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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 …...

To understand a speaker's turn of a con- versation, one needs to segment it into in- tonational phrases, clean up any speech re- pairs that might have occurred, and iden- …...

This paper analyses the relation between the use of similarity in Memory-Based Learning and the notion of backed-off smoothing in statistical language model- ing. We show that the two approaches …...

Language models for speech recognition con- centrate solely on recognizing the words that were spoken. In this paper, we advocate re- defining the speech recognition problem so that its goal …...

Srinivas (97) enriches traditional morpho-syntactic POS tagging with syntactic information by introducing Supertags. Unfortunately, words are assigned on average a much higher number of Supertags than traditional POS. In this …...

The paper presents a maximum entropy Chinese character-based parser trained on the Chinese Treebank (“CTB” hence- forth). Word-based parse trees CTB are first converted into character-in based trees, where word-level …...

This paper discusses the theoretical and practical concerns in part-of-speech (POS) tagging for Chinese. Unlike other languages such as English, Chinese lacks morphological marking in association with categorial alternations. We …...

We present new results for the DSTO project on document classification of military messages. We report more specifically on the improvements to the Part-Of-Speech (POS) tagging, probabilistic process that assigns …...

Discriminative models have been of inter- est in the NLP community in recent years. Previous research has shown that they are advantageous over generative mod- els. In this paper, we …...

Named Entity (NE) extraction is an important subtask of document processing such as in- formation extraction and question answering. A typical method used for NE extraction of Japanese texts is …...

In this paper we describe the (annotation) tools underly- ing two automatic techniques to analyse the meaning and use of backward causal connectives in large Dutch newspaper corpora. With the …...

This paper aims to further probe into the problems of ambiguities in automatic identification of determinative-measure compounds (DMs) in Chinese. It is known that Chinese DMs are identifiable by regular …...

Conditional random fields (Lafferty et al., 2001) are quite effective at sequence labeling tasks like shal- low parsing (Sha and Pereira, 2003) and named- entity extraction (McCallum and Li, 2003). …...

Faced with the problem of annotation er- rors in part-of-speech (POS) annotated corpora, we develop a method for auto- matically correcting such errors. Build- ing on top of a successful …...

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. …...

We describe a word alignment platform which ensures text pre-processing (to- kenization, POS-tagging, lemmatization, chunking, sentence alignment) as re- quired by an accurate word alignment. The platform combines two different …...

Combination of features contributes to a significant improvement in accuracy on tasks such as part-of-speech (POS) tag- ging and text chunking, compared with us- ing atomic features. However, selecting combination …...

As it serves as a basis for POS tagging, cat- egory induction, and human category ac- quisition, we investigate the information needed to disambiguate a word in a lo- cal …...

In this paper, we describe a new rerank- ing strategy named word lattice reranking, for the task of joint Chinese word segmen- tation and part-of-speech (POS) tagging. As a derivation …...

This paper proposes two techniques for fast sequential labeling such as part-of-speech (POS) tagging and text chunking. The first technique is a boosting-based al- gorithm that learns rules represented by …...

This paper describes POS tagging exper- iments with semi-supervised training as an extension to the (supervised) averaged perceptron algorithm, first introduced for this task by (Collins, 2002). Experiments with an …...

Although a lot of progress has been made recently in word segmentation and POS tagging for Chinese, the output of cur- rent state-of-the-art systems is too inaccu- rate to allow …...

. Part of Speech (POS) tagging is the task of labeling each word in a sentence with its appropriate syntactic category called part of speech. POS tagging is a very …...

The Viterbi algorithm is the conventional decoding algorithm most widely adopted for sequence labeling. Viterbi decoding is, however, prohibitively slow when the label set is large, because its time com- …...

AbstractWe investigate which distributional properties should be present in a tagset by examining different mappings of various current part-of-speech tagsets, looking at English, German, and Italian corpora. Given the importance …...

Modern unsupervised POS taggers usually apply an optimization procedure to a non- convex function, and tend to converge to local maxima that are sensitive to start- ing conditions. The quality …...

AbstractIn the POS tagging task, there are two kinds of statistical models: one is generative model, such as the HMM, the others are discriminative models, such as the Maximum Entropy …...

