Construction and Analysis of Japanese-English Broadcast News Corpus
with Named Entity Tags
Tadashi Kumano, Hideki Kashioka and Hideki Tanaka
ATR Spoken Language Translation Research Laboratories
2–2–2, Hikaridai, Keihanna Science City, Kyoto 619–0288, Japan
{tadashi.kumano, hideki.kashioka, hideki.tanaka}@atr.co.jp
Takahiro Fukusima
Otemon Gakuin University
1–15, Nishiai 2-chome, Ibaraki, Osaka 567–8502, Japan
fukusima@res.otemon.ac.jp
Abstract
We are aiming to acquire named entity
(NE) translation knowledge from non-
parallel, content-aligned corpora, by uti-
lizing NE extraction techniques. For this
research, we are constructing a Japanese-
English broadcast news corpus with NE
tags. The tags represent not only NE
class information but also coreference in-
formation within the same monolingual
document and between corresponding
Japanese-English document pairs. Anal-
ysis of about 1,100 annotated article pairs
has shown that if NE occurrence informa-
tion, such as classes, number of occur-
rence and occurrence order, is given for
each language, it may provide a good clue
for corresponding NEs across languages.
1 Introduction
Studies on named entity (NE) extraction are mak-
ing progress for various languages, such as En-
glish and Japanese. A number of evaluation work-
shops have been held, including the Message Under-
standing Conference (MUC)
1
for English and other
languages, and the Information Retrieval and Ex-
traction Exercise (IREX)
2
for Japanese. Extraction
accuracy for English has reached a nearly practi-
cal level (Marsh and Perzanowski, 1998). As for
Japanese, it is more diﬃcult to find NE bound-
1
http://www.itl.nist.gov/iaui/894.02/
related_projects/muc/
2
http://nlp.cs.nyu.edu/irex/
aries, however, NE extraction is relatively accurate
(Sekine and Isahara, 2000).
Most of the past research on NE extraction used
monolingual corpora, but the application of NE ex-
traction techniques to bilingual (or multilingual) cor-
pora is expected to obtain NE translation pairs. We
are developing a Japanese-English machine trans-
lation system for documents including many NEs,
such as news articles or documents about current
topics. Translating NE correctly is indispensable for
conveying information correctly. NE translations,
however, are not listed in conventional dictionaries.
It is necessary to retrieve NE translation knowledge
from the latest bilingual documents.
When extracting translation knowledge from
bilingual corpora, using literally translated parallel
corpora, such as oﬃcial documents written in sev-
eral languages makes it easier to get the desired in-
formation. However, not many of such corpora con-
tain the latest NEs. There are few Japanese-English
corpora which are translated literally. Therefore,
we decided to extract NE translation pairs from
content-aligned corpora, such as multilingual broad-
cast news articles including new NEs daily, which
are not literally translated.
Sentential alignment (Brown et al., 1991; Gale
and Church, 1993; Kay and R¨oscheisen, 1993; Ut-
suro et al., 1994; Haruno and Yamazaki, 1996) is
commonly used as a starting point for finding the
translations of words or expressions from bilingual
corpora. However, it is not always possible to cor-
respond non-parallel corpora in sentences. Past sta-
tistical methods for non-parallel corpora (Fung and
Yee, 1998) are not valid for finding translations of
words or expressions with low frequency. These
methods have a problem in covering NEs because
there are many NEs that appear only once in a cor-
pus. So we need a specialized method for extract-
ing NE translation pairs. Transliteration is used for
finding the translations of NE in the source language
from texts in the target language (Stalls and Knight,
1998; Goto et al., 2001; Al-Onazian and Knight,
2002). Transliteration is useful for the names of per-
sons and places; however, it is not applicable to all
sorts of NEs.
Content-aligned documents, such as a bilingual
news corpus, are made to convey the same top-
ics. Since NEs are the essential element of docu-
ment contents, content-aligned documents are likely
to share NEs pointing to the same objects. Con-
sequently, when extracting all NEs with NE class
information from each of a pair of bilingual docu-
ments separately by applying monolingual NE ex-
traction techniques, the distribution of the NEs in
each document may be similar enough to recognize
correspondences between the NE translation pairs.
