American Journal of Computational Linguistics 
Microfiche 26 
JUNCTION GRAMMAR 
AS A BASE FOR 
NATURAL LANGUAGE PROCESS I NG 
Brigham Young University 
Provo, Utah 
Copyright 1975 btj the Association for Computational Linguistics 
Abstract 
Junction Grammar, a model of language structure developed by 
Eldon Lytle, is being used to define the interlingua for a machine- 
assisted translation project. Junction Grammar representations 
(called junction trees) consist of word sense information inter- 
related by junctions, which contribute syntactic and semantic in- 
formation. The first step of the current translation system is 
interactive analysis. During this step, the program interacts with 
the human operator to resolve ambiguities and then produces a junc- 
tion tree representation of the meaning of the input text. The 
second and third steps of the translation process are automatic 
transfer and synthesis into one or more target languages. For 
each target language the transfer step makes adjustments on each 
junction tree, if needed, before sending it to the synthesis pro- 
gram for that language. This translation system is currently 
under development at Brigham Young University in Provo, Utah. Pre- 
sent lexicons for English analysis and Spanish, German, French, and 
Portuguese synthesis contain about 10,000 word senses each. 
TABLE OF CONTENTS 
Overview 
Introduction to Junction Grammar--by Eldon Lytle 
Dennis Packard 
A. Basic relative modifiers 
B. Noun complements 
C. Other modifiers as relative statements 
Implementation 
A. Analysis--by Daryl Gibb 
B. Transfer--by Alan Melby 
C. Synthesis--by Floyd Billings 
IV. Conclusion 
Page 
LIST OF SYMBOLS 
N Noun 
PN Predicate with a noun nucleus 
SN Predication with a noun nucleus 
A Adjective or adverb 
PA Predicate with an adjective or adverb nucleus 
SA Predication with an adjective or adverb nucleus 
V Ve rb 
PV Predicate with a verb nucleus 
SV Predication with a verb nucleus 
P Preposition 
PP Predicate with a preposition nucleus 
SP Predication with a preposition nucleus 
E Empty node 
JG Junction Grammar 
Adj Adjective 
Adv Adverb 
PAj Adjective predicate 
PA Adverb predicate 
v 
PX Any predicate 
SX Any predication 
I. An overview. 
Assuming that semantics must be taken into account in a trans- 
lation system, there are at least two major classes of intermed- 
iate representations to choose from for use in a translation sys- 
tem. One class of repre.sentations is non-linguistic. In this 
class syntax is ignored and use is made of various conceptual 
units and relations (e. g. Schankl s conceptual dependency) . Ano- 
ther class of representations is linguistic. In this class syntax 
and semantics are combined into a syntacto-semantic representation 
which is connected to surface structure in a fairly direct fashion 
(e.g. Montague grammars [I] and Junction Grammar [2]). 
We have chosen to test Junction Grammar as the interlingua 
for a machine-assisted translation project. The basic concepts of 
this model of language were developed by Eldon Lytle in the late 
196OVs, but, as with many theories, it has been under continual 
development ever since. 
For subject-verb-object sentences, junction trees look much 
like the familiar phrase markers. Let us then preview the steps 
of the Junction Grammar translation process using an extremely 
simple sentence. 
Given the English surface string, "He needs it", English 
analysis would produce the junction tree : 
Note that the tree has an order independent of the surface word 
order of the input text. The function m(x) produces the word 
sense or sememe of its argument. The values of this function 
have been implemented as positive integers called semantic in- 
dices. The plus signs under the categories PV (verbal predicate) 
and SV (verbal sentence) stand for adjunction, one of the basic 
types 
of junction recognized by Junction Grammar. 
Suppose we want to synthesize this junction tree into French. 
Transfer would adjust this tree because French expresses the mean- 
ing of 'needt as 'have need oft. Then French synthesis would per- 
form lexical selection and ordering to produce the string "Ila 
besoin de ca", or "11 en a besoinn. 
The following chapters will discuss junction trees in more 
detail and then explain how the analysis, transfer, and synthesis 
steps are currently implemented. 
11. Introduction to Junction Grammar. 
A. Basic Relative Modifiers. 
Consider the following sentence : 
(1) Every monkey that swallows that, gets indigestion. 
Utilizing a modification junction * called subjunction, consider 
the following as a junction marker for (1) : (Consider the term- 
inal words as names of sememes and consider quantifiers to be of 
a noun- type category) . 
E ve ry 
n 
gets indigestion 
monkey 
n 
that 
A 
V- N 
swallows that 
The problem with the above junction marker is that it is not 
clear which that is the relative pronoun. Following Montague (see also 
Partie [3] and Gabbay [4]) we could subscript the subjunction 
operation and the appropriate that with respect to which the 
modification occurs: 
Every /". gets indigestion 
N *I SV 
I 
monkey 
A 
V N 
swallows that 
The above tree would then be lexicalized as sentenc (1). If we 
had subscripted just the other - that then the mark~r would be lex- 
icalized not as sentence (1) but rather as: 
(1A) Every monkey that that swallows gets indigestion. 
A readable way of handling such clauses is the method used 
in Junction Grammar: The proform with respect to which the modi- 
fication occurs is directly joined to the noun being modified. 
Thus the structure takes the place of subscripts. 
Sentence (1) Sentence (1A) 
N A + + 
A 
PV 
/". sv 
N * N V+ N A 6 v+N A 
Every ASV,gets indigestion N V N + PV gets indi- 
N*N+pv Every mhatfi gestion 
monkey that 
N* N+V 
V + N monkey that swallows 
swallows that 
The reader will notice that the above diagrams are not normal bin- 
ary trees, but we call them trees or intersecting trees because 
they can be drawn as sets of cross-referenced trees. 
The follawing tree illustrates the notational variations of 
(a) drawing intersecting trees as cross-referenced sets of normal, 
trees, (b) drawing the junction symbol between the brothers (sub- 
ordinate nodes) instead of next to the father (superordinate) node, 
and (c) optionally leaving out the junction symbol when it is 
adjunction (+) . 
A 
N*N 
fi 
V + N V N 
$hit 
Every gets indigestidn 
swallows that 
N * N, 
monkey 
1 
It is interesting to note that one simple method of generating 
in a context-free way such intersecting trees as those used in 
Junction Grammar is to employ context-sensitive rules as node 
admissability conditions. This method is essentially in harmony 
with McCawleyV s [S] proposal. For example, the rule A+BC allows 
the well-formed structure A Further, the rule 
n 
B C 
A--BC/F - G is construed as saying that a subtree with A immediate- 
ly dominating the sequence BC is a well-formed subtree provided 
that elsewhere in the tree a node F immediately precedes A and A 
immediately precedes a node G. Thus, as an example, the following 
tree is well-formed from the rules indicated. 
S --, DAE 
D-F/ B 
E --t GH~ 
A- BC/F- 
- 
Though the tree is well-formed if the rules are node admissability 
conditions, FBCGH cannot be derived from this gramma? in a stan- 
dard rewrite derivation way. 
If such production rules were to be used, their form would be: 
W --3 XY 
Such production rules are type 0 and not type 1. 
Bm Noun Complements. 
It is instructive to contrast the above Junction Grammar 
treatment of relative clauses with its treatment of noun comple- 
ments. 
It would seem that there are serious theoretical problems 
associated with the phrase structure rules *NP?rNP S and 
NP-N S of Transformation Grammar [6] . 
RELATIVE CLAUSE RULE : NP+NP S 
COMPLEMENT RULE: NP-N S 
(2) The embarrassing fact that John was able to learn frus- 
trated his adversaries. 
n 
NP 
fact fact 
A 
which John was John was able 
able to learn to learn 
TG Treatment of Noun Complements and Relative Clauses. 
These rules propose to account for restrictive relative clauses 
and noun complements, respectively, both embedding an entire sen- 
tence to a nominal antecedent, encompassing both constituents with 
brackets labelled NP. It seems clear that the two structures in 
question are in fact related, i.e. in some sense similar, but not 
in the way suggested by the P-rules proposed to generate them. 
Specifically, in each case there seems to be an overlapping of 
constituents in the main clause with those in the subordinate 
clause: In the relative clause, an NP of the main clause coincides 
referentially with an NP of the dependent clause ; in the comple- 
ment, a noun, or potentially, a noun phrase, of the main clause 
is equated referentially with the entire dependent clause. Thus 
sentence (2) is ambiguous over the relative clause and the com- 
plement readings. (Notice that one can replace that with which 
for the relative clause reading but not for the complement read- 
ing.] There is nothing in the P-rule formulation to make this 
overlapping of constituents explicit, however. Hence, a mechanism 
for checking the coreference of NP1s is required so that the rela- 
tive clause transformation could apply to sentences embedded by 
NP-NP S and produce the appropriate relative pronoun. It is not 
clear, however, whether this mechanism is supposed to establish a 
coreference relation between the head N and the complement S in 
NP -+N S, since no T-rule seems to depend upon such a check. More- 
over, there is no clear justification for using N rather than NP 
to the right of tlie arrow in the complement rule, since the head 
of a complement can have articles and modifiers too. 
