| { | |
| "paper_id": "W06-0102", | |
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| "date_generated": "2023-01-19T04:00:45.282314Z" | |
| }, | |
| "title": "Regional Variation of Domain-Specific Lexical Items: Toward a Pan-Chinese Lexical Resource", | |
| "authors": [ | |
| { | |
| "first": "Oi", | |
| "middle": [ | |
| "Yee" | |
| ], | |
| "last": "Kwong", | |
| "suffix": "", | |
| "affiliation": { | |
| "laboratory": "", | |
| "institution": "University of Hong Kong", | |
| "location": { | |
| "addrLine": "Tat Chee Avenue", | |
| "settlement": "Kowloon, Hong Kong" | |
| } | |
| }, | |
| "email": "" | |
| }, | |
| { | |
| "first": "Benjamin", | |
| "middle": [ | |
| "K" | |
| ], | |
| "last": "Tsou", | |
| "suffix": "", | |
| "affiliation": { | |
| "laboratory": "", | |
| "institution": "University of Hong Kong", | |
| "location": { | |
| "addrLine": "Tat Chee Avenue", | |
| "settlement": "Kowloon, Hong Kong" | |
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| "abstract": "This paper reports on an initial and necessary step toward the construction of a Pan-Chinese lexical resource. We investigated the regional variation of lexical items in two specific domains, finance and sports; and explored how much of such variation is covered in existing Chinese synonym dictionaries, in particular the Tongyici Cilin. The domain-specific lexical items were obtained from subsections of a synchronous Chinese corpus, LIVAC. Results showed that 20-40% of the words from various subcorpora are unique to the individual communities, and as much as 70% of such unique items are not yet covered in the Tongyici Cilin. The results suggested great potential for building a Pan-Chinese lexical resource for Chinese language processing. Our next step would be to explore automatic means for extracting related lexical items from the corpus, and to incorporate them into existing semantic classifications.", | |
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| "abstract": [ | |
| { | |
| "text": "This paper reports on an initial and necessary step toward the construction of a Pan-Chinese lexical resource. We investigated the regional variation of lexical items in two specific domains, finance and sports; and explored how much of such variation is covered in existing Chinese synonym dictionaries, in particular the Tongyici Cilin. The domain-specific lexical items were obtained from subsections of a synchronous Chinese corpus, LIVAC. Results showed that 20-40% of the words from various subcorpora are unique to the individual communities, and as much as 70% of such unique items are not yet covered in the Tongyici Cilin. The results suggested great potential for building a Pan-Chinese lexical resource for Chinese language processing. Our next step would be to explore automatic means for extracting related lexical items from the corpus, and to incorporate them into existing semantic classifications.", | |
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| "section": "Abstract", | |
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| "text": "Many cities have underground railway systems. Somehow one takes the tube in London but the subway in New York. In a more recent edition of the Roget's Thesaurus (Kirkpatrick, 1987) , subway, tube, underground railway and metro are found in the same semicolon-separated group under head 624 Way. Similarly if one looks up WordNet (http://wordnet.princeton.edu; Miller et al., 1990) , the synset to which subway belongs also contains the words metro, tube, underground, and subway system; and it is further in-dicated that \"in Paris the subway system is called the 'metro' and in London it is called the 'tube' or the 'underground'\". Such regional lexical variation is also found in Chinese. For instance, the subway system in Hong Kong, known as the Mass Transit Railway or MTR, is called \u5730\u9435 in Chinese. The subway systems in Beijing and Shanghai, as well as the one in Singapore, are also known as \u5730\u9435, but that in Taipei is known as \u6377\u904b. Their counterpart in Japan is written as \u5730\u4e0b\u9244 in Kanji. Such regional variation, as part of lexical knowledge, is important and useful for many natural language applications, including natural language understanding, information retrieval, and machine translation. Unfortunately, existing Chinese lexical resources often lack such comprehensiveness.", | |
| "cite_spans": [ | |
| { | |
| "start": 161, | |
| "end": 180, | |
| "text": "(Kirkpatrick, 1987)", | |
| "ref_id": "BIBREF5" | |
| }, | |
| { | |
| "start": 360, | |
| "end": 380, | |
| "text": "Miller et al., 1990)", | |
