apart from other) for explicit detection of anaphoric references, it
raises issues in the case of highly synthetic languages, where
explicit linguistic markers, indicating which information is
already given (anaphors) and which is new (antecedents), in
general, are not available (here we are talking about individuals
that are referenced by NPs, not by anaphoric pronouns). In
analytical CNLs, analysis of the information structure of a
sentence is based on the strict word order (basically, the
subjectverb-object or SVO pattern) and systematic use of definite and
indefinite articles. In highly synthetic languages, articles are rarely
used and are ―compensated‖ by more implicit linguistic markers;
typically, by changes in the neutral word order, which is enabled
by rich inflectional paradigms and syntactic agreement.
As a case study, we have chosen Latvian [
        <xref ref-type="bibr" rid="ref6">6</xref>
        ], a member of the
Baltic language group (together with Lithuanian). Baltic
languages are among the oldest of the remaining Indo-European
languages. Syntactically they both are very closely related and are
highly synthetic with rich morphology; however, the definiteness
feature is not encoded even in noun endings as it is in case of
Bulgarian [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ], for instance. Thus, we will describe the
correspondence between the given/new information and word
order patterns in terms of topic-focus articulation [
        <xref ref-type="bibr" rid="ref3">3</xref>
        ]. Although
the topic (theme) and focus (rheme) parts of a sentence in general
Latvian are not always reflected by systematic changes in the
word order [
        <xref ref-type="bibr" rid="ref9">9</xref>
        ], in this paper we demonstrate that changes in word
order are reliable markers in the case of controlled Latvian,
allowing for systematic reconstruction of ―missing‖ articles.
Few other markers may be used in Latvian to indicate that an NP
is an anaphoric reference, namely, definite and indefinite endings
of adjectives and participles, if they are used as attributes.
However, such markers are optional and non-reliable even in
controlled language — attributes in domain-specific terms
(multiword units) often have definite endings by default. We might also
impose the usage of artificial determiners, using indefinite and
demonstrative pronouns, but then it would be Latvian-like
controlled language, not a subset of actual Latvian. The problem
is even more apparent in case of Lithuanian that has not been
historically influenced by German. Therefore the only formal and
general feature that indicates the status of an NP is its position in
a sentence — whether it belongs to the topic or focus part. Our
hypothesis is that the requirement for compliance with predefined
word order patterns in a controlled synthetic language is not only
reasonable, but also makes the CNL more natural and is
intuitively satisfiable by a native speaker. As our experiments
show, the proposed approach is directly applicable for Lithuanian
and can be adapted also for majority of Slavic languages (e.g.,
Russian and Czech) — the closest siblings to Baltic languages.
2. TERMINOLOGICAL STATEMENTS
In this paper we focus on terminological (TBox) statements of
OWL ontologies [
        <xref ref-type="bibr" rid="ref15">15</xref>
        ] that are supplemented with limited data
integrity constraints in form of SWRL rules [
        <xref ref-type="bibr" rid="ref18">18</xref>
        ] and SPARQL
queries [
        <xref ref-type="bibr" rid="ref16 ref17">16, 17</xref>
        ] (see Section 3). In this section we will consider
different types of statements defining atomic and complex classes,
properties, and property restrictions of a simplified university
ontology. Statements are given in parallel in Manchester OWL
Syntax [
        <xref ref-type="bibr" rid="ref4">4</xref>
        ], ACE [
        <xref ref-type="bibr" rid="ref2">2</xref>
        ], and ACE compliant controlled Latvian.
In Figure 1 the example ontology is visualized according to the
UML profile for OWL [
        <xref ref-type="bibr" rid="ref14">14</xref>
        ] — a user-friendly notation that
unveils the structure of the ontology in a highly comprehensible
form, but it is not well suited to capture complex restrictions and
integrity constraints. In the following two sections we will do both
verbalize the UML-defined structure and use CNL to define
additional restrictions and integrity constraints.
