INFERENCING ON LINGUISTICALLY BASED ZZ~IANTIC STRUCTUR~F 
Eva Ilaji~ov~, Milena Hn~tkov~ 
Department of Applied Mathematics 
Faculty of Mathematics and Physics 
Charles University 
~lalostransk4 n. 25 
118 O0 Praha I, Czechoslovakia 
ABSTRACT 
The paper characterizes natural lang- 
uage inferencing in the TIBAQ method of 
question-answering, focussing on three asp- 
ects: ~i) specification of the structures 
on which the inference rules operate, (ii) 
classification of the rules that have been 
formulated and implemented up to now, 
according to the kind of modification of 
the input structure ti~e rules invoke, an~ 
(iii) discussion of some points in which 
a proverly designed inference procedure 
may help the searc~ of the answer, and 
vice versa. 
I SPECIFICATION OF THE I:~PUT STRUCTURES 
FOR INFE~ENC I\[IG 
A. Outline of the TIBAQ ~lethod 
hhen the TIBA~ (~ext-and-~nference 
based ~nswering of ~uestions) project was 
~esigned, main emphasis was laid on the 
automatic build-up of the stock of know- 
ledge from the (non-~re-edited% input text. 
The experimental system based 6n this meth- od converses automatically the natural 
language input (both the questions and new 
Fieces of information, i.e. Czech sentences 
in their usual form) into the reDresentat- 
ions of n,eaning (tectogranmlatical repres- 
entations, TR's\]; these TR's serve as input 
structures for the inference procedure tilat 
enriches the set of TR's selected by the 
system itself as possibly relevant for an 
answer to the input question. In this en- 
riched set suitable TR's for direct and in- 
direct answers to the given question are 
retrieved, and then transfered by a synth- 
esis procedure into the output (surface) 
form if sentences (for an outline of the 
method as such, see Haji~ov~, 197~; 3aji~o- 
v~ and Sgall, 19~i; Sgall, 1982). 
B. :?hat Kind of Structure Inferences ~houl~i 
Be Based on 
To decide what kind of structures the 
inference procedure should operate, one has 
to take into account several criteria, some 
of which seemingly contradict each other: 
the structures should be as simple and 
transparent as possible, so that inferenc- 
ing can be perfor,ued in a well-defined way, 
and at the s~e ti~ue, these structures 
~hould be as"exDressive"as the natural lang- 
uage sentences are, not to lose any piece 
of information captured by the text. 
"~atural language has a major draw- 
back in its ambiguity: when a listener is 
told that the criticisl~ of the Polish del- 
egate was fully justified, one does not 
know (unless indicated by the context or 
situation) whether s/he should infer that 
soE~eone criticized the Polish delegate, or 
whether the Polish delegate criticized 
someone/something. On the other hand, there 
are means in natural language that are not 
preserved by most languages that logicians 
have used for drawing consequences, but 
that are critical for the latter to be 
drawn correctly: when a listener is told 
that ~ussiau is ~poken in SIBERIA, s/he 
draws conclusions partly different from 
those when s/he is told that in Siberla, 
RUS3IAN is spoken (caoitals denoting the 
intonation center); or, to borrow one of 
the widely discussed examples in linguist- 
ic writings, if one hears that Jonn called 
:ary a ~U~LICA~ and that then she insult- 
ed I~IM, one should infer that the sneaker 
considers "being a ~eoublican" an insult~ 
this is not the case, if the speaker said 
that then she I~SULTED hi~. 
These and similar considerations have 
led the authors of TIDAn to a stronc con- 
viction that the structures representing 
F.nowledge and serving as the base for in- 
ferencing in a q-uestion-answerin\[~ system 
with a natural language interface should 
be linguistically based: they should be de- 
prived of all ambiguities of natural lang- 
uage and at the same til:ie they should pre- 
serve all the information relevant for 
drawing conclusions that the natural lanci- 
uage sentences encompass. The exr.erir,~ental 
syster~, based on TI~A(:, which was carried 
out by the group of formal linauistics at 
Charles University, Prague \[implemented on 
~C 1040 c~:n?11ter, compatible with 15::4 360) 
works with representations of :~eaning (te- 
ctogrammatical representations, fR's2 
worked nut in the framework of functional 
generahive descrintion, or ~GD (for the 
linguistic background of this aopro~ch we 
refer to Sgall, 1964; ~;~all et ai.,1959; 
291 
Haji~ov~ and Jgall, 19:~O ). 