Still more serious is what appears to be implied by the rela- 
tive clause rule. Namely, the entire clause is bracketed with a 
nominal category (NP), suggesting that it, like the complement, 
is functioning in its entirety as a nominal constituent. The 
structural symmetry of these two rules results in a false general- 
ization (the illusion that both clauses were nominalized) while 
failing to make explicit the generality which actually exists and 
is semantically crucial (the referential overlap between consti- 
tuents in the main and dependent clauses). What is needed are 
structural representations which reflect the overlapping of con- 
stituents without violating what seem to be the correct categori- 
zations. 
The Junction Grammar solution is as follows: 
N 
sv 
An 
N * N 
N A * SV (that) 
fact which fact 
Relative Clause Noun Complement 
In the case of the relative clause, the intersection occurred on 
categorially homogeneous nodes (on Nls) , whereas in the comple- 
ment structure the intersection occurred on heterogeneous nodes 
(N /S) so that the entire subordinate clause intersected with an 
NP of the main clause. 
Subjunction can thus be seen to be of two basic types--full- 
subjunctions, as in noun complements, and interjunctions, as in 
relative clauses. In full-sub junction the modifying constituent 
node is ~omp~letely subjoined, e.g. number five, or the boy John as 
N * N 
boy John 
or the fact John came as 
N * SV (that) 
fact 
John came 
On the other hand, in interjunction the modifying constituent is 
just interjoined, e.g. the book (that) I read as 
sv 
N 
N I 
the book that 
+ v 
read 
or John failed. which sur~rised me as 
which A 
V + N 
- - 
John failed 
surprised me 
In both cases, however, the nodes which intersect referentially 
are directly joined to each other. 
The schematic expression for full-subjunction is Z+X*Y. 
The following are representative members of this schernq: 
N'N * SV 
Adj- Adj * PV 
(the fact) John came surprised us. 
N [the fact John came) 
n 
fact 
A 
John came 
Sneaking Russian is difficult. 
(Speaking Russian) 
N ft PV 
ing 
n 
speak Russian 
The speaking of Russian is difficult. 
N (speaking) 
n 
- ing speak 
Children such that they hate candy are rare. 
Adj (such that they hate candy) 
0". 
Adj * sv (that) 
such 
n 
they hate candy 
The boy readfng the book is John. 
eading the book) 
Adj A PV 
- ing 
read the book 
C. Other Modifiers as Relative Statements. 
Returning now to the discussion of relative modifiers, we 
continue our description of interjunction, which, as the reader 
will recall, entails intersecting trees corresponding to the fol- 
lowing schema : 
Basic relative modifiers are defined to be relative clauses 
of which the modifying node is of noun category, the relative mark- 
er for such clauses being in some cases null (e.g. the boy I saw 
was crying), or such words as which, who -9 and that. Non-basic 
relative modifiers are defined to be all others which entail in- 
terjunction. Some of these relatives have not in some cases been 
recognized in the literature as relative constructions at all, 
but were identified during the elaboration of junction theory by 
deducing from the interjunction schema specific possibilities not 
hitherto noted by observation of random data. This deduction was 
done in terms of the constituent categories extant in the junction 
grammar system of diagramming at that time. Sentences (3-8) below 
illustrate some of the non-basic relative modifiers in question. 
Notice that one might search available data a long time before 
finding an instance of some of the types exemplified, as each 
would require a special context. Yet, any grammar of English 
would be incomplete without them. The fact that some rules are 
used less in no way invalidates them; in a number of cases, de- 
ductions which at first seemed most ridiculous were found to have 
instances that were perfectly acceptable. 
The perspective deriving 
from this experience suggests that any grammar which is based on 
rules arrived at inductively, i.e. simply set down in a list as 
available data suggests them, will be incomplete at best, and 
most probably not motivated by any significant generalizations. 
Diagrams for sentences (5) - (8) will be supplied in the 
discussion of non-verb cored relatives. 
(3) Verb phrase. I hate war, like you. 
V N 
hate war 
(4) Verb. I peeled the peach, like you the apple. 
ach 
peeled like 
A 
the apple 
(5) Prepositional Phrase. My kite is on the roof, like your 
ball. 
(63 Preposition. Fred is above a store, like you were a 
bakery. 
(7) Adjective. He is like [such as) Bill is. 
(8) Noun. A soldier, as I am, seeks adventure. 
Junction Grammar claims that some statements occur without a 
verb in the relative modifier. One way to represent such sentences 
in a natural way is to allow non-verb cored statements as follows: 
SA SN 
N + PP N + PA 'N + PN 
A A 
John Bill I Jack 
P + N A 
I 
N 
at school old fireman 
We will indicate that a predicator (e.g. adjective or adverb) 
becomes a predicate without a direct object either by the notation 
, where E - means empty slot. 
Preposition cored: My kite is on the roof, like your ball. 
Fred is above a store, like you a bakery. 
(5) (6) SV 
N + PV 
n 
N + PV 
my kite I Fred I 
A 
v * A 
is M v * PP 
PP * PP + N 
is A 
A 
N 
P+N like A A 
On A 
a store 
the roof 
P you N+-. / PP 
above P \ 
like 
a b ake ry 
(7) Ad cored: He is like Bill was 
V' * PA Bill 
Ad E 
like 
(8) Noun cored: A soldier, as I am, seeks adventure. 
sv 
N A PV 
N + PV 
v 
n + 
N 
seeks adventure 
N * N + E 
A 
as 
a soldier 
Now consider the following two sentences: 
(9) A delegate from Canada proposed a compromise. 
(10) The old man answered the question. 
The modification occurring in these sentences can be expanded out 
to relative clauses and represented as follows: 
a M 
N*N PV 
delegate who I 
v 
a compromise 
A 
v * PP 
is 0". 
(was) P N 
from Canada 
(10) 
A 
PV 
N * SV 
- 
2L-. 
v 
the answered 
N *N PV 
man who I 
A 
V * PA 
is 
(was 1 
I 
A 
old 
However, these sentences can also be represented with rela- 
tive modifiers by employing the non-verb cored statements (below) : 
a 
SP proposed a com- 
N*N \ promise 
delegate $4 
P N 
from Canada 
the 
answered the 
N*N 
PA question 
man 0 I 
A 
old 
One benefit of considering modifiers such as these to entail 
entire statements is that various types of ambiguity occurring 
with them can be explained as types of ambiguity also character- 
istic of clausal statements. For instance, consider the follow- 
ing ambiguaus sentence : 
(11) John clumsily stepped on the snail. 
sv 
N SA 
John h 
K 
* PV PA 
0 A 
clumsily 
stepped on the snail 
The ambiguity in question hinges upon whether or not we con- 
sider the relative modification to be restrictive or non-restrictive, 
a contrast which in junction grammar is expressed by subcategorizing 
the sub junction operation (*) . 
Note also that semantic complexities which occur with the non- 
clausal modifiers of sentences (9) and (10) can also occur with 
basic relative clauses. For example, if John is tall (as a person) 
and John is a basketball player, we cannot conclude that John is 
a tall basketball player. And similarly, if John is an expert and 
John recommends Gillette, we cannot necessarily conclude that John 
is an expert who recommends Gilletfe (the reason being that he 
might be a blimp expert who just recommends Gillette products to 
his friends, while saying that he is an expert who recommends 
Gillette implies that he is an expert on the types of products 
that Gillette produces) . 
Further, if modifiers such as those in (9) and (10) are con- 
sidered to be relative statements, 
it explains our intuition that 
obviously, surprisingly, etc., are usually modifiers at statement 
level. For example, a natural way, it would seem, to represent 
charitable man is as follows: 
- 
N * A 
man charitable 
Similarly, for The man in need asked for help, man in need would 
be represented as follows: 
N * PP 
man A 
P N 
in need 
But if this were done, then obviously charitable man and man - 
obviously in need would, it seems, have to be represented as 
follows : 
A 
N Jt 
ma. A 
PP A 
A obviously 
P N 
in need 
N 
n 
N * A 
man 
A * A 
charitable obviously 
But this represents the reading in which obviously is taken 
as a manner adverb, and it seems that because we have not represent- 
ed the modification as a relative clause, we are prevented from 
using obviously as a sentence level modifier. 
Now consider the following sentence with its Junction Grammar 
(12) 
The obviously rich boy bought the Mercedes. 
SA SA 
N S A 
the &* * PA 
N ~t N PA 1 
boy 0 I A 
A obvious ly 
rich 
bought the Mercedes 
By expanding the rich relative clause to include a verb, the 
sentence might be lexicalized as: 
The boy who obviously was rich, bought the Mercedes. 
But also, obviously can be used as an adverb of manner. Taken in 
this way (12) would mean that the ostentatiously rich boy bought 
the Mercedes. As such, it would be diagrammed as follows: 
N c--- 
n 
N N SA 
the 
* 
A 
bought the Mercedes 
N -PA N s A 
boy 8 
PA *PA ft 
I 
A 
I 
A 
rich obviously 
Finally, consider these two relative modifier sentences: 
John runs as slowly as Bill walks. 
sv 
n 
N + PV SA 
John 
PV * PV PA 
I I Bill Nq 
v 
runs A SA Pv 
slowly 
M 
UA + 
PV * PV 
pl I 
v 
A * A walks 
as as 
Bill brought as many books as John bought paintings. 
sv 
n 
N + PV 
Bill fi 
V + N 
brought- 
* 
sv 
N 
2, books N + PV 
N * N John A 
N- + V 
I~ brought 
- 
N * N * N 
as as paintings 
It should be pointed out that the above discussion has omit- 
ted major areas of Junction Grammar, such as specializations of 
sub junction which indicate flow of information in "compilingu a 
junction tree, conjunction, and the function and application of 
lexical rules to junction trees. 
