waashk/dblp huggingface dataset:
obfuscating document stylometry to preserve author anonymity. this paper explores techniques for reducing the effectiveness of standard authorship attribution techniques so that an author a can preserve anonymity for a particular document d. we discuss feature selection and adjustment and show how this information can be fed back to the author to create a new document d' for which the calculated attribution moves away from a. since it can be labor intensive to adjust the document in this fashion, we attempt to quantify the amount of effort required to produce the anonymized document and introduce two levels of anonymization: shallow and deep. in our test set, we show that shallow anonymization can be achieved by making 14 changes per 1000 words to reduce the likelihood of identifying a as the author by an average of more than 83%. for deep anonymization, we adapt the unmasking work of koppel and schler to provide feedback that allows the author to choose the level of anonymization.
parsing with discontinuous constituents. by generalizing the notion of location of a constituent to allow discontinuous loctaions, one can describe the discontinuous constituents of non-configurational languages. these discontinuous constituents can be described by a variant of definite clause grammars, and these grammars can be used in conjunction with a proof procedure to create a parser for non-configurational languages.
a statistical analysis of morphemes in japanese terminology. in this paper i will report the result of a quantitative analysis of the dynamics of the constituent elements of japanese terminology. in japanese technical terms, the linguistic contribution of morphemes greatly differ according to their types of origin. to analyse this aspect, a quantitative method is applied, which can properly characterise the dynamic nature of morphemes in terminology on the basis of a small sample.
deductive parsing with multiple levels of representation. this paper discusses a sequence of deductive parsers, called pad1 -- pad5, that utilize an axiomatization of the principles and parameters of gb theory, including a restricted transformational component (move-&alpha;). pad2 uses an inference control strategy based on the 'freeze' predicate of prolog-ii, while pad3 -- 5 utilize the unfold-fold transformation to transform the original axiomatization into a form that functions as a recursive descent prolog parser for the fragment.
polarized unification grammars. this paper proposes a generic mathematical formalism for the combination of various structures: strings, trees, dags, graphs and products of them. the polarization of the objects of the elementary structures controls the saturation of the final structure. this formalism is both elementary and powerful enough to strongly simulate many grammar formalisms, such as rewriting systems, dependency grammars, tag, hpsg and lfg.
expressing disjunctive and negative feature constraints with classical first-order logic. in contrast to the "designer logic" approach, this paper shows how the attribute-value feature structures of unification grammar and constraints on them can be axiomatized in classical first-order logic, which can express disjunctive and negative constraints. because only quantifier-free formulae are used in the axiomatization, the satisfiability problem is np-complete.
finite-state approximation of constraint-based grammars using left-corner grammar transforms. this paper describes how to construct a finite-state machine (fsm) approximating a 'unification-based' grammar using a left-corner grammar transform. the approximation is presented as a series of grammar transforms, and is exact for left-linear and right-linear cfgs, and for trees up to a user-specified depth of center-embedding.
robust, finite-state parsing for spoken language understanding. human understanding of spoken language appears to integrate the use of contextual expectations with acoustic level perception in a tightly-coupled, sequential fashion. yet computer speech understanding systems typically pass the transcript produced by a speech recognizer into a natural language parser with no integration of acoustic and grammatical constraints. one reason for this is the complexity of implementing that integration. to address this issue we have created a robust, semantic parser as a single finite-state machine (fsm). as such, its run-time action is less complex than other robust parsers that are based on either chart or generalized left-right (glr) architectures. therefore, we believe it is ultimately more amenable to direct integration with a speech decoder.
a tag-based noisy-channel model of speech repairs. this paper describes a noisy channel model of speech repairs, which can identify and correct repairs in speech transcripts. a syntactic parser is used as the source model, and a novel type of tag-based transducer is the channel model. the use of tag is motivated by the intuition that the reparandum is a "rough copy" of the repair. the model is trained and tested on the switchboard disfluency-annotated corpus.
automatic construction of polarity-tagged corpus from html documents. this paper proposes a novel method of building polarity-tagged corpus from html documents. the characteristics of this method is that it is fully automatic and can be applied to arbitrary html documents. the idea behind our method is to utilize certain layout structures and linguistic pattern. by using them, we can automatically extract such sentences that express opinion. in our experiment, the method could construct a corpus consisting of 126,610 sentences.