C. l ectocrar.~n~tical ~eor:_'sentations 
One of the b~sic tenets of VGD is 
the articulation of the sc'~antic relation, 
i.e. th_- relation bet.:een sound and r,~ean- 
ing, into a hierarchy o\[ levels, connected 
with the relativiz~tion o\[ the rel~tion of 
form" an~ 'function' a:~ known from the 
• ~;ritings of Prague &chool sc'nolar,3. This 
relativizatio~ .iakes it i~ossibl.., to di'~t- 
ingui.~h t::o levels of se:,tence structure: 
the level of surface syntax and that of 
t~e underlying or tectogramomatical struct- 
ure of sentences. 
As for a forn~al specification of the 
comolex unit oF- this lev,;l, that is the T!~., 
the \[)re~{ent version (see :'l.<ite\]-, Sgall 
an/ qgall, in }~ress) w~rks ::ith the notion 
of basic .\]e})endency structure (5DR) ,;hich 
is defined a~ \] structure over the aloha- 
bet A (corres\~onding to tne labels of no~l- 
es) and the set of sy~,~ools C (corres~ond- 
ing.to the labels of e'lqes). 'i'he set of 
5Dr- s is the sec of the tectogra:unatical 
representations of sentences containing 
no coordinated structures. 'fi%e ~-\]Dq s are 
generated by the gra:,~.~ar G = (V.,V ,5,q), 
where V = A ka C, A = {(a ~, ,~)\], a is in- T 
terpreted as a lexical unit, g is a vari- 
aole standing for t and f (contextually 
bound and non-bound, res~ectively\] an., ~ 
is internreted as a set of <Ira,~,~aten~es be- 
longing to a; C is a '~et of com~)lementat- 
ions (c ~ C, where c is an inter;or denot- 
ing a certain type of comi~ler.'entation, 
called a functor),C" lenotes the set 
\[<, >, %, >c~ for uvery C ~ C. 
%'o reuresent coordination, the form- 
al a~paratus for sentence generation is to 
be complemented by another aluhabet Q, 
..,here q ~ e is interpreted as tynes of 
coordination (conjun~ive, disjunctive, ad- 
versative, ..., ap}9osition) , .Ind by ~ ne',,! 
kinu of brackets denotinq the boundary of 
coordinated structures; .3"={\[ , ~, \] for 
every q ~ ~. The structures generated oy 
the grammar are then called comT~lex '.\]e:gend- 
ency str~ctures (CD~). 
Coming back to the notions of elem- 
entary and com~!ex units of the tecto- 
gra~c, atical level, we can say that the 
comnlex unit of the TR is the com?lex de- 
pendency structure as briefly characteriz- 
ed above, while the ele.nentary units are 
the symbol~ of ti~e shaoes a, g, c, q, the 
ele\[:ents of 3"~, and the ~arentheses. 'i'he 
lexical units a are conceiv..,<~ of as elem- 
entary rather th~n zom:_~lex, since for the 
time being we .1o not work with anv kind of 
lexical d~co.,;>osition. ,'.very le:~ical unit 
is assig~le\] V.n~: \[eat:/re conte.':tually 
bound" or 'non-bound" . The set of gra.'nmat- 
e~,~zs GR cov:_'rs a :;ide ranme o£ \[}henomena; 
they can be classifie,i into two groups. 
