Rules based interlingua translation in ATLASmazzei/papers/mazzei-CIRMA12-02.pdf · 2 Interaction Models Group The linguistics of LIS Several articolators: parallelism Spatial “organization”

1Interaction

Models Group

Rules based interlingua

translation in ATLAS

Seminari CIRMA 201213-06-2012

Leonardo Lesmo & Alessandro Mazzei & Cristina Battaglino

Dipartimento di Informatica

Università degli Studi di Torino

[email protected]

2Interaction

Models Group

The linguistics of LIS

Several articolators: parallelism Spatial “organization” of the sentence Plural SOV Many local dialects A few linguistic studies No prepositions, genre, articles No natural written form (!!!): GLOSSE+feats

Meteo19-3

Interaction

Models Group

Rules-based Translation Architecture

DependencyGrammarfor Italian

Ontology

CCG for LIS

SpatialAllocationStrategy

Signary

Italian Sentence

AW-LIS

SpatialAllocationPlanner

Generator

Parser

SemanticInterpreter

AEW-LIS

AnimationInterpreter

Interaction

Models Group


GeneratorParserSemanticInterpreter

Interaction

Models Group



6Interaction

Models Group

A wide-coverage bottom-up rule-based dependency parser

Rules for: Chunking, Coordination, Verb-SubCat

Dependency relations

Morpho-syntactic

Syntactic-functional

Semantic

Turin University Parser

Interaction

Models Group

Chunking

Verb-SubCat


Paolo è davvero veloce


subjpredcompl

rmod


rmod

8Interaction

Models Group


Oggi ultimo giorno del mese di Giugno,

con valori di temperatura superiori alla media

Oggi ultimo giorno del mese di giugno , valori di mediaallasuperioritemperaturacon

rmod rmod rmod arg rmod arg

separator

rmod

arg rmod arg

rmod

arg arg

Interaction

Models Group



Interaction

Models Group

Semantic Interpreter

Frege compositional approach

Ontology based syntax-semantics interface

Sentence meaning is a complex semantic

network

Semantic objects (e.g. roles, time, space) are

encoded in the network

11Interaction

Models Group

££entity

££time-interval

££description

££it-geogr-area

££sea

££it-region

££it-adriatic-region

££day££evening

££geographic-area

££meteo-status-situation

££it-area-spec

£Adriatic

££weather-status-

description

£perturbato

££time-interval-description

££day-description

££deictic-day-

description

£today

£monday

££weather-status-

situation

££weather-event

££precipitation

££clouds££storm

££positive-eval-entity

££positive-day

££positive-evening

££evaluable-entity

= Description + Weather + World

12Interaction

Models Group

Computing Meaning by recursion

n

d1

di

dK... ...

... ... ...

13Interaction

Models Group

Ordinals

… ultimo giorno del mese …

ultimo[£last]

giorno[££day]

del mese[££month]

adjc+ordin-rmod rmod arg

14Interaction

Models Group

Ordinals in the ontology

££physical-entity ££part-of&part-smaller &part-bigger

££time-interval ££temporal-part-of

&temporal- part-smaller &temporal-

part-bigger

££day-month-part-of££day ££month

&day-in-daymonth

&month-in-daymonth

££ordinal-description

££sequenceable- entity

££entity-sequence&ord-described-item &reference-sequence

&ordinal- desc-selector ££ordinal-selector

£last

££day-sequence

15Interaction

Models Group

£last





part-bigger


&day-in-daymonth

&month-in-daymonth


££sequenceable-entity

££ordinal-selector


&ordinal- desc-selector

££day-sequence

ultimo[£last]

giorno[££day]

del mese[££month]


16Interaction

Models Group





part-bigger


&day-in-daymonth

&month-in-daymonth


££sequenceable- entity


&ordinal- desc-selector ££ordinal-selector

£last

££day-sequence

ultimo[£last]

giorno[££day]

del mese[££month]


17Interaction

Models Group

Ontological restriction

££day££month


&ord-described-item&reference-sequence

&ordinal- desc-selector

£last

⇝ultimo[£last]

giorno[££day]

del mese[££month]


18Interaction

Models Group

Semantic Interpreter

Oggi ultimo giorno del mese di giugno , valori di mediaallasuperioritemperaturacon

rmod rmod rmod arg rmod arg

separator

rmod

arg rmod arg

rmod

arg arg

Interaction

Models Group



Interaction

Models Group

Natural Language Generation

NLG systems use knowledge about language and the

application domain to automatically produce documents,

reports, explanations, help messages, and other kinds of texts

Interaction

Models Group

Natural Language Generation

NLG systems use knowledge about language and the

application domain to automatically produce documents,

reports, explanations, help messages, and other kinds of texts

DocumentPlanning

MicroPlanning

SurfaceRealization TEXT

● Lexicalization

● Aggregation

● Ref. Expression

● Word Order

● Functional Words

● Inflections

● Content Selection

Interaction

Models Group

NLG in ATLAS

LIS Dependency Tree

Semantic Network

MicroPlanning

SurfaceRealization

AbstractSyntax Tree

Interaction

Models Group

SentenceDesigner

OpenCCG

MicroPlanner● Homemade● LISP● Heuristics● Expert System● Taxonomy

Realizer● Take-away● Java● LIS-CCG (homemade)● AMMA-DB

ATLAS Generator

Interaction

Models Group

Sentence Designer

Algorithm:

1.Segmentation

Split the semantic network into singular messages

2.Lexicalization

Introduce quasi-lexical items

Introduce syntactic relations between items

3.SimplificationRemove non-necessary quasi-lexical items

Remove repetitions

Interaction

Models Group

Sentence Designer

LISA Expert System: ~50 rules

(defrule rule-TO-FORESEE-01 () (SEMANTIC-STATE (NAME ££TO-FORESEE-1) (ARG-1 ?X2)) (SEMANTIC-RELATION (NAME &FORESEEN) (ARG-1 ?X2) (ARG-2 ?X3)) => (assert (syntactic-relation (name SYN-OBJ) (arg-1 ?X2) (arg-2 ?X3))))

(defrule rule-COMPARISON-RELATION () (SEMANTIC-STATE (NAME ££COMPARISON-RELATION) (ARG-1 ?X12)) (SEMANTIC-RELATION (NAME &COMPAR-ARG1) (ARG-1 ?X12) (ARG-2 ?X11)) (SEMANTIC-RELATION (NAME &COMPAR-ARG2) (ARG-1 ?X12) (ARG-2 ?X14)) (SEMANTIC-RELATION (NAME &COMPAR-OP) (ARG-1 ?X12) (ARG-2 ?Y12)) => (assert (syntactic-relation (name SYN-SUBJ) (arg-1 ?y12) (arg-2 ?x11))) (assert (syntactic-relation (name SYN-OBJ) (arg-1 ?y12) (arg-2 ?x14))))

Interaction

Models Group

OpenCCGLIS-CCG : ~ 40 Syntactic Families, ~ 30 morphological Families

noun-II(nord-1533-1,it-northern-region,it-region,noun)...family TransV_III-A-s_nuvola-aumentare { entry: s<1> [E] \ np [X] : E:meteo-status-situation(* <SYN-SUBJ>X:clouds);};

family TransV_III-B { entry: s<1> [E PoS=verb] \ np [X] \ np [Y]: E:meteo-status-situation(* <SYN-SUBJ>X:evaluable-entity <SYN-OBJ>Y:evaluable-entity) ;};

family Adj-II { entry: n<~5> [X] \* n<5> [X] : X(<ATT>(P *)); entry: s <1>[X adj] \* np [Y] : X:weather-status-situation(*<SYN-SUBJ>Y:meteo-status-situation); entry: s <1>[X adj] \* np [Y] : X:weather-status-situation(*<SYN-SUBJ>Y:evaluable-entity); entry: s <1>[X adj] \* np <5> [X] : X(<SYN-RMOD-SEQPOS>(P *)); entry: s <~1> [Z adj] \* s <1>[Z] : Z:event( <COORD> (P *));}

Interaction

Models Group

SentenceDesigner

Interaction

Models Group

OpenCCG

superiore verb–3168-2

valore_valerenoun–80020- 2

temperaturanoun–2998-2

mediaadj–3072-2

RMODSUBJ OBJ

giornonoun–1052-2

mesenoun–1398-2

ogginoun–2669-2

ultimonoun–2747-1

RMOD

giugnonoun–3056-1

RMODSUBJ RMOD

Interaction

Models Group



Interaction

Models Group

Spatial Allocation Planner

Rule-based

Space

Iconic

Grammatical

Syntax

Phonology

Gravitation

Interaction Models Group

FUNCTION Split-space (…)

1. Trova dipendenti head in esame a cui si deve assegnare un sottospazio per caratteristiche strutturali della frase

2. Divide sottospazio di giorno tra i dipendenti trovati

3. Richiama Split-space sui dipendenti trovati

4. Assegna posizione all’head in esame

5. Trova dipendenti che rilocano sulla head genitore per caratteristiche strutturali della frase

Gestione spazio grammaticale


Split-space (giorno)1. Trova solo i dipendenti di “giorno” a cui si deve assegnare un

sottospazio per caratteristiche strutturali della frase: {oggi, mese}


Split-space (giorno)

Giorno

1. Trova solo i dipendenti di “giorno” a cui si deve assegnare un sottospazio per caratteristiche strutturali della frase: {oggi, mese}