111. Implementation. 
A. Analysis. 
The analysis step must accept natural language input and 
produce the appropriate junction tree for each segment of text 
(normally, but not necessarily, a segment is a sentence) , accord- 
ing to the context of that segment. 
Two types of ambiguity can be distinguished: word sense 
ambiguity and syntactic ambiguity. Without some logical proces- 
sing, an utterance such as "John bought some ink for the pen" is 
word sense ambiguous as to pen, between the writing utensil and 
the enclosure senses. Also, the sentence "The boy flipped the 
coin by the book," is syntactically ambiguous as to the point of 
intersection between the prepositional phrase and the rest of the 
sentence. 
Several English analysis systems (e. g. W. Woods, Y. Wilks , 
T . Winograd, etc .) have seen considerable success in resolving 
word sense and syntactic ambiguities automatically on texts that 
stay within some restricted vocabulary or context. However, no 
one has attempted to apply such principles to a large scale system 
(10,000 to 20,000-word lexicons) which can analyze a wide variety 
of structures and types of texts. At present, it is not known 
whether any system is expandable to such a degree or, even if it 
were, how many years would be needed to complete such a project 
and how much it would cost to run. Clearly, research and develop- 
ment in the area of automatic analysis should be continued. 
In the meantime, however, work is needed op the processing 
that must follow automatic analysis to form a zomplete translation 
sys tem. 
Therefore, our research group has decided to develop a machine- 
assisted translation system consisting of interactive analysis 
(where the human operator resolves difficult ambiguities via his 
video screen) followed by automatic transfer-synthesis into multi - 
ple target languages with junction trees as the interlingua. This 
configuration, which has also been proposed by Kay [7] , has some 
attractive features. Supposa that the Junction Grammar trapsfer- 
synthesis system produces acceptable translations of real-world 
text from the output of the interactive analyzer. The analyzer 
could then be replaced by a more automatic version without dis- 
turbing the rest of the system. 
On the other hand, if the whole system fails, we will not 
have invested nearly as much emfort as if we had tried to develop 
a large-scale automatic .analysis to junction trees. 
In addition, during the period of development and testlng, 
counters can easily be set up to keep statistics on what inter- 
actions are most common and therefore should be given priority 
in a more automatic version or during the testing phase of auta- 
matic routings to see if they disambiguate the same way the human 
does. 
Finally, regardless of the particular version of analysis 
used, the system divides the effort expended in doing the analysis 
by the number of target languages being translated into from the 
same junction tree. 
Now let us describe the current five -phase implementation 
of interactive analysis. The first phase performs limited mor- 
pheme splitting (e.g. possessives and contractions). As each 
word is identified it is matched against an index-sequential dic- 
tionary stored on disk. If there is more than one word sense 
associated with the word then several definitions are chained to 
the entry. These several meanings appear on the video screen and 
the human is asked to choose the meaning for this particular con- 
text. When a choice is entered, the information associated with 
that particular use of the word (or phrase of which it is the key- 
word) is retrieved from the dictionary. The dictionary contains 
semantic indices, categories, and binary features. Information 
specific to the source language and information considered to be 
language independent are represented in these features. This in- 
formation is put into a two dimensional array (Reference table) and 
will be available during the other phases. If a word is not in 
the dictionary, the person monitoring has the option of picking a 
synonym, or passing the word through untranslated as he would a 
proper noun, signaling only the category of the word (noun, verb, 
adjective, adve,rb, preposition). It is by this interactive process 
that we temporarily solve the word sense ambiguity problem. 
The second phase of analysis, called ffPHRASER", logically seg- 
ments the reference table (sentence) into "phrasesff containing a 
maximum of one noun each. The first word of the sentence starts 
the first phrase. Thereafter, a noun or comma ends a phrase, and 
the succeeding phrase begins with the next word. The senfence 
"The boy in the car ate a very good hamburger while driving down 
the street" is symbolically segmented as (The boy) (in the car) 
(ate a very good hamburger) (while driving down the street) . 
During the segmenting operation PHRASER assigns a global reference 
category to each element (word) of the reference table. The main 
purpose of PHRASER is to divide the sentence into "phrasesl1 or 
segments which are individually processed by the infix generat- 
tion routines as separate units, thus simplifying their task. 
The third phase of analysis is the syntactic resolver and in- 
fix builder (Figure 1). This phase produces an infix representa- 
tion equivalent to normal junction trees. For example, N1$(P+N2) 
is equivalent to The basic philo- 
N1 
* N* PP 
A 
P n- 
N2 
sophy of this routine is to process phrases generated in PHRASER 
by calculating their internal structure, then placing them in 
their proper structural position in the total sentence. This is 
facilitated by the introduction of what we call "order-rules. 11 
The Order-Rule 
As discussed earlier, a simple sentence can be represented in 
a tree diagram as SV 
N 
- 
+ PV 
subject 
v 
n 
+ N 
verb ob j ect 
which can be stated in an infix notation as (N+(V+N)), which will 
TYPSET (TYPE) INFIX ROUTINE 
Start 
a 
I Initialize Glo- I 
1 bal Variables I 
I Invoke Ordrrul 1) 
1 
Seg + 0 
Nounc* 0 
I INFX 00 
1 INFX ~ 01 
I Nouns 
~~ --- 
1 0011 I V Topic 
I INFX 03 
1 0100 I Verbs I INFX (14 I 
0111 I Adverbs I INFX 07 
1 I I 
0 10 1 
0110 
I 1000 I Prep Topic I INFX 08 I 
1 prepositions 1 INFX 09 
Adj Topic 
Adjectives 
I INFX 10 I 
INFX 05 
INFX 06 
1011 Conjunction INFX 11 
1100 Articles INFX 12 
1101 Adv Topic 
? 
Seg = C 
Seg + 1 
1 
Nounc Nounc+l 
YES 
, Put pointer to 
noun in nounlist 
(nounc) 
Figure 1. 
PHASE I1 I MAINLINE INFIXER. 
/use Typset 
(Seg) - for calling 
sequence (see tab1 
be called a clause order-rule. Notice that the order rule has 
the terminal nodes (N + (V + N)) as well as 
sub j verb ob j 
the father node markings (parentheses). 
( 
+ 
( 
+ 
pre- pre - 
I 1 
post post 
sentence predicate predicate sentence 
This gives seven slots of layers for the actual entries of the 
order-rule. An order-rule has the order portion, i .em (N+(V+N)) , 
and the entries that fill the slots of the order: subject 
verb 
object 
pre -predicate 
pre -sentence 
post predicate 
post sentence 
There are three basic constraints on order-rules . First, 
they can never represent discontinuous word order. The discon- 
tinuous orders (V, N subject, N object and N object, N subject, 
verb) cannot be represented directly but must use variant order 
rules. The second basic constraint in the use of order rules is 
that when order rules are interjoined, the first terminal node 
element of the subordinant order-rule must be the intersect node. 
For example: "I saw the boy that likes youv has two order rules. 
must be first terminal 
node of the subordinate order-rule 
I 
I saw boy-(N + (V + N)) 
that likes  you+(^ + (V + N)) 
I sawboy likes you 
When these are combined, the following interjunction will be cre- 
ated: (N + (V + (N $ (V + N)))) The third constraint is that 
all subordinate order rules must indicate their antecedent nodes 
in some other order-rule. 
To review, phase three routines build order-rule representa- 
tions; phase four inserts the slot or layers up into the order- 
rule, then it conflates all the order-rules into one linear infix 
string. This linear infix string cross references the information 
table produced in phase one (cross-referencing is achieved via 
doubly- linked- list processing) . 
The reader will recall f~om Section I that Junction Grammar 
relative clause modification involves an interj unction and phrasal 
modifiers (prepositional phrases, adjectives, and adverbs) have the 
same basic form as the clause. 
SP 
- 
X PP 
0 
P+N 
in barn 
v + N SP 
saw - 
N * N +PP 
boy n 
P+N 
in barn 
Notice the interjunction: 
u 
N*N+ PP 
boy A 
P+N 
in barn 
In infix notation this is: (N + (V + N $ (P +N))) 
I saw boy in barn 
providing of course that boy is what in barn modifies. 
An adjec- 
tive or adverb has the tree structure: SA 
n 
X + PA 
n 
A + E 
Adjectives normally pre-pose their head in English, so big boy j 
(A + E) $ N. "I saw the big boy in the unsightly barn" is 
big boy 
represented in infix notation as 
(N + (V + (A + E) $ N $ (P + (A + E) $ N))). 
I saw big boy in unsightly barn 
The order-rule with consitutent values for this is the following: 
(N + (V + N)) 
N 
V Note that we create new order- 
(A+E) $N$ (P+ (A+E) $N) 
rules only when we have new 
0 verb core predicates. 
B 
B 
B 
Phase three programs can generally identify the subject, pre- 
dicate, and, if present, indirect objects of clauses, both inde- 
pendent and subordinate. There are, however, certain areas of 
processing that present difficulties for the program. A simple 
sentence like, "I threw the ball in the roomw illustrates such 
problems because the program does not know without context whether 
in the room identifies which ball it was that I threw, the direction 
of its path (motion), or where I and the ball were during the ac- 
tion. As stated before, the key to this problem is the context. 