Grammatemes representing morphological 
rleanin C in the narrow sense are specific 
for different (semantic) word classes: for 
nouns, w~ distinguish grammatemes of num- 
ber an~ of delimitation (indefinite, def- 
inite, specifying):for adjectives and ad- 
verbs, grammate~es of degree, for verbs, 
we work with grammatemes of aspect (pro- 
cessual, complex, resultative), iterative- 
hess (iterative, non-iterative), tense 
(simultaneous, anterior, posterior), im- 
:nediateness (immediate, non--immediate), 
predicate modality (indicative, Dossibil- 
itive, necessitive, voluntative), assert- 
ive modality (affirmative, negative), and 
sentential modality (ieclarative, inter- 
rogative, imperative). The other group o~ 
gr~mmatemes is not - with some exceptions - 
%~ord-class specific and similarly as the 
set of the types of complementations is 
closely connected with the kinds of the 
dependency relations between the governor 
and the dependent node; thus the Locative 
is accom}~anied by one member of the set 
{in, on, under, between .... \]. 
%'he dependency relations are very 
rich and varied, and it is no wonder that 
there were many efforts to classify them. 
In FGD, a ,lear boundary is being made be- 
tween -~tJcipants (deep cases) and(free) 
modifications: participants are those com- 
!~lementations that can occur with the same 
verb token only once and that have to be 
sr~uci~ied for each verb (and similarly for 
each noun, adjective, etc.), while free 
modifications are those comolementations 
that may appear more than once with the 
same verb token and that can be listed for 
all the verbs once for all; for a ~ore 
detaile:i discussion and the use of operat- 
ional criteria for this classification, 
see ?anevov~ 1974; 1980; Eaji~ov~ and 
Panevov~, in press; Haji~ov~, 1977; 1983. 
Doth ;~articipants and modifications can 
be (semantically) optional or obligatory; 
~oth optional and obligatory oarticiDants 
are to be stated in the case frames of 
verbs, while modificatiors belong there 
only with such verbs with which they are 
obligatory. 
In the nresent version of FGD, the 
following five participants are disting- 
uished: actor/bearer, patient (objective), 
addressee, origin, an~ effect. The list 
o4 ~odifications is by far richer and more 
differentiated; a good starting ~oint for 
tills differentiation can be found in Czech 
gram~lars (esp. ~milauer, 1947). %'bus one 
can arrive at the following grou~?ings: 
(a) local: where, lirection, "~lhich ~:ray, 
(b) tem~3oral: when, since when, till when, 
how long, for ho%J long, luring, 
(c) causal: cause, condition real and un- 
rdal, aim, concession, consequence, 
(d) manner: manner, regard, extent, norm 
(criterion) , substitution, accompani- 
ment, means (instrument), difference, 
292 
benefit, comparison. 
In our discussion on types of complementat- 
ions we have up to now concentrated on comp- 
lementations of verbs; with Zhe FGD frame- 
work, however, all word classes have their 
frames. Specific to nouns (cf. Pi\[ha, 1980), 
there is the partitive participant (a glass 
of water) and the free modifications of 
appurtenance (a leg of the table\], of gen- 
eral relationship (nice weather), of ident- 
ity (the city of Prague\] and of a descript- 
ive attribute (golden Prague). 
To illustrate the structure of the re- 
presentation on the tectogrammatical level 
of FG;), we present in Fi~. $ a com21ex de- 
pendency structure of one of the readings of 
of the sentence "Before the ~ar began, 
Charles lived in P~AGUE and Jane in BFRLIN" 
(which it has in cormnon with "Before the be- 
ginning of the war, Charles lived in PRAGUE 
and Jane lived in rSERLIN ~) ;to make the 
graph easier to survey, we omit there the 
values of the gram.~atemes. 
lize t AND live t 
~arlest ~ Prague f ~ane t % Berlin f 
the linearized form: 
<~war t, {sing, def\])>Act (beglnt' {enter, compl, noniter, nonimmed, indic,lffirm, 
before\]\]>whe n (<(Charles t, {sing, det\]\].~Ac t (live t, {enter, compl, noniter, non- 
inmled, decler, indie,effirm\]\] whe~re(Pregue f, {sing,def,in\])> < ( Janet; {sing, 
def\] \] .~ct (liver' {enter, eompl, noniter,nonirmled, declar, indic, affirm)) where 
(Berlin , {sing, def, in)\] >SAND 
Fic.f. 1 
II INFERENCE TYPES 
A. \[q_eans of Implementation 
The inference rules are progranm~ed 
in 9-1anguage (Colmerauer, 1982), which 
provides rules that carry out transforr~at~ 
ions of oriented graphs. Since the struct- 
ures accepted by the rules must not con- 
tain complex labels, every complex sy~bol 
labelling a no~e in WR's has the form of a 
whole subtree in the Q-language notation 
(in a "~-tree). 