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| "section": "Introduction", | |
| "sec_num": "1" | |
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| "text": "To fill this gap, Tsou and Kwong (2006) proposed a comprehensive Pan-Chinese lexical resource, based on a large and unique synchronous Chinese corpus as an authentic basis for lexical acquisition and analysis across various Chinese speech communities. For a significant world language like Chinese, a useful lexical resource should have maximum versatility and portability. It is not sufficient to target at one particular community speaking the language and thus cover only language usage observed from that particular community. Instead, such a lexical resource should document the core and universal substances of the language on the one hand, and also the more subtle variations found in different communities on the other. As is evident from the above example on the variation of subway, regional variation should be captured for the lexical resource to be useful in a wide range of applications.", | |
| "cite_spans": [ | |
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| "start": 18, | |
| "end": 39, | |
| "text": "Tsou and Kwong (2006)", | |
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| "section": "Introduction", | |
| "sec_num": "1" | |
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| "text": "In this study, we investigate and compare the regional variation of lexical items from two spe-cific domains, finance and sports, as an initial and necessary step toward the more important undertaking of building a Pan-Chinese lexical resource. In addition, we make use of an existing Chinese synonym dictionary, the Tongyici Cilin (Mei et al., 1984) as leverage, and explore its coverage of such variation and thus the potential for enriching it. The lexical items under study were obtained from a synchronous Chinese corpus, LIVAC, which will be further introduced in Section 4. Corpus data from four Chinese speech communities were compared with respect to their commonality and uniqueness, and also against Cilin for their coverage. Results showed that 20-40% of the words extracted from the corpus are unique to the individual communities, and as much as 70% of such unique items are not yet covered in Cilin. It therefore suggests that the synchronous corpus is a rich source for mining region-specific lexical items, and there is great potential for building a Pan-Chinese lexical resource for Chinese language processing.", | |
| "cite_spans": [ | |
| { | |
| "start": 332, | |
| "end": 350, | |
| "text": "(Mei et al., 1984)", | |
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| "section": "Introduction", | |
| "sec_num": "1" | |
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| "text": "In Section 2, we will briefly review existing resources and related work. Then in Section 3, we will briefly outline the design and architecture of the Pan-Chinese lexical resource proposed by Tsou and Kwong (2006) . In Section 4, we will further describe the Chinese synonym dictionary and the synchronous Chinese corpus used in this study. The comparison of their lexical items will be discussed in Section 5. Future directions will be presented in Section 6, followed by a conclusion.", | |
| "cite_spans": [ | |
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| "end": 214, | |
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| "section": "Introduction", | |
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| "text": "The construction and development of large lexical resources is relying more and more on corpus-based approaches, not only as a result of the increased availability of large corpora, but also for the authoritativeness and authenticity allowed by the approach.", | |
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| "section": "Existing Resources and Related Work", | |
| "sec_num": "2" | |
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| "text": "The Collins COBUILD English Dictionary (Sinclair, 1987) is amongst the most well-known lexicographic fruit based on large corpora.", | |
| "cite_spans": [ | |
| { | |
| "start": 39, | |
| "end": 55, | |
| "text": "(Sinclair, 1987)", | |
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| "section": "Existing Resources and Related Work", | |
| "sec_num": "2" | |
