Proceedings of the Third NTCIR Workshop

Using the Diff Command in Patent Documents
Masaki Murata and Hitoshi Isahara
Communications Research Laboratory
2-2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0289, Japan
murata,isahara  @crl.go.jp
Abstract
We have been studying natural language processing
using the Unix command Diff. We previously proposed
ways to use Diff in natural language processing. In
this contest, we tried handling three problems by using Diff. One is to extract rewriting rules. The second
is to align the claims in a patent to the contents of thepatent. The third is to extract differences of claims ina patent. We obtained interesting results in the threestudies and showed the usefulness of Diff. These results would be useful for reading and writing patents.
Keywords: Diff, Patent, Extraction of rewriting rules, Alignment of claims and embodiments inpatents, Diff of claims

1 Introduction
In the PATENT task of NTCIR-3, we participatedin the optional task, where the participants can perform any kind of research related to patents. We thinkthat in a PATENT attempt, the optional task is very
interesting, because we have already heard that someparticipants in previous contests wanted to make theirstudies as freely as they wanted. Various new ideas or
new topics will come up in an optional task. These attempts would be novel and valuable. In the other contests, too, we hope that such attempts will be made.
In this contest, we made the following three studies
for the optional task of PATENT.



1. We extracted rewriting rules using data ofpatents.
2. We aligned the claim of a patent and its embodiment.
3. We extracted differences among plural claims ina patent.

 did not participate in the main task (retrieval task).
 We
Our proposals that we use Diff for the three methods had been already proposed by us in the web page(http://ntcirftp.nii.ac.jp/ntcpat/optional/proposal/crl.html).

© 2003 National Institute of Informatics

The first two topics were given by organizers of
PATENT as examples of the optional task. We consider these studies to be very interesting. The last topic
is our idea. We sometimes write a patent, and had
the experience of wanting to know the difference ofclaims. So, we did this study.
We have been studying natural language processing
using the Unix command Diff [6, 8, 9]. We previously
proposed ways to use Diff in natural language processing. The Diff command is very suitable for doing theabove three studies. We have already extracted rewriting rules by using Diff in some research topics. For
example, we used a pair of definition sentences having the same word entry in two different dictionaries
and extracted the differences between them. These extracted differences can be used as synonym phrases
because the definition sentences in the same entry
have the same meaning. In another situation, we usedaligned spoken-language and written-language texts
and extracted the differences between them. These
extracted differences can be used as rewriting rules
transforming spoken-language sentences into writtenlanguage sentences or transforming written-language
sentences into spoken-language sentences. Diff canalso be used for alignment. Diff has a function of
merging data like a DP-matching algorithm. So we
can align two related texts by using Diff. In this study,
we used this function for the alignment of a patentclaim and its embodiment (working example). Finally,
we used Diff for extracting the differences of patentclaims. Extracting differences is an original functionof Diff. Extracting differences between claims enables
us to understand the claims of a patent more deeply.

2 Diff and Mdiff
In this section, we describe Diff. Diff is a software program of Unix systems that is used to compare
files. The program displays line-by-line differences
between a pair of text files while retaining the order ofthe data. For example, suppose we have the following
two files: This section is from our paper [6, 9].

The Third NTCIR Workshop, Sep.2001 - Oct. 2002

File 1:Igotoschool.

File 2:Igotouniversity.

When we give these data to Diff, the difference is displayed in the following way.
< school.
> university.
Diff has a -D option, which is very useful. When
we use Diff with this option, common parts as well as
differences are displayed. That is, files can be mergedby using this option. However, the output of diff -D isin a form which is used for a C preprocessor such as“Ifdef” and this is difficult for people to read. Therefore, in this paper, we give the differences in the following way:;===== begin =====(The parts which only exist
in the first file);----------------(The parts which only exist
in the second file);===== end =====
where, “;===== begin =====” indicates the beginning of the differences, “;===== end =====” indicates the end of the differences, and “;----------------” indicates the boundary between
the two sets of data. In this paper, we refer to Diff inthe case where the files are merged by using the -D
option and the differences are displayed in the above
form as Mdiff.
When we give our earlier pair of files to Mdiff, we
obtain the following result.
I
goto;===== begin =====
school.
;----------------university.
;===== end =====“I go to” matches, while “school” and “university” aredifferences. The output of Mdiff is easy to examine
and understand because, unlike Diff, it also displays
the common parts.
We can reproduce the two original files from theoutput of Mdiff. When we take the common part andthe upper part of the differences, we obtain the contents of the first file. When we take the common partand the lower part of the differences, we obtain thecontents of the second file. We can reproduce all of
the original data in this way.

