Identification of Neologisms in Japanese Corpora using Synthesis
James Breen1, Timothy Baldwin2, Francis Bond3
1
Monash University, Melbourne, Australia
2
University Of Melbourne, Melbourne, Australia
3
Nanyang Technological University, Singapore
Abstract
We report on the investigation of a neologism detection approach involving the synthesis of possible
Japanese words by mimicking Japanese morphological processes, followed by testing for the presence ofcandidate words in Japanese corpora. A 2-kanji compound generation and classification technique resulted in
the detection of significant numbers of unrecorded terms.
Keywords: Japanese, term synthesis; n-gram corpora, neology
Introduction
This paper reports on part of a major study into the extraction of neologisms from Japanese corpora. In thestudy three main approaches were explored:a) analysis of morpheme sequences in Japanese texts to determine the presence of potential new or
unrecorded terms. The processes included processing the texts with a morphological analyzer toproduce sequences of tagged morphemes, tagging of the morphemes with features derived fromcombinatory data derived from large lexicons and corpora, and processing the tagged morphemeswith rule-based and machine-learning-based chunkers to assemble candidate words and expressions.
b) analysis of language patterns which are often used in Japanese in association with new and emerging
terms. These patterns are usually associated with discussions or explanations of new terms. (Breen etal., 2018)c) synthesis of possible Japanese terms by mimicking Japanese morphological processes, followed by
testing for the presence of candidate terms in Japanese corpora.
In this paper we report on the third of these, based on the synthesis of possible Japanese words. (Anothercomponent, covering compound verbs, has been reported separately. (Breen and Baldwin, 2009))
A central issue when dealing with neologisms in Japanese is the nature of the orthography, with its use ofmultiple scripts, primarily kanji (Chinese characters), e.g. 猫, 犬, 鳥, 牛, etc., of which approximately 2,500
are in common use and which are used mainly for nouns and the roots of verbs, adjectives, etc.; and thehiragana and katakana syllabaries, each of 46 symbols plus diacritics. A major issue is the absence of any
indication of the boundaries between the syntactic elements in texts. Automated text-processing in Japaneseusually relies on morphological analysis software such as MeCab (Kudo, 2008) which employ largemorpheme lexicons such as UniDic (Den et al., 2007), however unrecorded terms will (by definition) usually
not be found in these lexicons.
Lexicographical Aspects
The study reported here has concentrated on the identification of neologisms with a view to possibly
including them in a dictionary, and indeed many of those identified have been added to the online
JMdict Japanese dictionary (Breen, 2004). The process of assessing potential lexical items for suchinclusion is central to lexicography, and along with the establishment of an accurate translation into
the target language (English in this case) involves a range of processes and issues in determining
their suitability. In our study we have aimed identifying neologisms which are suitable for inclusion
in both coding and decoding dictionaries, an important issue as Japanese dictionaries compiled fornative speakers do not typically contain terms such as 凹状 (ôjô – concavity) as it is seen as a prefixplus-noun (concave shape), whereas the term should, and does, occur in dictionaries intended for non-nativespeakers.

The techniques used in this study focussed on terms that occur in corpora in significant enoughquantities to warrant further investigation. In addition, several of the techniques identified 2­kanji
terms which are typically nouns, and thus would be strong candidates for lexicalization. Thereremain questions such as whether identified compound nouns or multi­word expressions havemeanings which are idiomatic, novel or non­intuitive enough to warrant lexicalization. This is
widely recognized as one of the major challenges in lexicography (Atkins and Rundell, 2008). Somehave expressed the view that with the rise of electronic dictionaries, which do not have the size
limitations of printed dictionaries, there is little harm in relaxing this evaluation and including
larger numbers of non­idiomatic compounds, expressions, etc. In the case of Japanese there are
additional issues such as multiple surface­forms, reading variations, the extensive use of pseudo­
English constructions, etc. to take into account. A detailed analysis of the lexicographic issues
associated with Japanese dictionary entries, including the criteria for lexicalization, is reported
elsewhere (Breen, 2017).
Resources
As the experimentation with synthesized terms takes the form of create-and-test, a key requirement is accessto appropriate large-scale corpora to test for the presence and usage patterns of the terms.
The main accessible Japanese corpus for this type of testing is the Google n-gram Corpus (Kudo andKazawa, 2007), based on approximately 20 billion text segments extracted from WWW pages, and isprovided in the form of sets of 1-grams to 7-grams with counts of the numbers of occurrences. As the Googlecorpus only reports n-grams which occur 20 or more times a second n-gram corpus was assembled using thesmaller Kyoto University WWW Corpus, containing about 500 million text segments.
Investigation Approach
Three types of synthesized term formation were investigated:a) Abbreviation/Clipping. This is a very common and productive process in Japanese, wherein the(usually) leading character of each of the components of a composite are taken to form anabbreviated compound. An example of this is 学割 gakuwari “student discount” from the fullcompound 学生割引 gakuseiwaribiki. The terms produced by this process are typically nouns or
adjectival nouns, and hence if valid would be clear candidates for lexicalization.
b) Affixation. The addition of prefixes and suffixes, often written with a single kanji, is a very common
morphological process in Japanese (Tsujimura, 2006). Vance (1991) describes 63 single-kanji affixes
commonly employed. The process is very productive and the resulting terms are not usuallylexicalized unless they have an idiomatic meaning or unusual reading. Most of the terms arisingfrom this process are nouns, e.g. those arising from the affixation of 化 (ka: -ization). Some others,
such as 的 (teki: -like, -ical, -ish, etc.) form adjectives.
c) Compounding. As in many languages, the formation of terms by combining two or more words ormorphemes is very common. The components can be independent words, as in 秋空 akizora “autumnsky” where both 秋 aki and 空 sora can be used independently, or bound morphemes as in 警告
keikoku “warning” where neither component can be used alone. See Tanaka (2002) and Baldwin andTanaka (2004) for earlier work in this area.) Two types of synthesized compounds were investigated:
i. 2-kanji compounds, as in the examples above;ii. composites formed by aggregating known 2-kanji compounds, for example combining 警告(above) with 射撃 shageki “firing, shooting” forms a composite 警告射撃 keikoku shageki
meaning “warning shot”.
Synthesized terms which were not already recorded in a reference lexicon were considered if they occurred
more than 100 times in the corpus. The evaluation of such terms was carried out by examining theiroccurrences in a combination of syntactic contexts typically associated with nouns. Japanese uses a large
number of particles which are usually written in the hiragana syllabary. Counts of occurrences wereextracted for the terms encapsulated in 37 combinations of the following common pre/postpended particles.