A technique for finding bilingual NE correspon-
dences will have a wide range of applications other
than NE translation-pair extraction. For example,
• Bilingual NE correspondences have clues for
identifying corresponding parts in a pair of
noisy bilingual documents.
• The similarity of any two documents in dif-
ferent languages can be estimated by NE
translation-pair correspondence.
For this research, we obtained a Japanese-English
broadcast news corpus (Kumano et al., 2002) by
the Japanese broadcast company NHK
3
, and we are
manually tagging NEs in the corpus to analyze it
and to conduct NE translation-pair extraction exper-
iments.
The tag specifications are based on the IREX
NE task (Sekine and Isahara, 1999), the evaluation
workshop of Japanese NE extraction. We extended
the specifications to English NEs. In addition, coref-
erence information between NEs, within the same
monolingual document and between the correspond-
ing Japanese-English document pairs (henceforth,
3
Nippon Hoso Kyokai (Japan Broadcasting Corporation)
(http://www.nhk.or.jp/englishtop/)
we call these in a language and across languages,
respectively), is added to each of the tagged NEs,
for NE translation-pair extraction studies.
In Section 2, we will introduce the bilingual cor-
pus used in this study and describe its characteris-
tics. Then, we will discuss tag design for NE extrac-
tion studies, and explain the tag specifications and
existing problems. The current status of corpus an-
notation under these specifications will also be in-
troduced. We analyzed an annotated part of the cor-
pus in terms of NE occurrence and translation. This
analysis will be shown in Section 3. In Section 4,
we will mention future plans for the extraction of
NE translation-pairs.
2 Constructing a Japanese-English
broadcast news corpus with NE tags
2.1 Characteristics of the NHK
Japanese-English broadcast news corpus
We are annotating an NHK broadcast news corpus
with NE tags. The corpus is composed of Japanese
news articles for domestic programs and English
news articles translated for international broadcast-
ing
4
and domestic bilingual programs
5
.
Figure 1 shows an example of a Japanese news
article and its translation in English. The original
Japanese article and the translated English article
deal with the same topic, but they diﬀer much in de-
tails. The diﬀerence arises from the following rea-
sons (Kumano et al., 2002).
Audience Content might be added or deleted, ac-
cording to the audience, especially for interna-
tional broadcasting.
Broadcasting date The broadcasting of English
news is often delayed compared to the origi-
nal Japanese news. The time expressions might
be changed sometimes or new facts might be
added to the articles.
News styles/languages Comparing news articles
of two languages reveals that they have diﬀer-
ent presentation styles, for example, facts are
sometimes introduced in a diﬀerent order. The
4
NHK WORLD (http://www.nhk.or.jp/
nhkworld/)
5
http://www.nhk.or.jp/englishtop/
program_list/
Original article in Japanese (and its literal translation in English by authors):
1:�
UMoM��~	~apV�O�
����	G���M�
UK��ap

S�	�`�`h{
(There was a strong earthquake at 6:42 this morning in Izu Islands, the site of recent
numerous earthquakes. An earthquake of a little less than five in seismic intensity was
observed at Shikine Island.)
2:\w�T
S�U	�az
�az
S~Ubaz~Paz�hf���
i,]
w��p
S���w3��`�`h{
(In addition, an event of seismic intensity four was observed for Niijima and Kozu Is-
land, events seismic intensity three for Toshima Island and Miyake Island, and events of
seismic intensity two and one for various parts of Kanto Area and Shizuoka Prefecture.)
3:\w�
t����w	�xK��d�{
(There is no risk of tsunamis resulting from this earthquake.)
4:>	��wt���bq
o�x	�a~
�aw��p
ow
^x	G��z�

wF���b�������x�:�q
*^�oM�b{
(According to observations by the Meteorological Agency, the earthquake epicenter
was located in the sea at a depth of ten kilometers near Niijima and Kozu Island. The
magnitude of the earthquakes was estimated to be five point one.)