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| "text": "For natural language applications, much of the information in conventional dictionaries targeted at human readers must be made explicit. Lexical resources for computer use thus need considerable manipulation, customisation, and supplementation (e.g. Calzolari, 1982) . WordNet (Miller et al., 1990) , grouping words into synsets and linking them up with relational pointers, is probably the first broad coverage general computational lexical database. In view of the intensive time and effort required in resource building, some researchers have taken an alternative route by extracting information from existing machinereadable dictionaries and corpora semiautomatically (e.g. Vossen et al., 1989; Riloff and Shepherd, 1999; Lin et al, 2003) .", | |
| "cite_spans": [ | |
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| "start": 250, | |
| "end": 266, | |
| "text": "Calzolari, 1982)", | |
| "ref_id": "BIBREF0" | |
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| { | |
| "start": 277, | |
| "end": 298, | |
| "text": "(Miller et al., 1990)", | |
| "ref_id": "BIBREF8" | |
| }, | |
| { | |
| "start": 678, | |
| "end": 698, | |
| "text": "Vossen et al., 1989;", | |
| "ref_id": "BIBREF14" | |
| }, | |
| { | |
| "start": 699, | |
| "end": 725, | |
| "text": "Riloff and Shepherd, 1999;", | |
| "ref_id": "BIBREF9" | |
| }, | |
| { | |
| "start": 726, | |
| "end": 742, | |
| "text": "Lin et al, 2003)", | |
| "ref_id": "BIBREF6" | |
| } | |
| ], | |
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| "section": "Existing Resources and Related Work", | |
| "sec_num": "2" | |
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| "text": "Compared to the development of thesauri and lexical databases, and research into semantic networks for major languages such as English, similar work for the Chinese language is less mature. This gap was partly due to the lack of authoritative Chinese corpora as a basis for analysis, but has been gradually reduced with the recent availability of large Chinese corpora including the LIVAC synchronous corpus (Tsou and Lai, 2003) used in this work and further described below, the Sinica Corpus (Chen et al., 1996) , the Chinese Penn Treebank (Xia et al., 2000) , and the like.", | |
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| "end": 428, | |
| "text": "(Tsou and Lai, 2003)", | |
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| { | |
| "start": 494, | |
| "end": 513, | |
| "text": "(Chen et al., 1996)", | |
| "ref_id": "BIBREF2" | |
| }, | |
| { | |
| "start": 542, | |
| "end": 560, | |
| "text": "(Xia et al., 2000)", | |
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| "section": "Existing Resources and Related Work", | |
| "sec_num": "2" | |
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| "text": "An important issue which is seldom addressed in the construction of Chinese lexical databases is the problem of versatility and portability. For a language such as Chinese which is spoken in many different communities, different linguistic norms have emerged as a result of the individualistic evolution and development of the language within a particular community and culture. Such variations are seldom adequately reflected in existing lexical resources, which often only draw reference from one particular source. For instance, Tongyici Cilin (\u540c\u7fa9\u8a5e\u8a5e\u6797) (Mei et al., 1984 ) is a thesaurus containing some 70,000 Chinese lexical items in the tradition of the Roget's Thesaurus for English, that is, in a hierarchy of broad conceptual categories. First published in the 1980s, it was based exclusively on Chinese as used in post-1949 Mainland China. Thus for the subway example above, the closest word group found is \u706b\u8eca, \u5217\u8eca (train) only, let alone the subway itself and its regional variations.", | |
| "cite_spans": [ | |
| { | |
| "start": 555, | |
| "end": 572, | |
| "text": "(Mei et al., 1984", | |
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| "sec_num": "2" | |
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| "text": "With the recent availability of large corpora, especially synchronous ones, to construct an authoritative and timely lexical resource for Chinese is less distant than it was in the past. A large synchronous corpus provides authentic examples of the language as used in a variety of locations. It thus enables us to attempt a comprehensive and in-depth analysis of the core common language in constructing a lexical resource; and to incorporate useful information relating to location-sensitive linguistic variations.", | |
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| "sec_num": "2" | |
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| "text": "The Pan-Chinese lexicon proposed by Tsou and Kwong (2006) is expected to capture not only the core senses of lexical items but also senses and uses specific to individual Chinese speech communities.", | |
