Parsing Subordinate Clauses in T elugu using Rule-based Dependency Parser (2021)

Abstract: Parsing has been gaining popularity in recent years and attracted the interest of NLP researchers around the world. It is challenging when the language under study is a free-word order language that allows ellipsis like Telugu. In this paper, an attempt is made to parse subordinate clauses especially, non-finite verb clauses and relative clauses in Telugu which are highly productive and constitute a large chunk in parsing tasks. This study adopts a knowledge-driven approach to parse subordinate structures using linguistic cues as rules. Challenges faced in parsing ambiguous structures are elaborated alongside providing enhanced tags to handle them. Results are encouraging and this parser proves to be efficient for Telugu.

## introduction parsing, the word derived from latin (pars orationis), was originally used in elementary schools for grammatical explication of sentences @xcite . currently, parsing is a well-known and well-researched area in natural language processing (nlp) which involves analyzing sentences syntactically or syntactico-semantically. building parsers and treebanks have attracted several researchers for its utility in various larger nlp applications. an efficient and ready-to-use parser for languages like telugu, one of the most widely spoken dravidian languages is still under development, though a handful of resources are traced. telugu is a south-central dravidian language with free-word order and well-known for its agglutinating morphology. agglutination allows carrying multiple grammatical information on words in telugu. this grammatical information is quite helpful in parsing and stands as a rationale behind building the rule-based parser, despite multiple challenges. parsing free-word order and ag-glutinating languages like telugu is particularly challenging as they allow pro-drops, ellipsis and complex constructions. earlier attempts in developing telugu dependency parsers include mostly data-driven approaches @xcite @xcite @xcite @xcite . among the attempts made, udpipe for telugu foot_0 which is trained using telugu-mtg ud treebank @xcite is the only publicly accessible parser. there is an attempt in developing a rule-based parser with linguistic knowledge-driven approach @xcite for simple sentences. in this paper, we present our experiment in parsing subordinate clauses, particularly, non-finite verb clauses and relative participle clauses in telugu using rule-based dependency parser. ## a rule-based dependency parser this study uses a rule-based parser (rbp) which takes input from sentences that are morphologically analysed. telugu pos tagger, pruning and pickone-morph modules are used to select one analysis per token @xcite . the rbp follows dependency approach based on the indian theories of verbal cognition where three factors viz. ākānksā (expectancy), yōgyata (meaning compatibility), and sannidhi (proximity) are used and implemented initially for sanskrit @xcite . telugu rbp is adopted from sanskrit rbp and modified for telugu parsing @xcite . we model the parser as a tree where the nodes of a tree correspond to a word and the edges between nodes correspond to a relation between the corresponding words. parser is implemented using the functional programming language ocaml 2 to write rules and perl to generate dependency trees as graphs. the figure 1 explains the architecture of the rbp. telugu sentence morphological analysis select one morph apply rules convert to graphs if multiple relations filter dependency tree telugu rbp rules database pos tagging pruning pickone morph yes no figure 1: architecture in parsing simple sentences, 29 dependency labels are used and they are divided into kāraka(k) relations (for example, kartā (roughly equivalant to subject) (k1), karmā (object) (k2) etc.) and nonkāraka (for example, genitive (r6), associative(ras) etc.) labels. the dependency tree for the sentence (1) is seen in figure 2. (1) mā our nānna father rēpu tomorrow ūri village numci from vas-tā-ru come-fut-3.sg.hon. 'my father will come from village tomorrow' 3 subordinate clauses in telugu subordinate clauses in telugu include non-finite verb clauses, relative participle clauses and complementizer clauses. subordinate clauses in telugu do express ambiguity with different syntacticosemantic relations. non-finite verb clauses are highly productive in the formation of sentences in telugu and they constitute a large chunk in parsing task. they are dependent clauses which cannot stand alone in a sentence. they are realised as subordinate clauses which are derived from simple sentences with certain structural changes and precede the matrix clause by occurring to their left side. the verb of subordinate clause is syntactically the head of the clause but does not exhibit person-numbergender agreement with respective subjects, however it is marked for appropriate tense, aspect and mood. they are classified into conjunctive participles, conditionals, concessives and infinitives in telugu @xcite . conjunctive participles are divided into past, durative and negative. conditionals and concessives clauses can have both affirmative and negative forms whereas infinitives can have only affirmative form. relative participle clauses are primarily noun phrases which are further divided into past, durative, future/habitual and negative participles. negative participles do not differentiate for tense. complementizer clauses are formed by the quotative form i.e. ani 'that' which links both finite clauses. figure 3 provides the classification of subordinate clauses in telugu. examples of various types of subordinate clauses are provided in the in this paper, we present challenges in parsing non-finite verb clauses and relative participle clauses using rule-based parsing. we use the anncora tagset for tagging the dependency relations (version 2.5) @xcite . there is a great requirement for the enhancement of tags for telugu to disambiguate various functions of subordinate clauses. an attempt is made to build enhanced tags and implemented using linguistic cues as rules in rbp. ## enhanced anncora tagset anncora guidelines @xcite suggest the tag vmod for conjunctive participles, concessives, conditionals and nmod for relative participles. in this study, we have used multiple linguistic cues and enhanced subordinate clause tags as shown in the ## evaluation rules of rbp are framed based on the model sentences collected from various telugu grammar books @xcite , @xcite , @xcite . the purpose of choosing grammar texts for building rules is due to the wide-range of exceptions that are covered. these exceptions enabled us to segregate several cases of subordinate clause occurrences and providing fine-grain tags. around subordinate clause enhanced tag for telugu conjunctive participle vmod serial action vmod:cp serial simultaneous action vmod:cp simul manner vmod:cp manner conditional clauses condition vmod:cond serial action vmod:cond serial cause vmod:cond cause concessive clause vmod:conc infinitive clause vinf:k1 relative participle clause relativization of subject nmod:relcl k1 relativization of object nmod:relcl k2 relativization of location nmod:relcl k7 rbp works on the linguistic cues (verbal/nominal databases, grammatical information) provided to it. rbp fails when these linguistic cues are not included as part of database or when it encounters an exception. but these cues can be updated as and when rbp encounters a new corpus. another case in which rbp fails to deliver a correct parse is when pre-processing tools like morphological analyser, pos, pruning, pick-one morph provide an erroneous output. ## conclusion parsing of non-finite verb clauses and relative participle constructions in telugu is attempted in this paper using a rule-based parser. it is observed that knowledge-driven parser works better for agglutinating languages like telugu as many linguistic cues can be seen in the structure. parsing of subordinate clauses is challenging due to its diverse interpretations and usage. various ambiguous constructions are considered in this paper alongside adding enhanced/fine-grain tags to the existing anncora tagset. these tags are beneficial as the tag vmod is quite under-specified. results prove that rbp serves as an efficient parser for telugu and addition of linguistic cues can improve the performance further. parsing of other complex structures will be carried out in the future work.