Articles

We present an algorithm that automati- cally learns context constraints using sta- tistical decision trees. We then use the ac- quired constraints in a flexible POS tag- ger. The tagger is able to use informa- tion of any degree: n-grams, automati- cally learned context constraints, linguis- tically motivated manually written …...

We present a constraint-based morpholog- ical disambiguation system in which indi- vidual constraints vote on matching mor- phological parses, and disambiguation of all the tokens in a sentence is performed at the end by selecting parses that receive the highest votes. This constraint applica- tion paradigm makes the outcome of …...

This paper presents a method for the au- tomatic extraction of subgrammars to con- trol and speeding-up natural language gen- eration NLG. The method is based on explanation-based learning EBL. The main advantage for the proposed new method for NLG is that the complexity of the grammatical decision making process …...

Most algorithms dedicated to the generation of referential descriptions widely suffer from a fundamental problem: they make too strong assumptions about adjacent processing components, resulting in a limited coordination with their perceptive and linguistics data, that is, the provider for object descriptors and the lexical expression by which the chosen …...

We present an algorithm for simultaneously constructing both the syntax and semantics of a sentence using a Lexicalized Tree Adjoin- ing Grammar (LTAG). This approach captures naturally and elegantly the interaction between pragmatic and syntactic constraints on descrip- tions in a sentence, and the inferential interac- tions between multiple descriptions …...

This paper deals with the reference choices in- volved in the generation of argumentative text. Since a natual segmentation of discourse into attentional spaces is needed to carry out this task, this paper first proposes an architecture for natural language generation that combines hierarchical planning and focus-guided naviga- tion, a …...

We identify and validate from a large cor- pus constraints from conjunctions on the positive or negative semantic orientation of the conjoined adjectives. A log-linear regression model uses these constraints to predict whether conjoined adjectives are of same or different orientations, achiev- ing 82% accuracy in this task when each …...

Many current approaches to statistical lan- guage modeling rely on independence a.~- sumptions 1)etween the different explana- tory variables. This results in models which are computationally simple, but which only model the main effects of the explanatory variables oil the response vari- able. This paper presents an argmnent in favor …...

Several recent efforts in statistical nat- ural language understanding (NLU) have focused on generating clumps of English words from semantic meaning concepts (Miller et al., 1995; Levin and Pierac- cini, 1995; Epstein et al., 1996; Epstein, 1996). This paper extends the IBM Ma- chine Translation Group's concept of fertil- ity …...

In data-oriented language processing, an annotated language corpus is used as a stochastic grammar. The most probable analysis of a new sentence is constructed by combining fragments from the corpus in the most probable way. This approach has been successfully used for syntactic anal- ysis, using corpora with syntactic annota- …...

Verbal and compositional lexical aspect provide the underlying temporal struc- ture of events. Knowledge of lexical as- pect, e.g., (a)telicity, is therefore required for interpreting event sequences in dis- course (Dowty, 1986; Moens and Steed- man, 1988; Passoneau, 1988), interfacing to temporal databases (Androutsopoulos, 1996), processing temporal modifiers (An- tonisse, …...

We describe a formal framework for inter- pretation of words and compounds in a discourse context which integrates a sym- bolic lexicon/grammar, word-sense proba- bilities, and a pragmatic component. The approach is motivated by the need to han- dle productive word use. In this paper, we concentrate on compound nominals. …...

It is challenging to translate names and technical terms across languages with differ- ent alphabets and sound inventories. These items are commonly transliterated, i.e., re- placed with approximate phonetic equivalents. For example, computer in English comes out as ~ i/l:::'=--~-- (konpyuutaa) in Japanese. Translating such items from Japanese back to …...

We specify an algorithm that builds up a hi- erarchy of referential discourse segments from local centering data. The spatial extension and nesting of these discourse segments constrain the reachability of potential antecedents of an anaphoric expression beyond the local level of adjacent center pairs. Thus, the centering model is …...

Telegraphic messages with numerous instances of omis- sion pose a new challenge to parsing in that a sen- tence with omission causes a higher degree of ambi6u- ity than a sentence without omission. Misparsing re- duced by omissions has a far-reaching consequence in machine translation. Namely, a misparse of the …...

We derive the rhetorical structures of texts by means of two new, surface-form-based algorithms: one that identifies discourse usages of cue phrases and breaks sen- tences into clauses, and one that produces valid rhetorical structure trees for unre- stricted natural language texts. The algo- rithms use information that was derived …...

The way in which discourse features ex- press connections back to the previous dis- course has been described in the literature in terms of adjoining at the right frontier of discourse structure. But this does not allow for discourse features that express ez- pectations about what is to come in …...

Our goal is to identify the features that pre- dict the occurrence and placement of dis- course cues in tutorial explanations in or- der to aid in the automatic generation of explanations. Previous attempts to devise rules for text generation were based on in- tuition or small numbers of constructed …...

Most previous corpus-based algorithms dis- ambiguate a word with a classifier trained from previous usages of the same word. Separate classifiers have to be trained for different words. We present an algorithm that uses the same knowledge sources to disambiguate different words. The algo- rithm does not require a sense-tagged …...

In the past the evaluation of machine trans- lation systems has focused on single sys- tem evaluations because there were only few systems available. But now there are several commercial systems for the same language pair. This requires new methods of comparative evaluation. In the paper we propose a black-box …...