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| "section": "Proposal of a Pan-Chinese Thesaurus", | |
| "sec_num": "3" | |
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| "text": "The lexical database will be organised into a core database and a supplementary one. The core database will contain the core lexical information for word senses and usages which are common to most Chinese speech communities, whereas the supplementary database will contain the language uses specific to individual communities, including \"marginal\" and \"sublanguage\" uses.", | |
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| "sec_num": "3" | |
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| "text": "A network structure will be adopted for the lexical items. The nodes could be sets of nearsynonyms or single lexical items (in which case synonymy will be one type of links). The links will not only represent the paradigmatic semantic relations but also syntagmatic ones (such as selectional restrictions).", | |
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| "text": "We thus begin by investigating in depth the regional variation of lexical items, especially domain-specific words, among several Chinese speech communities. In addition, we explore the potential of enriching existing resources as a start. In the following section, we will discuss the Tongyici Cilin and the synchronous Chinese corpus used in this study in greater details.", | |
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| "text": "The Tongyici Cilin (\u540c\u7fa9\u8a5e\u8a5e\u6797) (Mei et al., 1984 ) is a Chinese synonym dictionary, or more often known as a Chinese thesaurus in the tradition of the Roget's Thesaurus for English. The Roget's Thesaurus has about 1,000 numbered semantic heads, more generally grouped under higher level semantic classes and subclasses, and more specifically differentiated into paragraphs and semicolon-separated word groups. Similarly, some 70,000 Chinese lexical items are organized into a hierarchy of broad conceptual categories in the Tongyici Cilin. Its classification consists of 12 top-level semantic classes, 94 sub-classes, 1,248 semantic heads and 3,925 paragraphs. (Tsou and Lai, 2003) . The corpus consists of newspaper articles collected regularly and synchronously from six Chinese speech communities, namely Hong Kong, Beijing, Taipei, Singapore, Shanghai, and Macau. Texts collected cover a variety of domains, including front page news stories, local news, international news, editorials, sports news, entertainment news, and financial news. Up to December 2005, the corpus has already accumulated about 180 million character tokens which, upon automatic word segmentation and manual verification, amount to over 900K word types.", | |
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| "section": "The Tongyici Cilin", | |
| "sec_num": "4.1" | |
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| "text": "For the present study, we make use of the subcorpora collected over the 9-year period 1995-2004 from Hong Kong (HK), Beijing (BJ), Taipei (TW), and Singapore (SG). In particular, we focus on the financial news and sports news to investigate the commonality and uniqueness of the lexical items used in these specific domains in the various communities. We also evaluate the adequacy of the Tongyici Cilin in terms of its coverage of such domain-specific terms especially from the Pan-Chinese perspective, and thus assess the room for its enrichment with the synchronous corpus. Table 1 shows the sizes of the subcorpora used for this study. ", | |
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| "start": 577, | |
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| "text": "Table 1", | |
| "ref_id": "TABREF2" | |
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| "text": "Word-frequency lists were generated from the financial and sports subcorpora from each individual community. For each resulting list, the steps below were followed to remove irrelevant items and retain only the potentially useful content words: Tables 2 and 3 for the two domains respectively. The lexical items retained, which are expected to contain a substantial amount of content words, are potentially useful for the current study. The lists in each domain (from the various subcorpora) were compared in terms of the items they share and those unique to individual communities. Their unique items were also compared against the Tongyici Cilin to investigate its adequacy and explore how it might be enriched with the synchronous corpus. The four subcorpora of the financial domain differ considerably in their sizes, and slightly less so for the sports domain. Despite this, we observed for both domains from Tables 2 and 3 that in general about 40-50% of all word types are numbers, non-Chinese words, proper names, and function words. Of the remaining items, about 20-30% have frequency greater than 5. These several thousand word types from each subcorpus are expected to be amongst the more interesting items and form the \"candidate sets\" for further investigation.", | |
