Recognition of the Coherence Relation 
between Te-linked Clauses 
Akira Oishi 
School of Information Science 
JAIST 
1-1 Asahidai, Tatsunokuchi, 
Ishikawa 923-1292, Japan 
oishi~j aist .ac .jp 
Yuji Matsumoto 
Graduate School of Information Science 
NAIST 
8916-5 Takayama, Ikoma, 
Nara 630-0101, Japan 
mat su@is, aist-nara, ac. jp 
Abstract 
This paper describes a method for recognizing coher- 
ence relations between clauses which are linked by te 
in Japanese -- a translational equivalent of English 
and. We consider that the coherence relations are 
categories each of which has a prototype structure 
as well as the relationships among them. By utiliz- 
ing this organization of the relations, we can infer an 
appropriate relation from the semantic structures of 
the clauses between which that relation holds. We 
carried out an experiment and obtained the correct 
recognition ratio of 82% for the 280 sentences. 
1 Introduction 
One of the basic requirements for understanding dis- 
course is recognizing how each clause coheres with 
its predecessor. Our linguistic and pragmatic com- 
petence enables us to read in conceivable relations 
even when two clauses are copresent without any 
overt cues, i.e., in parataxis. 
There has been a variety of definitions for coher- 
ence relations (see (Hovy and Maier, 1993) for a 
survey). However, the definitions are rather vague 
and they are often recognized to be underspecified 
(Moore and Pollack, 1992; Fukumoto and Tsujii, 
1994). This paper attempts to explicate how such 
coherence relations arise between segments of dis- 
course. We focus on re-linkage in Japanese -- a 
translational equivalent of English and-linkage, since 
mere parataxis ranges over too widely to capture the 
underlying principles on the coherence relations. 
We consider that coherence relations are cate- 
gories each of which has its prototypical instances 
and marginal ones. As with all instances of catego- 
rizations, the prototypical cases of each relation are 
clearly distinguishable from one another. In some 
cases, however, it is often hard to make clear argu- 
ment for a relation being one rather than another. 
In addition, these relations themselves are hierar- 
chically organized according to their specificity. By 
considering the prototype of each relation, we can in- 
fer an appropriate relation from the semantic struc- 
tures of the segments between which that relation 
holds. 
2 Categorization of Te-linkage 
Traditionally, te-constructions have been divided 
into three categories according to the function of 
te: (i) as a non-productive derivational suffix; (ii) 
as a linker joining a main verb with a so-called aux- 
iliary to form a complex predicate; and (iii) as a 
linker connecting two phrases or clauses. Since the 
derivatives and the auxiliaries are relatively fixed 
compared with the third category, we concentrate 
on the third category in this paper. 
Japanese re, like English and, is used to express a 
diverse range of coherence relations as shown below 1. 
(1) Circumstance 
itami-wo koraete hasiri-tuzuketa. 
pain-ACC endure-te run-continue-PAST 
"Enduring pain, (I) kept running." 
(2) Additive 
zyoon-wa akarukute kinben-da. 
Joan-TOP be-cheerful-te diligent COPULA- 
PRES 
"Joan is cheerful and diligent." 
(3) Temporal Sequence 
gogo-wa tegami-wo kalte, ronbun-wo yonda. 
afternoon-TOP letter-ACC write-te thesis- 
ACC read-PAST 
"In the afternoon, (I) wrote letters and read 
the thesis." 
(4) Cause-Effect 
talhuu-ga kite, ie-ga hakai-sareta. 
typhoon-NOM come-te houses-NOM destroy- 
PASSIVE-PAST 
"A typhoon came, and houses were destroyed." 
1The examples are borrowed from (Hasegawa, 1996). 
990 
(5) Means-End 
okane-wo karite, atarasii kuruma-wo kau. 
money-ACC borrow-te new car-ACC buy- 
PILES 
"(I) will borrow money and buy a car." 