2. Divide sottospazio di “giorno” tra i dipendenti trovati

Oggi MeseUltimo[-1 0 0 -0.5 0 0 0 0 0]

[0 0 0 +0.5 0 0 1 0 0]

[-1 0 0 0 0 0 1 0 0]

Giugno



2. Divide sottospazio di “giorno” tra i dipendenti trovati3. Richiama Split-space sui dipendenti trovati

Split-space (oggi) Split-space (mese)

Giorno

Oggi Mese

Ultimo[-1 0 0 -0.5 0 0 0 0 0]

[0 0 0 +0.5 0 0 1 0 0]

[-1 0 0 0 0 0 1 0 0]

Giugno




2. Divide sottospazio di “giorno” tra i dipendenti trovati3. Richiama Split-space sui dipendenti trovati4. Assegna posizione a ”giorno”

Rilocabile, non direzionale:(0.0 0.0 0.0)

[-1 0 0 0 0 0 1 0 0]

Split-space (oggi)

Split-space (mese)

Giorno

Oggi Mese

Ultimo[-1 0 0 -0.5 0 0 0 0 0] [0 0 0 +0.5 0 0 1 0 0]

Giugno




2. Divide sottospazio di “giorno” tra i dipendenti trovati3. Richiama Split-space sui dipendenti trovati4. Assegna posizione a “giorno”5. Esamina se ci sono dipendenti di “giorno” non ancora esaminati6. Li riloca sulla head “giorno”: {ultimo}

[-1 0 0 0 0 0 1 0 0]



[-1 0 0 0 0 0 1 0 0]

Split-space (oggi)

Split-space (mese)

Giorno

Oggi Mese

Ultimo[0 0 0 +0.5 0 0 1 0 0]

Giugno

[-1 0 0 -0.5 0 0 0 0 0]



AEW-LIS

Spatial Allocation Planner


Conclusioni

Sistema interlingua “classico” di machine translation Analisi profonda dell'italiano Generazione LIS Gestione grammaticale dello spazio

Ingegnerizzato Desktop demo WEB-service

Coverage and Quality Potenziamento delle basi di conoscenza Sistema di recovery ...

Interaction

Models Group

Coverage and Quality

The Welsh text says:I am not in the office at the moment. Send any work to be translated.

Interaction

Models Group

Grazie per l'attenzione.

Interaction

Models Group

WEBServer

Apache

POST /TURBTWebService/RULEBTranslator/01234 HTTP/1.1User-Agent: ATLAS-Orchestrator/1.0.0 (Linux)Host: localhost:8080Content-Type: text/xmlContent-length: ...

<?xml version="1.0"?> <text id="01234"> <sentence id="5" start_time="8.45" duration_time="1.425">Temporali a centro nord</sentence> <sentence id="6" start_time="9.875" duration_time="14.359">Sole a sud e al centro.</sentence></text>

ServletServer

Tomcat

RBT.java

TextID+

XML

Parser

Generator


FTPserver

4.1

4.3

4.45

1

2 3

HTTP/1.1 200 OK Content-Type: text/salContent-Length: ...

5 8.45 1.425 ftp://.../01234/atlas_aewlis_manual_movie_meteo_080701_030000_f1.xml6 9.875 14.359 ftp://.../01234/atlas_aewlis_manual_movie_meteo_080701_030000_f2.xml

7 6

8

SemanticInterpreter4.2

42Interaction

Models Group

Domani le nuvole sono in aumento al nord


Interaction

Models Group

SentenceDesigner

Esempio “Le nuvole sono in aumento al nord”

Interaction

Models Group

OpenCCG

nuvola_aumentare verb–2888-2

nuvolanoun–2667-2

nordnoun–1553-1

RMOD

SUBJ


Parametro input Descrizione parametro … GIORNO …

Sign id Id nel segnario ….

1053 …

Time Seq Posizione della frase … 4 …

Lemma Nome del lemma … Giorno …

Link Etichetta arco … nil

Arg-ref Direzione rilocazione … {} …

Dependents Lista dei dipendenti … {oggi, mese, giugno}

…

Reloc Rilocabilità … Yes …

Absolute position Posizione del segno non rilocabile

… Nil …

Dir Direzionalità … No …

Interaction

Models Group

NLG

DocumentPlanning

MicroPlanning

SurfaceRealization TEXT

● Lexicalization

● Aggregation

● Ref. Expression

● Word Order

● Functional Words

● Inflections

● Content Selection

like(Ale-4475,radio')

dislike(Ale-4475,tv')“Alex ama la radio

e Alex odia la TV”

amare

Alex radio

odiare

Alex TV

sbj obj

sbj obj

conj

Documents

Rules based interlingua translation in ATLASmazzei/papers/mazzei-CIRMA12-02.pdf · 2 Interaction Models Group The linguistics of LIS Several articolators: parallelism Spatial “organization”