The set of TR's constitutes a seman- 
tic network, in which the individu~l T!{'s 
are connected into a com\[~lex whole hy 
means of pointers between tl\]e occurrences 
of lexical units and the corresponding 
entries in the lexicon. (Ouestions of dif- 
ferent objects of the same kind referred 
to in different TR's will be handled only 
in the future ex\]~eriments.) 
The following procedures eperate o~n 
TI{ "s : 
(i\] the extraction of (possibly\] relevant 
pieces of information from the stock 
of kno,:?led~e ; 
(ii\] the application of inference rules on 
the relevant }?ieces of information, 
(iii) the retrieval of the answer(s). 
'\]:he extraction of the so-calleE rs- 
levant .~J~c,~s of inforT~'.~tion is based on 
~:atcbing the. ~"~.-. of the input question with 
the lexicon and extracti~,~ khos¢: Y\[''<~ that 
intersect with the Tq o~ the give,: questi- 
on in at least one s~-.ecific 1 ..... ~c~_ v~lue 
(i.e. other than the"g~nerll %ztor, -~.,:. 
one, the copula, etc.\] ; the rezt cf the 
t r~es (s~\]~-~oscd to }:~. irreluvant for ~h.- 
,liven questJ.~n) are th?.n d~let_~,}.. 
The set of i".!:~,'~nt U'. "'-~ \[~{ c,-cr-ztmi 
U.:O~l k. V t\['~: rules o~ i~r-~r ~.",.cc. r f \[, rui.? 
of in.fer~=r, Ce l..;z bee-\] ?.-~-li? ~, '::th i:h,.:: 
293 
source TR as well as the derived TR consti- 
tute a part of the stock of knowledge a,,d 
a,, serve as source TR s for further pro- 
cessing. In order to avoid infinite cycles, 
the whole proced :r= oI inferencing is div- 
ided into several Q-systems (notice that 
rules within a single Q-system are applied 
s ~o,:g as the conditions for their applic- 
ation are fulfilled, i.e. there is no order- 
ing of the rules ). 
E. Types of Inference Rules 
I. Rules operatin@ on a single TR: 
(i) the structure of the tree is preserv- 
ed; the transformation concerns only (a) 
part(s) of the .o..p~ex symbol of some node 
of the CDS (i.e. label(s) of some node(s)in 
the Q-tree of the TR): 
(a) change of a grammateme: 
V exform-POssib (Ndevice-ACt) 
(X-Pat) ... == 
Vperform-lndic INdevice -Act) 
~X-Pat) ... 
A0te:, In our highly simplified and 
schematic shapes of the rules we quote 
only thos~ labels of the nodes that 
are relevlnt for the rule in question; 
the sign == stands for "rewrite as"; 
Ndevice stands for any no~n ,,i%h the 
sem~,~t£u f=ature of "device", Vperfor m 
for a verb with the semantic feature 
of action ve£b=, ~ossib and II~dic de- 
note the |raimnatemes of predicate mod- 
ality. 
E x.: An implifier can activate a Das,-- 
ive network to form an active analogue. 
== An amplifier activates a passive 
network to form an active anal~gue. 
(b) change of a functor (type of complement- 
ation): 
V-use (Ni-Pat) (Nj-Accomp) ... == 
V-use (Ni-Regard) (~j-Pat) ... 
E__{x.: Operational amplifier is used with 
negative feedback. == With operational 
a,uplifier negative feedback is used. 