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| "start": 245, | |
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| "text": "Tables 2 and 3", | |
| "ref_id": "TABREF4" | |
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| "section": "Procedures", | |
| "sec_num": "4.3" | |
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| "text": "Comparing the candidate sets from various subcorpora, which reflect the use of Chinese in various Chinese speech communities, Tables 4 and 5 show the sizes of the intersection sets among different places for the two domains respectively.", | |
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| "text": "Tables 4 and 5", | |
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| "section": "Commonality among Various Regions", | |
| "sec_num": "5.2" | |
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| "text": "The intersection set for all four places contains slightly more than 1,000 lexical items in the financial domain. A quick skim through these common lexical items suggests that they contain, on the one hand, the many general concepts in the financial domain (e.g. \u516c\u53f8 company, \u5e02\u5834 market, \u9280\u884c bank, \u6295\u8cc7 invest / investment, \u696d \u52d9 business, \u767c\u5c55 develop / development, \u96c6\u5718 corporation, \u80a1\u4efd stock shares, \u80a1\u6771 shareholder, \u8cc7\u91d1 capital, etc.); and on the other hand, many reportage and cognitive verbs often used in news articles (e.g. \u8868\u793a express, \u8a8d\u70ba reckon, \u51fa\u73fe appear, \u53cd\u6620 reflect, etc.).", | |
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| "section": "Commonality among Various Regions", | |
| "sec_num": "5.2" | |
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| "text": "In the sports domain, more than 1,700 lexical items were found in all of the four subcorpora. Like its financial counterpart, we found many general concepts at the top of the list (e.g. \u7403\u54e1 player, \u7403\u968a team, \u8cfd\u4e8b match, \u6bd4\u8cfd competi-tion, \u806f\u8cfd league, \u6559\u7df4 coach, \u5c0d\u624b opponent, \u51a0\u8ecd champion, etc.).", | |
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| "section": "Commonality among Various Regions", | |
| "sec_num": "5.2" | |
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| "text": "The numbers of overlaps in Tables 4 suggest that lexical items used in Mainland China (as evident from BJ data) seem to have the least in common with the rest. For instance, compared to the overlap amongst all four regions (i.e. 1,039), the overlap has increased most when BJ was not included in the comparison; and when we compare any two regions, the overlap between BJ and TW is smallest. Nevertheless, such uniqueness of BJ data is less apparent in the sports domain. In particular, the difference between HK/BJ and BJ/TW is even slightly less than that in the financial domain.", | |
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| "section": "Commonality among Various Regions", | |
| "sec_num": "5.2" | |
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| "text": "If we look at the individual regions, HK apparently shares most (about 50%) with SG, and vice versa (about 68%), in the financial domain. At the same time, BJ also shares more with HK than with the other two regions, and so does TW. But surprisingly, BJ has over 60% overlap with SG and about 55% with TW in the sports domain. The overlaps of TW with HK and with BJ differ by more than 20% in the finance domain, but only by about 10% in the sports domain. All these patterns might suggest lexical items in the financial domain are more versatile and have more varied focus in different communities, whereas those in the sports domain reflect the more common interests of different places. ", | |
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| "section": "Commonality among Various Regions", | |
| "sec_num": "5.2" | |