5:�D�T��
��U��lh�~	~apx��U�Cs	�6q��Xj�Mh
	�6��&`oMoz
�D~	G��~Pap
S�	w�M�
��s`
h
S��w�
U�sIV�`h{
(In Izu Islands, where seismic activity has been observed from the end of June, repeated
cycles of seismic activity and dormancy have been observed. On the 30th of the previ-
ous month, a single strong earthquake having seismic intensity of a little less than six
was observed at Miyake Island, while two earthquakes having seismic intensity of five
were also observed there.)
6:\��w�
��o��w�
��px
�a�	�az~Pap
S�	w�
M3���s`hw��o\��pt
S�	�	�w�
U	G�sIVo
M�b{
(In a series of seismic events, seventeen earthquakes having seismic intensity over five
have been observed up to this point, including strong tremors with a seismic intensity
of a little less than six observed four times at Kozu Island, Niijima, and Miyake Island.)
Translated article in English:
1: A strong earthquake jolted
Shikine Island, one of the Izu
islands south of Tokyo, early
on Thursday morning.
2: The Meteorological Agency
says the quake measured five-
minus on the Japanese scale of
seven.
3: The quake aﬀected other is-
lands nearby.
4: Seismic activity began in the
area in late July, and 17 quakes
of similar or stronger intensity
have occurred.
5: Oﬃcials are warning of more
similar or stronger earthquakes
around Niijima and Kozu Is-
lands.
6: Tokyo police say there have
been no reports of damage
from the latest quake.
Figure 1: An article pair in an NHK broadcast news corpus
diﬀerence is due to language and socio-cultural
backgrounds.
2.2 NE tag design
We designed NE tags for NE translation-pair extrac-
tion research and working eﬃciency for manual an-
notation. The specifications are shown below.
• It is desirable that NE recognition guidelines
be consistent with NE tags of existing corpora.
Past guidelines of MUC and IREX should be
respected because they were configured as a re-
sult of many discussions. Consistent guidelines
enable us to utilize existing annotated corpora
and systems designated for the corpora.
• Within each bilingual document pair, corefer-
ence between NEs in a language and across lan-
guages will be specified. When several NEs
exist for the same referent in a document, it
is not always possible to determine the actual
translation for each instance of the NEs from
the counterpart document, because our corpus
is not composed of literal translations. There-
fore, coreference between NEs in a language
should be marked so that the coreference across
languages can be assigned between NE groups
that have the same referent. Coreference be-
tween NE groups is suﬃcient for our purpose.
• Assignment of coreference in a language is lim-
ited between NEs only. Although NEs may
have the same referent with pronouns or non-
NE expressions, these elements are ignored to
avoid complicating the annotation work.
2.3 Tag specifications
1. The tag specifications conform to IREX NE
tag specifications (IREX Committee, 1999) (an
English description in (Sekine and Isahara,
1999)) as regards the markup form, NE classes,
and NE recognition guidelines.
Japanese:
�
UMoM�<LOCATION ID=”1” COR=”2”>
(Izu Islands)
�~	~a</LOCATION>
p<DATE ID=”2” COR=”4”>
(today)
V�O</DATE><TIME ID=”3” COR=”5”>
(a.m.)
�
�
(6:42)
���	G��</TIME>�M�
UK�<LOCATION ID=”4” COR=”1”>
(Shikine Island)
�a</LOCATION>p
S�	�`�`h{···
English:
A strong earthquake jolted <LOCATION ID=”1” COR=”4”>
Shikine Island</LOCATION>, one of the <LOCATION ID=”2”
COR=”1”>Izu islands</LOCATION> south of <LOCATION ID=”3”>
Tokyo</LOCATION>, early on <DATE ID=”4” COR=”2”>Thursday
</DATE><TIME ID=”5” COR=”3”>morning</TIME>. ···
Figure 2: An annotation example
NE Class Example
Named entities (in the narrow sense):
ORGANIZATION The Diet; IREX Committee
PERSON (Mr.) Obuchi; Wakanohana
LOCATION Japan; Tokyo; Mt. Fuji
ARTIFACT Pentium Processor; Nobel Prize
Temporal expressions:
DATE September 2, 1999; Yesterday
TIME 11 PM; midnight
Number expressions:
MONEY 100 yen; $12,345
PERCENT 10%; a half
Table 1: NE Classes
Eight NE classes were defined at the IREX NE
task — the same 7 classes as MUC-7 (3 types
of named entities in the narrow sense, 2 types
of temporal expressions, and 2 types of number
expressions), and ARTIFACT (concrete objects
like commercial products and abstract objects
such as laws or intellectual properties). Table 1
shows a list of these.