      </p>
    </sec>
    <sec id="sec-2">
      <title>2.1 Classes</title>
      <p>Statements defining class hierarchies consist of subject and
subject complement. Subject (topic) is always universally
quantified, predicate noun — always existentially quantified:
(1) Class: Professor SubClassOf: Teacher
Every professor is a teacher.</p>
      <p>Katrs profesors ir kāds pasniedzējs.</p>
      <p>For the universal quantifier there is a corresponding
determiner/pronoun both in English and Latvian (as well as in
other analytical and synthetic languages). As to the existential
quantifier there is no counterpart for the indefinite determiner in
Latvian. We could artificially use an indefinite pronoun instead,
but such construction would be more than odd in this case.
Besides the fact that the subject complement is always indefinite it
also always appears in the focus part of a sentence (here and
further — formatted in bold), i.e., it always is new information
and, thus, the explicit linguistic marker (indefinite pronoun) can
be omitted without introducing any ambiguities. Similarly, class
equivalence can be defined by stating subclass axioms in both
directions (in two separate statements), and class disjointness —
by substituting the determiner ―every‖ with its antonym ―no‖:
(2) DisjointClasses: Assistant, Professor
No assistant is a professor.</p>
      <p>Neviens asistents nav profesors.</p>
      <p>In Latvian (and in many other synthetic languages), a negated
pronoun is used for the negative universal quantifier, and the
statement is negated twice by the copula, but these are minor
syntactic differences; the information structure remains the same.
This assumption can be directly extended to complex classes that
are combined from atomic ones by applying logical constructors:
(3) Class: Course SubClassOf: owl:Thing and
(MandatoryCourse or OptionalCourse)
Every course is something that is a mandatory course or that
is an optional course.</p>
      <p>Katrs kurss ir kaut kas, kas ir obligātais kurss vai kas ir
izvēles kurss.</p>
      <p>So far about cases when the verb phrase (VP) is a predicate
nominal. Another type of constructors for complex classes are
property restrictions — VPs consisting of a transitive verb
complemented by a direct object. In the following statement such
VP is used to implicitly specify an anonymous superclass.
(4) Class: Teacher SubClassOf: teaches some</p>
      <p>Course
Every teacher teaches a course.</p>
      <p>Katrs pasniedzējs pasniedz [kādu] kursu.</p>
      <p>Here the role of word order comes in. In Latvian, if the object
comes after the verb (the neutral word order) it belongs to the
focus part of the sentence (new information), but if it precedes the
verb — to the topic part (given information). In the case of the
inverse use of a property, the word order is changed for the whole
statement (in both languages), moving the agent to the focus:
(5) Class: Course SubClassOf: inverse (teaches)
some Teacher
Every course is taught by a teacher.</p>
      <p>Katru kursu pasniedz [kāds] pasniedzējs.</p>
      <p>Combinations of the introduced syntactic phrases can be further
used to explicitly specify complex superclasses (Statement 6) and
general class axioms, where anonymous is either the subclass
(Statement 7), or both the super- and the sub-class (Statement 8).
(6) Class: Student SubClassOf: Person and</p>
      <p>(inverse (enrolls) some AcademicProgram)
Every student is a person that is enrolled by an academic
program.</p>
      <p>Katrs students ir persona, ko uzņem [kāda] akadēmiskā
programma.
(7) Class: owl:Thing and (teaches some</p>
      <p>MandatoryCourse) SubClassOf: Professor
Everything that teaches a mandatory course is a professor.
Katrs, kas pasniedz [kādu] obligāto kursu, ir profesors.