Part-of-speech (POS) tag distributions are known to exhibit sparsity — a word is likely to take a single predominant tag in a corpus. Recent research has demonstrated that incor- porating …...

AbstractMany NLP applications need fundamental tools to convert the input text into appropriate form or format and extract the primary linguistic knowledge of words and sentences. These tools perform segmentation …...

AbstractWe present the Database of Catalan Adjectives (DCA), a database with 2,296 adjective lemmata enriched with morphological, syntactic and semantic information. This set of adjectives has been collected from a …...

AbstractWe present our efforts to create a large-scale, semi-automatically annotated parallel corpus of cleft constructions. The corpus is intended to reduce or make more effective the manual task of finding …...

The large combined search space of joint word segmentation and Part-of-Speech (POS) tag- ging makes efficient decoding very hard. As a result, effective high order features represent- ing rich contexts …...

Part-of-speech (POS) is an indispensable fea- ture in dependency parsing. Current research usually models POS tagging and dependency parsing independently. This may suffer from error propagation problem. Our experiments show …...

AbstractWe adopt the corpus-informed approach to example sentence selections for the construction of a reference grammar. In the process, a database containing sentences that are carefully selected by linguistic experts …...

This paper describes the features and the ma- chine learning methods used by Dublin City University (DCU) and SYMANTEC for the WMT 2012 quality estimation task. Two sets of features …...

The easy-first non-directional dependency parser has demonstrated its advantage over transition based dependency parsers which parse sentences from left to right. This work investigates easy-first method on Chinese POS tagging, …...

AbstractAlthough lexicography of Latin has a long tradition dating back to ancient grammarians, and almost all Latin grammars devote to wordformation at least one part of the section(s) concerning morphology, …...

AbstractThe present paper tackles the issue of PoS tag conversion within the framework of a distributed web service platform for the automatic creation of language resources. PoS tagging is now …...

AbstractDue to the increase in the number and depth of analyses required over the text, like entity recognition, POS tagging, syntactic analysis, etc. the annotation in-line has become unpractical. In …...

In this paper, we propose a novel decoding al- gorithm for discriminative joint Chinese word segmentation, part-of-speech (POS) tagging, and parsing. Previous work often used a pipeline method – Chinese …...

AbstractThis article describes the collecting, processing and validation of a large balanced corpus for Romanian. The annotation types and structure of the corpus are briefly reviewed. It was constructed at …...

In recent years, statistical parsers have reached high performance levels on well-edited texts. Domain adaptation techniques have improved parsing results on text genres differing from the journalistic data most parsers …...

We present a general framework containing a graded spectrum of Expectation Maximization (EM) algorithms called Unified Expectation Maximization (UEM.) UEM is parameterized by a single parameter and covers existing al- …...

_______________________________________________________________________ Automatic tagging of a learner corpus of English with a modified version of the Penn Treebank tagset This article covers the issue of automatic annotation of a learner corpus …...

This paper proposes a combined model for POS tagging, dependency parsing and co-reference resolution for Bulgarian — a pro-drop Slavic language with rich mor- phosyntax. We formulate an extension of …...

We report on the recent development of ParZu, a German dependency parser. We discuss the effect of POS tagging and morphological analysis on parsing perfor- mance, and present novel ways …...

We improve upon a previous line of work for parsing web data, by exploring the im- pact of different decisions regarding the training data. First, we compare train- ing on …...

Inspired by robust generalization and adver- sarial learning we describe a novel approach to learning structured perceptrons for part-of- speech (POS) tagging that is less sensitive to domain shifts. The …...

Most existing systems for subcategoriza- tion frame (SCF) acquisition rely on su- pervised parsing and infer SCF distribu- tions at type, rather than instance level. These systems suffer from poor …...

AbstractAnnotated word structures are useful for various Chinese NLP tasks, such as word segmentation, POS tagging and syntactic parsing. Chinese word structures are often represented by binary trees, the nodes …...

AbstractIn this paper, we present the digitization and annotation of a tales corpus - which is to our knowledge the only French tales corpus available and classified according to the …...