memoization of coroutined constraints. some linguistic constraints cannot be effectively resolved during parsing at the location in which they are most naturally introduced. this paper shows how constraints can be propagated in a memoizing parser (such as a chart parser) in much the same way that variable bindings are, providing a general treatment of constraint coroutining in memoization. prolog code for a simple application of our technique to bouma and van noord's (1994) categorial grammar analysis of dutch is provided.
verb paraphrase based on case frame alignment. this paper describes a method of translating a predicate-argument structure of a verb into that of an equivalent verb, which is a core component of the dictionary-based paraphrasing. our method grasps several usages of a headword and those of the def-heads as a form of their case frames and aligns those case frames, which means the acquisition of word sense disambiguation rules and the detection of the appropriate equivalent and case marker transformation.
estimators for stochastic "unification-based" grammars. log-linear models provide a statistically sound framework for stochastic "unification-based" grammars (subgs) and stochastic versions of other kinds of grammars. we describe two computationally-tractable ways of estimating the parameters of such grammars from a training corpus of syntactic analyses, and apply these to estimate a stochastic version of lexical-functional grammar.
diagnostic processing of japanese for computer-assisted second language learning. as an application of nlp to computer-assisted language learning(call), we propose a diagnostic processing of japanese being able to detect errors and inappropriateness of sentences composed by the students in the given situation and the context of the exercise texts. using ltag(lexicalized tree adjoining grammar) formalism, we have implemented a prototype of such a diagnostic parser as a component of a call system being developed.
a unification-based parser for relational grammar. we present an implemented unification-based parser for relational grammars developed within the stratified feature grammar (sfg) framework, which generalizes kasper-rounds logic to handle relational grammar analyses. we first introduce the key aspects of sfg and a lexicalized, graph-based variant of the framework suitable for implementing relational grammars. we then describe a head-driven chart parser for lexicalized sfg. the basic parsing operation is essentially ordinary feature-structure unification augmented with an operation of label unification to build the stratified features characteristic of sfg.
a method for correcting errors in speech recognition using the statistical features of character co-occurence. it is important to correct the errors in the results of speech recognition to increase the performance of a speech translation system. this paper proposes a method for correcting errors using the statistical features of character co-occurrence, and evaluates the method.the proposed method comprises two successive correcting processes. the first process uses pairs of strings: the first string is an erroneous substring of the utterance predicted by speech recognition, the second string is the corresponding section of the actual utterance. errors are detected and corrected according to the database learned from erroneous-correct utterance pairs. the remaining errors are passed to the posterior process which uses a string in the corpus that is similar to the string including recognition errors.the results of our evaluation show that the use of our proposed method as a post-processor for speech recognition is likely to make a significant contribution to the performance of speech translation systems.
unification-based multimodal parsing. in order to realize their full potential, multimodal systems need to support not just input from multiple modes, but also synchronized integration of modes. johnston et al (1997) model this integration using a unification operation over typed feature structures. this is an effective solution for a broad class of systems, but limits multimodal utterances to combinations of a single spoken phrase with a single gesture. we show how the unification-based approach can be scaled up to provide a full multimodal grammar formalism. in conjunction with a multidimensional chart parser, this approach supports integration of multiple elements distributed across the spatial, temporal, and acoustic dimensions of multimodal interaction. integration strategies are stated in a high level unification-based rule formalism supporting rapid prototyping and iterative development of multimodal systems.
learning attribute selections for non-pronominal expressions. a fundamental function of any task-oriented dialogue system is the ability to generate nominal expressions that describe objects in the task domain. in this paper, we report results from using machine learning to train and test a nominal-expression generator on a set of 393 nominal descriptions from the coconut corpus of task-oriented design dialogues. results show that we can achieve a 50% match to human performance as opposed to a 16% baseline for just guessing the most frequent type of nominal expression in the coconut corpus. to our surprise our results indicate that many of the central features of previously proposed selection models did not improve the performance of the learned nominal-expression generator.
match: an architecture for multimodal dialogue systems. mobile interfaces need to allow the user and system to adapt their choice of communication modes according to user preferences, the task at hand, and the physical and social environment. we describe a multimodal application architecture which combines finite-state multimodal language processing, a speech-act based multimodal dialogue manager, dynamic multimodal output generation, and user-tailored text planning to enable rapid prototyping of multimodal interfaces with flexible input and adaptive output. our testbed application match (multimodal access to city help) provides a mobile multimodal speech-pen interface to restaurant and sub-way information for new york city.