(8) Class: owl:Thing and (inverse (includes)
some AcademicProgram) SubClassOf: inverse
(teaches) some Teacher
Everything that is included by an academic program is
taught by a teacher.</p>
      <p>Katru, ko ietver [kāda] akadēmiskā programma, pasniedz
[kāds] pasniedzējs.</p>
      <p>+enrolls
&lt;&lt;owlClass&gt;&gt;</p>
      <p>Student
&lt;&lt;objectProperty&gt;&gt;
takes</p>
      <p>&lt;&lt;owlClass&gt;&gt;</p>
      <p>AcademicProgram
+constitutes</p>
      <p>+includes
+takes
&lt;&lt;owlClass&gt;&gt;</p>
      <p>Course
&lt;&lt;owlClass&gt;&gt;
MandatoryCourse
+teaches
&lt;&lt;owlClass&gt;&gt;</p>
      <p>OptionalCourse
&lt;&lt;disjointWith&gt;&gt;
&lt;&lt;owlClass&gt;&gt;</p>
      <p>Person
&lt;&lt;owlClass&gt;&gt;</p>
      <p>Professor
&lt;&lt;objectProperty&gt;&gt;
teaches
&lt;&lt;disjointWith&gt;&gt;
&lt;&lt;owlClass&gt;&gt;</p>
      <p>Teacher
In English, both active and passive voice sentences are still SVO
sentences; the inverse direction of the property is indicated by the
passive voice. In Latvian, the voice remains active, but the
syntactic functions of both NPs are interchanged in such a case,
making it an OVS sentence (semantic roles remain the same in
both languages). Thus, it turns out that the object stands to the left
from the verb — in the topic part, indicating that it should be
given information. However, recall that in TBox statements there
is no doubt which determiner has to be assigned with the topic —
it is always universally quantified (unless it is an anaphoric
pronoun that links a relative clause to its anchor).</p>
      <p>Also, it should be mentioned that in the above provided SVO
statements (4–8) the indefinite pronoun ―kāds‖ is given in square
brackets, which means that in these cases it might be optionally
used as a counterpart for the indefinite article. This conforms to
the language intuition (see Section 4) and emphasizes the
indefiniteness of the NP — the explicit marker improves
readability (interpretation) as there is no relative clause associated
with the NP, which would then serve as an indicator of
indefiniteness.</p>
      <p>
        Another aspect that should be mentioned is that there has not been
made any differentiation between animate and inanimate things —
quantifiers ―everything‖, ―something‖, ―nothing‖, and the relative
pronoun ―that‖ are used in all cases. This makes Statement 7 in
English and Statement 8 in Latvian odd, which has been noticed
by our respondents (see Section 4). However, we ignore this issue
in this paper for the sake of simplicity and for compliance with the
ACE verbalizer [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ] (although ACE parser supports such
differentiation, it is discarded at the ontological level).
      </p>
    </sec>
    <sec id="sec-3">
      <title>2.2 Properties</title>
      <p>The already introduced syntactic constructions can also be used to
define properties and their restrictions. Thus, to specify the
domain and range of a property, in the topic part of the statement
one has to refer the universal class, which is then specified in the
relative clause, referring the property of interest. The subject is
complemented by a predicate nominal in the focus part (see the
statements 9–10). Note that usage of definite and indefinite NPs
(i.e., references to concrete classes) is not possible in property
definitions (except when stating the domain and range), as this
would go beyond the expressivity of OWL (see the next section).
(9) ObjectProperty: teaches Domain: Teacher
Everything that teaches something is a teacher.</p>
      <p>Katrs, kas kaut ko pasniedz, ir pasniedzējs.
