waashk/dblp huggingface dataset:
a probabilistic context-free grammar for disambiguation in morphological parsing. one of the major problems one is faced with when decomposing words into their constituent parts is ambiguity: the generation of multiple analyses for one input word, many of which are implausible. in order to deal with ambiguity, the mor-phological parser morpa is provided with a probabilistic context-free grammar (pcfg), i.e. it combines a "conventional" context-free morphological grammar to filter out ungrammatical segmentations with a probability-based scoring function which determines the likelihood of each successful parse. consequently, remaining analyses can be ordered along a scale of plausibility. test performance data will show that a pcfg yields good results in morphological parsing. morpa is a fully implemented parser developed for use in a text-to-speech conversion system.
well-nested parallelism constraints for ellipsis resolution. the constraint language for lambda structures (clls) is an expressive tree description language. it provides a uniform framework for underspecified semantics, covering scope, ellipsis, and anaphora. efficient algorithms exist for the sublanguage that models scope. but so far no terminating algorithm exists for sublanguages that model ellipsis. we introduce well-nested parallelism constraints and show that they solve this problem.
horn extended feature structures: fast unification with negation and limited disjunction. the notion of a horn extended feature structure (hoxf) is introduced, which is a feature structure constrained so that its only allowable extensions are those satisfying some set of horn clauses in feature-term logic. hoxf's greatly generalize ordinary feature structures in admitting explicit representation of negative and implicational constraints. in contradistinction to the general case in which arbitrary logical constraints are allowed (for which the best known algorithms are exponential), there is a highly tractable algorithm for the unification of hoxf's.
bilingually motivated domain-adapted word segmentation for statistical machine translation. we introduce a word segmentation approach to languages where word boundaries are not orthographically marked, with application to phrase-based statistical machine translation (pb-smt). instead of using manually segmented monolingual domain-specific corpora to train segmenters, we make use of bilingual corpora and statistical word alignment techniques. first of all, our approach is adapted for the specific translation task at hand by taking the corresponding source (target) language into account. secondly, this approach does not rely on manually segmented training data so that it can be automatically adapted for different domains. we evaluate the performance of our segmentation approach on pb-smt tasks from two domains and demonstrate that our approach scores consistently among the best results across different data conditions.
remarks on plural anaphora. the interpretation of plural anaphora often requires the construction of complex reference objects (refos) out of refos which were formerly introduced not by plural terms but by a number of singular terms only. often, several complex refos can be constructed, but only one of them is the preferred referent for the plural anaphor in question. as a means of explanation for preferred and non-preferred interpretations of plural anaphora, the concept of a common association basis (cab) for the potential atomic parts of a complex object is introduced in the following. cabs pose conceptual constraints on the formation of complex refos in general. we argue that in cases where a suitable cab for the atomic refos introduced in the text exists, the corresponding complex refo is constructed as early as in the course of processing the antecedent sentence and put into the focus domain of the discourse model. thus, the search for a referent for a plural anaphor is constrained to a limited domain of refos according to the general principles of focus theory in nlp. further principles of interpretation are suggested which guide the resolution of plural anaphora in cases where more than one suitable complex refo is in focus.
collocations in multilingual generation. we present a proposal for the structuring of collocation knowledge' in the lexicon of a multilingual generation system and show to what extent it can be used in the process of lexical selection. this proposal is part of polygloss, a new research project on multilingual generation, and it has been inspired by work carried out in the semsyn project (see e.g. [r&ouml;sner 1988]). the descriptive approach presented in this proposal is based on a combination of results from recent lexico-graphical research and the application of meaning-text-theory (mtt) (see e.g. [mel'&ccaron;uk et al. 1981], [mel'&ccaron;uk et al. 1984]). we first outline the overall structure of the dictionary system that is needed by a multilingual generator; section 2 gives an overview of the results of lexicographical work on collocations and compares them with "lexical functions" as used in meaning-text-theory. section 3 shows how we intend to integrate collocations in the generation dictionary and how "lexical functions" can be used in generation.