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| "text": "Next we compared the lists with respect to what they have unique to themselves. Table 6 shows the numbers of unique items found in each list, together with examples from the most frequent 20 unique items in each case. Again, taking the size difference among the candidate sets into account, about 40% of the lexical items found in HK data are unique to the region, which re-echoes the versatility and wide coverage of interests of HK data. This is especially evident when compared to only about 20% of the candidate sets for SG are unique to Singapore. 1 Looking at the unique lexical items found in individual regions, it is not difficult to see the region-specific lexicalisation of certain concepts. For instance, in terms of housing, \u5c45\u5c4b (housing under the Home Ownership Scheme) is a specific kind of housing in Hong Kong, \u7d44\u5c4b is a specific term in Singapore (as seen in SG data), whereas housing is generally expressed as \u4f4f \u623f in Mainland China (as seen in BJ data). Similarly, \u64cd\u7df4 (HK) and \u51ac\u8a13 (BJ) both refer to training, but may relate to different practice in the two communities. Such regional variation lends strong support to the importance of a Pan-Chinese lexical resource.", | |
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| "text": "1", | |
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| "text": "Table 6", | |
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| "section": "Uniqueness of Various Regions", | |
| "sec_num": "5.3" | |
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| "text": "The lists of unique items also suggest the various focus and orientation in different Chinese speech communities. For example, while Hong Kong pays much attention to the real estate market and stock market, Mainland China may be focusing more on the basic needs like water, farming, poverty alleviation, etc., and Singapore is relatively more concerned with local affairs like port management. The passion for baseball, among other more popular sports like soccer, is most obvious from the unique lexical items found in TW data.", | |
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| "text": "As mentioned earlier, the Tongyici Cilin contains some 70,000 lexical items under 12 broad semantic classes, 94 subclasses, and 1,428 heads. It was first published in the 1980s and was based on lexical usages mostly of post-1949 Mainland China. In this section, we discuss the results obtained from comparing the unique lexical items found from individual subcorpora with Cilin, which are shown in Table 7 .", | |
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| "ref_spans": [ | |
| { | |
| "start": 398, | |
| "end": 405, | |
| "text": "Table 7", | |
| "ref_id": "TABREF9" | |
| } | |
| ], | |
| "eq_spans": [], | |
| "section": "Comparison with Tongyici Cilin", | |
| "sec_num": "5.4" | |
| }, | |
| { | |
| "text": "On the one hand, Cilin's collection of words may be considerably dated and obviously will not include new concepts and neologisms arising in the last two decades. On the other hand, the data in LIVAC come from newspaper materials in the 1990s. So overall speaking, for each of the unique word lists, much less than 50% are covered in Cilin.", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Comparison with Tongyici Cilin", | |
| "sec_num": "5.4" | |
| }, | |
| { | |
| "text": "Nevertheless, there is still an apparent gap between Cilin's coverage of the unique items from various places. About 40% of the unique items found in BJ for both domains are covered; but for other places, the coverage is more often less than 30% in either or both domains. Again, this could be considered a result of Cilin's bias toward lexical usages in Mainland China.", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Comparison with Tongyici Cilin", | |
| "sec_num": "5.4" | |
| }, | |
| { | |
| "text": "In addition, while almost 40% of the unique items in BJ data are found in Cilin, many of these unique items covered are amongst the most frequent items. On the contrary, even though about 560 unique items in HK data are also found in Cilin, only 3 out of the 20 most frequent items are amongst them. In addition, the apparent coverage does not necessarily suggest the correct match of word senses. For instance, \u5c45\u5c4b is found under head Bn1 together with other items like \u4f4f\u623f, \u4f4f\u5b85, etc., all of which only refer to the general concept of housing, instead of the housing specifically under the Home Ownership Scheme as known in Hong Kong. Also, coverage of words like \u6668\u66e6, \u5e1d\u738b and \u6c34\u624b in the sports domain does not match their actual usages which refer to team names. A more interesting example might be \u706b\u934b, which is used in the basketball context in TW data, and in no way refers to the literal \"hot pot\" sense.", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Comparison with Tongyici Cilin", | |