Table 1. Examples of a claim and its embodiment
A claim sample
Claim 1.
A
methodforpredicting
whether
data
that
is
not
yet
known
to
be
positive

Its embodiment sampleThe
methodpredicts
whether
data
that
is
not
yet
known
to
be
positiveornot

Since Mdiff only displays the common part of thedata once, it is able to reduce the amount of data. Since
it is possible to fully reproduce the original data from
Mdiff’s output, we are able to say that Mdiff compresses the data while retaining the original information.
Since the output of Diff is difficult to read andthe output of Mdiff contains all information output byDiff, we use Mdiff for our explanations in the following sections. In the following sections, let’s look atsome actual examples of the application of Mdiff topatents.

3 Extraction of rewriting rules in patents
We have already confirmed that two different
texts having the same meaning can be used to extract the rewriting rules (paraphrases) [5, 8]. In
the paper [8], we used the spoken-language andwritten-language and extracted the difference between them. These extracted differences could be
used as rewriting rules transforming spoken-languagelike sentences into written-language-like sentencesor transforming written-language-like sentences into
spoken-language-like sentences. We performed thestudy on the transformation of written-language-like
sentences into spoken-language by using the extracted
transformation rules. In the paper [5], we used definition sentences of two different dictionaries and extracted the differences between them. These extracted
differences could be used as synonym phrases. We
performed the study on a sentence compression (summarization) and sentence polishing-up system using
extracted synonym phrases [7].

Proceedings of the Third NTCIR Workshop

Freq.
65087
63369
42577
31058
18566
17212
14195
13962
13753
13674
12201
11875
11864
11046
9954

Table 4. The differences between claims and embodiments (Top 15)
Matching part in front
ClaimsEmbodiments
Matching part behind

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In this contest, we made the following two kindsof experiments for extraction of rewriting rules frompatents.
1. Extraction of rewriting rules by comparing aclaim of a patent and its embodiment.
2. Extraction of rewriting rules by comparing an
abstract of a patent and its abstract generated by
JAPIO.
We describe these two experiments in the next two
sections.

3.1 Comparison of a claim and its embodiment
We describe our method of extracting the differences between a claim and its embodiment. We firstdivide a claim and its embodiment into words by using
the Japanese morphological analyzer ChaSen [3] andobtain the results shown in Table 1. In these samples,
we used English ones. Next, we use Mdiff for thesedata and obtain the results shown in Table 2. Fromthese results, we obtain the differences shown in Table
3.
We used this method for the Japanese patents andobtained many differences. We used about 100,000
patents for the experiments. We obtained 4,444,046
kinds of differences. We extracted regions from “ .*.* ” to “ (.*.*|.*.*) ” asembodiments from patents. We showed the differences having the highest 15 frequencies in Table 4.
<RET> is the code of carriage return. The other

+
B





SGML tags were originally contained in the patentdata. From Table 4, we learned many things. For example, we found that the index number of a component of a system (“ ” in “
” (back
plate)) written in embodiments were often eliminated” (mentioned previin claims. We found that “” (mentioned above) written in claims
ously) and “were often eliminated in embodiments. We found that“ ” (,), “ ” (case-particle), and “ ” (of) were supplemented in embodiments. Such interesting results
could be extracted very easily by using Mdiff. Thismethod can also obtain synonym phrases. We extracted synonym phrases shown in Table 6. We consider that sentences in embodiments are simpler andeasier to understand than sentences in claims. Extracted synonym phrases as shown in Table 6 can beused to transform difficult sentences like claims intoeasier sentences like embodiments.

+





!'#6"&.*)+8X

3.2 Comparison of an original abstract and
JAPIO’s abstract

Next, we used an original abstract and the corresponding JAPIO abstract to extract transformation
rules. We used the same method as the previous section. Although a patent contains an abstract, JAPIO
made a new abstract based on an original abstract by
supplementing some explanations. We think that theextraction of transformation rules of an original abstract into a JAPIO abstract is interesting. If we can doso, we may be able to transform an original abstract
into a JAPIO abstract automatically.

good differences, we have already developed better methods using
probabilities and used these methods for our previous papers [5, 8].

These methods need much time, so we did not use them in this study.
Katoh et. al. used DP matching and frequencies of differences toextract the transformation rules for automatic summarization [2].