Vperfor m LNi-Act ) (Nj-Pat) ... == 
Vperfor m (Dgen-ACt) (~li-Instr) (Nj-Pat).. 
E x.: Operational amplifiers perform 
mathematical operations == Mathematic- 
al operations are performed by means 
of operational amplifiers. 
Note: Act, Pat, Instr, Accomp, Reg- 
ard stand for the functors of Actor, 
Patient, Instrument, Accompaniment 
and Regard, respectively; D denot- 
es a general participant, gen 
~g~ change of the lexical part of the comp- 
lex symbol accompanied by a change of 
some gramnlateme or functor: 
V.-Possibl ((few)Ni) (V-use(Nk-ACc°mpneg) 
...)... ==Vi-Necess ((most)Ni) (V-use 
( Nk-ACcompposit)...)... 
Ex.: With few hlgh-performance oper- 
a-~ional amplifiers it is possible to 
maintain a linear relationship betw- 
een input and output without employ- 
ing negative feedback.== Hith most 
&i. it is necessary to maintain ... 
employing negative feedback. 
(ii) a whole subtree is replaced by another 
subtree: 
Ex.: a negative feedback == a negat- 
ive feedback circuit 
(iii) extraction of a subtree to create an 
independent TR: 
- relative clause in the topic part 
of the TR 
V i (Vj-Gener-L(...))... == 
Vj-Gener-L (...) 
Ex.: An operational amplifier, which 
a--~tivates a passive network to form 
an active analogue, is an unusually 
versatile device. == An operational 
amplifier activates a passive net- 
work to form an active analogue. 
Note: L stands for the grammateme 
"contextually bound", R for "non- 
-bound", Gener for the functor of 
general relationship. 
- causal clause in TR's with affir- 
mative modality 
Vi-Affirm (Vj-Cause (...))... == 
vj t...) 
EX.: Since an operational amplifier 
i-~ designed to perform mathematical 
operations, such basic operations 
as ... are performed readily. == 
An operational amplifier is designed 
to perform mathematical operations. 
- deletion of an attribute in the 
focus part of a TR 
V i (Nj-R (X-Gener-R)) 
V i (Nj-R) ... 
i 6 0 
294 
E_~x.: Operational amplifiers are used 
as regulators ... to minimize load- 
ing of reference ~\]iod~ vermittlng 
full exploitation of the diode's 
precision temperature stability. == 
Operational amplifiers are used as 
regulators ... to minimize loading 
of reference diodes. 
(iv) the transformation gives rise to two 
TR s 
distributivity of conjunction and 
disjunction (under certain condit- 
ions: e.g. for the distributivity 
of disjunction to hold, the gramm- 
ateme of Indic with the main verb 
is replaced by the grammateme of 
Possib) 
E x.: Operational amplifiers are used 
in active filter networks to provide 
gain and frequency selectivity. == 
Operatinal amplifiers are used in 
active filter networks to provide 
gain. Operational amplifiBrs are 
used in active networks to provide 
frequency selectivity. 
2. Rules operatin 9 (simultaneously) on two 
TR s 
left-hand side of the rule refers 
to two TR's) 
- conjoining of TR's with the same 
Actor 
Ex.: An operational amplifier act- 
ivates a passive network to form an 
active analogue. An operational 
amplifier performs mathematical op- 
erations. =~ An operational amplif- 
ier activates .... and performs .... 
use of definitions: the rule is 
triggered by the presence of an as- 
sertion of the form "X is called Y" 
and substitutes all occurrences of 
the lex~cal labels X in all TR's by 
the lexical label Y 
III EFFECTIVE LINKS BETWEEN INFERENCING 
AND ANSWER RETRIEVAL 
A. The Retrieval Procedure 
Th~ retrieval of an answer in the en- 
riched set of assertions (TR's) is perform- 
ed in the following stepsl 
(a) first it is checked whether the 
lexical value of the root of the TR is id- 
entical with that of the TR of the question; 
if the question has the form "What is per- 
formed (done, carried out) by X?", then 
the TR from the enriched set must include 
an action verb as a label of its root; 
(b) the path leading from the root to the 
wh-word is checked (yes-no questions are. 