As a matter of fact, almost every prepositional phrase is ambigu- 
ous in the computer environment. For this reason, we have the 
program query the person monitoring the program and ask, 
I (1) threw (2) ball (3) in (4) room (5) 
"What does 'prep-object1 modify?", in this case, "What does in- 
room1 modify?" If the answer is "3" [ball) then the infix would be 
(N + CY + N S (P + Nl)) 
I threw ball in room 
and it would identify which ball was thrown. If PV 2 is entered, 
it is interpreted to modify the predicate (throw + ball) ; then 
the infix would be (N + (V + N) $ (P + N)) and implies 
I threw ball in room 
that the phrase tells where the action took place. If "ZU(throw) 
is entered, the infix would be (N +(V $ (P + N) + N)) and 
the phrase modifies the verb. Note that in addition to identify- 
ing the ambiguity, we can signal the intended meaning and represent 
any of those meanings in a systematic manner. 
Another "conte~tual~~ problem in English is the identification 
of the antecedents for relative pronouns. "I saw the boy in the 
car that the girl loves .If The question, of course, is: "What 
does the girl love--the boy or the car?" This is solved by having 
the program ask "Does 'that1 refer to X?If where X is popped off 
of a push-down stack of previously encountered nouns. The relatives 
that, who, whom, and which all invoke new order-rules. The result 
- - 
of this interaction is to point the subordinate order-rule to the 
antecedent identified by the human s response. 
(N + CV + N) I 
N ('1 
V(s aw) V(1oves) 
w 
(boy) N $ (P + N) (in car) Topic N 
Combining t-he prepositional phrase and antecedent problems, we pro- 
duce a sentence like this: 
I saw 
the big 
red 
car 
by the church on which the 
birds ate 
12 3 4 5 6 7 8 9 10 11 12 13 14 
the bread. 
15 16 
The program will ask what by the church modifies--we will answer 
"6" (car). Then it will ask "Does which refer to church?" This 
is really asking "Did the birds eat the bread on the church?" 
If 
we say "No" then it will ask, "Does which refer to car?" "Yes." 
Next the program asks "What does 'on-which1 modify?" This is 
somewhat difficult because we have a prepositional phrase whose 
antecedent is in one clause yet the phrase modifies something in 
another. In the example the prepositional phrase modifies the 
predicate 'birds ate the bread' by telling where the action hap- 
pened. 
N (11 no, - N (birds) 
V (saw) V (ate) 
(A+E) $ (A+E) $N$ (P+N~ 
N (bread) 
big red car by chtlrch 
0 (N + P) $ pre PV 
topic (on) 
Passive constructions may have an ambiguous element in them: 
*'The cake was eaten by the dog.'1 The question is: did the dog do 
the eating or does the prepositional phrase tell where the cake 
was eaten. Interaction indicates which reading should be repre- 
sented. 
Complement constructions can be identified in this same way 
(through interactio-n) . "It surprised Aunt Jane that the girl loves 
the car." In this instance the program asks "Does 'that' refer 
During the layer insert phase the pre PV will be inserted to 
the left of the predicate parenthesis, making the topic the first 
node encountered. 
to Aunt Jane?" Reply "No." "Does 'that1 refer to it?" This time 
the reply is "YesCu where the "C" indicates that the subordinate 
clause is the complement of - it. 
This structure is not interjoined 
but fully sub j oined . 
PV 
A 
N * S(that) V N 
#--. 
It A surprised Aunt Jane 
N PV 
girl A 
V N 
loves car 
The infix notation for the above is : (N * (N + (V + N)) +(V + N)) . 
It girl loves car surp. A.Jane 
The order rule representat ion : 
(N + (V + N)) (N + (V + N)) 
N (it)* N (girl) 
V (surprised) 
N (Aunt Jane) 
V (loves) 
N (car) 
0 
* (The operation of full 
sub j unct ion) 
0 
0 
A variation of the complement response is: "He came after we ate 
dinner .'I The program asks "What does after-we ' modify?" This is 
erroneous, and is so indicated by answering instead what the true 
prepositional phrase "after-it (that) ff modifies and putting a "Ctt 
for complement at the end of the reply: "PV 2C." The "C" will re- 
move the "we" as object of the preposition and replace it with a 
noun 
tt it tl A new order-rule is then invoked, pointing to the noun 
llit.w The underlying structure is represented "after it that we 
ate dinner" PP 
I\ 
P+N 
after /\ 
N * SV (that) 
it A 
N 
we A 
V N 
ate dinner 
or, in infix: (N + (V + N) $ (P + N * (N + (v+ N)))). 
The details of the other interactive situations will be omit- 
ted. Interaction is necessary for the adjectival like as in "1 saw 
a man with a dog like you." The question is, "What is like you, 
the man or the dog?" So the program asks, RDoes 'like' refer to 
dog?" If the response is "no," then the program asks, "Does 'liket 
refer to man?" 
Participles and gerunds are very ambiguous. For example, "I 
like chewing gum." Is it "1 like to chew gumv or "1 like chewing- 
gum"? Again, "John's hobby is shocking me ." Is the "shocking" a 
progressing verb or is it a gerund? At this point we have the pro- 
gram ask, "What type of participle is X ing"; the replies can be: 
N Adj for the chewing-gum type, use of an ing form 
V for the progressive verb 
Adj X (where X* is"the segment modified) for adjectival 
participles 
Adv X (where X is the segment modified) for adverbial 
participles 
Of course, the infinitive form also is often ambiguous. For 
example, "I like to buy candym is much different from "He sent me 
to buy candy." There are several answers to the program's question, 
"What type of infinitive is 'to X '?I' where X is the verb. 
Other questions that the programs are designed to ask all 
have two points in common: first, they are stimulated when the 
surface string does not map into the underlying semantic string 
on a one-to-one basis; second, when the decision is made by the 
human as to its use and the reply given to the program, the pro- 
cessing continues in standard existing programs and no ad hoc 
routines are needed. 
The output of phase three is a series of order-rules. Each 
order-rule has the form: 
(N + (V + N)) order specifier 
N (subject) 
V (verb) 
N (object) 
Pre -predicate modifiers 
Pre-sentence modifiers 
Post predicate modifiers 
Post sentence modifiers 
layers or slots 
for elements 
If a sentence in the input stream should have more than one clause, 
there will be at least one order-rule for each: 
Unfortunately, I plainly saw the little boy in the big red car that 
1 2 3 4 5 6 7 8 9 19 11 12 13 14 
the girl loves. 
15 16 17 18 
(A+E) $ N $ (P + (A+EI $ (A+E) $N) 14 X (topic) 
4 
(A+E) $ 0 
1 
(A+E) $ 0 
Phase four will make one continuous infix string of these 
order-rules. First, the rules are checked for those situations 
where both of the father nodes of an interjunction are available 
for further junctions. If such a situation exists, then the 
operations involved are marked. Next, all the layers are insert- 
ed into the order-rule, giving the following: 
Notice that the second rule still points to the antecedent in the 
first order rule. Next all order-rules are conflated into one, 
by performing the necessary interjunctions between order-rules . 
The above infix string is now ready for phase five. 
Phase five converts the infix notation into postfix notation 
to be used as input to the transfer-synthesis steps. 
As a summary of this section, we will follow a sample sentence 
through the five phases of analysis. 
Figure 2 shows the processing involved to disambiguate the re- 
ference for some of the words in the input string* In this sen- 
tence there were several potentially ambiguous sequences (See Figure 
3) "TPUTV1 identifies the computer programs question of the operator 
and "TGET" shows the ~eply. Most of these are self-explanatory. 
This interplay between man and program makes it possible for the 
computer to build a structure depicting its syntax and semantics 
for the given context, provided of course that the human responds 
correctly to the questions. The output of phase three is several 
order rules which are merged into one infix structure (Figure 4). 