(10) ObjectProperty: teaches Range: Course
Everything that is taught by something is a course.</p>
      <p>Katrs, ko kaut kas pasniedz, ir kurss.</p>
      <p>Although property hierarchies, characteristics, and chains can be
defined in the same manner, by additionally exploiting the
anaphoric pronoun ―it‖, in many cases usage of if-then
constructions together with variables is at least more concise, if
not more comprehensible as well (especially in property
chaining). Exceptions are functional and inverse functional
properties that are defined by cardinality restrictions and can be
stated more naturally without anaphoric references, and reflexive
and irreflexive properties — their verbalization in CNL is more
natural if the reflexive pronoun ―itself‖ is used.</p>
      <p>For instance, the definition of a property chain given in
Statement 11 could be paraphrased by using pronouns instead of
variables — ―Everything that includes something that is taken by
something enrolls it.‖ — but such paraphrase would more likely
confuse a human interpreter, especially when resolving the
anaphoric reference.</p>
      <p>(11) ObjectProperty: enrolls SubPropertyChain:
includes o inverse (takes)
If [something] X includes something that is taken by
[something] Y then X enrolls Y.</p>
      <p>Ja [kaut kas] X ietver kaut ko, ko ņem [kaut kas] Y, tad X
uzņem Y.</p>
      <p>Note that the pronoun ―something‖ may be omitted in the
apposition phrases — this not only makes the statements more
comprehensible, but also allows to reduce or even to hide the
issue of discrimination between animate and inanimate things
(accordingly, X and Y in Statement 11). For instance, when
declaring that two properties are disjoint, we can avoid the use of
the indefinite pronoun at all:
(12) DisjointProperties: teaches, takes
If X teaches Y then X does not take Y.</p>
      <p>Ja X pasniedz Y, tad X neņem Y.</p>
      <p>The concise form, however, has a drawback in the case of a highly
synthetic CNL. In English, the strict word order (and the change
of the voice) enables the unambiguous detection of which variable
represents the agent in any of the SVO chunks. In Latvian,
provided that all the properties involved are represented by
transitive verbs (instead of comparative phrases, for instance, as in
―X is smaller than Y‖), the agent/subject can be recognized only
due to the different ending if compared with the object; the verb
itself does not change. Plain variables, of course, are not inflected.
Although for a human interpreter it usually causes no ambiguities
(due to the rich background knowledge, and knowledge of lexical
semantics), suffixes have to be added to the variables to enable the
automatic parsing. Nevertheless, this is still a more user-friendly
solution (see Statement 13) than the use of the artificial apposition
phrases. Moreover, even if indefinite apposition phrases are used,
they are applicable only in the if-clauses; for the then-clauses
definite apposition phrases should be introduced, making such
statements even more unnatural.</p>
      <p>(13) ObjectProperty: includes InverseOf:</p>
      <p>constitutes
If X includes Y then X is constituted by Y.</p>
      <p>Ja X-s ietver Y-u, tad X-u veido Y-s.</p>
      <p>Although property axioms can be seen as a special case, variables
may be used in statements defining classes as well (e.g.,
Statement 7 in Section 2.1 can be paraphrased in ACE as ―If X
teaches a mandatory course then X is a professor.‖). The formal
nature of CNL then becomes explicit more widely, losing the
seeming naturalness that, of course, is not a self-purpose; variable
constructions should be allowed as an alternative to improve
readability in certain cases (e.g., for tracking coreferences in
complex rules). Allowing for such alternatives, however,
introduces an issue in the verbalization direction — how to decide
(encode in the grammar) in which cases variables are preferable
over indefinite and definite NPs.</p>
      <p>Nevertheless, variable constructions are partially out of the scope
of this paper, as there is no need for information structure analysis
to cope with utterances of anaphoric pronouns and variables. Note
that we have already violated the word order guidelines in some
of the previous examples — in Latvian, the indefinite pronoun
―kaut kas‖ typically goes before the verb if it is not specified by a
relative clause (see the statements 9–10). Thus, formally it
belongs to the topic, although it is always new information. But,
again, this causes no ambiguities.</p>
      <p>In overall, if we are restricting our synthetic CNL to cover
terminological statements (class and property definitions) only,
information structure analysis is not necessary at all: since OWL
axioms are variable-free, any noun phrase that is not explicitly
universally quantified is existentially quantified. However, we
have now laid the foundations to extend controlled Latvian for
support of data integrity constraints.