=

~

v

=



~

v

 Although, in this study, we used the frequency for obtaining

The Third NTCIR Workshop, Sep.2001 - Oct. 2002

Table 5. The differences between orginal abstracts and JAPIO’s abstracts (Top 15)
Freq.
Matching part in front
Original abst. JAPIO’s abst.
Matching part behind
331309
<BR>
85681
<RET>
</P><RET>
38422
<P>
22309
17729
14055
9913
9071
8464
8181
<BR>
6276
5776
3739
3719
<P>
3690

>$8guB¶b·:oP@¸P¹>º¼$½8¾À¿_ÀÁÂHÑÒ Ó ÔÏl¿Ð(Õ+PÖ|rÞ ß@°àc(Ú £:@Û6Ü3(Ý,èé@°J=´ê8ë ì µ'\%Ä0,/1
8mPo ï ð'\ô÷cÛ6ø034Í ùv§¦ ¨c~




? 8
'
,c×>Ø´Wá/1h0pv§¦ ¨c~We used about 100,000 patents for the experiments.
We obtained 870,145 kinds of differences. The results
are shown in Table 5. From the results, we found thatJAPIO transformed a small-font character “ ” into a” tonormal-size character “ ” and “ ” in “
(subject or theme)“ ”. We found thatwhich is a mark describing the subject of a patent in
an abstract was transformed into <P> which indicatesa mark of a boundary of paragraphs. We found that
<BR> inserted into an original abstract was eliminatedin JAPIO’s abstracts. We also found that “ ” in “
” (Diamond abrasive 1) which is anindex number of a component of a system was supplemented in JAPIO’s abstracts. Our extracted differences contain many kinds of interesting transformation rules shown in Table 7. These rules would be very
useful to transform an original abstract into a JAPIO
abstract automatically.

Ê ü

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4 Alignment of claims and embodimentsin patents
This section describes alignment of claims and embodiments in patents. We had studied alignment of awritten paper and its corresponding speech using Diff[6, 9]. In this section, we used the same idea. We describe the method in the case of patents.
Here, let’s try to determine the parts of the embodiments to which each claim corresponds by using
Mdiff. We suppose that the content is laid out in thesame order in the claims and in the embodiments. In
advance, we place symbols such as <Claim 1>, asþ A small-font character is right in Japanese grammar. “ÿ ” ismore natural in Japanese character fonts. Use of a normal-size character for “ ” and “  ” for “ ÿ ” is JAPIO’s special notation.

?Ê ,×:Ù$W
/1

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( ,8$@¢¡=£>¤:!$¡=£:¥© ª0«\%¬ ;­ ®cg(W$¯@°J*1±²g´³ µ»
Ã'\6Ä Å*p(g(W>ÆV(,Ç È´},.É
p$\6Ë Ìcg(W>Í ÎÏlÐ´Ú$£:"Û6Ü3PÝ,âã Ò ä å ßÓ æ çuh(@´Ú$£:*ÛÜ3PÝ0,íîuñò,"ó_ ã0/01hpÓæp%Í ù'\%ú û0/01:ú û<Claim 1>(the contents of Claim 1)<Claim 2>(the contents of Claim 2)<Claim 3>(the contents of Claim 3)
Figure 1. Structure in the claims

shown in Figure 1, into the claims. This is so that weare easily able to recognize the claims of the patent.
By applying Mdiff to claims of a patent and its embodiments after both have been transformed so that eachline has one word, we obtained the results shown in
Figure 2. Next, we obtained the results shown in Figure 3 by eliminating the upper parts of the differences,i.e., those that correspond to the claims, and leaving
symbols such as <Claim 1> in place. The symbols
such as <Claim 1> are only inserted in the data ofthe embodiments. We are then able to recognize theclaims of the patent that correspond with a given partof the embodiments.
To put this simply, we place information to indicate
claim numbers in the data of embodiments. We thenuse the merging function of Mdiff to match the parts ofthe claims and embodiments. Then, by eliminating thecontents of the claim, we are left with information on
the claim numbers. We can easily align a claim with acorresponding embodiment by using Mdiff.
We used this method for the first thousand patents
among the patents given from PATENT of NTCIR-3.
Some patents were aligned roughly well. Some patents  In Japanese patents, we can use existing symbols such as “

” instead of <Claim 1>.

