Character-level Dependency Annotation of C hinese (2023)

Abstract: In this paper, we propose a new model for annotating dependency relations at the Mandarin character level with the aim of building treebanks to cope with the unsatisfactory performance of existing word segmentation and syntactic analysis models in specific scientific domains, such as Chinese patent texts. The result is a treebank of 100 sentences annotated according to our scheme, which also serves as a training corpus that facilitates the subsequent development of a joint word segmenter and dependency analyzer that enables downstream tasks in Chinese to be separated from the non-standardized pre-processing step of word segmentation.

## introduction word segmentation has long been a chickenand-egg problem in chinese. the notion of distinct words with spaces as natural boundaries in languages using the latin alphabet has never been widely agreed upon in chinese. in the absence of both natural delimiters and inflection marks, two main indicators of wordhood @xcite , the distinction between words and larger lexical units in chinese has been an unfamiliar and confusing concept since it was introduced by zhang shizhao in 1907. this has resulted in a low agreement rate of 76% on lexicality among native chinese speakers @xcite . all existing mandarin treebanks and syntactic annotation schemes for mandarin chinese employ word segmentation as the first step in the annotation. however, their segmentation criteria are far different without a clear unified standard. at the same time, dependency analyzers trained on these treebanks end up with inconsistent results with each other, especially on corpora containing a large number of domain-specific new terms, such as patent texts @xcite it is in this context that we decided to explore the idea of developing a character-based chinese annotation schema. a treebank annotated with additional internal relations of words can be used as a resource to train a joint segmenter-parser, combining the two steps into one. moreover, @xcite also showed that character-level annotations, even coarse ones, can help improve the results of dependency analysis for chinese of different text types. in the most widely accepted morphological theory of chinese @xcite @xcite , complex words are derivative words or compound words. the second group includes five types: modifier-head type, coordinative type, predicate-object type, predicate-complement type, and subject-predicate type. he @xcite and @xcite suggest in their work that there is a parallelism between compound word structure and syntactic structure in chinese, from which from which it is feasible to build a new dependency model that unifies the character level with the current word level relationship. some previous works have also discussed the possibility of the joint dependency parsing and multi-word expression recognition on other languages @xcite . from this perspective, it is important to integrate the new word internal relations of the new words into dependency trees built on the basis of similar distributional criteria. this is why this work chose to base itself on a variant of ud @xcite , surface-syntactic universal dependencies (sud), which is a near-isomorphic but more surface syntactic alternative schema of ud with a more classical word distribution-based dependency structure that favors functional heads. and to obtain the relationships between these roles, we applied syntactic tests that allowed us to identify the head and internal structure of the composite based on distributional criteria. after discussing chinese morphology and syntactic theory, the parallelism between chinese compound word structure and syntactic structure is discussed especially in sections 2 and 3. the next two sections explain the complete annotation process, including two sub-steps. (1) automatic tokenization, pos tagging and dependency parsing using existing nlp pipelines (section 4.1); and (2) manual correction and annotation follo-wing our sud-based character-level annotation schema (section 4.2). then, section 4.3 describes the conversion of the character-level treebank to a standard word-level ud treebank and the evaluation of the automatically converted treebank. ## the annotation schema for chinese word internal relations instead of the conventional first step of word segmentation in chinese treebank annotation, the annotation of character-based treebanks starts with the analysis of the relations between individual characters. such relations can be typical syntactic relations, internal relations of words that do not conform to any syntactic relations in modern chinese, or the third between the two kinds of relations mentioned above, which are more frozen than independent syntactic constituents but still largely corresponds to certain syntactic structures in this section, we explain the criteria for wordhood and parts-of-speech. our model annotates these relations between characters at all three levels of granularity simultaneously. without the word segmentation process, all characters of a sentence are separated. moreover, the word level is distinguished from the syntactic level by the sub-relation ":m", instead of the blank. the criteria for this distinction are described in section 2.1, and the next section 2.2 explains the choice of part-of-speech labels, especially at the character level. ## correspondence between chinese word internal structures and dependency relations in sud the annotation of syntactic relations is based on the surface-syntactic universal dependency (sud) model proposed by @xcite . and based on this, we added our own characterlevel annotation labels by analogy with the surface-syntactic relations of sud. in this section, we introduce six categories of character-level relations in modern chinese vocabulary. for each category, we describe the definition of a category, and its correspondence with the syntactic relations in sud, and give some criteria to test whether a compound belongs to a certain category (see the full decision tree in appendix a). ## construction and annotation of the character-based chinese patent tree-bank to apply this annotation schema in a real corpus, we chose patents, one of the most challenging genres for syntactic parsing tasks due to their syntactic complexity and frequent use of uncommon domain-specific terms. ## conclusion and future works in this paper, we propose a new characterbased chinese annotation model. instead of starting with non-standardized, informationwasting word segmentation, we analyze the word internal structures and distribute syntactic-liked labels based on the parallelism between compound word structure and syntactic structure in chinese. finally, we annotated the first character-level tree database consisting of 100 patent claim sentences. based on this character-level treebank, we have the possibility to train a character-based dependency analyzer by bootstrapping that can handle both word segmentation and syntactic analysis simultaneously. in future work, we are also interested in developing a premoderne chinese treebank containing a richer character-level structure foot_6 .