3. DATA INTEGRITY CONSTRAINTS
In this section we will add some implication rules and data
integrity queries to our example ontology, making an actual
exploitation of the topic-focus articulation (TFA) — when
specifying integrity constraints, one cannot avoid the usage of
variables or definite/indefinite NPs.</p>
    </sec>
    <sec id="sec-4">
      <title>3.1 SWRL Rules</title>
      <p>
        In SWRL rules [
        <xref ref-type="bibr" rid="ref18">18</xref>
        ], variables are used, which cause at least one
anaphoric reference, when a rule is verbalized in CNL. In
terminological statements, changes in the word order are caused
only due to an inverse use of a property, but in the case of rules
(verbalized in controlled Latvian), the word order has to be
changed also to indicate whether an NP (the subject or the object)
introduces a new individual or is an anaphoric reference:
(14) Rule: Student(?x1), MandatoryCourse(?x2),
AcademicProgram(?x3), enrolls(?x3, ?x1),
includes(?x3, ?x2) -&gt; takes(?x1, ?x2)
Every mandatory course that is included by an academic
program is taken by every student that is enrolled by
the academic program.
      </p>
      <p>Katru obligāto kursu, ko ietver [kāda] akadēmiskā
programma, ņem katrs students, ko [šī] akadēmiskā
programma uzņem.</p>
      <p>In the above statement, inverse properties are used in both relative
clauses, causing the swapping of the subject and the object. In the
first case, the subject (―akadēmiskā programma‖) stands to the
right from the verb, indicating that it belongs to the focus part —
new information. In the second case, the subject (again,
―akadēmiskā programma‖) stands to the left from the verb — in
the topic part of the clause, indicating that this is already given
information (a reference to the individual introduced in the first
relative clause). Thus, in the latter relative clause, the property
(verb) is alone in the focus — the new information is the
relationship between the two already given individuals (the
student and the academic program).</p>
      <p>The English and Latvian verbalizations of the above rule are more
clearly aligned in Figure 2 (the optional ―articles‖ are not used).</p>
      <p>every
mandatory course</p>
      <p>that
is included by</p>
      <p>an
academic program
is taken by
every
student</p>
      <p>that
is enrolled by</p>
      <p>the
academic program
katru
obligāto kursu</p>
      <p>ko
ietver
akadēmiskā programma
ņem
katrs
students</p>
      <p>ko
akadēmiskā programma
uzņem
To emphasize that an NP is an anaphoric reference, we could
optionally use the demonstrative pronoun ―šis‖ (―this‖), which
usually sounds natural in Latvian. Theoretically, this would allow
us to place the NP also to the right from the verb, but both
stylistically and intuitively the preferable position is still to the
left, which causes the correct intonation.</p>
      <p>Let us consider one more rule (Statement 15) where the indefinite
pronoun ―kāds‖ is not anymore offered as an optional attribute. It
is omitted due to the cascade of relative clauses that modify all the
indefinite NPs.</p>
      <p>(15) Rule: Person(?x1), MandatoryCourse(?x2),
AcademicProgram(?x3), enrolls(?x3, ?x1),
includes(?x3, ?x2), takes(?x1, ?x2) -&gt;</p>
      <p>Student(?x1)
Every person that takes a mandatory course that is included
by an academic program that enrolls the person is a
student.</p>
      <p>Katra persona, kas ņem obligāto kursu, ko ietver
akadēmiskā programma, kas [šo] personu uzņem, ir
students.</p>
      <p>Due to the cases when the usage of the indefinite and
demonstrative pronouns might improve the readability of a rule,
an implementation of an additional concrete grammar of surrogate
Latvian, where the usage of indefinite and demonstrative
pronouns in the role of articles is always mandatory, would be a
simple but naive trade-off. Such a coarse-grained grammar could
be used to paraphrase (on demand) the purely TFA-based
sentences, both user-provided and auto-generated (verbalized).