2. IREX’s NE classes and NE recognition guide-
lines are applied to English for consistency be-
tween Japanese and English NEs. For English-
specific annotation, such as prepositions or de-
terminers in NE, the MUC-7 Named Entity
Task Definition (Chinchor, 1997) is consulted
6
.
3. The SGML markup form of the IREX tag is
extended by adding the following two tag at-
tributes, which represent coreference informa-
tion in a language, and across languages.
ID=”NE group ID” (mandatory)
Each NE is assigned an attribute ID and
an ID number as its value. All corefer-
ent NEs in each language document are
6
The tag specifications of IREX NE and those of MUC-7 do
not diﬀer radically, because IREX NE tags are designed based
on the discussions of MUC.
given the same ID number
7
. The same
ID number is assigned to NEs that have
diﬀerent forms, such as the full name and
the first name or the oﬃcial name and the
abbreviated form, in addition to NEs with
the same form. Basically, NE are assigned
the same ID number when they belong to
an NE class and have the identical surface
form
8
.
COR=”ID for corresponding NE groups in
the other language” (optional)
When there exists a corresponding NE
(group) belonging to the same NE class
in the other language, an attribute COR
is given to each NE (group) in both lan-
guages, and the ID number for the coun-
terpart is assigned as a value to each other.
Annotations by the specifications are illustrated
in Figure 2.
2.4 Current status of the corpus annotation
Annotators who have experience in translation work
and in the production of linguistic data are engaging
in the tag annotation. Plans call for a total of 2,000
article pairs to be annotated, and about 1,100 pairs
have been finished up to the present.
2.5 Problems
Some problems became obvious in the course of
discussions of tag specifications and tag annotation
work. They confuse annotators and make the result
inaccurate. Typical cases are shown below.
2.5.1 The granularity diﬀerence between
Japanese and English
In Japanese, a unit smaller than a morpheme may
be accepted as an NE according to IREX guidelines.
7
ID numbers do not maintain uniqueness across the docu-
ments.
8
There are some exceptions. See Section 2.5.3.
(last Sunday and this Sunday)
sensyuu-no nichiyou -to konsyuu-no nichiyou
J:
�	?w<DATE ID=”1”>�5</DATE>q	?w<DATE ID=”2”>�5</DATE>
E: <DATE COR=”1”>last Sunday</DATE> and <DATE COR=”2”>this Sunday</DATE>
Figure 3: Assignment of diﬀerent group IDs with NEs having the same surface form
On the other hand, English does not accept any unit
smaller than a word by MUC-7 guidelines. Some
Japanese NEs cannot have a counterpart English
NE, even if they have a corresponding English ex-
pression because of the diﬀerence in the segmenta-
tion granularity. For example, “����(amerika;
America)” in the Japanese morpheme “����

(amerika-jin; America-people)” is treated as an NE,
while no NE can be tagged to “American”, the En-
glish counterpart of “����
.”
2.5.2 Translation problems
NEs have the same problem that translation in
general has: What is the exact translation word(s)
for an expression?
• Semantically corresponding expressions may
not be assigned corresponding NE relations,
because they belong to diﬀerent NE classes or
an expression in a language is not recognized
as an NE. For example, a non-NE word “
S�
(seifu; government)” which means Japanese
government in Japanese articles is often trans-
lated as the English NE: “Japan.”