(6) Contrast 
zyoon-wa syuusyoku-site tomu-wa kekkon-sita. 
Joan-TOP get-a-job-re Tom-TOP marry-PAST 
"Joan got a job, and Tom got married." 
(7) Concession 
kare-wa okane-ga atte kasanai. 
he-TOP money-NOM there-be-re lend-NEG- 
PILES 
"Although he has money, (he) won't lend (it to 
anyone)." 
When such a relation is understood to be intended 
by the speaker, it is always inferable solely from the 
conjuncts themselves. 
Although re-linkage exhibits an extreme degree of 
semantic nonspecificity, it is nonetheless very com- 
mon in actual usage2and does not cause problem in 
communication. We will see how such diversity of 
relations arise in the next section. 
3 Organization of the Coherence 
Relations 
Although the semantic relations between the re- 
linked constituents are diverse, not all relations im- 
plicated by parataxis can be expressed by re-linkage 
(Hasegawa, 1996). For example, if the clauses equiv- 
alent to I sat down and The door opened are pre- 
sented paratactically in Japanese, the interpreter 
naturally reads in a Temporal Sequence relation, just 
as in English. But this relation is not an available in- 
terpretation when the clauses are linked by re. That 
is, among the relations potentially implicated by two 
copresent clauses, some are filtered out by re-linkage. 
We presume that the inherent meaning of te is 
"togetherness." The only relations that fit with this 
meaning are possible to arise within re-linkage. The 
notion of "togetherness" can be divided into two cat- 
egories according to the temporal properties of re- 
lations. One in parallel and the other in series. In 
the former, two events occur simultaneously or two 
2 On the basis of a corpus of 3,330 multi-predicate sen- 
tences sampled from various types of text, Saeki (Saeki, 
1975) reports a total of 26 connectives (1,047 tokens al- 
together), of which te holds the foremost rank: it occurs 
512 times, while the second most frequent connective, 
9a, occurs only 141 times. According to Inoue (Inoue, 
1983), te appears most frequently in spontaneous speech 
(34.5% of all connectives) and in informal writing (27%). 
In formal writing such as newspaper editorials, te ranks 
second (17.2%) after ren'yoo linkage (36.9%). The actual 
occurrence of te is much more frequent than these num- 
bers suggest, because these data do not include cases in 
which the second predicate is a so-called auxiliary. 
states hold at the same time, while in the latter, two 
events occur successively. 
These two categories are further divided into 
smaller categories according to the event structures 
of conjuncts. The category of sequential relations 
contains both Cause-Effect and Temporal Sequence. 
When two events which are linked solely by temporal 
sequentiality are expressed via te-linkage, the con- 
juncts must share an agentive subject. Thus, causa- 
tion and one person's volitional acts are sufficient to 
be recognized as togetherness. 
On the other hand, in order for the category of 
parallel occurrence of events to be compatible with 
re-linkage, they must be homogeneous in some sense. 
One such example is the case where a thing has two 
different properties (Additive) and another is the 
cases where two different things have similar prop- 
erties or are engaged in similar events (Contrast). 
As for the Additive relation, the subject of the sec- 
ond conjunct is often omitted since it is the same as 
that of the first. In addition, both predicates of the 
conjuncts are stative -- adjectives or stative verbs 
-- because they have no temporal boundaries as op- 
posed to events and can easily hold at the same time 
within one person. As for the Contrast relation, the 
subjects of the conjuncts must be different from each 
other and hence both of them are explicitly men- 
tioned (often marked with the contrastive wa). In 
general, the similarities of the predicates appear as 
the syntactic parallelism as the example (6) shows. 
The other sub-category of the parallel occurrence 
of events is "accompaniment," where the second 
clause is foregrounded and the first backgrounded. 
The prototypical instance of this category is the case 
where the first clause denotes a state and the second 
an event, since we have a tendency to focus on a 
changing event rather than stable state. Thus, the 
Circumstance relation composes this category. The 
cases where the first clause denotes some manner 
of event are also contained in this category, since a 
manner accompanies an event. 
