Paper

Automated Filipino Verbal Sentence Evaluator
Jennefer B. Jore
Associate Software Engineer
Cybergate 1, Robinson’s Pioneer,
Boni Ave., Manadaluyong
Philippines
jennefer.b.jore
@yaccenture.com
Ana Ruby B. Ramos
Associate Software Engineer
Cybergate 1, Robinson’s Pioneer,
Boni Ave., Manadaluyong
Philippines
mam.ana.ruby.r.cordero
@accenture.com
Qurrata-Ayn K. Karim
3rd author's affiliation
1st line of address
2nd line of address
Telephone number, incl. country code
Ayn_karim@yahoo.com
Erlyn Q. Maguilimotan
Faculty,
Computer Science Dept.
College of Science and Information
Technology
Ateneo De Zamboanga University
erlynqm@yahoo.com
Ebony C. Domingo
Chairperson,
Computer Science Dept.
College of Science and Information
Technology
Ateneo De Zamboanga University
domingoeboc@yahoo.com
ABSTRACT
Grammar acquisition is an important part of language acquisition
and learning for human beings. Many projects have been designed
to assist in the grammar development of people by having
automated checking of grammars both for fixed word order and
free word order languages. The Filipino language is a free word
order language. It exhibits the problem of discontinuous
constituents. Several approaches used to treat this problem use a
hierarchical syntactic structure that resulted to parsing and
processing delays. One approach that also treats this problem
called Tagalog Free-Word Order (TagFWO) Parser uses a flat
syntactic structure. This approach is able to solve the problem of
discontinuous constituents syntactically. However, the semantic
side is not treated by this approach. The aim of this research then
is to develop a system that evaluates a Filipino verbal sentence by
checking the syntactic structure and semantic relation of the
constituents of the sentence.
The Automated Filipino Verbal Sentence Evaluator is a system
capable of evaluating Filipino verbal sentences based on its
grammar. It uses a Parser in checking the grammar structure, and
the Lexical Functional Grammar (LFG) formalism for the
grammar relation. Grammar structure takes into account the
syntax of the sentence by verifying if such sentence structure
valid in the system. Grammar relation considers the functional
relationship of each constituent in the sentence by checking if the
doer in the sentence has the capability to do such action.
The system is trained on a set of Filipino 33 verbal and nonverbal
sentences (grammatical and ungrammatical). The results
showed that the grammatical verbal sentences were all evaluated
properly with their corresponding detailed user evaluation
feedback. The grammatical non-verbal and ungrammatical
sentences are rejected and outputted a corresponding error
message.
The method developed in this research has resolved issues on
syntactic and semantic relations in tagalong verbal sentences.
However the issues of lexical ambiguities and deeper semantic
interpretations have not yet been included in this research. This
study can further be enhanced to embrace a more complex verbal
system of the Filipino language considering other parts of speech.
General Terms
Algorithms, Languages.
Keywords
Grammar checker, Filipino, natural language processing, artificial
intelligence, text processing.
1. INTRODUCTION
Language systems consist of words arranged in certain learned
ways (grammar and syntax). Internationalization of language
systems is developed through recognition of syntactic structures
or grammar of a language. Syntactic analysis is the process of
determining the syntactic structure of a sentence according to
grammar rules. This analysis is vital for the recognition of the
grammatical correctness of a sentence [14].
Syntactic analysis is subdivided into structure and relation. One
major application of structural syntactic analysis is parsing. This
method is the decomposition of scanned tokens in an input stream
(a sentence in a language) into components based on phrase
structure grammar rules. Grammar is defined as a system of rules
and principles that determine the formal, legal and semantic
properties of sentences [5] and the description of the signals
which lead to the understanding of a language. Most studies
conducted in the field of syntactic analysis are concentrated on
parsing algorithms.
Parsing algorithms are given higher priority than grammatical
relation is because researchers in this field are seeking a universal
model on syntax for both free and fixed word order languages.
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However, fixed word order languages are considered in most
investigations [9].
Fixed word order languages are languages that have a strict
ordering of constituents [3] and is said to be configurational,
while free word order languages do not follow any rule for the
ordering of the constituents and is said to be non-configurational.
