What is UnificationBased Grammar?
Unificationbased grammar (UBG) is a family of formal grammatical frameworks that represent linguistic knowledge as a set of feature structures. A feature structure is a set of attributevalue pairs (e.g., tense=Past, person=3), and the central operation is unification: the merging of two compatible structures into a single, richer one. If the structures contain contradictory values, unification fails, preventing the construction of an illformed sentence.
The most widely used UBG frameworks are:
- LexicalFunctional Grammar (LFG)
- HeadDriven Phrase Structure Grammar (HPSG)
- AttributeValue Matrix (AVM) based approaches
Because Vietnamese is an analytic, isolating language with little inflection, a unificationbased approach offers a natural way to capture its grammatical phenomena (word order, particles, classifier system, tonerelated syntax) without inventing unnecessary morphological rules.
Why Use Unification for Vietnamese?
Vietnamese presents several challenges that fit well with unification:
- Word order is crucial. Since there are no rich case markings, the relative positions of subject, verb, object, and adjuncts determine grammatical relations.
- Particles and function words. Words such as , ang, s, cng carry aspectual, modal or discourse information. Their contribution can be expressed as feature values that percolate through the phrase structure.
- Classifier system. Numeralclassifiernoun sequences require the noun to be compatible with the classifiers semantic class. Unification can enforce this compatibility.
- Topiccomment structure. Vietnamese frequently uses a fronted topic that is not syntactically integrated as a subject. A
topicfeature can be attached to a clause and checked against discourse constraints.
Core Feature Structure Design
The following simplified set of attributes is typical for an HPSGstyle Vietnamese grammar:
[ CAT = phrase HEAD = [ POS = noun | verb | particle | ... ] VAL = [ SUBJ = < > COMPS = < > MOD = < > ] SEM = [ MODE = declarative | interrogative | imperative TENSE = past | present | future ASPECT = perfective | imperfective | progressive POLARITY = + | - TOPIC = <?> ]]
CAT distinguishes between lexical items and phrasal constituents. HEAD stores partofspeech information and any languagespecific properties (e.g., CLF for classifier compatibility). VAL records valence requirements: the list of expected subjects (SUBJ), complements (COMPS) and modifiers (MOD). SEM contains the semantic and pragmatic features that will be passed up the tree.
Illustrative Analyses
1. Simple Declarative Clause
Sentence: Hoa n cm. (Hoa eats rice.)
[ PHRASE HEAD = [ POS = verb TENSE = present ] VAL = [ SUBJ = < NP[HEAD=noun, INDEX=hoa] > COMPS = < NP[HEAD=noun, INDEX=cm] > ] SEM = [ MODE = declarative EVENT = eat(hoa, cm) ] ]
2. Aspectual Particles
Sentence: Hoa ang n cm. (Hoa is eating rice.)
[ PHRASE HEAD = [ POS = verb TENSE = present ASPECT = progressive ] VAL = [ SUBJ = < NP[INDEX=hoa] > COMPS = < NP[INDEX=cm] > ] SEM = [ MODE = declarative EVENT = eat(hoa, cm) ] ]
The particle ang contributes the feature ASPECT=progressive. Unification forces the verb phrase to inherit this value.
3. Classifier Compatibility
Sentence: Ba con mo. (Three cats.)
[ NP HEAD = [ POS = noun CLASS = animal ] QUAN = [ NUM = three CLF = con ] SEM = [ QUANTITY = three(cat) ] ]
The classifier con has a lexical entry that restricts CLASS=animal. Unification between the classifier and the noun fails for ba ci bn (*three chairs with classifier con), thus preventing semantically illformed phrases.
4. TopicComment Construction
Sentence: V nh, ti s i. (As for going home, I will go.)
[ CLAUSE HEAD = [ POS = verb TENSE = future ] VAL = [ SUBJ = < NP[INDEX=ti] > COMPS = < > ] SEM = [ MODE = declarative TOPIC = v nh EVENT = go_home(ti) ] ]The fronted phrase v nh is stored in the
TOPIC attribute; discourse rules can later check that the topic is salient in the discourse model.