Automatic induction of rules for text simplification

Long and complicated sentences pose various problems to many state of the art natural language technologies We have been exploring methods to automatically transform such sentences as to make them simpler These methods involve the use of a rule based system driven by the syntax of the text in the domain of interest Hand crafting rules for every domain is time consuming and impractical This paper describes an algorithm and an implementation by which generalized rules for simpli cation are auto matically induced from annotated training material with a novel partial parsing technique which combines constituent structure and dependency in formation This algorithm described in the paper employs example based generalizations on linguistically motivated structures The Need for Text Simpli cation Long and complicated sentences pose various problems to many state of the art natural language technologies For example in parsing as sentences become syntactically more complex the number of parses increases and there is a greater likelihood for an incorrect parse In machine translation complex sentences lead to increased ambiguity and potentially unsatisfactory translations Complicated sentences can also lead to confusion in assembly use maintenance manuals for complex equipment We have been exploring methods to automatically simplify such sentences Chandrasekar Chandrasekar et al Consider for example the following sentence On leave from the National Centre for Software Technology Gulmohar Cross Road No Juhu Mumbai India The embattled Major government survived a crucial vote on coal pits closure as its last minute concessions curbed the extent of Tory revolt over an issue that generated unusual heat in the House of Commons and brought the miners to London streets Such sentences are not uncommon in newswire texts Compare this with an equivalent manually simpli ed multi sentence version The embattled Major government survived a crucial vote on coal pits closure Its last minute concessions curbed the extent of Tory revolt over the coal mine issue This issue generated unusual heat in the House of Commons It also brought the miners to London streets Most of the problems listed above are either eliminated or substantially re duced for the simpli ed version shown in For instance simpler sentences have fewer constituents hence fewer ambiguities in identifying attachments and thus are parsed faster Simpli cation would also be of great use in several areas of natural language processing such as machine translation information retrieval and in applications where clarity of text is imperative Of course one may lose some nuances of meaning from the original text in the simpli cation process There has been interest in simpli ed English from companies such as Boeing and Xerox Researchers at Boeing Hoard et al Wojcik et al have developed a Simpli ed English Checker However their focus is on carefully con straining the use of words in a speci c domain and in providing a tool to authors of machine maintenance operation manuals to help them adhere to guidelines aimed at clear written communication In contrast our aim is to develop a sys tem to semi automatically simplify text from any domain The following is the outline of this paper In Section we present an ar chitecture for simpli cation The method used for analysis of input is discussed in Section and the notion of supertags is outlined In Section we describe a method by which generalized rules are automatically induced from annotated training material of newspaper text in English We discuss some of the issues pertaining to simpli cation in Section The Architecture of Simpli cation Our simpli cation system processes one sentence at a time Discourse related issues are not considered We view simpli cation as a two stage process analysis followed by transformation The analysis stage provides a structural description of the input and the transformation stage uses this representation for simpli ca tion The most obvious choice for the analysis stage is to use a full parser to obtain the complete structure of a sentence If all the constituents of the sentence along with the dependency relations are given simpli cation is very straightforward However it is well known that as sentences become syntactically more complex the number of parses increases and there is a greater likelihood for an incorrect parse We have discussed two alternative approaches to analyzing text using a nite state grammar approach Chandrasekar and a dependency based approach Chandrasekar et al We summarize the dependency based approach in the next section Note that this approach is di erent from a full parsing approach in that a complete constituent structure is not created We de ne articulation points to be those points where sentences may be split for simpli cation Segments of a sentence between two articulation points may be extracted as simpli ed sentences The nature of the segments delineated by the articulation points depends on the type of the structural analysis performed If the sentences are viewed as linear strings of words we could de ne articulation points to be say punctuation marks If the words in the input are also tagged with part of speech information we can split sentences based on the category information for instance at relative pronouns With part of speech information subordinating and coordinating conjunctions may also be detected and used as articulation points However with just this information the span of the subordi nating coordinating clause would be di cult to determine On the other hand if the sentence is annotated with phrasal bracketings the beginnings and ends of phrases could also be articulation points For example the sentence with a relative clause annotated with phrasal bracketing can be simpli ed into two sentences as shown in using a rule such as the one shown in that relies on skeletal phrasal structure and punctuation information Talwinder Singh NP who RelPron masterminded V the Kanishka crash NP was killed V in a erce two hour encounter NP PP Talwinder Singh was killed in a erce two hour encounter Talwinder Singh masterminded the Kanishka crash W X NP RelPron Y Z W X NP Z X NP Y The rule is interpreted as follows If a sentence starts with some segment W and a noun phrase X NP and is then followed by a phrase of the form RelPron Y followed by some Z where Y and Z are arbitrary sequences of words then the sentence may be simpli ed into two sentences namely the sequence W X followed by Z and the sequence X followed by Y However the rule shown above does not handle reduced relatives such as the one in sentence The creator of Air India Mr JRD Tata NP believes V that COMP the airline NP known V for its on board service NP PP could return V to its old days of glory NP PP To solve such problems we use a representation which combines dependency information with constituent structure providing attachment and scope informa tion This representation is described in the next section We need a variety of rules to simplify text from any particular domain How ever hand crafting simpli cation rules is time consuming and not very practical While some of the rules are likely to be common across domains several are likely to be domain speci c We ideally need a method to develop rules which can be easily induced for a new domain In this paper we present an algorithm and an implementation to automatically induce rules for simpli cation given an annotated aligned corpus of complex and simple text In addition to developing rules we need gap lling routines For example if we separate a relative clause from a sentence for example we must insert a copy of the head noun at the gap in the relative clause The exact choice of the gap llers is a complicated task based on a variety of pragmatic factors and will not be discussed in this paper