Proceedings of the Third NTCIR Workshop

Table 2. The results of Mdiff of a claim
and its embodiment
The results of Mdiff;===== begin =====
Claim 1.
A;—————–
The;===== end =====
method;===== begin =====
forpredicting;—————–
predicts;===== end =====
whether
data
that
is
not
yet
known
to
be
positive



Ä
V


Its embodimentThe
predicts

were not aligned well at all. We did not examine theaccuracy rates. One example of roughly good alignment is shown in Table 5. The claims of it  are shown in
Table 4. Words surrounded by brackets, “ ” and “ ”,
in Table 5 appear in claims and embodiments. In Table 5, two marks for index numbers for claims, “” (Claim 1) and “” (Claim 2),) describes
were inserted. Paragraph 15 (Claim 2, so the result is roughly good. However, Paragraph 16 contains the content of Claim 1, not of Claim
2. So, the result is not so good. The reasons for producing bad results are as follows: The contents in embodiments are not in the same order as in the claims.
The contents of a certain claim appear in several separate parts of embodiments. Mdiff can be used only
when the contents of a certain claim appear in one party z +¢~v§wy z B6~v ÖÖ0+>¿r~

Claims(provide)(based on)(provide)

Embodiments

cg (have)cÈ (according to)





(attach);===== begin =====<Claim 1>(content of the claim only);—————–(content of the embodiment only);===== end =====(content of the claim and embodiment);===== begin =====(content of the claim only);—————–(content of the embodiment only);===== end =====(content of the claim and embodiment);===== begin =====<Claim 2>(content of the claim only);—————–(content of the embodiment only);===== end =====

Table 3. The differences between a claim
and its embodiment
A claim
Claim 1. A
for predicting

Table 6. The differences between claims
and embodimentsv§w

Figure 2. Results of applying Mdiff toclaims of a certain patent and embodiments of it

of embodiments and it appears in the same order as in
the claim. There are many cases when our supposition
is not true. We may have better used another method
such as passage retrieval based on a bag of words. 
However, our method of using Mdiff is a very simple
method, and it can be used very easily. We can obtain even a few useful results, such as in Table 5, very
easily by using Mdiff.

5 Extraction of differences between
claims
We finally made experiments extracting differencesamong plural claims in a patent. This study is a newtrial. We applied Mdiff to two claims among plural
claims in a patent after both claims had been transFor the alignment of the transcription and its corresponding paper, the technologies of information retrieval or similar methods
were used [11, 1].

The Third NTCIR Workshop, Sep.2001 - Oct. 2002

<Claim 1>
Table 7. The differences between original
abstracts and JAPIO’s abstracts (Samemeaning)
Freq.
1752

Original!#"0/1hp \]&%p´/1$(obtain)(mentioned previously)°rJ(mentioned above)(is done)(do)(the corresponding)(this)(that is)× (6, /1
(so as to)·1×)(%,(that is a goal)
1135
1129
1011
837

(content of the claim and embodiment)

JAPIO(provide)
1350

=1

á

hp:,'01

795
756(content of the embodiment only)<Claim 2>

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1(so that)¸:á
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711 hp6'01(that is)692 *.$'01(that is)640 hp &\ +#,*p´/1(that is a characteristic)/01.u$I8g.W
579 g

Figure 4. A sample of claims of a certain
patent(do. And)

formed so that each line has one word. We obtained
results such as in Figures 6 and 7. Figure 6 is the result of claims in Figure 4 and Figure 7 is the result ofclaims in Figure 8. From this result, we can understand differences of claims very easily. For example,
inFigure 6 we found that the differences are “-.
” (host system) and “0/” (printer). However, when the differences are more complicated, theresults of Mdiff are difficult to see as shown in Figure
7. We found that Mdiff has trouble when differences
are complicated.
To solve this problem, we developed two new methods of obtaining differences. These methods do not
use the Diff command, so they are not suitable for our
purpose of using Diff. However, these new methods
are useful, so we show them here.
The first new method extracts all words from all
claims of a patent other than the currently analyzed
claim and specifies words in the currently analyzed
claim that do not appear in other claims. The resultis shown in Figure 9. The words that do not appear

 %3c

(content of the embodiment only)
Figure 3. Results of insertion of information on claim numbers in embodiments

751

(do)