Non-configurational means the verb, as the head of the sentence
structure, along with the other constituents in the structure can be
treated as sisters [7]. In a configurational setting the verb and
other constituents cannot be treated as sisters. A separate verb
node is required. Current approaches on free word order
languages are based the configurational approach and thus,
resulting to problems of capturing discontinuous constituents
which are present in free word order languages [3].
Current treatment to this problem is already available. One
approach to this problem is scrambling approach which involves
transformations of a constituent from its original position to other
positions until the right position is found [3]. However, this
approach creates parsing delays due to searching of the adjacent
constituents. Another approach is the sortal hierarchy of types,
which was modeled using the German language [11].
Unfortunately, this approach cannot be applied to Filipino
because it is unsuitable for representing adjacent constituents.
Another approach is the discontinuous dependency parsing which
was applied to Russian and Latin [1]. This approach is applicable
to other languages; however, it is time consuming. It backtracks
and finds an alternative solution thus, exhibits non-determinism
due to the lack of a predictive capability [3].
One research in the Philippines on syntactic analysis is called
Tagalog Free Word Order (TagFWO) Parser by Editha D.
Dimalen [3]. TagFWO Parser is a web-based implementation of a
new technique to address the problem of discontinuous
constituents in a free word order language, Tagalog. It uses flat
syntactic structure that differs from the current approaches that
uses a hierarchical syntactic structure. It uses the concept of Head
Specifier and Head Complement rules to handle the constituency
of tagalong language. It is appropriate for Tagalog language and
require less computing time in contrast to other existing approach.
However, the above-mentioned approaches are focused on the
syntactic structure of the sentences and less on the grammatical
relations. A study by Kroeger [7] showed the insufficiency of
phrase structure rules to capture the syntactic relations and the
importance played by grammatical relations for the Filipino
language. Filipino is the national language of the Philippines. This
language is characterized to be non-configurational. As nonconfigurational,
Filipino does not follow fixed ordering of words
in sentence constructions. Thus, phrase structure rules are not
considered to be sufficient to address the non-configurationality
of the language.
Syntactic relationships and grammatical relations in Filipino are
signified by case markings and verbal affixations [8]. These
syntactic attributes contribute working out what is to be means in
a sentence. The affixations in the Filipino language signify
semantic criteria and categories. Phrasal structures do not succeed
in understanding lexical structures in words but only
componential functions within phrases [6].
Grammar formalism is needed in order to capture syntactic
relationships and grammatical relations of each constituent in a
sentence in any natural language like Filipino. The Lexical
Functional Grammar (LFG) is able to capture both of these
syntactic attributes. Dimalen [6] made use of Head-driven Phrase
Structure Grammar (HPSG) formalism. However, according to
the author, LFG is simpler while retaining the same capabilities of
HPSG. This research then developed an automated grammar
checker for Filipino verbal sentences, which used LFG grammar
formalism.
2. FILIPINO VERBAL SENTENCE
Filipino verbal sentences are sentences that contain a verb or verb
form in the predicate position. The verbal form of the predicate
determines the role of the noun(s) in the sentence. This depends
on the affix in the verb which tell whether the noun is being an
actor, object, instrument, etc.
One interesting feature of the Filipino language is its focus
system. This means that the role of the noun in focus is reflected
in the verb. Focus is the feature of a verbal predicate that
determines the semantic relationship between a predicate verb and
its topic [12]. There are two types of focus that occur on a basic
Filipino sentence: Actor-focus, the focus is on the actor or doer,
and Goal-focus, does not focus on the actor. There are different
classes of goal-focus. However, Schachter and Otanes [12]
pointed out that only two from these classes are found in basic
Filipino sentence: Object focus, and Directional-focus. The use of
this different focus is based on their affixes.
The verb is based on the use of affixes. The affix is a way of
packaging in some extra information into a word. Filipino uses
affixes in a similar way to indicate tenses of a verb, if an action is
completed or not. In addition to this, Filipino uses affixes to
indicate the role of the focus of the sentence. In other words,
affixes are used to determine what the focus is doing in the
sentence.
2.1 LFG as a grammar checker
A grammar checker was developed to address the problem on
word order, subject-verb agreement and pragmatically in correct
constituent orders of German sentences. This project made use of
LFG and supplemented with rule components for analysis of
ungrammatical input. LFG is composed of constituent-structure
containing the linear hierarchical constituent order and functional
structure representing functional relations and grammatical
features by means of attribute value matrices. Having rule-based
grammar checker with LFG, this project was able to parse
unrestricted input and identify correct errors. However,
orthography and morphological error identified are still
unresolved [4].