THE(I) SWIMMING(21 COACH(3) LIVING(4) IN(5) C$ALIFoRNIA(6) BOUGHT (7) 
THE(8) OLD(9) HOUSE(10) ON(11) THE (12) HILL(13) THAT(14) RESEMBLES(15) 
THE (16) CHURCH (1 7) THAT (18) YOUR(19) GRANDFATHER(20) ATTENDED (2 1) 
(22) WHICH(23) SURPRISED(24) THE(25) PEOPLE(26) IN(27) THE(28) 
  OWN(^^) . (30) 
ENTER MEANING FOR: COACH (3) 
1 N T$HE COACH ENCOURAGED THE TEAM TO DO BETTER. (PERSON THAT TRAINS, 
TUTORS) 
2 N H$E RODE IN THE QUAINT OLD COACH TO THE STATION. (VEHICLE) 
3 V M$Y FATHER WILL COACH THE BASEBALL TEAM. (ACT AS A COACH) 
ENTER MEANING FOR: LIVING (4) 
1 N H$E EARNED HIS LIVING BY REPAIRING REFRIGERATORS. (SUSTENANCE) 
2 V I$ LIVE IN THE U$NITED S$TATES OF A$MERIcA. (DWELL) 
3 V S$HE CHOOSES TO LIVE THE PRINCIPLES OF THE GOSPEL. (OBEY ,KEEP) 
ENTER MEANING FOR: IN(5) 
1 A ***PARTICLE OF VERB + PARTICLE COMBINATION*** 
2 P T$HE SHOE WAS IN THE KITCHEN. (CONCRETE LOCATION) 
3 P T$HERE SHOULD BE LOVE IN THE FAMILY. (ABSTRACT LOCATION) 
4 P T$HE SENATOR SPOKE IN HONOR OF THE MAYOR'S ACCOMPLISHMENTS. 
5 P L$ETtS GO IN THE HOUSE. (DESTINATION ; INTO) 
6 P I$ DID THE EXERCISE IN TEN MINUTES. (WITHIN OR DURING A PERIOD 
OF TIME) 
7 P W$E MUST SAY IT IN WORDS AND ACTIONS. (INDICATE MEANS) 
8 P DUMMY PREPOSITION 
ENTER MEANING FOR: THAT(14) 
1 N I$ WOULD LIKE TO READ THAT BOOK. (ARTICLE--FAR DEMONSTRATIVE, 
SINGULAR) 
2 N T.$HAT IS THE MOST INTERESTING MOVIE I$ 'VE SEEN. (PRONOUN--3P, 
S , DEM ,NOM) 
3 N I$ HAVE NEVER SEEN THAT BEFORE. (PRONOUN--3P ,S ,DEM,OBJ) 
4 N TSHE FIRST PERSON THAT CALLS WILL WIN A PRIZE. (TOPIC) 
Figure 2 
ENTER MEANING FOR: CHURCH (17) 
1 N H$E HAS BEEN A MEMBER OF THAT CHURCH FOR SEVERAL YEARS. 
(OR- 
GANIZATION) 
2 N W$E SAW THE CHURCH THAT WAS JUST BUILT. (BUILDING) 
3 N T$HE C$HURCH IS CONTINUING TO GROW THROUGHOUT A$SIA. (L$D$S$ 
c $HURCH) 
Figure 2 (cont .) . 
PHASE 3 
*TPUT* 
*TPUT* 
*TPUT* 
*TPUTh 
*TPUT* 
*TPUT* 
*TGET* 
*TPUT* 
*TGET* 
*TPUT* 
*TGET* 
*TPUT* 
*TGET* 
*TPUT * 
*TGET* 
*TPUT* 
*TGET* 
*TPUT* 
*TGET* 
*TPUT* 
*TGET* 
*TPUT* 
*TGET* 
SENTENCE 3 
THE (1) SWIMMING(2) COACH(3) LIVING(4) IN(5) C$ALIFORNIA(6) 
BOUGHT(7) THE(8) OLD(9) HOUSE (10) ON(11) THE(12) HILL(13) 
THAT(14) RESEMBLES (15) THE (16) CHURCH (17) THAT (18) YOUR(19) 
GRANDFATHERCZO) ATTENDED(Z1) , (22) WHICH (23) SURPRISED (24) 
THE(25) PEOPLE(26) IN(27) THE(28) TOWN(29) . (30) 
WHAT TYPE OF PARTICIPLE IS SWIMMING(Z)? 
NADJ 
WHAT TYPE OF PARTICIPLE IS LIVING(4)? 
ADJ3 
WHAT DOES IN(5) - C$ALIFORNIA(~) MODIFY? 
4 
WHAT DOES ON(11) - HILL(12) MODIFY? 
10 
DOES THAT(14) REPRESENT HILL(13)? 
NO 
DOES THAT(14) REPRESENT HOUSE(lO)? 
YES 
DOES THAT (18) REPRESENT CHURCH (17) ? 
YES 
WHAT DOES WHICH(23) REFER TO? 
SV7 
WHAT DOES IN(27) - TOWN(29) MODIFY? 
26 
Figure 3. 
PHASE 4 SENTENCE 3 Output of phase three (input to phase 4) 
*** LEVEL 1 *** ANTECEDENT 0 FROM LEVEL 0 ORDER TYPE 1 
ORDER NODE #( (N*(V+N)) N$ A+E - V+ 
REF 1 31 2 32 3 33 7 
ORDER NODE (A+E) N$(P+N)) )/I 
REF 9 10 11 13 
*** LEVEL 2 *** ANTECEDENT 33 FROM LEVEL 1 ORDER TYPE 5 
ORDER NODE ( * ( V $ ( P + N ) 4- E ) ) /I 
REF 2 4 5 6 
~lc-tc* LEVEL 3 *JC* ANTECEDENT 10 FROM LEVEL 1 ORDER TYPE 1 
ORDER NODE #(N- (V3N))I 
REF 3 14 15 17 
*** LEVEL 4 *** ANTECEDENT 17 FROM LEVEL 1 ORDER TYPE 2 
ORDER NODE I!( (N-V)4( (A*N)+E) N ) /I 
REF 4 18 21 34 19 20 
*** LEVEL 5 *** ANTECEDENT 0 FROM LEVEL 1 ORDER TYPE 1 
ORDER NODE INN- (V+N$(P+N) )# 
REF 5 23 24 26 27 29 
Figure 4. 
B. Transfer 
Withih the context of Junction Grammar, a transfer grammar 
from a source language S to a target language T is an algorithm 
which inputs a junction tree from an analysis grammar of S and 
outputs the junction tree, with any needed adjustments, to a 
synthesis grammar of T. 
In the present implementation, we are developing transfer 
grammars from English into Spanish, German, French, and Portu- 
guese (abbreviated SSP, GER, FRN, and POR) . Figure I is a gen- 
eral diagram of the flow of information in the transfer system. 
4 
English b Transfer Pre- 
Analysis 
, paration Phase 
i 
J-Trees and lists 
, 
of transfers to 
Junction Rule perform 
Key Files for 
SPN ,FRN ,GER,POR 
Transfer Language 
t 
Interpreter Phase 
, 
A 
Semantic Index Transferred J-Tre 
Key Files for 
SPN,FRN ,GER,POR 
A d Conversion to 
Synthesis Repre- 
sentation and 
Synthesis 
Preparation Phase 
. 
b 
- 
Transfer Pro- 
gram File for 
SPN , FRN , GER, POR 
J-Trees 
adjusted 
to POR 
SPN FRN GE R POR 
SYN SYN SYN SYN 
m.- 
Figure 1. 
In the preparation phase, each junction tree is scanned for 
junction rules and semantic indices which stimulate transfers go- 
ing into a given language. This scanning is accomplished by con- 
sulting files which associate key junction rules and semantic 
indices with transfer numbers. The list of transfers is then 
associated with the tree. 
After the preparation phase, the transfer language interpre - 
ter phase (Phase two) executes those transfer programs whose num- 
bers have been recorded. Of course, as the transfer executes, it 
may check the context and decide not to change the junction tree. 
All the transfer programs are in one file so that several lang- 
uages can share common algorithms. The third phase of transfer 
converts the adjusted junction trees to synthesis representation, 
adding to them features from the target language lexicons. None 
of the three phases of transfer contain any language-specific 
coding; only the files are language-specific. Thus, a transfer 
grammar can be made machine executable simply by loading records 
into the key files and the transfer program files. 
Transfer programs are written in a linguistic programming 
language called Transfer Language (TL) (see [8]). The TL loader 
compiles the programs into a pseudo-machine language which is stored 
in the transfer program file and is interpreted at execution time 
in the second phase of transfer. Before describing TL in detail, 
we present an entry from a simple transfer grammar. Figure 2 
shows the necessary input to the TL loader and the semantic key 
file loader. This figure shows the form of entries loaded under 
the current transfer system implemented on an IBM 360. 
//GRAMMAR JOB (. . .) 
/ ILOADPGM EXEC TRNTLSLD 
"THI S PROCEDURE LOADS TRANSFER PROGRAMS" 
19 
"SIMPLE TRANSFER FROM "X MISSES Y" TO "Y MISSES TO Xu 
*E. G. "HE MISSES HER" TO ELLE LUI MANQUE" 
*THIS TRANSFER INSERTS INTO THE JUNCTION TREE THE INDIRECT OBJECT 
*PREPOSITION, WHICH HAS BEEN ASSIGNED SEMANTIC INDEX lf8086 
LET =2 BE Y{A(A(=l))) 
LET =3 BE Y(A(=l)) 
REPLACE =2 WITH =3 
REPLACE =3 WITH E 
JOIN =I $ (Pl0086 + =3) 
*I 
/)LOADKEY EXEC TRNTKLD , LANG=FRN *THIS PROCEDURE LOADS KEYS* 
//*WHEN GOING INTO FRENCH, STIMULATE TRANSFER 19 FROM SEMEME r9172.0fffl 
//*ANY OTHER VERB WHICH CHANGES FROM "X VERB Y" TO "Y VERB TO X" COULD 
//*ALSO KEY INTO TRANSFER 19 
FRN05916. fl0g 19 
I/ 
Figure 2. 
A simple transfer program and its key. 