The notion of the manner is continuous to the 
means since the means and manner of an event are 
often coextensive in that the means of an event often 
determines the manner of the event. This is exem- 
plified by English with as well as Japanese de, which 
are used both as an instrumental or means marker 
and as a marker of manner (How is similarly poly- 
semous) (Goldberg, 1996). 
The Means-End relation is also continuous to cau- 
sation, since the means can be interpreted as a kind 
of causation. This is exemplified by Japanese doosite 
(why/ ow) as follows: 
(18) doo-site kitano? 
"Why/How did you come?" Answer: 
(18a) densya-de (means) 
"by train" 
(18b) aitakatta-kara (reason) 
991 
"since (I) want to meet (you)" 
(18b) expresses the reason why the speaker came to 
the hearer -- "the wish to meet the hearer caused 
him/her to come." Thus, this relation associates the 
two extremes i.e., parallelism and sequentiality. 
Finally, the Concession is closely related to both 
Cause and Contrast. In the Concession relation, the 
first clause implies something and the second clause 
denys it. The implied states or events are often those 
to be caused by the events or states denoted by the 
first clause, and then denied and contrast with the 
second clause. 
The whole organization is shown in Figure 1. Note 
togethernese 
parallel sequential ./7"-.. /"-.. 
Additive Contrast accompaniment Cause Temporal Sequence 
.......... 2":-:.:~ 
Circumstance Manner Means Concession 
(Vw, e,g,p)go(e, y,p) ^ locational(e) A goal(g) 
D pp("w - ni",g) A place(g) 
(¥w, e, g, p)go(e, y, p) A posessional(e) ^ goal(g) 
D pp("w -- ni", g) A thing(g) 
(Vw, 8, y, p)be(s, y, l) A locational(e) A at(l, p) 
D pp("w -- ni",p) A place(p) 
(Vw, e, x, y)act(e, x, y) D pp("w-ga", x)Aanimate(x) 
(Vw, e, y, s )become( e, y, 8) ~ pp( "w -- ga", y) 
(¥w,s,y,l)beCs, y,l) D pp("w - ga",y) 
(Vw, e, x, y)act(e, x, y) ~ W("v' -- o", y) 
(Vw, e, ~, y, 8)aS(e, ~, y) ^ become(e, y, 8) 
mo("w - o", y) 
J 
Figure 2: Examples of the linking rules 
Figure 1: The organization of the relations with te- 
linkage 
that this organization of the relations are viewed 
from the perspective of re-linkage. The different or- 
ganizations may emerge via the other linkages. 
4 Recognizing the Coherence 
Relations 
4.1 Overview 
Theoretically, it is more likely that when we have 
heard/read the first clause and te, we narrow down 
the possible relations by inferring the content of the 
second clause. For example, if the first clause de- 
notes an action, we will infer what is caused by the 
action or another action which may follow the action 
-- that is, Cause or Temporal Sequence will be ex- 
pected. On the other hand, if the first clause denotes 
a state, Circumstance or Additive will be expected. 
In practice, however, we have both clauses at hand. 