We propose three improvements to ad- dress the drawbacks of state-of-the-art transition-based constituent parsers. First, to resolve the error propagation problem of the traditional pipeline approach, we incorporate POS tagging …...

AbstractPart-of-Speech (POS) tagging is a crucial task in Natural Language Processing (NLP). POS tags may be assigned to tokens in text manually, by trained linguists, or using algorithmic approaches. Particularly, …...

Code-mixing is frequently observed in user generated content on social media, especially from multilingual users. The linguistic complexity of such content is compounded by presence of spelling vari- ations, transliteration …...

AbstractIn this paper, we present a parallel literary corpus for Serbian, English and French, the TALC-sef corpus. The corpus includes a manually-revised pos-tagged reference Serbian corpus of over 150,000 words. …...

We report an empirical investigation on type-supervised domain adaptation for joint Chinese word segmentation and POS-tagging, making use of domain- specific tag dictionaries and only un- labeled target domain data …...

AbstractThis paper presents an end-to-end automatic processing system for Arabic. The system performs: correction of common spelling errors pertaining to different forms of alef, ta marbouta and ha, and alef …...

We propose a transition-based model for joint word segmentation, POS tagging and text normalization. Different from pre- vious methods, the model can be trained on standard text corpora, overcoming the …...

This paper describes the implementation, im- provement and evaluation of the machine translation (MT) system proposed by Jackov (2014) when used as a feature-rich part-of- speech (POS) tagger for Bulgarian. …...

In this paper we explore a POS tagging ap- plication of neural architectures that can infer word representations from the raw character stream. It relies on two mod- elling stages …...

We propose online unsupervised domain adaptation (DA), which is performed in- crementally as data comes in and is appli- cable when batch DA is not possible. In a part-of-speech (POS) …...

Part-of-Speech (POS) tagging is a key step in many NLP algorithms. However, tweets are difficult to POS tag because there are many phenomena that frequently appear in Twitter that are …...

In this paper, we introduce a new approach for joint segmentation, POS tagging and de- pendency parsing. While joint modeling of these tasks addresses the issue of error prop- agation …...

. Robust statistical NLP tools, such as pos-taggers and syntax parsers, often use knowledge-poor features, which can easily be applied to any language, but which do not take into account …...

AbstractIn this paper, we empirically explore the effects of various kinds of skip connections in stacked bidirectional LSTMs for sequential tagging. We investigate three kinds of skip connections connecting to …...

AbstractWe propose a new approach to PoS tagging where in a first step, we assign a coarse-grained tag corresponding to the main syntactic category. Based on this high-precision decision, in …...

AbstractIn this paper, we propose a new annotation approach to Chinese word segmentation, part-of-speech (POS) tagging and dependency labelling that aims to overcome the two major issues in traditional morphology-based …...

AbstractPart-of-Speech(POS) tagging is a key step in many NLP algorithms. However, tweets are difficult to POS tag because they are short, are not always written maintaining formal grammar and proper …...

Part-of-speech (POS) taggers trained on newswire perform much worse on domains such as subtitles, lyrics, or tweets. In addition, these domains are also heterogeneous, e.g., with respect to registers and …...

AbstractThis paper relates to the challenge of morphological tagging and lemmatization in morphologically rich languages by example of German and Latin. We focus on the question what a practitioner can …...

AbstractWe present a study of the adequacy of current methods that are used for POS-tagging historical Dutch texts, as well as an exploration of the influence of employing different techniques …...

AbstractThis article describes the conversion of the Norwegian Dependency Treebank to the Universal Dependencies scheme. This paper details the mapping of PoS tags, morphological features and dependency relations and provides …...

AbstractThis paper proposes a generic method for the comparative evaluation of system outputs. The approach is able to quantify the pairwise differences between two outputs and to unravel in detail …...

AbstractPart of speech (POS) taggers and dependency parsers tend to work well on homogeneous datasets but their performance suffers on datasets containing data from different genres. In our current work, …...

AbstractTraining a POS tagging model with crosslingual transfer learning usually requires linguistic knowledge and resources about the relation between the source language and the target language. In this paper, we …...