| "sec_num": "5.4" | |
| }, | |
| { | |
| "text": "Results from the above comparisons thus support that (1) different Chinese speech communities have their distinct usage of Chinese lexical items, in terms of both form and sense;", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Comparison with Tongyici Cilin", | |
| "sec_num": "5.4" | |
| }, | |
| { | |
| "text": "(2) such variation is found in different domains, such as the financial and sports domain; (3) existing lexical resources, the Tongyici Cilin in particular as in our current study, should be enriched and enhanced by capturing lexical usages from a variety of Chinese speech communities, to represent the lexical items from a Pan-Chinese perspective; and (4) lexical items obtained from the synchronous Chinese corpus can supplement the existing content of the Tongyici Cilin, with more contemporarily lexicalised concepts, as well as variant expressions of similar and related concepts from various Chinese speech communities.", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Comparison with Tongyici Cilin", | |
| "sec_num": "5.4" | |
| }, | |
| { | |
| "text": "Hence it remains for us to further investigate how the related lexical items obtained from the synchronous corpus should be grouped and incorporated into the semantic classification of existing lexical resources; and to further explore how they might be extracted in a large scale by automatic means. These will definitely be amongst the most important future directions as discussed in the next section.", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Comparison with Tongyici Cilin", | |
| "sec_num": "5.4" | |
| }, | |
| { | |
| "text": "In the current study, we have investigated the regional variation of lexical items from the financial and sports domain, and the coverage of the Tongyici Cilin for such variation. The results suggested great potential for building a Pan-Chinese lexical resource for Chinese language processing. Our next step would thus be to further investigate more automatic means for extracting the near-synonymous or closely related items from the various subcorpora. To this end, we would explore algorithms like those used in Lin et al. (2003) . Of similar importance is the mechanism for grouping the related lexical items and incorporating them into the semantic classifications of existing lexical resources. In this regard we will proceed with further in-depth analysis of the classificatory structures of individual resources and fit in our Pan-Chinese architecture.", | |
| "cite_spans": [ | |
| { | |
| "start": 516, | |
| "end": 533, | |
| "text": "Lin et al. (2003)", | |
| "ref_id": "BIBREF6" | |
| } | |
| ], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Future Work", | |
| "sec_num": "6" | |
| }, | |
| { | |
| "text": "Apart from the Tongyici Cilin, there are other existing Chinese lexical resources such as HowNet (Dong and Dong, 2000) , SUMO and Chinese WordNet (Huang et al., 2004) , as well as other synonym dictionaries from which we might draw reference to build up our Pan-Chinese lexical resource.", | |
| "cite_spans": [ | |
| { | |
| "start": 97, | |
| "end": 118, | |
| "text": "(Dong and Dong, 2000)", | |
| "ref_id": null | |
| }, | |
| { | |
| "start": 146, | |
| "end": 166, | |
| "text": "(Huang et al., 2004)", | |
| "ref_id": "BIBREF4" | |
| } | |
| ], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Future Work", | |
| "sec_num": "6" | |
| }, | |
| { | |
| "text": "In this paper, we have investigated the regional variation of lexical items in two specific domains from a synchronous Chinese corpus, and explored their coverage in a Chinese synonym dictionary. Results are encouraging in the sense that 20-40% of the candidate words from various subcorpora are unique to the individual communities, and as much as 70% of such unique items are not yet covered in the Tongyici Cilin. It therefore suggests great importance and potential for a Pan-Chinese lexical resource which we aim to construct. The synchronous corpus is a valuable resource for mining the region-specific expressions while existing synonym dictionaries might provide a ready-made semantic classificatory structure. Our next step would be to explore automatic means for extracting related lexical items from the corpus, and to incorporate them into existing semantic classifications. ", | |
| "cite_spans": [], | |
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| "eq_spans": [], | |