The details of TL needed to fully understand Figure 2 will be 
explained later. For now, let us consider the simple linguistic 
principle behind the example. When translating "1 miss my brotherff 
into French, brother becomes the syntactic subject, giving "man 
frere me manque," which, taken literally back into English, is 
"my brother (to) me misses." In terms of verb orientation, the 
English verb to miss is normally used as a "subject is interested 
person" verb while in French the sense wish someone were here 
is a "subject is interesting person" verb. Note, however, that the 
other sense of to not hit is a "subject is interested" verb in 
French, the same as English, i.e. "1 threw the ball but I missed 
him" is translated "J1ai lance la balle mais je 1' ai manque, 
f I 
and receives a different semantic index in analysis. Therefore, 
it does not stimulate a transfer as does t-he first word sense. 
In Figure 2, the desired adjustment from "X misses Y1' to 
IrY misses Xfl is accomplished by a transfer program which has been 
numbered 19. In transfer 19, the first two statements (LET ...; 
LET.. .) set pointers to crucial nodes of the junction tree and 
the next three statements (REPLACE ...; REPLACE ...; JOIN ...) make 
the direct object into the subject and the subject into the in- 
direct object. The transfer will be executed at the appropriate 
time because at the bottom of Figure 2 we associate the semantic 
index 5916 (to miss someone, i.e. wish he were there) with trans- 
fer 19 going into French (FRN@5916.@@g 19). The qualifier 
attached to the semantic index is a sememic refinement code used 
to make very fine distinctions if needed. Work on this aspect 
of our lexicon is in its formative stages and will be reported 
later. 
With the preliminary example of Figure 2 in mind, let us now 
examine transfer language as a programming language. 
GENERAL STRUCTURE OF TL 
TL is a free-format, block-structure, list-processing lang- 
uage similar in general form to PL/I or ALGOL. Internal to a 
transfer program are DO-END blocks and external are subroutine 
blocks. Computer scientists may be interested to know that TL 
contains no GOTO-type statement. The central data structure is a 
junction tree, represented as one doubly-linked list whose inter- 
nal structure is logically a set of intersecting binary trees in 
postfix notation. Of course, TL shields the user from the details 
of linked list manipulation through the use of high-level commands. 
The user data types are: (1) address variables (e.g. '=4') 
which point to nodes of the junction tree, (2) condition variables 
(e.g. T4') which can be true-false or contain integer values (such 
as semantic indices) , (3) parameters (e.g. 'P2') which contain op- 
tional information associated with a sememe key in addition to the 
number of the transfer program to invoke, and (4) integer constants. 
As previously mentioned, a transfer grammar is a set of keys 
and transfer programs. The transffer programs are not ordered re- 
lative to each other; .their execution is stimulated by the presence 
of a key sememe or junction rule in a junction tree. When a given 
top-level transfer (i.e. one that is invoked directly by sememe or 
rule, not invoked by another transfer) is executed, add-ress var- 
iable one (1 is pointed at the sememe or junction rule which 
stimulated the transfer program. Normally, a top-level transfer 
progrdm will begin with some statements which derive (from the ad- 
dress in =1) the addresses of some other crucial nodes in the junc- 
tion tree. Then, except in the simplest cases, this context will 
be tested and appropriate manipulations, if any, will be performed 
on the junction tree. If errors are detected during the execution 
of one of the transfers on a list, control is normally returned to 
the transfer supervisor, which continues processing the sentence by 
invoking the next transfer on the list. However, the user may 
choose to set up "ON UNITS" which intercept error conditions and 
invoke some specified transfer designed for error recovery. 
TRANSFER LANGUAGE STATEMENT TYPES 
Let us now consider the most important statement types in 
TL, beginning with assignment, which is accomplished with the 
LET statement. 
LET. - One form of LET is used to move around the junction 
tree. For example, if =3 is set to the address of the verb of 
a clause, we can point =5 to the direct object, skipping over any 
verb-level moiiifiers, by the statement: LET =5 BE Y(A(=3)). 
The built-in fanction A moves to the next level of adjunction 
(e.g. from a V to its PV) and Y moves down the tree to the right 
brother 
Other built-in functions include X [which moves down to the 
left brother) , L (which moves up to the father) , B (which moves 
down successive sons, or left brothers, until reaching a terminal 
node), S (which moves from the father of a point of intersection 
in a ranking tree to the corresponding father node in the subor- 
dinate tree) , R (which moves from subordinate trees to ranking 
trees), and C (which moves to the SV governing the start node). 
In the example LET =5 BE Y(A(=3)) , the movement is relative to an 
initial node pointed to by -3. In this initial address slog we 
can also use the symbol H, which stands for the topmost node of 
the highest ranking subtree of the junction tree, or '=' , which 
stands for the address of the most recently created node in the 
tree. 
Another form of LET assigns values to condition variables. 
When an address variable is assigned to a condition variable 
(e.g. 
LET C7 BE =S) , the condition variable receives the semantic index 
of the node pointed to by the address variable. Also available 
in TL is an easily expandable set of built-in functions to perform 
such tasks as indicating the category of a node, checking for the 
presence or absence of certain semantic features on a node, or 
reporting on the structural context of a node. For example, LET 
C7 BE INODCAT(=8) sets C7 to a number indicating the category of 
the node pointed to by =8. Other special forms of the LET state- 
ment set features and the special pointer , which indicates 
the top of the junction tree. 
JOIN. The JOIN statement allows the user to insert any de- 
sired structure into the junction tree. The dollar sign ($) is 
used to indicate an interjunction; otherwise, the symbols used 
in the JOIN statement are a straightforward infix representation 
of a segment of a tree. Thus, if we assume the fragmented tree: 
and execute the statement JOIN =4 $ (Plfl267<12> + =5) 9 we 
obtain the tree: 
whose P node contains the semantic index 10267 and the semantic 
featu~e number 12. Also, the /=9 indicates that the primary 
result of the last performed operation should be pointed to by =9 
UNJOIN. If we then execute UNJOIN =9 on the junction tree 
just obtained, we u~do the effect of the interjunction, obtaining 
the trees : 
REPLACE. If, using the same tree, we execute the statements 
LET =7 BE X(=4), LET =8 BE Y(=4), and REPLACE =4 WITH =2, we set 
some pointers and switch subject and the object, obtaining: 
Finally, if we replace the left conjoined part of the subject with 
nothing, i.e. by the statement REPLACE =7 WITH g, then we obtain: 
Note that the unneeded operation and label node are deleted auto- 
matically. 
IF. The IF statement with optional ELSE clause is simply 
- 
borrowed from PL/I, but one form of the IF statement deserves com- 
ment. An expandable set of KEYWORDS is available, each of which 
indicates that a built-in function is to be called and its value 
compared against a predefined constant associated with the KEYWORD. 
For example, IF =14 ISA VERB--- is equivalent (using C49 as a work 
variable] to the two statements : LET C49 BE INODCAT(=3) 
IF C49 EQ 5 THEN--- 
since 5 is the number which stands for the category V. 
SKIP and HALT. SKIP exits from the current transfer program, 
while HALT returns control to the supervisor, which moves on to 
the next top-level transfer. 
TRANSFER. The statement TRANSFER 11 is simply a call to t-rans- 
fer number 11 as a subroutine, while the statement TRANSFER C4 is a 
call to that transfer program whose number is in C4 at the time 
that statement is interpreted. There sqems to be no need for an 
algebraic do-loop in transfer but a while-loop is useful. For ex- 
ample, TRANSFER 12 WHILE C2 executes transfer number 12 repeatedly 
until some context Lest within transfer 12, or some other transfer 
called by it, sets condition variable 2 to false (Lea to zero). 
ON. The statement ON CONDITION(N0-LABEL) TRANSFER 1 sets 
- 
up an ON UNIT so that if at any time during transfer on the current 
node an attempt is made to move up from a node without a label, 
transfer 1 will be executed. If an error occurs in transfer 1, 
control is then passed to the supervisor which processes the 
next top-level transfer. 
A few final details should be mentioned. When a transfer 
is called, it executes to its end or until a SKIP statement is 
executed. Comments can be scattered through a transfer program 
by enclosing them by t/* ----- */' or beginning the record with I*' 
Figure 3 summarizes the selected statement types we have dis- 
cussed. 
- LET =4 BE Y(A(z2)) 
- LET =9 BE H 
- LET =11 BE = 
- LET C7 BE 4 
- LET C7 BE ~5 
- LET C7 BE C2 
- LEX C7 BE INODCAT (=8) 
- LET C7 BE P4 
- LET FEATURES (=9) BE <-SINGULAR, +MASS) 
- LET H BE =9 
- JOIN =4 $ (PI8267 12 + =5) 159 
- UNJOIN =12 
- REPLACE =lO WITH =2 
- REPLACE =3 WITH @ 
- IF C9 IS TRUE THEN stmt 
- IF C2 EQ 12 THEN DO stmtl stmt2 . . . END 
- IF =14 ISA VERB THEN stmt ELSE stmt 
- TRANSFER 11 
- TRANSFER C2 
- TRANSFER 12 WHILE C2 
- SKIP 
- HALT 
- ON CONDITION(14) TRANSFER 2 
Figure 3. 
Sample Transfer Language Statements. 
SAMPLE TRANSFERS 
Having discussed the major statement types in TL, let us con- 
sider a few specific transfers. This will be but an indication of 
what is done in transfer, but later reports are expected to present 
substantial transfer grammars between language pairs. 