neural network probability estimation for broad coverage parsing. we present a neural-network-based statistical parser, trained and tested on the penn treebank. the neural network is used to estimate the parameters of a generative model of left-corner parsing, and these parameters are used to search for the most probable parse. the parser's performance (88.8% f-measure) is within 1% of the best current parsers for this task, despite using a small vocabulary size (512 inputs). crucial to this success is the neural network architecture's ability to induce a finite representation of the unbounded parse history, and the biasing of this induction in a linguistically appropriate way.
inference in datr. datr is a declarative language for representing a restricted class of inheritance networks, permitting both multiple and default inheritance. the principal intended area of application is the representation of lexical entries for natural language processing, and we use examples from this domain throughout. in this paper we present the syntax and inference mechanisms for the language. the goal of the datr enterprise is the design of a simple language that (i) has the necessary expressive power to encode the lexical entries presupposed by contemporary work in the unification grammar tradition, (ii) can express all the evident generalizations about such entries, (iii) has an explicit theory of inference, (iv) is computationally tractable, and (v) has an explicit declarative semantics. the present paper is primarily concerned with (iii), though the examples used may hint at our strategy in respect of (i) and (ii).
mixing modes of linguistic description in categorial grammar. recent work within the field of categorial grammar has seen the development of approaches that allow different modes of logical behaviour to be displayed within a single system, something corresponding to making available differing modes of linguistic description. earlier attempts to achieve this goal have employed modal operators called structural modalities, whose use presents a number of problems. i propose an alternative approach, involving co-existence and interrelation of different sublogics, that eliminates the need for structural modalities, whilst maintaining the descriptive power they provide.
wysiwym - building user interfaces with natural language feedback. wysiwym ('what you see is what you meant') is a user-interface technique which uses natural language generation (nlg) technology to provide feedback for user interactions. to date, the technology has been applied in a number of demonstrator applications, using customised, non-portable implementations. in this demonstration, we introduce a wysiwym library package, designed to be used as a modular component of a larger java-based application. we show how the overall design of the package aims to support a range of possible applications using simple configuration options and java subclassing, and illustrate the approach using examples ranging from the simplest proof-of-concept application to a complex web-delivered authoring tool for pharmaceutical leaflets.
parsing and derivational equivalence. it is a tacit assumption of much linguistic inquiry that all distinct derivations of a string should assign distinct meanings. but despite the tidiness of such derivational uniqueness, there seems to be no a priori reason to assume that a grammar must have this property. if a grammar exhibits derivational equivalence, whereby distinct derivations of a string assign the same meanings, naive exhaustive search for all derivations will be redundant, and quite possibly intractable. in this paper we show how notions of derivation-reduction and normal form can be used to avoid unnecessary work while parsing with grammars exhibiting derivational equivalence. with grammar regarded as analogous to logic, derivations are proofs; what we are advocating is proof-reduction, and normal form proof; the invocation of these logical techniques adds a further paragraph to the story of parsing-as-deduction.
experiments on candidate data for collocation extraction. the paper describes ongoing work on the evaluation of methods for extracting collocation candidates from large text corpora. our research is based on a german treebank corpus used as gold standard. results are available for adjective+noun pairs, which proved to be a comparatively easy extraction task. we plan to extend the evaluation to other types of collocations (e.g., pp+verb pairs).
descriptional anaphora in discourse representation theory. standard discourse representation theory (drt) was designed mainly to explain the so-called donkey-sentences. the pronouns playing such a prominent role in all these sentences belong, however, exclusively to one (particularly simple) type of pronoun. we try to extend drt in order to cover an equally important type of pronoun, the so-called "descriptional" pronoun. discourse referents are now used to carry information on the intension of their referents as well as on the extension. this allows, at the same time, to suggest accessibility rules for pronouns which are more appropriate than those suggested by traditional drt. these new rules are based on the genericness of the sentences involved.
iteration, habituality and verb form semantics. the verb forms are often claimed to convey two kinds of information:1. whether the event described in a sentence is present, past or future (= deictic information.2. whether the event described in a sentence is presented, as completed, going on, just starting or being finished (= aspectual information)it will be demonstrated in this paper that one has to add a third component to the analysis of verb form meanings, namely whether or not they express habituality.the framework of the analysis is model-theoretic semantics.