| "section": "Conclusion", | |
| "sec_num": "7" | |
| }, | |
| { | |
| "text": "Upon further analysis, on average about 60% of these \"unique\" items were actually found in one or more of the other regions, but with frequency 5 or below. Since the difference in frequency is quite large for most items, we can reasonably treat them as unique to a particular community.", | |
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| "text": "This work is supported by Competitive Earmarked Research Grant (CERG) of the Research Grants Council of Hong Kong under grant No.CityU1317/03H. The authors would like to thank the anonymous reviewers for comments.", | |
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| "text": "a) Remove all numbers and non-Chinese words. (b) Remove all proper names, including those annotated as personal names, geographical names, and organisation names. Proper names have been annotated in the corpora during the process of word segmentation. (c) Remove function words. (d) Remove lexical items with frequency 5 or below. The numbers of remaining items in each subcorpus after the above steps are listed in", | |
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| "content": "<table><tr><td>Subcorpus</td><td>All</td><td>After (a)</td><td>After (b)</td><td>After (c)</td><td>After(d)</td></tr><tr><td>HK</td><td>39,190</td><td>35,720</td><td>25,289</td><td>21,502</td><td>6,316</td></tr><tr><td>BJ</td><td>27,971</td><td>26,049</td><td>19,799</td><td>16,598</td><td>3,878</td></tr><tr><td>TW</td><td>32,706</td><td>30,231</td><td>20,361</td><td>17,248</td><td>4,601</td></tr><tr><td>SG</td><td>34,040</td><td>31,974</td><td>19,995</td><td>16,780</td><td>5,120</td></tr></table>", | |
| "type_str": "table", | |
| "text": "Number of word types remaining after various data cleaning steps for the financial domain", | |
| "num": null | |
| }, | |
| "TABREF5": { | |
| "html": null, | |
| "content": "<table><tr><td>5 Results and Discussion</td></tr><tr><td>5.1 Lexical Items from LIVAC</td></tr></table>", | |
| "type_str": "table", | |
| "text": "Number of word types remaining after various data cleaning steps for the sports domain", | |
| "num": null | |
| }, | |
| "TABREF8": { | |
| "html": null, | |
| "content": "<table><tr><td>Region</td><td>Financial</td><td/><td>Sports</td><td/></tr><tr><td/><td>Found in Cilin</td><td>Not in Cilin</td><td>Found in Cilin</td><td>Not in Cilin</td></tr><tr><td>HK</td><td>560 (26.60%)</td><td>1545</td><td>884 (36.68%)</td><td>1526</td></tr><tr><td/><td>\u6e1b\u50f9 \u7d14\u5229 \u5c45\u5c4b \u6236\u53e3 \u62c6\u606f</td><td>(73.40%)</td><td>\u73fe\u6642 \u64cd\u7df4 \u62ab\u7532 \u6668\u66e6 \u653b\u5805</td><td>(62.32%)</td></tr><tr><td/><td>\u61a7\u61ac \u5bb9\u8a31 \u5012\u9000 \u901a\u544a \u7d50\u9918</td><td/><td>\u5927\u52c7 \u5e1d\u738b \u86cb \u7b54 \u722d\u52dd</td><td/></tr><tr><td>BJ</td><td>369 (39.55%)</td><td>564</td><td>355 (39.14%)</td><td>552</td></tr><tr><td/><td>\u8fb2\u6751 \u62bd\u67e5 \u4f4f\u623f \u904b\u884c \u9ee8</td><td>(60.45%)</td><td>\u81ea\u884c\u8eca \u7279\u7d1a \u4e2d\u5b78\u751f \u524d\u885e \u81ea\u6cbb\u5340</td><td>(60.86%)</td></tr><tr><td/><td>\u8d70\u79c1 \u54c1\u7a2e \u6797\u696d \u9109\u93ae \u68ee\u6797</td><td/><td>\u5f69\u7968 \u8fb2\u6c11 \u89e3\u653e\u8ecd \u68cb\u58c7 \u5e79\u90e8</td><td/></tr><tr><td>TW</td><td>265 (29.74%)</td><td>626</td><td>354 (27.19%)</td><td>948</td></tr><tr><td/><td>\u5951\u7d04 \u5c08\u6848 \u4e0d\u52d5\u7522 \u6539\u9078 \u80a1\u5229</td><td>(70.26%)</td><td>\u6295\u624b \u91d1\u525b \u96f7\u516c \u4fdd\u9001 \u6253\u9ede</td><td>(72.81%)</td></tr><tr><td/><td>\u901a\u8def \u95dc\u5361 \u9031 \u7d42\u5834 \u5e2d\u6b21</td><td/><td>\u5730\u4e3b \u6c34\u624b \u5831\u5c0e \u7e3d\u548c \u665a\u9593</td><td/></tr><tr><td>SG</td><td>333 (37.42%)</td><td>557</td><td>281 (26.91%)</td><td>763</td></tr><tr><td/><td>\u516c\u5bd3 \u5e73\u65b9\u82f1\u5c3a \u6e2f\u52d9 \u6236\u982d \u5171\u7ba1</td><td>(62.58%)</td><td>\u6548\u52de \u661f\u671f\u516d \u661f\u671f\u4e09 \u57ce\u9580 \u88dc\u8db3</td><td>(73.08%)</td></tr><tr><td/><td>\u6587\u544a \u5730\u5951 \u6d77\u4e8b \u8f2a\u8239 \u958b\u92b7</td><td/><td>\u661f\u671f\u56db \u661f\u671f\u4e94 \u661f\u671f\u5929 \u8173\u8e0f\u8eca \u661f\u671f\u4e8c</td><td/></tr></table>", | |
| "type_str": "table", | |
| "text": "Uniqueness of individual subcorpora", | |
| "num": null | |
| }, | |
| "TABREF9": { | |
| "html": null, | |
| "content": "<table/>", | |
| "type_str": "table", | |
| "text": "Coverage of the Tongyici Cilin for the unique lexical items in individual subcorpora", | |
| "num": null | |
| } | |
| } | |
| } | |
| } |