AbstractWe pose the general task of user-factor adaptation – adapting supervised learning models to real-valued user factors inferred from a background of their language, reflecting the idea that a piece …...

AbstractPart-of-speech (POS) tagging for morphologically rich languages such as Arabic is a challenging problem because of their enormous tag sets. One reason for this is that in the tagging scheme …...

AbstractThis paper describes our system, dubbed MoRS (Modular Ranking System), pronounced ‘Morse’, which participated in Task 3 of SemEval-2017. We used MoRS to perform the Community Question Answering Task 3, …...

AbstractWe present neural network-based joint models for Chinese word segmentation, POS tagging and dependency parsing. Our models are the first neural approaches for fully joint Chinese analysis that is known …...

AbstractWe propose a sequence labeling framework with a secondary training objective, learning to predict surrounding words for every word in the dataset. This language modeling objective incentivises the system to …...

AbstractWe evaluate a semantic parser based on a character-based sequence-to-sequence model in the context of the SemEval-2017 shared task on semantic parsing for AMRs. With data augmentation, super characters, and …...

The Part-Of-Speech tag of a word can pro- vide crucial information for a large num- ber of tasks, and so, it is of utmost im- portance that the POS tagged …...

Dependency treebank is an important resource in any language. In this paper, we present our work on building BKTreebank, a dependency treebank for Vietnamese. Important points on designing POS tagset, …...

AbstractGenerating character-level features is an important step for achieving good results in various natural language processing tasks. To alleviate the need for human labor in generating hand-crafted features, methods that …...

Speech corpora are key components needed by both: linguists (in language analyses, research and teaching languages) and Natural Language Processing (NLP) researchers (in training and evaluating several NLP tasks such …...

AbstractWe investigate the design challenges of constructing effective and efficient neural sequence labeling systems, by reproducing twelve neural sequence labeling models, which include most of the state-of-the-art structures, and conduct …...

AbstractThis paper presents three ongoing projects for NLP in Cook Islands Maori: Untrained Forced Alignment (approx. 9% error when detecting the center of words), speech-to-text (37% WER in the best …...

AbstractWe present a graph-based Tree Adjoining Grammar (TAG) parser that uses BiLSTMs, highway connections, and character-level CNNs. Our best end-to-end parser, which jointly performs supertagging, POS tagging, and parsing, outperforms …...

Parts of Speech (POS) tagging is an important pre-requisite for various Natural Language Processing tasks. POS tagging is rather challenging for morphologically rich languages such as Tamil. Being low-resourced, Tamil …...

Lack of parallel training data influences the rare word problem in Neural Machine Translation (NMT) systems, particularly for under- resourced languages. Using synthetic parallel training data (data augmentation) is a …...

AbstractNeural morphological tagging has been regarded as an extension to POS tagging task, treating each morphological tag as a monolithic label and ignoring its internal structure. We propose to view …...

Part-of-speech (POS) tagging is one of the most important addressed areas in the natural language processing (NLP). There are effective POS taggers for many languages including Arabic. However, POS research …...

In this paper, we describe the process of creating an Amharic Dependency Treebank, which is the first attempt to introduce Universal Dependencies (UD) into Amharic. Amharic is a morphologically-rich and …...

This platform includes two main concepts. One, provide multifaceted and deep evaluation for users of Natural Language Processing (NLP) System (such as Syntaxnet or CoreNLP), to help them choose the …...

We propose the first multi-task learning model for joint Vietnamese word segmentation, part- of-speech (POS) tagging and dependency parsing. In particular, our model extends the BIST graph-based dependency parser (Kiper- …...

AbstractCRF has been used as a powerful model for statistical sequence labeling. For neural sequence labeling, however, BiLSTM-CRF does not always lead to better results compared with BiLSTM-softmax local classification. …...

AbstractMachine translation of ancient languages faces a low-resource problem, caused by the limited amount of available textual source data and their translations. We present a multi-task modeling approach to translating …...

AbstractIn Chinese dependency parsing, the joint model of word segmentation, POS tagging and dependency parsing has become the mainstream framework because it can eliminate error propagation and share knowledge, where …...