how does natural language quantify? it has traditionally been assumed that natural language uses explicit quantifier expressions (such as "all" and "most", "the" and "a") for the purpose of quantification. we argue that expressions of the first type are comparatively rare in real world natural language sentences, and that the latter (articles) cannot be considered straightforward quantifiers in the first place. however, practically all applications of natural language processing require sentences to be quantified unambiguously. we list a few possible (syntactical, semantical, and "pragmatical") sources of "implicit" quantificational information in natural language; they combine in sometimes intricate ways to give a sentence a (more or less) unambiguous quantification.
a machine learning approach to the identification of wh gaps. in this paper, we pursue a multi-modular, statistical approach to wh dependencies, using a feedforward network as our modeling tool. the empirical basis of this model and the availability of performance measures for our system address deficiencies in earlier computational work on wh gaps, which require richer sources of semantic and lexical information in order to run. the statistical nature of our models allows them to be simply combined with other modules of grammar, such as a syntactic parser.
generating sentences from different perspectives. certain pairs or groups of sentences appear to be semantically distinct, yet specify the same underlying state of affairs, from different perspectives. this leads to questions about what that underlying state of affairs might be, and, for generation, how and why the alternative expressions might be produced. this paper looks at how such sentences may be generated in a natural language interface to a database system.
algorithms for analysing the temporal structure of discourse. we describe a method for analysing the temporal structure of a discourse which takes into account the effects of tense, aspect, temporal adverbials and rhetorical structure and which minimises unnecessary ambiguity in the temporal structure. it is part of a discourse grammar implemented in carpenter's ale formalism. the method for building up the temporal structure of the discourse combines constraints and prefernces: we use constraints to reduce the number of possible structures, exploiting the hpsg type hierarchy and unification for this purpose; and we apply preferences to choose between the remaining options using a temporal centering mechanism. we end by recommending that an underspecified representation of the structure using these techniques be used to avoid generating the temporal/rhetorical structure until higher-level information can be used to disambiguate.
a dynamic logic formalisation of the dialogue gameboard. this paper explores the possibility of using the paradigm of dynamic logic (dl) to formalise information states and update processes on information states. in particular, we present a formalisation of the dialogue gameboard introduced by jonathan ginzburg. from a more general point of view, we show that dl is particularly well suited to develop rigorous formal foundations for an approach to dialogue dynamics based on information state updates.
a best-first search algorithm for generating referring expressions. existing algorithms for generating referential descriptions to sets of objects have serious deficits: while incremental approaches may produce ambiguous and redundant expressions, exhaustive searches are computationally expensive. mediating between these extreme control regimes, we propose a best-first searching algorithm for uniquely identifying sets of objects. we incorporate linguistically motivated preferences and several techniques to cut down the search space. preliminary results show the effectiveness of the new algorithm.
the donkey strikes back: extending the dynamic interpretation "constructively". the dynamic interpretation of a formula as a binary relation (inducing transitions) on states is extended by alternative treatments of implication, universal quantification, negation and disjunction that are more "dynamic" (in a precise sense) than the usual reductions to tests from quantified dynamic logic (which, nonetheless, can be recovered from the new connectives). an analysis of the "donkey" sentence followed by the assertion "it will kick back" is provided.
ambiguous propositions typed. ambiguous propositions are analyzed in a type system where disambiguation is effected during assembly (i.e. by coercion). ambiguity is introduced through a layer of types that are underspecified relative to a pre-existing collection of dependent types, construed as unambiguous propositions. a simple system of reasoning directly with such underspecification is described, and shown to be sound and complete for the full range of disambiguations. beyond erasing types, the system supports constraints on disambiguations, including co-variation.
integrating "free" word order syntax and information structure. multiset-ccg is a combinatory categorial formalism that can capture the syntax and interpretation of "free" word order in languages such as turkish. the formalism compositionally derives the predicate-argument structure and the information structure (e.g. topic, focus) of a sentence, and uniformly handles word order variation among arguments and adjuncts within a clause, as well as in complex clauses and across clause boundaries.