Languages frequently differ in their preferred wnceptualiza- 
tion of a given action. For example, English prefers eat supper to 
sup, while French prefers souper to prendre le souper. Similarly, 
to watch television has become the single sememe fernsehen in Ger- 
man. Alternatively, a verb and non-verbal participle [9] may cor- 
respond to a single verb (e.g. make happy goes to alegrarse in 
Spanish). Several examples of such patterns are listed in Figure 
All these correspondences are handled in TL by writing one 
simple transfer for each general pattern and then loading the 
appropriate keys. For example, the first case (V + N+V + E) 
could be treated by keying on the verb in each case and loading as 
parameters with the key the crucial object or objects. This will 
cause collapse and the composite sememe to be formed. In order to 
make this and the subsequent examples easier to follow we will use 
the English words themselves instead of their semantic indices. 
Thus, we might load the following keys: 
FRN EAT 12 PI. = LUNCH, JOIN DEJEUNER =11 
P2 = SUPPER, JOIN SOUPER =12 
SPN GIVE 12 P1 = THANKS, JOIN AGRRDECER =I1 
GER TAKE 12 P1 = WALK, JOIN SPAZIERGEHEN =11 
P2 = BATH, JOIN BADEN =12 
GER WRITE 12 P1 = POEM, JOIN DICHTEN =I1 
to eat lunch ---r dejeuner (FRN) 
to eat supper * souper [FRN) 
to eat breakfast desagunar (SPN) 
to give thanks - agradecer (SPN) 
50 take a walk- spaziergehen (GER) 
to take a bath baden (GER) 
to have an accident 4 verunglticken (GER) 
to write a poem- dichten (GER) 
to point rnontrer du doigt (FRN) 
to clap- battre des mains (FRN) 
V$ (A* (A+E) +E) +E--+V+E 
to make sad * attrister (FRN) 
to make angry -+ encolorizarse (SPN) 
to stare at Xj regarder X fixQment (FRN) 
to turn the pages of a book + fculletcr un liver (FRN) 
Figure 4. 
Some multisememe-single sememe associations. 
and treat them all with the following transfer: 
12 
*SET =2 TO THE OBJECT 
LET =2 BE Y(L(=l)) 
*SEE IF THE OBJECT CORRESPONDS TO ONE OF THE PARAMETERS 
IF (=2,=3) ISA MATCH THEN DO 
REPLACE =1 WITH =3 
REPLACE 32 WITH E 
END 
"I 
This transfer is straightforward except for the statement "IF (=2 ,=3) 
ISA MATCH.. . ." Here it is assumed MATCH has been defined as a key- 
word so that this statement is equivalent to the pair of statements: 
LET C49 BE SMATCH (=2,=3) 
IF C49 IS TRUE . . . 
The built-in function SMATCH checks the parameters of the stimu- 
lating key against the index of the node pointed to by the first 
argument (52) . It either returns FALSE (no match) or TRUE and 
points the second argument (-3) to the proper composite node made 
available through the auxiliary JOIN parameters of the transfer 
key. 
In this simple transfer, any modifiers on the object would 
cancel the transfer by blocking a match (e.g. eat a big supper 4 
manger un grand souper), but if the transfer writer so desired, he 
could easily UNJOIN an adjective on the object and JOIN it onto the 
predicate as an adverb (e. g. SOUPER GRAND) . This could be done by 
expanding the first statement to the following: 
LET =4 BE Y(L(=l)) 
LET =2 BE B(=4) 
IF =4 ISAN INTERJUNCTION THEN DO 
LET =5 BE Y(S(=4)) 
LET =6 BE L(=l) 
UNJOIN =4 
JOIN (ADV * =4) + E 
JOIN =6 $ = 
END 
Now let us consider a transfer stimulated by a difference in 
productivity of a junction pattern between two languages. English 
and French both have possessive adjectives (his, my+son, sa, ses, 
mon, ma, mes) but on non-pronouns the English adjectival form be- 
comes prepositional in French, e. g. my friend's mother's kitchen- 
la cuisine de la mere de mon copain (the kitchen of the mother of 
my friend). 
Fortunately, in TL we need not consider the embedded cases 
separately from the simple case; rather we can write one transfer 
which will be involved automatically by the transfer supervi si en 
for each occurrence of the possessive. The basic transfer should 
modify structure in the following way: 
N=4 * N=2 SP 
0-l 
* 
becomes: 
N N=2 * N 
A 
PP 
A=l * N=3 
A 
P + N=3 
('~1 -pronoun (of1 
This might be done by the following transfer (stimulated by - 's) : 
17 
LET =3 BE Y(L(=l)) 
IF =3 ISMARKED -PRONOUN THEN DO 
LET =4 BE L(L(=l)) 
REPLACE =4 WITH fl 
REPLACE =3 WITH fl 
JOIN =2 $ (OF + 13) 
END 
*I 
In the case of one embedding the boy's mother's kitchen, the trans- 
fer would be executed on boy's and then on mother's, changing 
structure as follows : 
(1) before transfer: 
N 
A 
N*N 
kitchen 
N*A 
n 
A*N 
s A 
N*N 
mother 
NA 
n 
A*N 
's boy 
(2) after first execution of transfer 17: 
N*N 
kitchen 
N*A 
n 
A*N 
IS ,--.A 
N*N PP 
mother A 
P+N 
of boy 
(3) finally, after second execution of transfer 17: 
N" * N PP 
kitchen 
A 
P+N SP 
of - 
N*N PP 
mother A 
P+N 
of boy 
Before leaving this second example, it should be remarked that 
in this transfer, as with all transfers, we do not consider ques- 
tions of differing word order or inflectional patterns between 
languages. In transfer we simply modify the structure, and syn- 
thesis later produces the proper word order and inflection through 
the lexical-rule system. 
As a final example we will consider a simplified version of 
an extensive transfer written as a major component of a thesis 
which considered several forms of the English passive [lo]. In 
our simplifiad version we do not make many of the needed checks 
to weed out unwanted modifiers, etc. 
Consider the three closely related sentences: 
(1) 
John gave him a bopk. 
(2) He was given a book by John. 
(3) A book was given to him by John. 
Many grammars would consider these sentences to have the same mean- 
ing and give them the same underlying representation. Junction 
Grammar, taking a slightly different approach, chooses to repre- 
sent them in such a way that indicates both their similarities 
and their differences. This attitude is based on two assumptions 
of Junction Grammar. 
(1) The path between deep and surface structure should gen- 
erally be direct, not tortuous, and 
(2) Any difference in structure implies some difference, how- 
ever minute, in meaning, since meaning (in Junction Gram- 
mar) is defined as the compositidn of structure, refer- 
ence, and context. 
However, the philosophical gulf between Junction Grammar and 
other grammars is not as wide as might appear at first, for if in 
any patticular application area it is useful to ignore such dif- 
ferences as those between the passive and the active, standard 
junction trees can easily be passed through a special normalizing 
transfer grammar. One transfer in such a normalizing grammar would 
be the following, which is stimulated by the rule A * PV and trans- 
fers sentences of type (2) and (3) into active sentence9 of type (I), 
examples of which are shown in Figure 5. (Going into this trans- 
fer, it is assumed that =1 is set to the label node of the rule 
A * PV.) 
15 
*PASSIVE-ACTIVE TRANSFER 
*SEE SWLE JUNCTION TREES IN FIGURE 5 
*FIRST, DETERMINE WHETHER THIS IS INDEED A PASSIVE SENTENCE. 
LET =2 BE Y(=l) 
IF =2 NOTMARKED PASSIVE -PARTICIPLE THEN STOP 
*FIND THREE ELEMENTS- -THE AGENTIVE , THE OBJECTIVE, AND THE DATIVE, 
* (TO DRAW ON FILLMORE ' S TERMINOLOGY) . 
LET =3 BE Y(X(S(L(=l)))) 
LET =4 BE Y(=2) 
LET =5 BE Y(X(S(X(=Z)))) 
*ALSO FIND THE SYNTACTIC SUBJECT 
LET =6 BE Y(A(A(L(T(=l))))) 
*SWITCH THE PASSIVE CONSTITUENT (IT MAY BE DATIVE OR OBJECTIVE) 
WITH ITS CORE FERENT , THE SYNTACTI C SUBJECT 
IF -5 ISMARKED PASSIVE-CONSTITUENT THEN DO 
REPLACE =5 WITH =6 
LET =6 BE =5 
END 
ELSE DO 
REPLACE 5:4 WITH =6 
LET =6 BE =4 
END 
*NOW TRANSFER FROM PASSIVE TO ACTIVE BY PLACING THE AGENTIVE ELE- 
*MENT AS THE SUBJECT AND THE PASSIVE PARTICIPLE AS THE PREDICATE. 
REPLACE =6 WITH =3 
LET =7 BE X(L(x6) ) 
*REPLACE THE PREDICATE WITH A DUMMY ONE. 
REPLACE =7 WITH PV=8 
REPLACE =8 WITH =2 
*I 
[Figure 5 begins here and continues on the following page.] 
sv 
(1) John gave him a book. A 
N + PV 
John 
2 
v * v 
give A 
P + N 
003 he 
(2) He was given a book by John. 
A * ~~=2(-passive by John 
participle) 
n 
P + N=14 (passive constituent) 
(3) A book was given to him by John. 
sv 
/-'- 
N=6 + PV 
book ,'-, 
V+E 
0"'. 