Therefore, we adopt the following algorithm: 
STEP1 Assume part of semantic structures of the 
conjuncts by reverse linking 
STEP2 Unify them with a verb's semantic struc- 
tures 
STEP3 Infer the most feasible relation between 
them 
In STEP1, part of the semantic structure of each 
clause is abductively assumed by applying linking 
rules backward. The linking rules are regular ways of 
(vs, y, z, l)be(s, y, l) ^ at(l, z) ~ State(s) 
(re, z, y)act(e, x, y) D TransAct(e) 
(re, z)act(e, z) D IntransAct(e) 
(re, y,p)go(e, y,p) A path(p) D Move(e) 
(re, y, s, l, z)become(e, y, s) h be(s, y, l) h at(l, z) 
D Achievement(e) 
(re, e~, e~, ,~, y)act(el, x, y) ^ cause(e, e,, e~) 
^becomeCe~, y, s) ^ be(s, y,l) ^ at(l, z) 
D Accomplishment(e) 
(Vs)State(s) A thing(y) A place(z) D verb("aru", e) 
(Vs)State(s)Aanimate(y)hplace(z) D verb("iru",e) 
(re)Move(e) A mannerl D verb("hashiru", e) 
(re)Move(e) h rnanner2 D verb("aruku",e) 
(Ve)Accomplishment(e)Amanner3 D verb( "nuru", e 
(re)Accomplishment(e) A manner4 ^ locational(e) 
D verb("sosogu", e) 
(re)Accomplishment(e) A statelh 
identi f icational( e ) D verb( "mitasu", e) 
J 
Figure 3: Examples of the verbs' semantic structures 
992 
mapping open arguments -- i.e., variables of seman- 
tic structures whose referents can be expressed syn- 
tactically by a phrase within the same clause as the 
predicate -- onto grammatical functions or under- 
lying syntactic configurations by virtue of thematic 
roles (thematic roles are positions in a structured 
semantic representation). In the case of Japanese, 
they are triggered by case particles. In STEP2, 
the verb's semantic structures are invoked and uni- 
fied with the outputs of STEP1. The examples of 
the linking rules and verbs' semantic structures are 
shown in Figure 2 and 3 respectively. 
However, since the real texts contain far more 
complexity and ambiguity than the examples given 
in this paper, we have to correct the outputs of the 
processes manually (the gapped arguments are filled 
by hand). We now focus on the processes that cal- 
culate the coherence relations. 
4.2 The Properties Relevant to the 
Coherence Relations 
What is essential for recognizing the coherence rela- 
tion between clauses is that the constituents of one 
clause bear certain kind of structural relationship to 
those of the other. Although there are an infinite 
number of situations, there seems to be only a small 
number of properties relevant to the coherence rela- 
tions that can hold between them. They are: 
1) the identity and agentivity of the subjects in 
the two clauses 
2) the thematic and aspectual properties of the 
event denoted by each clause 
3) canonical events associated with the noun that 
is relevant to both clauses 
Before going through the use of these properties, 
let's consider the other information which affects our 
construal of the relations. 
There are some adverbials or fixed expressions 
which coerce the interpretation into the specific re- 
lation. In addition, there are narrow-range verb 
classes which specialize the implicated relation by 
virtue of their inherent meaning. For example, 
Table 1: The expressions that specialize the relations 
verbs that take a temporal NP as the subject and 
means "the passage of time" such as sugiru(pass 
away), tatu(go by), keikasuru(elapse), etc., imply 
the Temporal Sequence relation when followed by te. 
Verbs that express "using" such as tukau(use}, siy- 
ousuru(make use of), katuyousuru(apply), etc., im- 
ply the Means-End relation. They are summarized 
in Table 1. In Table 1, \[TE\] means temporal ex- 
pressions such as days, months, years, centuries, etc. 
The verbs and fixed expressions appear in the first 
clause, while the adverbials in the second. These 
fixed expressions should be listed as a unit in the 
lexicon. 
When these expressions appear in the test sen- 
tences, we can identify the relation regardless of the 
procedure described below. Otherwise, we have re- 
course to the aforementioned properties. 
4.3 The Prototypes and the Extensions 
In the previous study, We have classified verbs into 
30 semantic categories, and for each category we 
have given a lexical conceptual structure (LCS) rep- 
resentation (Oishi and Matsumoto, 1997). Since the 
LCS representation involves lexical decomposition 
(Jackendoff, 1990), we can utilize the verb internal 
semantic structure so as to calculate coherence rela- 
tions in a farely principled way. 