LFG has two structures for representing different levels of
linguistics information: constituent structure (c-structure) and the
functional structure (f-structure). The c-structure in LFG
represents the external structure of a sentence in the form of a
phrase structure tree [15]. It shows the syntactic constituents of
the sentence. It relies on the grammar rules defined by the LFG. It
is the more concrete level of linear and hierarchical organization
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of words into phrases [2]. It contains lexical and functional
categories. A sample c-structure is shown in Figure 1 applying
phrase structure rules for the sentence “natulog ang bata” .
checks for the capability of the doer to do the task which is the
verb. It checks the lexical entry of the verb if such object is
accepted to it. It also checks the relationship between the two
nouns through the verb. Since the verb accepts an object and the
doer has the capability to do the action based from the lexical
entry, then, f-structure considers this sentence as grammatically
correct.
Figure1. Sample c-structure with Functional Schemata
The functional schemata ( SUBJ) = and = show in symbols
the role of each string play in a sentence (Mangulimotan, 2001). f-
structure does not have direct mapping from cstructure. It is
constructed from instantiation. Thus, the arrows symbols assume
referential values that point to their values () and to which
immediately dominates them () [10].
3. SYSTEM WORKFLOW
The overall flow of the system is shown in figure 3. An input
sentence is passed on to the Lexical Analyzer module. There are
three applications that process the sentence in this module. The
first application is called Tokenization which separates each word
of the sentence as a unique entity called token. Once tokenized,
the first token which should be the verb, is passed on to the
second application called Word Stemming. This application
determines the root word of the verb by extracting the affixes. At
the same time, it checks the validity of the root word form using
the lexicon. Based from the extracted affix, the focus type of the
sentence can be determined [13]. The remaining tokens are also
checked if such word exists in the lexicon. The final application
for this module is Tagging. Each token is tagged with the proper
part-of-speech tags which are passed on to the parser.
The f-structure models the internal structure of a language and the
functional roles of each constituent or word order in producing
the meaning of the sentence [2].Each word is designated a set of
categories like subject, object, topic, focus, aspect, case, number,
gender, and other important lexical attributes. This is how f-structure
checks the grammaticality sentence “bumili ang bata ng isda” ( Figure 2).
Figure 2. Sample f-structure
The verb Bumili is considered to be in actor focus since it has the
affix um and thus, making the actor as the subject of the sentence.
The determiner ang determines the subject. The noun bata which
is preceded by the determiner ang and the focus signifies the term
as the subject. Thus from the relationship alone of these three
constituents, the f-structure can immediately identify the subject.
The verb Bumili is an actor focus for it has the affix um. As a rule,
actor focus requires an actor to make the sentence complete. The
object is an optional in the sentence. However, in this sentence, an
object phrase is included. To check if the phrase is an object, a
determiner ng is checked after the subject. The noun isda which is
preceded by ng signifies the term as the object. f-structure does
not only rely on checking the subject and doer rather it also
Figure 3. Architectural Design
The parser verifies the grammar structure through the grammarrule
specified in the system. It is the syntactic structure that is
evaluated by the parser first through the grammar syntax rules
provided by the system. The semantic side is evaluated by Lexical
Functional Grammar (LFG).
LFG evaluates the semantic of the sentence by means of
grammatical relations. Each word in the sentence has their
respective lexical information defined in the lexicon. After LFG
evaluates, the systems outputs a user feedback that states the
evaluation process of the system.
4. RESULTS AND DISCUSSION
Filipino verbal sentence is the main study of this research. The
following rules that were adopted in different Balarilang Filipino
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ooks were used as a basis for determining grammatically correct
and wrong Filipino verbal sentences.
Figure 4. Grammar Rules
This research initially made use of 16 verbs and 38 nouns chosen
randomly from the Handbook of Tagalog Verbs by Teresita V.
