German ) Corpus Representativity , Bigrams , and PoS-Tagging Quality

After some theoretical discussion on the issue of (different meanings of the term) representativity of a corpus, this paper takes this issue into practice and shows how a representative (in one of the meanings) corpus of German can be achieved. The approach is based on the idea of application of "invalid bigrams", i.e. of abolishing pairs of adjacent tags which constitute an incorrect configuration in a text of German (e.g., the bigram [ARTICLE,FINITE VERB]). On this spot, the paper puts forward a list of such bigrams for the STTS tagset (widely used for PoS-tagging German corpora). The power of the approach is illustrated on the results achieved on the NEGRA corpus. Finally, some general implications for tagging and taggers are mentioned. 1 The Representativity Issue "Representativity" is a noun which bears two theta-roles: representativity is necessarily a representativity of a (representing) agent wrt. a patient (being – or not being, as it might happen – represented). A typical example from the area of corpus linguistics is the representativity of a corpus wrt. some language phenomenon. In this paper, we intend to scrutinize the issue of representativity of a part-of-speech (PoS) tagged corpus in some detail. In order to stay on a nontrivial but still easily understandable level, let us consider the case of representativity of the NEGRA corpus of German wrt. to bigrams contained1. In this case, the phenomena whose presence and relative frequency are at stake are: 1 The case of a trigrams, used more usual in tagging practice, would be almost identical but require more lengthy explanations. For the conciseness of argument, we thus limit the discussion to bigrams. • bigrams, i.e. pairs [First,Second] of tags of words occurring in the corpus adjacently and in this order • unigrams, i.e. the individual tags. We shall define the qualitative representativity wrt. bigrams as the kind of representativity meeting the following two complementary requirements: • the representativity wrt. the presence of all valid bigrams of the language in the corpus, which means that if any bigram [First,Second] is a bigram in a correct sentence of the language, then such a bigram occurs also in the corpus this requirement might be called positive representativity • the representativity wrt. the absence of all invalid bigrams of the language in the corpus, which means that if any bigram [First,Second] is a bigram which cannot occur in a correct (i.e. grammatical) sentence of the language, then such a bigram does not occur in the corpus this requirement might be called negative representativity. If a corpus is both positively and negatively representative, then indeed it can be said to be a qualitatively representative corpus. In our particular example this means that a bigram occurs in a qualitatively representative (wrt. bigrams) corpus if and only if it is a possible bigram in the language (and from this it already follows that any unigram occurs in such a corpus if and only if it is a possible unigram2). From this formulation, it is also clear that the 2 This assertion holds only on condition that each sentence of the language is of length two (measured in words) or longer. Analogical limitation holds in the case of trigrams, etc. qualitative representativity depends on the notion of grammaticality, that is, on the "language competence" – on the ability of distinguishing between a grammatical and an ungrammatical sentence. The quantitative representativity of a corpus wrt. bigrams can then be approximated as the requirement that the frequency of any bigram and any unigram occurring in the corpus be in the proportion "as in the language performance" to the frequency of occurrence of all other bigrams or unigrams, respectively3. However, even when its basic idea is quite intuitive and natural, it is not entirely clear whether the quantitative representativity can be formalized rigorously. At stake is measuring the frequency of a bigram (and of a unigram) within the "complete language performance", understood as set of utterances of a language. This set, however, is infinite if considered theoretically (i.e. as set of all possible utterances in the language) and finite but practically unattainable if considered as a set of utterances realized within a certain time span. For this reason, we refrain from quantitative representativity in the following and we deal with qualitative representativity only. 2 The Bigram Issue or Towards Negative Representativity wr t. German Bigrams From a linguistic viewpoint, the pair of tags [First,Second] is a valid bigram in a certain natural language if and only if there exists a sentence (at least one) in this language which contains two adjacent words bearing the tags First and Second, respectively. Such a sentence then can be assigned its structure, and hence a valid bigram [First,Second] comes into being via a structural configuration where there occur two adjacent constituents LC (for "Left Constituent") and RC (for "Right Constituent"), such that LC immediately precedes RC and the last (rightmost) element of the terminal yield of LC is First and the first (leftmost) element of the terminal yield of RC is Second, cf. Fig. 1, where also the common ancestor (not necessarily the mother) of LC and RC is depicted (as AC, "Ancestor Constituent"). 3 From this it easily follows that any quantitatively representative corpus is also a qualitatively representative corpus. Fig. 1 AC