• A non-literal translation of an NE may cause
diﬃculty in recognizing corresponding rela-
tions. Correspondences for some expressions
cannot be decided with the information repre-
sented in documents: Relative temporal expres-
sions in Japanese are often translated as ab-
solute expressions in English and those corre-
spondences cannot be identified without con-
sulting the calendar; Money expressions are
generally converted to dollars and the ex-
change rate at the relative time is needed to
confirm correspondences. For example, we
found a translation pair of money expressions
“~
�/(sanzen-oku-en; three hundred bil-
lion yen)” and “three billion U-S dollars” in our
corpus, which constitutes a rough conversion
from yen into dollars when the articles were
produced.
2.5.3 Assigning NE group IDs
We defined NEs that have the identical surface
form and the same NE class to be coreferent and
assigned the same NE group ID, in order to make
coreference judgment easier. There are some cases
where we cannot apply this rule, especially to tem-
poral expressions or number expressions.
The example in Figure 3 shows the translation
pair “
�	?w�5q	?w�5(last Sunday and this
Sunday)” and “last Sunday and this Sunday” anno-
tated with NE tags. Japanese temporal expressions
“
�	?w�5(last Sunday)” and “	?w�5(this
Sunday)” are translated into English as “last Sun-
day” and “this Sunday” respectively. When anno-
tating NE tags for this translation pair, only “�5
(Sunday)” in those temporal expressions in Japanese
is regarded as an NE according to the IREX’s NE
specifications. This causes a problem in which the
two NEs of the same surface form that are assigned
the same NE class have diﬀerent referents. Each of
them should assign correspondence to diﬀerent NEs
in the counterpart: the former to “last Sunday” and
the latter to “this Sunday.”
Tentatively, we allowed a diﬀerent NE group ID to
be assigned to an NE with the identical surface form
in an NE class, as shown in Figure 3. It would be
better reexamine the consistency of the NE tag spec-
ification between Japanese and English, and the ne-
cessity of coreference information for temporal ex-
pressions and number expressions.
3 Analysis
We conducted an elementary investigation into
1,096 pairs of annotated Japanese and English ar-
ticles.
3.1 Corpus size
Table 2 shows the content size of our corpus by
the number of sentences and the morphemes/words.
The content decreases significantly when translating
from Japanese to English. This fact points out that
NE class
Japanese English
tokens
avr. per
types
avr. per
tokens
avr. per
types
avr. per
( art. / sent.) ( art. / sent.) ( art. / sent.) ( art. / sent.)
Total 24,147 (22.03/ 4.13) 12,809 (11.69/ 2.19) 15,844 (14.46/ 2.03) 10,353 ( 9.45/ 1.32)
ORGANIZATION 5,160 ( 4.71/ 0.88) 2,558 ( 2.33/ 0.44) 2,882 ( 2.63/ 0.37) 1,863 ( 1.70/ 0.24)
PERSON 3,525 ( 3.22/ 0.60) 1,628 ( 1.49/ 0.28) 2,800 ( 2.55/ 0.36) 1,410 ( 1.29/ 0.18)
LOCATION 8,737 ( 7.97/ 1.49) 3,752 ( 3.42/ 0.64) 5,792 ( 5.28/ 0.74) 3,302 ( 3.01/ 0.42)
ARTIFACT 455 ( 0.42/ 0.08) 282 ( 0.26/ 0.05) 241 ( 0.22/ 0.03) 193 ( 0.18/ 0.02)
DATE 4,342 ( 3.96/ 0.74) 2,959 ( 2.70/ 0.51) 2,990 ( 2.73/ 0.38) 2,620 ( 2.39/ 0.34)
TIME 854 ( 0.78/ 0.15) 740 ( 0.68/ 0.13) 245 ( 0.22/ 0.03) 232 ( 0.21/ 0.03)
MONEY 577 ( 0.53/ 0.10) 462 ( 0.42/ 0.08) 517 ( 0.47/ 0.07) 375 ( 0.34/ 0.05)
PERCENT 497 ( 0.45/ 0.08) 428 ( 0.39/ 0.07) 377 ( 0.34/ 0.05) 358 ( 0.33/ 0.05)
Table 3: NE frequency
articles
sentences morphemes/words
(avr. per article) (avr. per sent.)