Although reading of such surrogate statements perhaps is easier
than writing, this would be confusing to the end-users anyway
(see the next section). To provide more fine-grained paraphrases
and to protect the users from a confusingly verbose look-ahead
editor, the TFA-based grammar can be improved at least by
distinguishing two types of NPs: those that are modified by
relative clauses, and those that are not. In the latter case, usage of
the indefinite or demonstrative pronoun is preferable.
However, if a statement is written in synthetic language, the best
paraphrase could be its translation into analytical language (e.g.,
English), or alternatively (for an advanced user) — in a
humanreadable formal syntax like the Manchester OWL Syntax.</p>
    </sec>
    <sec id="sec-5">
      <title>3.2 SPARQL Queries</title>
      <p>When executing SWRL rules, potentially new facts are inferred
and added to the ontology (ABox) whenever the body of a rule is
satisfied. If this is the intention and if the rule (its verbalization)
does not include negated atoms or disjunctions then it is the right
choice; otherwise we would end up with unwanted entailments or
would not be able to translate the statement into SWRL. For
example, if we would try to redefine the property chaining defined
in Statement 11 (in Section 2.2) as a more specific rule (by
referring to the concrete classes) — ―Every student that takes a
course that is included by an academic program is enrolled by the
academic program.‖ — the effect would be that a student, taking
a course that is included by another academic program, is
automatically enrolled by that program.</p>
      <p>
        By asking SPARQL queries we can verify integrity constraints
relying on the closed world assumption (negation as failure) [
        <xref ref-type="bibr" rid="ref13">13</xref>
        ],
without introducing unintended entailments. Thus, Statement 11
can be alternatively (but not equally) specified in CNL as the
following query:
(16) ASK WHERE {
?x1 rdf:type Student.
?x1 takes ?x2.
?x2 rdf:type Course.
?x3 rdf:type AcademicProgram.
?x3 enrolls ?x1.
      </p>
      <p>NOT EXISTS {?x3 includes ?x2}}
Is there a student that takes a course that is not included by
an academic program that enrolls the student?
Vai ir kāds students, kas ņem kursu, ko neietver
akadēmiskā programma, kas studentu uzņem?
In the case of consistency checking, the ASK form of a query
(yes/no question) is entirely appropriate and its verbalization
syntax is not much different from that of rules. Note that in such
queries the first NP is always indefinite (although appearing in the
topic) and the corresponding indefinite pronoun is always
explicitly attached to it.</p>
      <p>
        The current SPARQL specification [
        <xref ref-type="bibr" rid="ref16">16</xref>
        ] does not directly provide
an operator for negation as failure; it is possible by combining the
OPTIONAL, FILTER and !BOUND operators. However, if the
!BOUND operator is applied to a variable (in our example, x3)
that is used also outside the OPTIONAL block then the result, of
course, will not be what expected. Therefore, for the sake of
simplicity, we have used the NOT EXISTS pattern that will be
provided by the SPARQL 1.1 specification [
        <xref ref-type="bibr" rid="ref17">17</xref>
        ].
      </p>
    </sec>
    <sec id="sec-6">
      <title>4. EVALUATION</title>
      <p>To verify whether the proposed assumptions on which the
proofof-concept implementation [20] is based are linguistically
motivated and universally applicable in highly synthetic CNLs, an
initial evaluation was performed. About ten linguists (both
Latvians and Lithuanians), specialized in Baltic languages,
received nearly twenty examples, covering different types of
statements and different levels of complexity. For each example
several alternative translations were given in Latvian and
Lithuanian in parallel (see Table 1). Among the alternative
choices were the ―literal‖ (surrogate) translation, the pure
TFAbased translation, and a combination of the previous two, in order
to seemingly improve the readability. The respondents were asked
to sort the choices (in their native language) by priority from 1 to
3 (1 goes for the best translation of the original statement in
ACE), or rejected at all (0). The respondents were introduced with
the basic limitations of CNL, but they were also asked to follow
their language intuition.</p>
      <p>Every student is a person that is enrolled by an academic program.</p>
      <p>ALV
ALT
BLV
BLT
CLV
CLT</p>
      <p>Katrs students ir kāda persona, ko uzņem kāda
akadēmiskā programma.</p>
      <p>Kiekvienas studentas yra koks nors asmuo, kurį priima
kokia nors akademinė programa.</p>
      <p>Katrs students ir persona, ko uzņem akadēmiskā
programma.</p>
      <p>Kiekvienas studentas yra asmuo, kurį priima akademinė
programa.</p>
      <p>Katrs students ir persona, ko uzņem kāda akadēmiskā
programma.</p>
      <p>Kiekvienas studentas yra asmuo, kurį priima kokia nors
akademinė programa.
