FMZ

Elaborazione del linguaggio naturale

Fabio Massimo Zanzotto

FMZ

Part five

Feature Structures

FMZ

Where we are?

Target of the analysis:– interpret NL sentences with respect to a sort of

anambiguos internal laguage

• Natural Languages is a ambiguous and social beast vs. Formal Languages is unambiguous and “top-down” decided

• What’s a language model:– treating infinite sentences with generative machinaries

with a finite set of rules

FMZ

How we proceeded so far...

ASSIOM: A syntactic interpretation of a sentence helps in understanding its semantics

Let’s build a syntactic model for NL!!• Analysis of the chomsky hierarchy• Use of Context-free formalisms and related

parsing algoritms– CYK

– DCG (in prolog)

FMZ

How we proceeded so far...

OBSERVATION: NL is more difficult that what we may think

Let us renounce to the total grammaticality!!!

• Model offering Partial Analysis– CYK– Chart parsing and early algorithm

FMZ

Our Aim

Lines of development

Grammatical Representation Power: Build a formalism/model able to give the possibility of reducing the unnecessary interpretations

Grammar Use: Build a formalism (and an associated algorithm) able to represent partial analysis

FMZ

Our Aim

Lines of development

Grammatical Representation Power:

• CFG (context free grammars) DCG

Grammar Use:

• CYK

• Chart and Early Algorithm

FMZ

Observing natural language

Toy Examples:

... La vecchia porta la sbarra ...

... Il vecchio porta la sbarra ...

... Flying planes can be dangerous ...

... Flying planes is dangerous ...

FMZ

A sample Grammar (introspectively produced)

S NP VP | S SBAR | SBAR S

SBAR CongSub S

S S CongCoord S | S, S CongCoord S

NP NP SBAR

VP VerbX NP | VerbX NP PP

VerbX Verb | Modal Verb

NP Art Noun | Art Adj Noun | Noun | Verb Noun | NP PP

PP Prep NP

FMZ

Observations

• The sample grammar is insufficient!!• Spurious interpretations are produced for

unambiguous sentences• Loosing the eternal struggle between coverage and

induced ambiguity

NP Art Noun | Art Adj Noun | Noun | Verb Noun | NP PP

... the old man carries apples ...A) the old man (VP carries apples)B) the old man (NP carries apples)

FMZ

Necessary extensions

• Introducing notions like:– gender: masculine, feminine– number: singular, plural– person (for verbs)– time (for verbs)– mood (for verbs)

FMZ

Grammar

Adding number (Sing, Plur)

NPSing ArtSing NounSing

NPPlur ArtPlur NounPlur

VPSing VerbXSing NP | VerbXSing NP PP

VPPlur VerbXPlur NP | VerbXPlur NP PP

S NPSing VPSing | NPPlur VPPlur

FMZ

Grammar

Adding number (Sing, Plur) and gender (Mas, Fem)

NPMasSing ArtMasSing NounMasSing

NPFemSing ArtFemSing NounFemSing

NPMasPlur ArtMasPlur NounMasPlur

NPFemPlur ArtFemPlur NounFemPlur

VPSing VerbXSing NP | VerbXSing NP PP

VPPlur VerbXPlur NP | VerbXPlur NP PP

S NPMasSing VPSing | NPFemSing VPSing | NPMasPlur VPPlur | NPFemPlur VPPlur

!!Rules are uncontrollably proliferating!!

FMZ

Feature Structures

FMZ

What do we desire?

Adding number (Sing, Plur) and gender (Mas, Fem)

NPMasSing ArtMasSing NounMasSing

NPFemSing ArtFemSing NounFemSing

NPMasPlur ArtMasPlur NounMasPlur

NPFemPlur ArtFemPlur NounFemPlur

NP_Gen:X_Num:Y Art_Gen:X_Num:Y Noun_Gen:X_Num:Y

FMZ

Feature Structures

Feature structures (information containers) are:• Sets of attribute-value pairs• a value of an attribute may be:

– a final value (i.e., an element from a set)

– a feature structure

Agreement:

npCat:

Gen: mas

Num: sing

FMZ

Feature Structures

Formally if F is a feature structure,

• F is a set of pairs (f,v)

• given (f,v)F– v is a final value – v is a feature structure

FMZ

Feature Structures: Lexicon• nouns

– forma_superficiale– lemma– genere– numero

• verbs– forma_superficiale– radice– coniugazione: are, ere, ire– genere: mas, fem– numero: sing, plur– persona: 1,2,3– modo: indicativo, congiuntivo, imperativo– tempo: presente, passato,...– verso: attivo, passivo

FMZ

Lexicon: examples

forma_superficiale: mangeremo

radice: mangi

coniugazione: are

numero: plur

persona: 2

modo: indicativo

tempo: futuro

FMZ

Lexicon: examples

forma_superficiale: mangerebbe

radice: mangi

lemma: mangiare

coniugazione: are

numero: sing

persona: 3

modo: condizionale

tempo: presente

FMZ

Lexicon: examples

forma_superficiale: uomini

lemma: uomo

numero: plur

genere: mas

FMZ

How to use the lexicon?