As mentioned in the introduction, we consider 
each relation as a category. Categories cannot be 
defined in terms of necessary and sufficient condi- 
tions, but rather each instance is categorized accord- 
ing to its similarity to the prototypes of the cate- 
gories (Rosch, 1973; Lakoff, 1987; Taylor, 1989). 
We define a prototypical structure for each rela- 
tion by means of the predicates used in the LCSs as 
follows: 
• Circumstance 
\[x ACT\]2 WITH \[x BE z\]x 
• Additive 
\[x BE zx\]x AND \[x BE z212 
• Temporal Sequence 
\[x GO TO zx\]l THEN \[x GO (FROM zx) TO z2\]~ 
relations 
Temporal Sequence 
Means-End 
Cause-Effect 
Circumstance 
\] categories 
passage verbs 
ending verbs 
continuing verbs 
adverbials 
fixed expressions 
using verbs 
fixed expressions 
fixed expressions 
static relation verbs 
examples 
sugiru(pass away), keikasuru(elapse) ... owa u(end), oeru( ni h)... 
tuzuku(continue), hikituzuku(follow) ... 
sonogo(after that}, imadeha(nowadays} ... 
\[Tg\]ni-natte(set in), \[Tglhodo-site(afler)... 
tukau(use), siyousuru(make use of) ... 
ni-yotte(by means of) 
dake-atte(on account of), wo-ukete(given) ... 
sou(be parallel to), motozuku(be based) ... 
993 
• Cause-Effect 
\[x ACT ON y\]~ CAUSE \[y BECOME z b 
• Means-End 
• Contrast 
\[x ACT\]2 BY ix ACT\]I 
ix ACT\]I WHILE \[y ACT\]2 
• Concession 
ix ACT ON YL BUT \[y NOT BECOME z\]~ 
Here, WITH, AND, THEN, etc., are mnemonic 
names for the relations and each can be considered 
as a function that takes two events or states as its 
arguments and returns a coherent event or state. 
We use the infix notation for each function rather 
than prefix. The square brackets identify the se- 
mantic structure of a clause and their subscripts de- 
notes the surface ordering of the clauses linked by re. 
ACT, BE, GO, and BECOME are also functions and 
they correspond to actions, states, movement, and 
inchoatives respectively. They express broad-range 
classes of the events which are constructed by the 
previous steps (see Figure 3). The whole structures 
incorporate the identity between the subjects of two 
clauses by the variables x and y. Agentivity of each 
subject is implied by the types of the events: ACT 
> GO > BECOME > BE. 
Often, these prototypical structures are lexical- 
ized and expressed by a single clause. For example, 
the Cause-Effect relation is lexicalized into accom- 
plishment verbs (Talmy, 1985) and the Means-End 
relation can be expressed by an adjunct event noun 
followed by the case particle de. They must be ex- 
tended so that they can cover wider range of in- 
stances of re-linkage. The result of the extension is 
shown in Table 2 (for cases each of which shares a 
subject) and Table 3 (for cases each of which has 
distinct subjects), where each column corresponds 
to the type of the event in the first clause and each 
row to the second. The prototypes are boldfaced 
and they are extended to the other boxes with some 
directions and constraints. 
For example, the Temporal Sequence relation has 
a prototype structure, which is roughly read as 
"someone goes to somewhere, and then he/she goes 
(from there) to elsewhere." This expresses our com- 
mon sense that one person cannot move along two 
different paths at the same time, which implys that 
the two movements by a person must be sequential. 
