A Corpus for Classifying Usages ofJapanese Compound Functional Expressions
Masatoshi Tsuchiya† and Takehito Utsuro‡ and Suguru Matsuyoshi‡
Satoshi Sato†† and Seiichi Nakagawa‡‡†Computer Center / ‡‡Department of Information and Computer Sciences,Toyohashi University of Technology, Tenpaku-cho, Toyohashi, 441–8580, Japan‡Graduate School of Informatics, Kyoto University, Sakyo-ku, Kyoto, 606–8501, Japan††Graduate School of Engineering, Nagoya University,
Furo-cho, Chikusa-ku, Nagoya, 464–8603, JAPAN
Abstract
Aiming at being used as a corpus for training/testing a tool which properly recognizes and interprets Japanese (compound)functional expressions, this paper studies how to develop a corpus of Japanesefunctional expressions. This paper focuses on 125 major (mostly compound)functional expressions which have noncompositional usages, and reports current
status of developing a corpus of those major functional expressions.

1 Introduction
As in the case of other languages, the Japanese language has various types of functional words such as
post-positional particles and auxiliary verbs. In addition to those functional words, the Japanese language has much more compound functional expressions which consist of more than one words including both content words and functional words.
Those single functional words as well as compound
functional expressions are very important for recognizing the syntactic structures of Japanese sentences and for understanding their semantic contents. Recognition and understanding of them arealso very important for various kinds of NLP applications such as dialogue systems, machine translation, and question answering. However, recognitionand semantic interpretation of compound functional
expressions are especially difficult because it often
happens that one compound expression may haveboth a literal (in other words, compositional) content word usage and a non-literal (in other words,non-compositional) functional usage.
For example, Table 1 shows two example sentences of a compound expression “に (ni) ついて(tsuite)”, which consists of a post-positional particle“に (ni)”, and a conjugated form “ついて (tsuite)” ofa verb “つく (tsuku)”. In the sentence (A), the compound expression functions as a case-marking particle and has a non-compositional functional meaning“about”. On the other hand, in the sentence (B), theexpression simply corresponds to a literal concatenation of the usages of the constituents: the postpositional particle “に (ni)” and the verb “ついて(tsuite)”, and has a content word meaning “follow”.
Therefore, when considering machine translation of
those Japanese sentences into English, it is necessary to precisely judge the usage of the compound
expression “に (ni) ついて (tsuite)”, as shown in theEnglish translation of the two sentences in Table 1.
There exist widely-used Japanese text processing
tools, i.e., pairs of a morphological analysis tool anda subsequent parsing tool, such as JUMAN1 + KNP2and ChaSen3 + CaboCha4 . However, they process
those compound expressions only partially, in that
their morphological analysis dictionaries list only
limited number of compound expressions. Furthermore, even if certain expressions are listed in a morphological analysis dictionary, those existing tools
often fail in resolving the ambiguities of their usages, such as those in Table 1. This is mainly because the framework of those existing tools is notdesigned so as to resolve such ambiguities of compound (possibly functional) expressions by carefully
considering the context of those expressions.
Considering such a situation, it is necessary to1

http://www.kc.t.u-tokyo.ac.jp/
nl-resource/juman-e.html
2
http://www.kc.t.u-tokyo.ac.jp/
nl-resource/knp-e.html
3
http://chasen.naist.jp/hiki/ChaSen/
4
http://chasen.org/˜taku/software/cabocha/Table 1: Translation Selection of a Japanese Compound Expression “に (ni) ついて (tsuite)”
私 (watashi) は (ha) 彼 (kare)に (ni) ついて (tsuite)
話した (hanashita)
(A)
(I)
(TOP)
(he)
(about)(talked)(I talked about him.)
私 (watashi) は (ha) 彼 (kare) に (ni) ついて (tsuite) 走った (hashitta)
(B)
(I)
(TOP)
(he)
(ACC)
follow(ran)(I ran following him.)
Table 2: Classification of Functional Expressions based on Grammatical Function# of major# ofGrammatical Function Typeexpressions variants
Examplesubsequent to predicate
3667となると
post-positional/ modifying predicate(to-naru-to)
particle
subsequent to nominal
45
121
にかけては
type
/ modifying predicate(ni-kakete-ha)
subsequent to predicate, nominal
23という/ modifying nominal(to-iu)auxiliary verb type42
146ていい (te-ii)
total
125
337
—
develop a tool which properly recognizes and semantically interprets Japanese compound functional
expressions in a scale much larger than existing
Japanese text processing tools. Especially aiming
at being used as a corpus for training/testing sucha tool, this paper studies how to develop a corpus
of Japanese functional expressions. We focus on
125 major (mostly compound) functional expressions which have non-compositional usages, and report current status of developing a corpus of thosemajor functional expressions.