“l’uomo mangierebbe pere”

that may be seen:[forma_supericiale: l’][forma_supericiale: uomo][forma_supericiale: mangierebbe] [forma_supericiale: pere]

forma_superficiale: mangierebbe

radice: mangi

lemma: mangiare

coniugazione: are

numero: sing

persona: 3

modo: condizionale

tempo: presente

FMZ

Comparing feature structures: subsumption

• A Feature Structure F1 subsumes F2 (F1 F2) if all the information that is in the F1is also in F2

Formally,

F1 F2 se e solo se

v = v’ oppure

(f,v) F1(f,v’) F2. v v’

FMZ

After the lexicon and the subsumption“l’uomo mangierebbe pere”

that may be seen:[forma_supericiale: l’][forma_supericiale: uomo][forma_supericiale: mangierebbe] [forma_supericiale: pere]

forma_superficiale: mangierebbe

radice: mangi

lemma: mangiare

coniugazione: are

numero: sing

persona: 3

modo: condizionale

tempo: presente

forma_superficiale: uomolemma: uomonumero: singgenere: mas

FMZ

What if?

“l’uomo mangierebbe pere”

that may be seen:[ forma_supericiale: l’][ forma_supericiale: uomo][ forma_supericiale: mangierebbe , forma_fonologica: xxxx ] [ forma_supericiale: pere]

forma_superficiale: mangierebbe

radice: mangi

lemma: mangiare

coniugazione: are

numero: sing

persona: 3

modo: condizionale

tempo: presenteSubsumption is not sufficient!

FMZ

Unification

Unification is a partial operation between two feature structures so that the new feature structure contain all the information of the two

F1F2 is so that:– F1 F1 F2

– F2 F1 F2

– if H has the property F1 H and F2 H then

F1 F2 H

FMZ

Unification Exampleforma_superficiale: mangierebbe

radice: mangi

lemma: mangiare

cat: verbo

coniugazione: are

numero: sing

persona: 3

modo: condizionale

tempo: presente

forma_superficiale: mangierebbeforma_fonologica: xxx

forma_superficiale: mangierebbe

radice: mangi

forma_fonologica: xxx

lemma: mangiare

cat: verbo

coniugazione: are

numero: sing

persona: 3

modo: condizionale

tempo: presente

=

=

FMZ

Unification

forma_superficiale: mangierebbe

radice: mangi

lemma: mangiare

cat: verbo

coniugazione: are

numero: sing

persona: 3

modo: condizionale

tempo: presente

forma_superficiale: mangiaforma_fonologica: xxx

Unification between two feature structures may not exist.

FMZ

Coindexing

What if we want to apply this rule?

forma_superficiale: mangierebbe

radice: mangi

lemma: mangiare

cat: verbo

coniugazione: are

numero: sing

persona: 3

modo: condizionale

tempo: presente

forma_superficiale: uomolemma: uomocat: nomenumero: singgenere: mas

cat: s cat: nomenumero: [1]

cat: verbonumero: [1]persona: 3

FMZ

Feature Structures in Prolog

• feature structures will be represented as a open list of attribute value pairs

• : (the colon) will be used to form attribute value pairs

es.[number:sg, person:3 | _ ]

[cat:np, agr:[number:sg, person:3 | _ ] | _ ]

FMZ

Unification in Prolog

unify0(Dag,Dag) :- !.    

     unify0([Feature:Value|Rest],Dag) :-       val(Feature,Value,Dag,StripDag),        unify0(Rest,StripDag).  val(Feature,Value1,[Feature:Value2|Rest],Rest) :-    !,    unify0(Value1,Value2).val(Feature,Value,[Dag|Rest],[Dag|NewRest]) :-    !,    val(Feature,Value,Rest,NewRest).

FMZ

Where we worked today?

Lines of development

Grammatical Representation Power: Build a formalism/model able to give the possibility of reducing the unnecessary interpretations

Grammar Use: Build a formalism (and an associated algorithm) able to represent partial analysis