This prototype is extended so as to cover such sit- 
uations as "someone goes to somewhere, and then 
he/she does something/becomes something/stays 
there" or "someone does something/become some- 
thing/stays somewhere, and then he/she goes to else- 
where." They are expressed by vertical and hori- 
zontal extensions of the prototype in Table 2. The 
Table 2: The combinations of event types (identical 
subjects) 
2nd clause 
ACT 
GO 
ACT 
Means 
Cir(manner) 
TempSeq 
TempSeq 
Cir(manner) 
Means 
Cause 
Means 
Cir(manner) 
Cir(manner) 
1st clause 
GO \[ BECOME 
TempSeq 
TempSeq TempSeq 
Cause 
Cause Cause 
TempSeq 
TempSeq 
I BE 
Circum 
TempSeq 
Circum 
Circum 
Cause 
Additive 
Cause 
Circum 
Table 3: The combinations of event types (distinct 
subjects) 
2nd clause 
ACT 
GO 
BECOME 
BE 
Ist clause 
ACT I GO I BECOME 
Contrast 
Contrast 
Cause Cause Contrast 
Cause 
Concession 
I BE 
Circum 
Circum 
Cause 
Circum 
Contrast 
Circum 
movements involved in these situations are loca- 
tional and the other events must be done volitionally 
by the same person. Another extension covers sit- 
uations where "someone does something, and then 
he/she does something else." This is based on the 
fact that one person cannot generally engage in two 
actions at the same time. Of course, any type of 
events may occur sequentially. However, there ex- 
ists the constraint on the fitness with te-linkage as 
mentioned in the previous section. 
The explanation for the other relations is detailed 
in (Oishi, 1998). 
As a result of the extensions, many boxes have 
two or more relations. Notice that the nearer re- 
lations in the organization tend to be in the same 
boxes. To discriminate among them, we specify for 
each combination of event types such algorithm as 
follows (below, I(i,j) means that two clauses share 
an subject and D(i,j) means that two clauses have 
distinct subjects, where i is the event type of the 
first clause and j the second): 
• I(ACT,ACT), I(ACT,GO) 
If either clause contains the expressions which 
fix the temporal boundary, then Temporal Se- 
quence; 
else if the verb of the first clause involves a man- 
ner component, then Circumstance; 
otherwise, Means-End. 
• I(ACT,BECOME) 
If the second event is psychological, then 
Cause-Effect; 
994 
else if the verb of the first clause involves a man- 
ner component, then Circumstance; 
otherwise, Means-End. 
• I(GO,BECOME) 
If the second event is psychological, then 
Cause-Effect; 
otherwise, Temporal Sequence. 
• I(BECOME,GO) 
If the first event is perceptual, then Cause- 
Effect; 
otherwise, Temporal Sequence. 
• I(BE,GO) 
If either clause contains the expressions which 
fix the temporal boundary, then Temporal Se- 
quence; 
otherwise, Circumstance. 
• I(BE,BECOME) 
If the second event is psychological, then 
Cause-Effect; 
otherwise, Circumstance. 
• I(BE,BE) 
If the second state is psychological, then Cause- 
Effect; 
else if the both predicates are property- 
denoting adjectives or nouns, then Additive; 
otherwise, Circumstance. 
• D(BECOME,BECOME) 
If the both subjects are marked with wa, then 
Contrast; 
otherwise, Cause-Effect. 
* I(BE,BECOME) 
If the first state is relational, then Circum- 
stance; 
otherwise, Cause-Effect. 
• D(BE,BE) 
If the both subjects are marked with wa, then 
Contrast; 
otherwise, Circumstance. 
On the other hand, there remain some boxes 
blank. They should be resolved by using the third 
property -- the canonical events associated with the 
noun that is relevant to both clauses. The generative 
lexicon will serve the purpose (Pustejovsky, 1995). 
At present, however, we have not yet fully imple- 
mented the lexicon for nouns. Therefore, we give 
the Circumstance relation as a default. 
5 Experiment and Discussion 
An experiment of recognizing coherence relations of 
te-linkage were done for 280 sentences which were 
randomly extracted from EDR Corpus (EDR, 1995). 
The analysis results are shown in Table 4, where the 
coherence relations in the sentences were classified 
into 7 categories by authors and compared with the 
outputs of the program. 