AbstractRecently, pre-training contextualized encoders with language model (LM) objectives has been shown an effective semi-supervised method for structured prediction. In this work, we empirically explore an alternative pre-training method for …...

AbstractNamed entities pose a unique challenge to traditional methods of language modeling. While several domains are characterised with a high proportion of named entities, the occurrence of specific entities varies …...

AbstractContextualized representations give significantly improved results for a wide range of NLP tasks. Much work has been dedicated to analyzing the features captured by representative models such as BERT. Existing …...

AbstractLinguistic Code-switching (CS) is still an understudied phenomenon in natural language processing. The NLP community has mostly focused on monolingual and multi-lingual scenarios, but little attention has been given to …...

AbstractWord embeddings and pre-trained language models allow to build rich representations of text and have enabled improvements across most NLP tasks. Unfortunately they are very expensive to train, and many …...

AbstractCode-switching is the use of more than one language in the same conversation or utterance. Recently, multilingual contextual embedding models, trained on multiple monolingual corpora, have shown promising results on …...

AbstractWe look into the task of generalizing word embeddings: given a set of pre-trained word vectors over a finite vocabulary, the goal is to predict embedding vectors for out-of-vocabulary words, …...

AbstractScientific keyphrase identification and classification is the task of detecting and classifying keyphrases from scholarly text with their types from a set of predefined classes. This task has a wide …...

AbstractPerformance in cross-lingual NLP tasks is impacted by the (dis)similarity of languages at hand: e.g., previous work has suggested there is a connection between the expected success of bilingual lexicon …...

AbstractThis paper presents the first ever comprehensive evaluation of different types of word embeddings for Sinhala language. Three standard word embedding models, namely, Word2Vec (both Skipgram and CBOW), FastText, and …...

AbstractPart of speech (POS) tagging is a familiar NLP task. State of the art taggers routinely achieve token-level accuracies of over 97% on news body text, evidence that the problem …...

AbstractThe adaptation of pretrained language models to solve supervised tasks has become a baseline in NLP, and many recent works have focused on studying how linguistic information is encoded in …...

AbstractWe explore the impact of leveraging the relatedness of languages that belong to the same family in NLP models using multilingual fine-tuning. We hypothesize and validate that multilingual fine-tuning of …...

AbstractContextual word-representations became a standard in modern natural language processing systems. These models use subword tokenization to handle large vocabularies and unknown words. Word-level usage of such systems requires a …...

AbstractAdapting word order from one language to another is a key problem in cross-lingual structured prediction. Current sentence encoders (e.g., RNN, Transformer with position embeddings) are usually word order sensitive. …...

AbstractGreedy algorithms for NLP such as transition-based parsing are prone to error propagation. One way to overcome this problem is to allow the algorithm to backtrack and explore an alternative …...

AbstractIn this paper we present the Serbian part of the ELTeC multilingual corpus of novels written in the time period 1840-1920. The corpus is being built in order to test …...

AbstractPart-of-Speech (POS) tagging is an important component of the NLP pipeline, but many low-resource languages lack labeled data for training. An established method for training a POS tagger in such …...

AbstractThis paper presents a language-independent approach for morphological disambiguation which has been regarded as an extension of POS tagging, jointly predicting complex morphological tags. In the proposed approach, all words, …...

AbstractIn this paper we present the final result of a project focused on Tunisian Arabic encoded in Arabizi, the Latin-based writing system for digital conversations. The project led to the …...

AbstractWe introduce Textstar, a graph-based summarization and keyphrase extraction system that builds a document graph using only lemmatization and POS tagging. The document graph aggregates connections between lemma and sentence …...

AbstractWe present ZAEBUC, an annotated Arabic-English bilingual writer corpus comprising short essays by first-year university students at Zayed University in the United Arab Emirates. We describe and discuss the various …...

AbstractNeural language models play an increasingly central role for language processing, given their success for a range of NLP tasks. In this study, we compare some canonical strategies in language …...

AbstractWe present Expected Statistic Regulariza tion (ESR), a novel regularization technique that utilizes low-order multi-task structural statistics to shape model distributions for semi- supervised learning on low-resource datasets. We study …...