pre:
post:

は (wa), が (ga), に (ni), の (no), な (na), て (te), や (ya)を (wo), が (ga), に (ni), の (no), な (na), や (ya)Two types of evaluation were carried out on the sets of counts:a) a machine-learning analysis using support-vector machine (SVM) models trained on the patterns ofcounts from a range of established terms (Chang and Lin, 2011);b) a heuristic approach using rules based on the numbers of encapsulations.
Investigation Outcomea) Abbreviation/Clipping. Of 33,000 synthesized abbreviations 7,900 were evaluated of which 162
were identified as potential new nouns (2.0%). Hand-checking a sample revealed that few wereactually valid abbreviations. Most were other types of collocations.
b) Affixation. Initial testing of potential terms generated by this technique resulted in large numbers
which were clearly in regular use. It quickly emerged, however, that they almost always had quite
predictable meanings and were unlikely to be included in a dictionary unless quite relaxed
lexicalization criteria were applied. For example the noun 衒衒 gengaku “pedantry” can take suffixes
such as the personalizing suffix 者 sha to form 衒学者 gengakusha “pedant” or the adjective-forming
suffix 的 teki (mentioned earlier) to form 衒学的 gengakuteki “pedantic”.
c) Compounding.
i. 2-kanji compounds. As there are over 6 million combinations of the most common 2,500 kanji,
two samples each of 40,000 compounds were generated from two ranges of kanji from whichwere excluded kanji for numerics, common affixes, etc. The unlexicalized compounds weretested against the two corpora, resulting in 200-500 compounds being classified from eachsample. Hand-checking selections of these revealed that most were valid terms, with about 60%
being proper names. Examples of such terms include 移弦 igen “string-crossing” (violin, etc.
technique), 春苗 shunbyô “spring seedlings” (also a girl's name), and 母珠 moshu “large bead(s)in a Buddhist rosary”. The precision of the technique, i.e. the proportion of classified terms
which proved to be valid, was quite high. As the compounds are typically simple nouns most of
the non-name terms were clear candidates for lexicalization.
ii. 4-kanji compounds. The potential numbers of 4-kanji compounds which can be generated fromknown 2-kanji compounds is very large, however few record sufficient counts in the n-gram
corpora to be considered further. Several batches of 1 million compounds were generated, with400-500 from each being accepted for further analysis, and 30-50 being flagged by the models as
potential terms. Again hand-checking confirmed their validity, with terms such as 英国王室
eikokuôshitsu “British royal family”, and 欧州遠征 ôshûensei “European campaign” (esp. withsporting teams) being identified. A point to note is that many of the accepted terms havemeanings which are readily apparent from the components, and hence are unlikely to beincluded in a general dictionary unless the usual criteria were relaxed. It was noted thatcompounds formed from components which were polysemous were more likely to have nonintuitive meanings, which indicates a possibly fruitful area of future study.
As mentioned earlier, the synthesized compounds were tested using both machine-learning and heuristicmodels. It was noted that in general the heuristic models performed more effectively than the machinelearning approach.
Conclusion
In this paper we describe the investigation of a neologism detection approach involving the synthesis ofpossible Japanese terms by mimicking Japanese morphological processes, followed by testing for thepresence of candidate terms in Japanese corpora in appropriate syntactic contexts. Synthesized terms which
passed this evaluation were assessed by regular lexicographic processes to determine their suitability forlexicalization. Of the techniques tested: abbreviation, affixation and compounding, the latter showed
particular promise, with the 2-kanji compound generation and classification resulting significant numbers ofunrecorded terms deemed suitable for inclusion in dictionaries.

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