excluded from the first stage of our exper- 
iments); the rightmost path in the relevant 
TR must coincide with the wh-path in its 
lexical labels, contextual--boundness, 
grammatemes and functors (with some poss- 
ible deviations determined by conditions 
of substitutability: Singular - Plural, 
Manner - Accompaniment, etc.); the wh-word 
in the question must be matched by ~-lex- 
ical unit of the potential answer, where 
the latter may be further expanded; 
(c~ if also the rest of the two compared 
TR s meet the conditions of identity or 
substitutability, the relevant TR is mark- 
ed as a full answer to the given question; 
if this is not the case but at least one 
of the nodes depending on a node included 
in the wh-path meets these conditions, then 
the relevant TR is marked as an indirect 
(partial) answer. 
B. Towards an Effective Application of 
Inference Rules 
In the course of the experiments it 
soon became clear that even with a very 
limited number of inference rules the mem- 
ory space was rapidly exceeded. It was 
then necessary to find a way how to achie- 
ve an effective application of the inferen- 
ce rules and at the same time not to re- 
strict the choice of relevant answers. 
Among other things, the following issues 
should be taken into consideration: 
The rules substituting subtrees for 
subtrees are used rather frequently, as 
well as those substituting only a label 
of one node (in the Q-tree, i.e. one ele- 
ment of the complex symbol in the CDS), 
preserving the overall structure of the 
tree untouched. These rules operate in 
both directions, so that it appears as use- 
ful to use in such cases a similar strat- 
egy as with synonymous expressions, i.e. 
to decide on a single representation both 
in the TR of the question and that includ- 
ed in the stock of knowledge; this would 
lead to an important decrease of the num- 
ber of TR's that undergo further inference 
transformations. 
Only those TR's are selected for the 
final steps of the retrieval of the answer 
(see point (a) in III.A) that coincide 
with the TR of the question in the lexical 
label of the root, i.e. the main verb. If 
the inference rules are ordered in such a 
way that the rules changing an element of 
the label of the root are applied before 
the rest of the rules, then the first 
step of the retrieval procedure can be 
made before the application of other in- 
ference rules. This again leads to a con- 
295 
siderable reduction of the number of TR's 
on which the rest of the inference rules 
are applied; only such TR's are left in the 
stock of relevant TR's 
(i)that agree with the TR of the question 
in the label of the root (its ~exical lab- 
el may belong to superordinated or subord- 
inated lexioal values: device - amplifier, 
etc.), 
(ii) that i~clude the lexical label of 
the root oC the question in some other 
place than at the root of the relevant 
TR, 
(iii) if the question has the form "Which 
N " (i.e the wh-n~de depends on its • o- , o 
head in the relation of general relation- 
ship), then also those TR's are preserved 
that contain an identical N node (noun) 
on any level of the tree. 
The use of Q-language brings about 
one difficulty, namely that the rules 
have to be formulated for each level for 
the tree separately. It is possible to 
avoid this complication by a simple tempor- 
ary rearrangement of the Q-tree, which re- 
sults in a tree in which all nodes with 
lexical labels are on the same level; the 
rules for a substitution of the lexical 
labels can be then applied in one step, 
after which the tree is "returned" into 
its original shape. 
These and similar considerations have 
led us to the following ordering of the in- 
dividual steps of the inference and retrie- 
val procedure: 
I. application of rules transforming 
the input structure to such an extent that 
the lexlcal label of the root of the tree 
is not preserved in the tree of a potent- 
ial answer; 
2. a partial retrieval of the answer 
according to the root of the tree; 
3. application of rules substituting 
other labels pertinent to the root of the 
tree; 
4. partial retrieval of the answer 
according to the root of the tree; 
5. application of inference rules 
operatinq on a single tree; 
6. application of inference rules 
operating on two trees; 
7. the steps (b) and (c) from the 
retrieval of the answer (see III.A above). 
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297 