2 Developing a Corpus of Japanese
Functional Expressions
2.1

Japanese Functional Expressions

There exist several collections which list Japanesefunctional expressions and examine their usages.
For example, (Morita and Matsuki, 1989) examines450 functional expressions and (Group Jamashii,1998) also lists 965 expressions and their example
sentences. Compared with those two collections,Gendaigo Hukugouji Youreishu (National Language
Research Institute, 2001) (henceforth, denoted asGHY) concentrates on 125 major functional expressions which have non-compositional usages, as wellas their variants5 (337 expressions in total), and col5
For each of those 125 major expressions, the differences
between it and its variants are summarized as below: i) insertion/deletion/alternation of certain particles, ii) alternation oflects example sentences of those expressions. As afirst step of developing a corpus of Japanese functional expressions, we start with those 125 major
functional expressions and their variants.
As in Table 2, according to their grammatical
functions, those 337 expressions in total are roughlyclassified into post-positional particle type, and auxiliary verb type. Functional expressions of postpositional particle type are further classified into
three subtypes: i) those subsequent to a predicate
and modifying a predicate, which mainly function
as conjunctive particles and are used for constructing subordinate clauses, ii) those subsequent to anominal, and modifying a predicate, which mainlyfunction as case-marking particles, iii) those subsequent to a nominal, and modifying a nominal, whichmainly function as adnominal particles and are used
for constructing adnominal clauses. For each of
those types, Table 2 also shows the number of major
expressions as well as that of their variants listed in
GHY, and an example expression. Furthermore, Table 3 gives example sentences of those example expressions as well as the description of their usages.
2.2Classification of Functional/Content Usages

The task of developing a corpus of Japanese functional expressions roughly consists of collecting exsynonymous words, iii) normal/honorific/conversational forms,iv) base/adnominal/negative forms.

Table 3: Examples of Classifying Functional/Content Usages(1)

Expression

Example Sentence (English Translation)

Usageとなるとしかしこの病気に効果がない となると事は重大だ。
(The situation is serious if it is not effective
against this disease.)
彼が社長になるための条件の一つとなると 考えられている。

functional(to-naru-to)
(2)

(3)

(4)となると(to-naru-to)(They think that it will become a requirement for him to be the president.)

にかけてはお金を儲けること にかけては 素晴らしい才能をもっている。

(ni-kakete-ha)(He has a great talent for earning money.)にかけてはあまり気 にかけては いない。

(ni-kakete-ha)(I do not worry about it.)(5)という(to-iu)

彼は生きている という 知らせを聞いた。
(I heard that he is alive.)(6)という「遊びに来て下さい」 という 人もいる。

(to-iu)(Somebody says “Please visit us.”.)(7)ていい(te-ii)

この議論が終ったら休憩し ていい 。
(You may have a break after we finish thisdiscussion.)(8)ていいこのかばんは大きく ていい 。

(te-ii)(This bag is nice because it is big.)

ample sentences of those expressions and of judging
the usages of those expressions. Most of the 125 major functional expressions we consider in this paper
are compound expressions which consist of one ormore content words as well as functional words. As
we introduced with the examples of Table 1, it is often the case that they have both a compositional content word usage as well as a non-compositional functional usage. For example, in Table 3, the expression “となると (to-naru-to)” in the sentence (2) has
the meaning “ that (something) becomes ∼”, whichcorresponds to a literal concatenation of the usagesof the constituents: the post-positional particle “と”,the verb “なる”, and the post-positional particle “と”, and can be regarded as a content word usage.
On the other hand, in the case of the sentence (1),(となると (to-naru-to) = if)content(∼ となると (to-naru-to)= that (something) becomes ∼)functional(∼ にかけては (ni-kakete-ha)= for ∼)content( (∼ を) 気にかけては((∼)-wo-ki-ni-kakete-ha)= worry about ∼)functional(∼ という (to-iu) = that ∼)content(∼ という (to-iu)= say (that) ∼)functional(∼ ていい (te-ii) = may ∼)content(∼ ていい (te-ii)= nice because ∼)the expression “となると (to-naru-to)” has a noncompositional functional meaning “if”.
Based on the discussion above, in the current version of the corpus, we classify the usages of thoseexpressions into two classes: functional and content. Here, functional usages include both noncompositional and compositional functional usages,
although most of the functional usages of those
125 major expressions can be regarded as noncompositional. On the other hand, content usages
include compositional content word usages only.
2.3

Procedure of Corpus Development

The corpus from which we collect example sentences of functional expressions is 1995 Mainichi
newspaper text corpus (1,294,794 sentences,Table 5: Number of Expressions classified by Rate of Functional Usage (for 127 Functional Expressions)
Rate of Functional Usage
100% 100∼90% 90∼50% 50∼0%28149

