Ықтималдық моделі

In this paper we investigate polysemous adjectives whose meaning varies depending on the nouns they modify (e.g., fast). We acquire the meanings of these adjectives from a large corpus and …...

Title generation is a complex task involving both natural language understanding and natural language synthesis. In this paper, we propose a new probabilistic model for title generation. Different from the …...

Aligning words from sentences which are mutual translations is an important problem in different set- tings, such as bilingual terminology extraction, Ma- chine Translation, or projection of linguistic fea- tures. …...

In this paper we propose a data intensive ap- proach for inferring sentence-internal tempo- ral relations, which relies on a simple prob- abilistic model and assumes no manual cod- ing. …...

This article studies different aspects of a new approach for word sense disambiguation using statistical information gains from a target language monolingual corpus. Here, the source language is English and …...

This paper presents a maximum entropy word alignment algorithm for Arabic- English based on supervised training data. We demonstrate that it is feasible to cre- ate training material for problems …...

Previous research applying kernel meth- ods to natural language parsing have fo- cussed on proposing kernels over parse trees, which are hand-crafted based on do- main knowledge and computational con- …...

We present an integrated probabilistic model for Japanese syntactic and case structure analysis. Syntactic and case structure are simultaneously analyzed based on wide-coverage case frames that are constructed from a …...

In this paper, we present a method for guessing POS tags of unknown words us- ing local and global information. Al- though many existing methods use only local information (i.e. …...

Named-entity recognition systems extract entities such as people, organizations, and locations from unstructured text. Rather than extract these mentions in isolation, this paper presents a record extraction sys- tem that …...

We present the psycholinguistically moti- vated task of predicting human plausibility judgements for verb-role-argument triples and introduce a probabilistic model that solves it. We also evaluate our model on the …...

Previous results have shown disappointing performance when porting a parser trained on one domain to another domain where only a small amount of data is available. We propose the use …...

The majority of the state-of-the-art ap- proaches to recognizing textual entailment focus on defining a generic approach to RTE. A generic approach never works well for every single entailment pair: …...

This paper describes a probabilistic model for coordination disambiguation integrated into syntactic and case structure analy- sis. Our model probabilistically assesses the parallelism of a candidate coordinate structure using syntactic/semantic …...

Words of foreign origin are referred to as borrowed words or loanwords. A loanword is usually imported to Chinese by phonetic transliteration if a translation is not easily available. Semantic …...

This paper presents a probabilistic model for Japanese zero anaphora resolution. First, this model recognizes discourse en- tities and links all mentions to them. Zero pronouns are then detected by …...

The most critical issue in generating and recognizing paraphrases is development of wide-coverage paraphrase knowledge. Previous work on paraphrase acquisition has collected lexicalized pairs of expres- sions; however, the results …...

. This work is part of a large research project entitled "Oreillodule" aimed at developing tools for automatic speech recognition, translation, and synthesis for Arabic language. Our attention has mainly …...

This paper proposes a novel method to analyze syntactic dependencies and label semantic dependencies around both the verbal predicates and the nouns. In this method, a probabilistic model is designed …...

This paper presents a probabilistic model for resolution of non-pronominal anaphora in biomedical texts. The model seeks to find the antecedents of anaphoric expres- sions, both coreferent and associative ones, …...

The work presented in this paper explores a supervised method for learning a prob- abilistic model of a lexicon of VerbNet classes. We intend for the probabilis- tic model to …...

A range of Natural Language Process- ing tasks involve making judgments about the semantic relatedness of a pair of sen- tences, such as Recognizing Textual En- tailment (RTE) and answer …...

Datasets annotated with semantic roles are an important prerequisite to developing high- performance role labeling systems. Unfortu- nately, the reliance on manual annotations, which are both difficult and highly expen- …...

Learning by Reading (LbR) aims at enabling machines to acquire knowledge from and rea- son about textual input. This requires knowl- edge about the domain structure (such as en- tities, …...

AbstractResearchers in the fields of psycholinguistics and neurolinguistics increasingly test their experimental hypotheses against probabilistic models of language. VALEX (Korhonen et al., 2006) is a large-scale verb lexicon that specifies …...

Methods for information extraction (IE) and knowledge base (KB) construction have been intensively studied. However, a largely under-explored case is tapping into highly dynamic sources like news streams and social …...

We describe a new probabilistic model for extracting events between major polit- ical actors from news corpora. Our un- supervised model brings together famil- iar components in natural language pro- …...

When reviewing scientific literature, it would be useful to have automatic tools that iden- tify the most influential scientific articles as well as how ideas propagate between articles. In this …...

We address the problem of discovering topical phrases or “aspects” from microblogging sites like Twitter, that correspond to key talking points or buzz around a particular topic or entity of …...

The phonotactics of a language describes the ways in which the sounds of the language combine to form possible mor- phemes and words. Humans can learn phonotactic patterns at the …...

Cross-lingual text classification is a major challenge in natural language processing, since often training data is available in only one language (target language), but not avail- able for the language …...

As documents tend to contain temporal information, extracting such information is attracting much research interests re- cently. In this paper, we propose a hybrid method that combines machine-learning models and …...

Different from traditional active learning based on sentence-wise full annotation (FA), this paper proposes active learning with dependency-wise partial annotation (PA) as a finer-grained unit for dependency parsing. At each …...

Word embedding has been widely studied and proven helpful in solving many natural lan- guage processing tasks. However, the ambi- guity of natural language is always a prob- lem on …...

We present a probabilistic model of the in- fluence of language on the behavior of the U.S. Supreme Court, specifically influence of amicus briefs on Court decisions and opin- ions. …...

We study the problem of automatically building hypernym taxonomies from tex- tual and visual data. Previous works in taxonomy induction generally ignore the increasingly prominent visual data, which encode important …...

AbstractMuch like sentences are composed of words, words themselves are composed of smaller units. For example, the English word questionably can be analyzed as question+able+ly. However, this structural decomposition of …...

AbstractThis paper describes an unsupervised model for morphological segmentation that exploits the notion of paradigms, which are sets of morphological categories (e.g., suffixes) that can be applied to a homogeneous …...

AbstractWe present a corpus of anaphoric information (coreference) crowdsourced through a game-with-a-purpose. The corpus, containing annotations for about 108,000 markables, is one of the largest corpora for coreference for English, …...

AbstractIn this paper, we present two methods to identify and categorize the offensive language in Twitter. In the first method, we establish a probabilistic model to evaluate the sentence offensiveness …...

AbstractIn linguistics and cognitive science, Logical metonymies are defined as type clashes between an event-selecting verb and an entity-denoting noun (e.g. The editor finished the article), which are typically interpreted …...

AbstractA case-based reasoning (CBR) system solves a new problem by retrieving ‘cases’ that are similar to the given problem. If such a system can achieve high accuracy, it is appealing …...

AbstractThe quality estimation of artifacts generated by creators via crowdsourcing has great significance for the construction of a large-scale data resource. A common approach to this problem is to ask …...

AbstractWhile often assumed a gold standard, effective human evaluation of text generation remains an important, open area for research. We revisit this problem with a focus on producing consistent evaluations …...

AbstractIdentifying phone inventories is a crucial component in language documentation and the preservation of endangered languages. However, even the largest collection of phone inventory only covers about 2000 languages, which …...