chart generation. charts constitute a natural uniform architecture for parsing and generation provided string position is replaced by a notion more appropriate to logical forms and that measures are taken to curtail generation paths containing semantically incomplete phrases.
unification-based multimodal integration. recent empirical research has shown conclusive advantages of multimodal interaction over speech-only interaction for map-based tasks. this paper describes a multimodal language processing architecture which supports interfaces allowing simultaneous input from speech and gesture recognition. integration of spoken and gestural input is driven by unification of typed feature structures representing the semantic contributions of the different modes. this integration method allows the component modalities to mutually compensate for each others' errors. it is implemented in quick-set, a multimodal (pen/voice) system that enables users to set up and control distributed interactive simulations.
minority vote: at-least-n voting improves recall for extracting relations. several nlp tasks are characterized by asymmetric data where one class label none, signifying the absence of any structure (named entity, coreference, relation, etc.) dominates all other classes. classifiers built on such data typically have a higher precision and a lower recall and tend to overproduce the none class. we present a novel scheme for voting among a committee of classifiers that can significantly boost the recall in such situations. we demonstrate results showing up to a 16% relative improvement in ace value for the 2004 ace relation extraction task for english, arabic and chinese.
user expertise modeling and adaptivity in a speech-based e-mail system. this paper describes the user expertise model in athosmail, a mobile, speech-based e-mail system. the model encodes the system's assumptions about the user expertise, and gives recommendations on how the system should respond depending on the assumed competence levels of the user. the recommendations are realized as three types of explicitness in the system responses. the system monitors the user's competence with the help of parameters that describe e.g. the success of the user's interaction with the system. the model consists of an online and an offline version, the former taking care of the expertise level changes during the same session, the latter modelling the overall user expertise as a function of time and repeated interactions.
metonymy: reassessment, survey of acceptability, and its treatment in a machine translation system. in this article we outline a basic approach to treating metonymy properly in a multilingual machine translation system. this is the first attempt at treating metonymy in an machine translation environment. the approach is guided by the differences of acceptability of metonymy which were obtained by our comparative survey among three languages, english, chinese, and japanese. the characteristics of the approach are as follows:(1)influences of the context, individuals, and familiality with metonymy are not used.(2) an actual acceptability of each metonymic expression is not realized directly.(3) grouping metonymic examples into patterns is determined by the acceptability judgement of the speakers surveyed as well as the analysts' intuition.(4) the analysis and generation components treat metonymy differently using the patterns.(5) the analysis component accepts a wider range of metonymy than the actual results of the survey, and the generation component treats metonymy more strictly than the actual results.we think that the approach is a starting point for more sophisticated approaches to translation in a multilingual machine translation environment.
atomization in grammar sharing. we describe a prototype shared grammar for the syntax of simple nominal expressions in arabic, english, french, german, and japanese implemented at mcc. in this grammar, a complex inheritance lattice of shared grammatical templates provides parts that each language can put together to form language-specific grammatical templates. we conclude that grammar sharing is not only possible but also desirable. it forces us to reveal crosslinguistically invariant grammatical primitives that may otherwise remain conflated with other primitives if we deal only with a single language or language type. we call this the process of grammatical atomization. the specific implementation reported here uses categorial unification grammar. the topics include the mono-level nominal category n, the functional distinction between argument and non-argument of nominals, grammatical agreement, and word order types.
resolving translation mismatches with information flow. languages differ in the concepts and real-world entities for which they have words and grammatical constructs. therefore translation must sometimes be a matter of approximating the meaning of a source language text rather than finding an exact counterpart in the target language. we propose a translation framework based on situation theory. the basic ingredients are an information lattice, a representation scheme for utterances embedded in contexts, and a mismatch resolution scheme defined in terms of information flow. we motivate our approach with examples of translation between english and japanese.
towards testing the syntax of punctuation. little work has been done in nlp on the subject of punctuation, owing mainly to a lack of a good theory on which computational treatments could be based. this paper described early work in progress to try to construct such a theory. two approaches to finding the syntactic function of punctuation marks are discussed, and procedures are described by which the results from these approaches can be tested and evaluated both against each other as well as against other work. suggestions are made for the use of these results, and for future work.