J
1,096
5,851 (5.34) 321,204 (54.90)
E 7,815 (7.13) 181,180 (23.18)
Table 2: Corpus size
the content tends to be lost through the translation
process.
3.2 In-language characteristics of NE
occurrences
3.2.1 Frequency
The number of occurrences for each NE class is
listed in Table 3. The distribution of NE classes is
almost the same as that in the data for MUC-7 or
IREX.
By comparing the decrease in content (cf. Ta-
ble 2), the number of NE tokens also decreases for
translations. However, the degree of the NE de-
crease is less than that of the morphemes/words. It
is also remarkable that the number of NE types is
fairly well preserved. Notice that only a small num-
ber of tokens in the NE class TIME appear in En-
glish. The reason may be that detailed time infor-
mation may become less important for English ar-
ticles, which are intended for audiences outside of
Japan and broadcast later than the original Japanese
articles.
3.2.2 NE characteristics within NE groups
To examine the surface form distribution in the
same NE groups, we counted the number of mem-
bers ( freq) and sorts of surface form (sort) for each
NE group in each article. The probability that a
given member has a unique surface form in a group
NE class
Japanese English
freq sort uniq freq sort uniq
Average 1.89 1.10 0.131 1.53 1.14 0.332
ORG. 2.02 1.12 0.144 1.55 1.16 0.345
PERSON 2.17 1.12 0.121 1.99 1.49 0.655
LOCATION 2.33 1.14 0.114 1.75 1.07 0.105
ARTIFACT 1.61 1.05 0.072 1.25 1.05 0.216
DATE 1.47 1.08 0.175 1.14 1.03 0.200
TIME 1.15 1.02 0.098 1.06 1.01 0.182
MONEY 1.25 1.03 0.109 1.38 1.35 0.936
PERCENT 1.16 1.00 0.008 1.05 1.06 0.278
Table 4: Surface form distribution in the same NE
groups
that has two or more members (uniq) has also been
calculated as follows:
uniq=
freq−2
C
sort−2
freq−1
C
sort−1
=
sort−1
freq−1
( freq≥2).
Table 4 shows the values averaged for all the NE
groups that appeared in all articles.
In English, a repetition of the same expression is
not conventionally desirable. Therefore, pronouns
or paraphrases are used frequently. On the other
hand, Japanese does not have such a convention.
This diﬀerence is considered to be the reason for the
result shown in Table 4: freq in English is smaller
than that in Japanese, and sort in English is larger
than that in Japanese. As a result, uniq in English is
higher than that in Japanese. These tendencies diﬀer
slightly according to the NE classes.
• The sort of English PERSON is notably large. In
English, the name of a person is usually first ex-
pressed in full, and after that, it tends to be ex-
pressed only by the family name. In Japanese,
only the family name is generally used from the
beginning, especially for well-known persons.
NE class
J→E J←E
token type token type
Average 0.742 0.639 0.842 0.786
ORGANIZATION 0.684 0.612 0.877 0.837
PERSON 0.881 0.777 0.938 0.898
LOCATION 0.799 0.673 0.833 0.753
ARTIFACT 0.701 0.628 0.925 0.912
DATE 0.717 0.656 0.761 0.742
TIME 0.207 0.184 0.596 0.591
MONEY 0.593 0.595 0.781 0.733
PERCENT 0.712 0.692 0.830 0.827
Table 5: Cross-language corresponding rate
NE class
Japanese English
freq sort uniq freq sort uniq
Average 2.19 1.14 0.134 1.64 1.17 0.342
ORG. 2.25 1.17 0.164 1.62 1.19 0.364
PERSON 2.45 1.14 0.110 2.07 1.53 0.645
LOCATION 2.77 1.19 0.117 1.94 1.10 0.112
ARTIFACT 1.80 1.06 0.075 1.27 1.05 0.222
DATE 1.60 1.10 0.167 1.17 1.04 0.211
TIME 1.30 1.04 0.106 1.07 1.01 0.250
MONEY 1.24 1.04 0.138 1.47 1.43 0.934
PERCENT 1.20 1.00 0.010 1.06 1.01 0.250
Table 6: Surface form distribution in the same NE
groups (only for those having cross-language corre-
spondences)
• The uniq of English MONEY is quite high. A
money expression in Japanese tends to be trans-
lated into English as both the original currency
(usually yen) and dollars.