Grammatical Function Typesubsequent to predicate
post-positional/ modifying predicate
particle
subsequent to nominal
type/ modifying predicate
subsequent to predicate, nominal/ modifying nominal
auxiliary verb type
total
Table 4: Number of Sentences collected from 1995
Mainichi Newspaper Texts (for 337 Expressions)50 ≤ # of sentences
0 < # of sentences < 50
# of sentences = 0# of expressions
187 (55%)
117 (35%)
33 (10%)47,355,330 bytes). For each of the 337 expressions,m (set as 50 in the current version of the corpus)
sentences are collected according to the followingprocedure.
1. The expression is morphologically analyzed by
MeCab6 , and its morpheme sequence7 is obtained.
2. The corpus is morphologically analyzed by
MeCab, and m sentences which include themorpheme sequence of the expression are collected.
3. Each sentence is annotated with one of the usages functional/content by an annotator.
4. At least one researcher validates the annotationof the usage.
5. (For the collected m sentences, if the rateof functional usage is less than a thresholdp, sentences with functional usage are collected by considering the constraints against
the immediately preceding morpheme as wellas those against immediately subsequent morpheme. Similarly, if the rate of content usage isless than a threshold q, sentences with content
6

http://chasen.org/˜taku/software/mecab/
For those expressions whose constituent has conjugationand the conjugated form also has the same usage as the expression with the original form, the morpheme sequence is expanded so that the expanded morpheme sequences include thosewith conjugated forms.
718973030032521434627214usage are collected.)83 Corpus of Japanese Functional
Expressions: Current Status
First, Table 4 classifies the 337 expressions according to the number of sentences collected from the1995 Mainichi newspaper text corpus. For morethan half of the 337 expressions, more than 50 sentences are collected, although about 10% of the 377expressions do not appear in the whole corpus. We
have finished validation by at least one researcher
for 127 expressions (out of those 187 expressions
with more than 50 sentences), which include the 125
major ones. For each of the grammatical function
types of functional expressions listed in Table 2, Table 5 classifies the expressions of that type according to the rate of functional usage. Roughly speaking, functional expressions of the auxiliary verb typetend to have high rate of functional usage. Among
those of the post-positional particle types, thosewhich funtion as case-marking particles also tend tohave high rate of functional usage. These are partly
because of the characteristics of the newspaper text.

4 A Corpus Browsing Tool
We also developed a tool for browsing the corpus
of Japanese functional expressions. This tool is forbrowsing the example sentences of Japanese functional expressions and also for selectively retrieving
sentences which satisfy certain constraints. Specificfacilities of the tool are described as below.
First, the list of 125 major functional expressions
as well as their variants (337 expressions in total)
can be browsed. Those functional expressions are8In the current version of the corpus, this requirement is ignored.

classified according to their grammatical functions
as in Table 2.
Second, among those 337 expressions, for 127 expressions for which we have finished validation by aresearcher, example sentences annotated with functional/content usage distinction are browsed. The
tool also has a facility of showing the result of morphological analysis of each sentence, where the sentence is segmented into the sequence of morphemes
annotated with their parts-of-speech. Figure 1 (a)shows the snapshot of the browser for the expression “∼ となると (to-naru-to)”, whose usages aredescribed in the sentences (1) and (2) of Table 3of the paper. In this snapshot, for simplicity, partsof-speech of the morphemes are annotated only tothe morpheme immediately preceding the expression, and the part-of-speech tags are translated intoEnglish.
Third, example sentences can be selectively retrieved by specifying constraints on the parts-ofspeech of the morphemes around the expression.
Figure 1 (b) shows the snapshot of the browser specifying the parts-of-speech of the immediately preceding morpheme as noun or adverb. In this case,the retrieved example sentences are those with content usage, which is described in the sentence (2) ofTable 3 of the paper. Similarly, Figure 1 (c) shows
the snapshot of the browser specifying the parts-ofspeech of the immediately preceding morpheme asverb or adjective or auxiliary verb. In this case,the retrieved example sentences are those with functional usage, which is described in the sentence (1)of Table 3 of the paper. This facility of selective retrieval with constraints is very useful for discovering
effective features when developing a tool of recognizing and judging the usage of those functional expressions.

5 Concluding Remarks
Aiming at being used as a corpus for training/testinga tool which properly recognizes and semanticallyinterprets Japanese (compound) functional expressions, this paper studied how to develop a corpus
of Japanese functional expressions. We focused on
125 major (mostly compound) functional expressions which have non-compositional usages, and reported current status of developing a corpus of thosemajor functional expressions.

References
Group Jamashii, editor. 1998. Nihongo Bunkei Jiten. Kuroshio
Publisher. (in Japanese).
Y. Morita and M. Matsuki. 1989. Nihongo Hyougen Bunkei,volume 5 of NAFL Sensho. ALC. (in Japanese).
National Language Research Institute. 2001. Gendaigo Hukugouji Youreishu. (in Japanese).

(a) Without Constraints on the POS of the Left Morpheme(b) With the Constraints on the POS of the Left Morpheme as “Noun,Adverb”.

(c) With the Constraints on the POS of the Left Morpheme as “Verb,Adjective,AuxiliaryVerb”.
Figure 1: Example Sentences of a Functional Expression “∼ となると (to-naru-to)”