temporal centering. we present a semantic and pragmatic account of the anaphoric properties of past and perfect that improves on previous work by integrating discourse structure, aspectual type, surface structure and commonsense knowledge. a novel aspect of our account is that we distinguish between two kinds of temporal intervals in the interpretation of temporal operators --- discourse reference intervals and event intervals. this distinction makes it possible to develop an analogy between centering and temporal centering, which operates on discourse reference intervals. our temporal property-sharing principle is a defeasible inference rule on the logical form. along with lexical and causal reasoning, it plays a role in incrementally resolving underspecified aspects of the event structure representation of an utterance against the current context.
movement in active production networks. we describe how movement is handled in a class of computational devices called active production networks (apns). the apn model is a parallel, activation-based framework that has been applied to other aspects of natural language processing. the model is briefly defined, the notation and mechanism for movement is explained, and then several examples are given which illustrate how various conditions on movement can naturally be explained in terms of limitations of the apn device.
fsa: an efficient and flexible c++ toolkit for finite state automata using on-demand computation. in this paper we present the rwth fsa toolkit --- an efficient implementation of algorithms for creating and manipulating weighted finite-state automata. the toolkit has been designed using the principle of on-demand computation and offers a large range of widely used algorithms. to prove the superior efficiency of the toolkit, we compare the implementation to that of other publically available toolkits. we also show that on-demand computations help to reduce memory requirements significantly without any loss in speed. to increase its flexibility, the rwth fsa toolkit supports high-level interfaces to the programming language python as well as a command-line tool for interactive manipulation of fsas. furthermore, we show how to utilize the toolkit to rapidly build a fast and accurate statistical machine translation system. future extensibility of the toolkit is ensured as it will be publically available as open source software.
robust interaction through partial interpretation and dialogue management. in this paper we present results on developing robust natural language interfaces by combining shallow and partial interpretation with dialogue management. the key issue is to reduce the effort needed to adapt the knowledge sources for parsing and interpretation to a necessary minimum. in the paper we identify different types of information and present corresponding computational models. the approach utilizes an automatically generated lexicon which is updated with information from a corpus of simulated dialogues. the grammar is developed manually from the same knowledge sources. we also present results from evaluations that support the approach.
can nominal expressions achieve multiple goals? an empirical study. while previous work suggests that multiple goals can be addressed by a nominal expression, there is no systematic work describing what goals in addition to identification might be relevant and how speakers can use nominal expressions to achieve them. in this paper, we first hypothesize a number of communicative goals that could be addressed by nominal expressions in task-oriented dialogues. we then describe the intentional influences model for nominal expression generation that attempts to simultaneously address the identification goal and these additional goals with a single nominal expression. our evaluation results show that the intentional influences model fits the nominal expressions in the coconut corpus as well as previous accounts that focus solely on the identification goal.
defining the semantics of verbal modifiers in the domain of cooking tasks. seafact (semantic analysis for the animation of cooking tasks) is a natural language interface to a computer-generated animation system operating in the domain of cooking tasks. seafact allows the user to specify cooking tasks using a small subset of english. the system analyzes english input and produces a representation of the task which can drive motion synthesis procedures. this paper describes the semantic analysis of verbal modifiers on which the seafact implementation is based.
using terminological knowledge representation languages to manage linguistic resources. i examine how terminological languages can be used to manage linguistic data during nl research and development. in particular, i consider the lexical semantics task of characterizing semantic verb classes and show how the language can be extended to flag inconsistencies in verb class definitions, identify the need for new verb classes, and identify appropriate linguistic hypotheses for a new verb's behavior.
use of mutual information based character clusters in dictionary-less morphological analysis of japanese. for languages whose character set is very large and whose orthography does not require spacing between words, such as japanese, tokenizing and part-of-speech tagging are often the difficult parts of any morphological analysis. for practical systems to tackle this problem, uncontrolled heuristics are primarily used. the use of information on character sorts, however, mitigates this difficulty. this paper presents our method of incorporating character clustering based on mutual information into decision-tree dictionary-less morphological analysis. by using natural classes, we have confirmed that our morphological analyzer has been significantly improved in both tokenizing and tagging japanese text.
the replace operator. this paper introduces to the calculus of regular expressions a replace operator and defines a set of replacement expressions that concisely encode alternate variations of the operation. replace expressions denote regular relations, defined in terms of other regular expression operators. the basic case is unconditional obligatory replacement. we develop several versions of conditional replacement that allow the operation to be constrained by context.