• The freq of temporal and number expressions
are smaller than those of named entities in the
narrow sense.
3.3 Cross-language characteristics of NE
occurrences
3.3.1 Correspondence across languages
We calculated the rates for a given NE in a doc-
ument to have a corresponding NE in the counter-
part language. The units of NE correspondences we
used for these calculations are both NE token and
NE group (type). The results, shown in Table 5,
show that an NE that appeared in English will have
a Japanese NE correspondent with a high rate.
We also conducted the same survey as we did in
Table 4 for only NEs having cross-language corefer-
ences, whose results are shown in Table 6. A com-
parison of both results shows that the freq for only
NEs having cross-language coreferences is larger,
NE class
J→E J←E
All Corr. only All Corr. only
All NEs 0.291 0.774 0.483 0.774
Average 0.304 0.790 0.494 0.790
ORG. 0.269 0.808 0.568 0.809
PERSON 0.403 0.877 0.671 0.875
LOCATION 0.318 0.746 0.461 0.745
ARTIFACT 0.410 0.725 0.662 0.710
DATE 0.307 0.805 0.428 0.805
TIME 0.033 0.815 0.227 0.815
MONEY 0.170 0.829 0.407 0.829
PERCENT 0.509 0.903 0.658 0.903
Table 7: Preservation ratio of NE order
especially in Japanese. An NE occurring more times
in an article may have more important information
and is more likely to appear in the translation.
3.3.2 Preservation of NE order
We investigated how well the order of NEs oc-
curring in an article is preserved in the counterpart
language as follows:
1. In every article, we eliminated all NEs except
the first occurrence of every NE group.
2. We calculated the ratio between all of the pos-
sible NE pairs in the source language and those
translated into the target language with the
same order of occurrence.
Table 7 lists the average preservation ratios of the
NE order for all NEs (“All”) and for NEs having
corresponding NEs in the counterpart (“Corr. only”).
The scores labeled “All NEs” express ratios for the
order of all NEs. The preservation ratio for each
NE class is listed below in the table. The NE or-
ders are preserved so well even for all NEs that they
can be used for determining cross-language corre-
spondences.
4 Conclusion
In this paper, in which we aimed to acquire NE trans-
lation knowledge, we described our construction of
a Japanese-English broadcast news corpus with NE
tags for NE translation-pair extraction. The tags rep-
resent NE characteristics and coreference informa-
tion in a language and across languages. Analysis
of the annotated 1,097 article pairs has shown that
if NE occurrence information, such as classes, num-
ber of occurrences and occurrence order, is given for
each language side, it may provide a good clue for
determining NE correspondence across languages.
Our future plans are listed below.
• The problems in Section 2.5 need to be reex-
amined from the point of view of what infor-
mation bilingual corpora should have for NE
translation-pair extraction research.
• The proposed analysis in Section 3 pointed out
that identifying coreferences in a language is
very important for achieving NE translation-
pair extraction. Richer coreference information
should be annotated in our corpus for coref-
erence identification studies. We are planning
to annotate coreference information for pro-
nouns and some other non-NE expressions, re-
ferring to the MUC-7 coreference task defini-
tion (Hirschman and Chinchor, 1997).
• Corpora with diﬀerent characteristics, such as a
bilingual newspaper corpus, will be annotated
and analyzed.
Acknowledgments This research was supported
in part by the Telecommunications Advancement
Organization of Japan.

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