0
1
2
The respondents were also invited to give an alternative
translation for each example, if none of the proposed ones was
enough satisfactory. This option was used rather frequently,
resulting in some interesting suggestions. Those that can be
systematized will be taken into account.</p>
      <p>In overall, most of the literal translations, using the artificial
―articles‖, were rejected or assigned with the lowest priority.
There was no consensus, however, whether the indefinite and
demonstrative pronoun in certain cases should be used to improve
readability or not; even the same respondent usually did not act
consistently among different examples. However, in most cases,
the usage of the pronoun is preferred, if the NP is not modified by
a relative clause.</p>
      <p>It should be mentioned that almost all the respondents were
disappointed with the uniform approach to animate and inanimate
things. Although this is not directly related to the topic of this
paper, this issue has to be taken into account, which means that
one more feature has to be incorporated in the domain-specific
lexicons (in the noun and pronoun entries) and exploited in the
grammars. However, the issue will still remain, if other tools are
used in the workflow (e.g., the ACE verbalizer).</p>
      <p>Based on these results, an improved grammar is being developed,
which will be evaluated by a wider audience.</p>
    </sec>
    <sec id="sec-7">
      <title>5. CONCLUSION</title>
      <p>
        We have shown that in controlled Latvian, which is a highly
synthetic CNL, where definite and indefinite articles are not used,
the topic-focus articulation can be reflected by systematic changes
in the neutral word order. This provides a simple and reliable
mechanism (guidelines) for deterministic (predictable) analysis of
the information structure of a sentence, enabling automatic
detection of anaphoric NPs. As the very initial evaluation
confirms, native speakers tend to follow such guidelines rather
intuitively. Moreover, in languages where the semantic and
pragmatic aspects of the sentence are more studied [
        <xref ref-type="bibr" rid="ref11">11</xref>
        ], the
general correlations between the word order and given/new
information are being taught even in language learning courses for
beginners [
        <xref ref-type="bibr" rid="ref12">12</xref>
        ].
      </p>
      <p>
        At the time of writing, the proof-of-concept implementation of
Latvian-English CNL covers most of the syntactic constructions
that were introduced in the previously given examples. The aim
for the near future is to extend the TFA-based grammar to cover
the full expressivity of terminological statements and rules, while
remaining compliant with ACE. Future work is (a) to introduce
support for assertional statements — the problem is how to
determine, whether the subject noun (in the case of the neutral
word order) represents given or new information, (b) to make a
more detailed investigation on data integrity queries that are
important in practical applications and will make a rather
extensive use of anaphoric references, and (c) to consider pros and
cons for using the GF Resource Library [
        <xref ref-type="bibr" rid="ref8">8</xref>
        ].
      </p>
    </sec>
    <sec id="sec-8">
      <title>6. ACKNOWLEDGMENTS</title>
      <p>This research has been supported by the European Social Fund.
The author would like to thank Gunta Nešpore, Baiba Saulīte,
Guntis Bārzdiņš and Kārlis Čerāns for the valuable discussions on
linguistic and semantic aspects, as well as the reviewers for the
detailed comments and suggestions, and the respondents for their
help in the initial evaluation of the proposed approach.
[19] http://protegewiki.stanford.edu/index.php/OWL2UML
[20] http://eksperimenti.ailab.lv/cnl/</p>
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