V * PA 
n 
A+E SP 
A- * PV=Z (passive by John 
participle) 
V + N=4 @assive constituent) 
give 
The above description of Transfer Language and the sample 
transfers should convey some idea of transfer within Junction 
Grammar, but it should also point out the difficulty of comparing 
Junction Grammar transfer with the intermediate adjustment phase 
of some other translation system (e.g. [ll], [12], [13]). The 
reason for the difficulty is simply that a transfer phase is 
tightly interlaced with the analysis and synthesis phases and the 
theoretical base. For example, we do some adjustments in transfer 
which otner systems neutralize in analysis, while some other sys- 
tems consider aspects of word order and word choice in transfer 
which we handle in analysis and synthesis. 
C. Synthesis. 
The input to this program is a junction tree or J-tree. The 
program applies lexical ordering rules, lexical hiatus rules, 
lexical matching rules, lexical agreement rules, and graphologi- 
cal and phonological adjustment rules. Figure 1 shows the synthe- 
sis mainline in a simplified form which omits some details pertain- 
ing to the processing of intersecting trees and discontinuities. 
Basic processing follows the figure. First a J-tree is read 
in to the computer. The perspective routine recognizes some 
essential relationships which are implicit in the J-tree and makes 
them available to the synthesis program in an explicit form. Then, 
beginning with the topmost node of the J-tree, the cycle processes 
the nodes one at a time. Label nodes are processed by the hiatus 
and ordering routines. The LHO algorithm determines the ordering 
procedure which should be employed and takes the steps necess.ary 
to implement it. These steps always include designating the order 
in which the operands of the label node should be processed. They 
may include the marking of hiatus (understood) elements, discon- 
tinuous elements, and insertion points. 
Processing continues through the J-tree in the sequence 
designated by the LHO algorithm until the entire J-tree has been 
interpreted. Terminal nodes are interpreted by the.LMA (lexical 
matching and agreement) routines and appropriate lexical man'ifes - 
tations are generated. 
start 
D 
Figure 1. 
The Simplified Synthesis Mainline. 
Two types of lexical ordering rules are used in the synthesis 
programs. There are: (1) left-right and right-left ordering of 
operands, and (2) discontin~ous ordering. These will be considered 
individually 
(1) When the LHO (lexical hiatus and ordering) algorithm 
interprets a label node, it designates one of its operands as the 
first operand and the other as the second operand. Processing 
then moves to the operand designated as the first. At the top of 
the chart the flow of processing is controlled by whether a node 
is terminal or a label. At the bottom of the chart, the order of 
processing is determined by whether the node which has just been 
processed was designated as a first or a second operand. Process- 
ing moves from the first operand to the second and from the second 
back to the label node. 
This seemingly simple ordering procedure gives the junction 
grammar system great flexibility and power. A single junction 
which has two operands has two ordering possibilities. However, 
if one of those operands i's itself a junction with two possible 
orders, then the string is capable of four orders. In a similar 
manner, a string of three junctions can be ordered in eight dis- 
tinct ways. In general, a tree composed of N junctions can be 
ardcled in 2" distinct patterns. 
(2) Discontinuous ordering exists when sentences elements 
which are most closely related structurally are not contiguous. 
The sentences "It surprised me that he cameM and "It is so big 
that I can't lift it" have discontinuous order. With continuous 
ordering they would read "It that he came surprised me" and "It 
was so that I can't lift it big." 
The synthesis program handles discontinuous ordering by 
redirecting the flow of processing in such a way that the discon- 
tinuous element is omitted at its normal position and processed 
instead at a predetermined insertion point. Figure 2 shows the 
synthesis mainline with the reset routines and their skip points. 
Figure 3 shows the reset routines in detail. 
If the flow of processing is followed as shown in the figures, 
the operation of the reset routines is relatively simple. On 
each cycle the reset routines check the node which is being inter- 
preted to determine if it has been designated by the LHO algorithm 
as an insertion point or a disconf inuous element. If it has not, 
no action is taken. If it has, normal processing is interrupted 
to achieve the desired order. For instance, if the reset routine 
at the top of the diagram detects that a node is a discontinuous 
element, it causes the flow of p~ocessing to jump to the second 
skip point. This bypasses the LHO and LMA routines, in effect 
omitting the discontinuity. At the bottom of the chart processing 
resumes just as if the discontinuity had not been omitted. In a 
similar manner the reset routines direct processing from the in- 
sertion point to the discontinuity and from the discontinuity back 
to the insertion point. 
The ordering of intersecting structures is quite similar to 
the ordering of discontinuous elements. When the point of inter- 
section is reached, the flow of processing shifts to the top of 
the subordinate structure and that entire structure is processed. 
Then processing shifts back to the main structure which is completed 
in the usual manner. Thus, the point of intersection has some sim- 
ilarity to an insertion point while an intersecting structure re- 
sembles the discontinuous element. This same procedure is follow- 
ed when there are several intersections. 
The lexical matching rules access the target language lexicon. 
The lexical agreeement rules examine the junction and feature en- 
vironment in which the particular sememe appears in orde~ to deter- 
inine which inflected form should appear. 
At present, most inflected forms appear in the lexicon in full. 
Others, however, are generated by the synthesis program from stems 
and endings. The two approacE.es are theoretically equivalent since 
most of the inflected forms in the lexicon are generated from stems 
and endings by the lexicon building routine anyway. 
Thus, the synthesis program interprets a J-tree to generate 
an output string. When this output string has been adjusted by 
the graphological and phonological rules, which shape the final 
form of the output, the target language text appears. 
Figure 2. 
reset 
before 
The Synthesis Mainline Including the 
Processing of Discontinuities. 
Interpret 
topmost 
node 
.L 
- -- L 
7 
I 
label erminal . 
" I 
C 
Interpret 
first 
operand 
4 r 
return to 
label node 
z 
J-Tree 
4 
second 
Stop 
operand 
operand 
I - 
Interpret 
second 
ope rand 
Enter 
process 
disconti * 
nuity 
I no 
b 
( Return 1 
Reset Before 
Enter 
Reset After 
Figure 3 
The Reset Before and Reset After Routines. 
' 
A 
Yes 
) 
process 
insertion 
point 
no 
Y 
d 
yes 
process 
7 cl:l:pnti- 1 
IV. Conclusion. 
It is proposed that junction schemata of the type illustrated 
constitute a universal pool of structural patterns available to 
all languages. 
Presumably, most languages use the majority of 
them but no one language need use them all. Perhaps no two lang- 
uages use exactly the same subset, nor any two persons speaking 
the same language, for that matter. Languages can be expected to 
vary in their manner of realizing junction patterns as surface 
strings. Specifically, the lexical stock, word order, concord, 
inflection and conjugation paradigms, etc., are known, for the most 
part, to be language specific. 
Our experience to date supports such expectations. For ex- 
ample, the basic word order for Japanese can be obtained by shift- 
ing the left-right options on subjunction used by English to 
right-left. While English uses heterogeneous interjunction freely 
("John passed, which surprised us", etc .) , Japanese does not ; it 
either uses the corresponding full-sub junction ("That John passed 
surprised us") , or two conjoined sentences ("John passed, and this 
surprised us"). Of course, the lexical stock and morphophonemic 
patterns of Japanese are radically different from those of English. 
But the conclusion we have been forced to repeatedly is that while 
surface phenomena are vastly disparate from language to language, 
junction phenomena are more alike than different . 
While we use the familiar ANALYSIS/TRANSFER/SYNTHESIS scheme 
as a general framework for our translation system, the design of 
these components is rigidly governed by the junction grammar 
model, with junction trees serving as the interlingua. 
Analysis, operating in an interactive mode, produces junction 
trees from the source text. The data thus obtained is then passed 
to the transfer segment of the system. 
Transfer from a source language A to a target language B be- 
gins with inspection of every junction rule and semantic index 
appearing in the junction trees produced by analysis. If some 
rule or semantic index of A does not belong to the subset used 
by language 3, then a transfer subroutine adjusts the junction 
tree. The library of A-B transfer subroutines is a partial con- 
trastive grammar of fanguages A and B. However, since word order 
and other lexical phenomena are abstracted away from the semantic 
component in our model, these cto not enter into transfer at all, 
but are handled independently by lexical synthesis for language B. 
The adjusted trees output by transfer are passed to a syn- 
thesis program. The four steps of the synthesis process corre- 
spond to four lexical rule types--ordering, matching, ellipsis 
(or hiatus) , and agreement. 
Our development group is currently engaged in developing 
English analysis and transfer-synthesis for translation into 
Spanish, French, and German, using the University's IBM 360/65. 
Our system's dictionaries are largely based on a vocabulary drawn 
from a data base ofmaterials published for the membership of the 
LDS (Mormon) Church, and hence they are not technically oriented. 
at present. Currently, each lexicon contains entries for over 
10,000 semantic indices and we hope to double this size by the 
end of 1976. 
We expect that this prototype will provide a gauge for the 
utility of various on-line interaction techniques for compuber- 
assisted translation systems and for the feasibility of achieving 
commercial grade computer-assisted translation via the junction 
grammar model of language described herein. Work is also in 
progress to develop a phonological component of Junction Grammar 
that accounts for the connection between prosodic features (pitch, 
amplitude, duration, pause, etc.) and semantic considerations of 
sentences. 

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