The relations are not balanced in number. This 
seems to be due to the genre of texts from which the 
test sentences were picked up (most of them were 
news articles). The numbers in parentheses show 
those of test sentences that matched with the fixed 
expressions in Table 1. 
The precision on the whole is 82%. This shows 
that to a large extent we can cope with the problem 
to recognize the coherence relations between clauses 
(at least when linked by re), given the event types of 
the clauses and the fixed expressions in the lexicon. 
Most of errors are caused by ambiguity of the rela- 
tion. There were many examples which were difficult 
even for humans to make clear judgements. This re- 
flects the fact that the coherence relations do not 
have definite borders. 
However, there were some errors which show a 
crucial limitation of our method. This appears as the 
bad marks in both precision and recall for the Con- 
cession relation, even though the number is small. 
For example, there is a test sentence such as follows: 
(19) ano hito-wa 82sai-ni natte, annani koukisin 
ippal-da. 
that person-TOP 82-years-old-DAT become-te, 
so curiosity be-full-PRES 
"Although that person is 82 years old, (he/she) 
is full of curiosity." 
Table 4: The results of the experiment 
coherence 
relations 
Temporal Sequence 
Circumstance 
Cause-Effect 
Means-End 
Additive 
Concession 
Contrast 
Total 
judgement 
by human(a) 
89 
75 
64 
45 
3 
3 
280 
output of 
program(b) 
81/46) 
83(22) 58(13/ 
48(12) 
3 
2 
280(92) 
number of 
agreements(c) 
recall(%) 
c/a×lO0 
precision(%) 
c/b x 100 
79 89 98 
63 84 76 
48 75 82 
34 76 71 
3 100 100 
33 
i00 
82 229 
20 
50 
82 
995 
Since the combination of the event type here is 
I(BECOME,BE), our program gave it the Circum- 
stance relation as a default. However, we know that 
in general the person who is 82 years old is not 
so curious, therefore the Concession relation arises. 
Thus, our common sense knowledge is crucial to our 
recognition of the coherence relations. In (Hovy and 
Maier, 1993), they classified the Concession rela- 
tion as interpersonal (i.e., author-and/or addressee- 
related) rather than ideational (i.e., semantic), since 
they defined it as "one of the text segments raises 
expectations which are contradicted/violated by the 
other." The use of interpersonal relations is predi- 
cated mainly on the interests, beliefs, and attitudes 
of addressee and/or author. To deal with this prob- 
lem, we must incorporate the notion of intentional 
structure and focus space structure (Grosz and Sid- 
ner, 1986). 
Since we have focused on te-linkage in this paper, 
we need not to consider how clauses are combined. 
However, to detect the discourse structure, we need 
to extend the method so as to deal with the relations 
between sentences. We must estimate some kind of 
reliable scores among possible segments and choose 
the relation having the maximum score (Kurohashi 
and Nagao, 1994). These issues remain to be studied 
in the future. 
6 Summary 
Since the semantic relations exhibited by re-linkage 
vary so diversely, it has been claimed that the inter- 
preter must infer the intended relationship on the 
basis of extralinguistic knowledge. The particulars 
of individual common sense knowledge are crucial 
to understanding any discourse (Hobbs et al., 1993; 
Asher and Lascarides, 1995). Nevertheless, one can, 
through the use of the relevant structures of events, 
eliminate a very large number of rules for calculating 
the plausible relations. 
Although we have concentrated on re-linkage in 
this paper, we consider that the method can be 
applied to pure parataxis with necessary modifica- 
tions. For the relations we have examined are not 
attributable to the meaning of te itself (though it re- 
stricts the range of them), but are implicated by the 
linked conjuncts. The same is true of English and. 
In both and- and re-linkage, the perceived coherence 
relations are present even if the linked constitutes 
are in pure parataxis without and or re. Thus, this 
approach can be extended so as to detect the whole 
discourse structure, though further study must be 
done to examine all relations. 

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