Ramos [12]. These were made part of the lexicon. The system
was tested and evaluated using different Filipino verbal and nonverbal
sentences. There were seven (7) grammatically correct
Filipino verbal sentences that was successfully evaluated by the
system. Taking all the possible orderings of the 7 sentences, it
resulted to thirty-three (33) combinations in all due to free-word
ordering. The system has been able to evaluate the sample
sentences. Grammatically correct verbal sentences were
acknowledged with a detailed evaluation as an output of the
system while grammatically wrong sentences were also
acknowledged and given with the necessary information for being
incorrect.
5. RECOMMENDATIONS
The Automated Filipino Verbal Sentence Evaluator has resolved
the issues on syntactic and semantic relations. However, the
issues of lexical ambiguities and deeper semantic interpretations
have not yet been included in this research. But, with LFG’s
ability of employing semantic relation rules, it is possible to
resolve the issues on lexical ambiguities and deeper semantic
interpretations. However, this requires changes in the semantic
rule and is subject to further investigations.
This study can further be enhanced to embrace a more complex
verbal system of the Filipino language. Other Filipino parts of
speech may also be considered as an additional scope to the study.
In line with this, an automated Filipino essay evaluator can be
developed through this advance studies.
Kroeger [7] has said that Philippine-type languages exhibit
structural similarities. This means that it is possible for the system
to be also used for other Philippines languages and requires only
additional entries in the lexicon. Moreover, this research has made
a very significant contribution in the field of Natural Language
Processing especially in the different researches and studies
conducted for the Filipino language.
6. REFERENCES
[1] Covington, M.Discontinuous Dependency Parsing of Free
and Fixed Word Order. Available:
http://www.ai.uga.edu/ftplib/ai_reports/reports.txt, 1994.
[2] Dalrymple,M. A Lexical Functional Grammar. Available :
http://users.ox.ac.uk/~cpgl0015/lfg.pdf, 2001.
[3] Dimalen, E. Algorithm for Consituent Structures of Tagalog.
MS Thesis, De Lasalle University Professional Schools, Inc.
Manila, Philippines, 2003.
[4] Fortmann, C.and Frost, M. An LFG Grammar Checker for
CALL. Available: ftp://www.ims.uniuttgart.de/pub/Users/forst/Fortmann:Forst-ICALL04.pdf
[5] Fries, P.The 31st International Systematic Functional
Congress. Doshisha University,Kyoto, Japan.
vailable:http://www1.doshisha.ac.jp/~mtatsuki/ISFC31/pages
/abstract_plenary.pdf, 2004.
[6] Hoopman, H., Sportiche, D. and Stabler, E.. An Introduction
to Syntactic Analysis and Theory. Available:
http://www.linguistics.ucla.edu/people/sportiche/isat.pdf,
2002.
[7] Kroeger, P..Phrase Structure and Grammatical Relations in
Tagalog.Dissertations in Linguistics. Stanford, CA: Center
for the Study of Language and Information.xiv,240p, 1993.
[8] Lupyan, G. Modelling Syntactic Devices: An Explanation of
Language Evolution from Connectinist and Memetic
Perspectives.
Available:http://www.isr/uiuc.edu/~amag/langev/paper/lupya
n02modeling.html, 2002.
[9] Maegard, B.Machine Translation.
Available:http://www.cs.uregina.ca/Research.Techreports/95
09.ps, 2002.
[10] Manguilimotan, E.(2001). Syntactic Representation of
Tausug Verbal Sentences. MS Thesis, MSU-Iligan Institute
of Technology, Iligan City, Philippines, 2001.
[11] Oliva, K.The Proper Treatment of Word order in HPSG.In
the Proceedings of the 14 th International Conference on
Computational Linguistics, Nantes.
Available:http//www.acl.ldc.upenn.edu/C/C92?c92-
1031.pdf, 1992.
[12] Ramos, T.Handbook of Tagalog Verbs. University of Hawaii
Press, 320 pp., 1986.
[13] Schachter, P. & Otanes, F. Tagalog Grammar Reference.
University of California Press. Berkeley, CA, 1972.
[14] Tablante, N..The Predictive Value of Knowledge in
Grammar in the Writing Proficiency of the Freshmen
Engineering Students, 1997.
[15] Wong, S.(2001). Lexical Functional Grammar.
Available:
http://www.fi.muni.cz/usr/wong/teaching/mt/notes/node15.html.is
o-8859-1, 2001.
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