(content of the embodiment only)µin other claims are surrounded by brackets, “ ” and“ ”. The result is easier to see than the result of Figure 7. From Figure 9, we very easily found that the” (Claim 2) is “characteristic of “
” (a device to prevent slipping
H9I3J
KPQM
at the upper and lower parts). If we understand the” (a device tocharacteristic of Claim 2 is “KM
prevent slipping), we can extract embodiments corresponding to Claim 2 easily by extracting paragraphs” (a device to prevent
containing this term “KM
slipping). In the example of Figure 5, we can obtainthe correct corresponding part, Paragraph 15, which” (a device to prevent
contains the term “K0RM
slipping). This method is very useful for extracting
distinguishing characteristics and it can be also used
for extracting the corresponding part of embodiments
to a certain claim, i.e., aligning claims and embodiments in Section 4.
Next, we used the first new method for another casewhich has three claims such as in Figure 10. In thiscase, we obtained a result shown in Figure 10. In thisresult, we could not obtain the characteristics of Claim”. To solve this problem,
2 and Claim 3, “KPSM
we made the second new method. This method extracts all words from all claims of a patent above the$tv wy8z B%~
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Proceedings of the Third NTCIR Workshop

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1  h@&p =,*>× r c©¥= ,0© W=V= 1 u\C  O\ )
h(IPj jhp%#H  Ap z01 u TFigure 5. Actual results of insertion of information on claim numbers in embodiments$0/r30.LTG)¡$X;=====
begin =====
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Y/%3.LG
T )¡$.Y Z8D £u;===== end =====

Figure 6. A result of Mdiff of claims(Case 1);=====
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;—————–;—————–)

;===== end =====

hp$\A+#,*p:/01OC F u
Figure 7. A result of Mdiff of claims(Case 2)currently analyzed claim and specifies words in thecurrently analyzed claim that are not appearing in theabove claims. The result is shown in Figure 11. In
this case, we could extract the characteristics of Claim”, in Claim 2. With this
2 and Claim 3, “KPSM
method, we can find new terms as distinguishing characteristics. This method is also useful.
Although these two new methods did not use Diff
commands, they used an idea of extracting differencesin Diff commands. We think that these methods haveinteresting aspects as Diff has. In the future work, wewould like to use these two methods for other applications of natural language processing. ¤>t¥For example, we are now thinking of using the second new
method to examine the problems of new information and old information in anaphora resolution [10, 4].

The Third NTCIR Workshop, Sep.2001 - Oct. 2002

xv wyz +9ar~P /630>L8T`5¡ X>µ -. \/1hp \O+,"pP/01Pwy z+$Á ¢.]/%3L TG\¡>PY8Z8D £uvxwyz #+ iÐ~P8  /630>L8`T 5¡ X(]
 /3\/1hp O\ +,"pP/01Pwy z +$Á ¢.]/%3L GT \¡>PY8Z8D £uFigure 8. The claims of Case 2

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08h0p$A\ +#,*p:/O1 C# u


1

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

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657
p$/@1@pcp*8,) :3;57@,<==°´àc8ct8,
@ØO?*\OPQ0hp \O+,"pP/1C0Fu v§w0y z B%`~ @YØ ?  8#t ,  F KPRMc`8t"\§0hp$A
\ +#,*p:/0O1  C uv§wy$zý
%
l
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t'\  hp$A\ +#,*p:/0O1 C F u
Figure 11. A result of New Method 21Figure 9. A result of New method 1

vxw*y=z +Ð ~  1 t'91  ë'G#  1 @t \240,åß=gG67 1 *p(/1 pp* ,  :;
70,<B=°ràc.
t0, @Ø?*\ P08h0p$A\ +#,*p:/O1 C# F u
vxwyzÏB6G~ @OØ ?>F 8t0#, KPSM$t*\ \ 0hp$A\ +#,*p:/O1 C# u 
vxwyz l%G~ 'OØ ?$8t H9I\Jt 0, K0QM
t'\  8h0p$A\ +#,*p:/O1 C# F uFigure 10. A result of New Method 1 withanother case

6 Conclusion
In the PATENT task of NTCIR-3, we participated in
the optional task, where the participants can perform
any kind of research relating to patents, and we madethe following three kinds of studies.
1. We extracted rewriting rules using data ofpatents.
2. We aligned a patent claim and its embodiment.
3. We extracted differences among plural claims ina patent.
We had shown many examples in the previous papers [6, 8, 9]. In the current study, we could also show
more examples of a Diff command and show its usefulness and effectiveness. We hope that Diff will beapplied to an ever-widening range of studies.
In Section 5, we showed two new methods not using Diff. These methods would also be interesting. In
future work, we would like to use them for many otherapplications of natural language processing.

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