using a text model for analysis and generation. the following paper concerns a general scheme for multilingual text generation, as opposed to just translation. our system processes the text as a whole, from which it extracts a representation of the meaning of the text. from this representation, a new text is generated, using a text model and action rules.this process is done in six steps: word analysis, sentence analysis using a functional grammar, reference solving and inference, construction of the text pattern, sentence generation, and word generation. different kinds of information are used at each step of the process: text organization, syntax, semantic, etc.all the knowledge, as well as the text, is given in a declarative manner. it is expressed in a single formalism named functional descriptions. it consists of lexical data, a functional grammar, a knowledge network, action rules for reference solving and sentence generation, models of text, rules of structuration, and sentence schema.text representation, included in the semantic network, is composed of different kinds of objects (not necessarily distinct): text organization, syntactical information, objects introduced by the discourse, affirmations on these objects, and links between these affirmations.
exploiting conversational implicature for generating concise explanations. this paper presents an approach for achieving conciseness in generating explanations, which is done by exploiting formal reconstructions of aspects of the gricean principle of relevance to simulate conversational implicature. by applying contextually motivated inference rules in an anticipation feed-back loop, a set of propositions explicitly representing an explanation's content is reduced to a subset which, in the actual context, can still be considered to convey the message adequately.
effect of utilizing terminology on extraction of protein-protein interaction information from biomedical literature. as the amount of on-line scientific literature in the biomedical domain increases, automatic processing has become a promising approach for accelerating research. we are applying syntactic parsing trained on the general domain to identify protein-protein interactions. one of the main difficulties obstructing the use of language processing is the prevalence of specialized terminology. accordingly, we have created a specialized dictionary by compiling on-line glossaries, and have applied it for information extraction. we conducted preliminary experiments on one hundred sentences, and compared the extraction performance when (a) using only a general dictionary and (b) using this plus our specialized dictionary. contrary to our expectation, using only the general dictionary resulted in better performance (recall 93.0%, precision 91.0%) than with the terminology-based approach (recall 92.9%, precision 89.6%).
rigid grammars in the associative-commutative lambek calculus are not learnable. in (kanazawa, 1998) it was shown that rigid classical categorial grammars are learnable (in the sense of (gold, 1967)) from strings. surprisingly there are recent negative results for, among others, rigid associative lambek (l) grammars.in this paper the non-learnability of the class of rigid grammars in lp (associative-commutative lambek calculus) and lp&oslash; (same, but allowing the empty sequent in derivations) will be shown.
classifying biological full-text articles for multi-database curation. in this paper, we propose an approach for identifying curatable articles from a large document set. this system considers three parts of an article (title and abstract, mesh terms, and captions) as its three individual representations and utilizes two domain-specific resources (umls and a tumor name list) to reveal the deep knowledge contained in the article. an svm classifier is trained and cross-validation is employed to find the best combination of representations. the experimental results show overall high performance.
lexicon acquisition with a large-coverage unification-based grammar. we describe how unknown lexical entries are processed in a unification-based framework with large-coverage grammars and how from their usage lexical entries are extracted. to keep the time and space usage during parsing within bounds, information from external sources like part of speech (pos) taggers and morphological analysers is taken into account when information is constructed for unknown words.
dealing with conjunctions in a machine translation environment. a set of rules, named csdc (conjunct scope determination constraints), is suggested for attacking the conjunct scope problem, the major issue in the automatic processing of conjunctions which has been raising great difficulty for natural language processing systems. grammars embodying the csdc are incorporated into an existing atn parser, and are tested successfully against a wide group of "and" conjunctive sentences, which are of three types, namely clausal coordination, phrasal coordination, and gapping. with phrasal coordination the structure with two nps coordinated by "and" has been given most attention.it is hoped that an atn parser capable of dealing with a large variety of conjunctions in an efficient way will finally emerge from the present work.
rules for pronominalization. rigorous interpretation of pronouns in possible when syntax, semantics, and pragmatics of a discourse can be reasonably controlled. interaction with a database provides such an environment. in the framework of the user specialty languages system and discourse representation theory, we formulate strict and preferential rules for pronominalization and outline a procedure to find proper assignments of referents to pronouns.
grouping words using statistical context. this paper describes the use of statistical analyses of untagged corpora to detect similarities and differences in the meaning of words in text. this work is motivated by psychological as well as by computational issues. the limitations of the method of cluster analysis in assessing the success of such analyses are discussed, and ongoing research using an alternative unsupervised neural network approach is described.