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We report grammar inference experiments on partially parsed sentences taken from the Wall Street Journal corpus using the inside-outside algorithm for stochastic context-free grammars. The initial grammar for the inference …...

The described tagger is b,'used on a hidden Markov model and uses tags composed of features such as part- of speech, gender, etc. 'l?he contextual probability of a tag (state …...

This paper presents a statistical model which trains from a corpus annotated with Part-Of- Speech tags and assigns them to previously unseen text with state-of-the-art accuracy(96.6%). The model can be …...

This paper discusses research on distin- guishing word meanings in the context of information retrieval systems. We conduc- ted experiments with three sources of evid- ence for making these distinctions: …...

In this paper we deal with several kinds of anaphora in unrestricted texts. These kinds of anaphora are pronominal references, surface- count anaphora and one-anaphora. In order to solve these …...

In this paper we present an algorithm to an- chor floating quantifiers in Japanese, a language in which quantificational nouns and numeral- classifier combinations can appear separated from the noun …...

This paper investigates the use of clustering techniques in word-sense classification, which identifies different contexts that a word was used with the same or similar sense. For simplicity, we have …...

It. is common in NLP that the categories into which text is classified do not have fully objective def- initions. Examples of such categories are lexical distinctions such as part-of-speech …...

This paper presents a novel statistical model for automatic identification of English baseNP. It uses two steps: the N- best Part-Of-Speech (POS) tagging and baseNP identification given the N-best POS-sequences. …...

We describe how unknown lexical en- tries are processed in a unification-based framework with large-coverage gram- mars and how from their usage lexi- cal entries are extracted. To keep the …...

In this paper, we present an application- oriented evaluation of three Part-of- Speech (PoS) taggers in a word sense disambiguation (WSD) system. Follow- ing the intuition that high quality input …...

This paper describes the SyntaLex entries in the English Lexical Sample Task of SENSEVAL-3. There are four entries in all, where each of the dif- ferent entries corresponds to use …...

. In this paper, we present an empirical study that utilizes morph-syntactical information to improve translation quality. With three kinds of language pairs matched according to morph-syntactical similar- ity or …...

AbstractThis paper presents a reordering framework for statistical machine translation (SMT) where source-side reorderings are integrated into SMT decoding, allowing for a highly constrained reordered search graph. The monotone search …...

Historically, unsupervised learning tech- niques have lacked a principled technique for selecting the number of unseen compo- nents. Research into non-parametric priors, such as the Dirichlet process, has enabled in- …...

Evaluation and error analysis of machine translation output are important but difficult tasks. In this work, we propose a novel method for obtaining more details about ac- tual translation errors …...

We present a word substitution approach to combine the output of different machine translation systems. Using part of speech information, candidate words are deter- mined among possible translation options, which …...

We present a method for incorporat- ing arbitrary context-informed word at- tributes into statistical machine trans- lation by clustering attribute-quali ed source words, and smoothing their word translation probabilities using …...

AbstractIn this paper we present a description of negation cues and their scope in biomedical texts, based on the cues that occur in the BioScope corpus. We provide information about …...

We describe a new scalable algorithm for semi-supervised training of conditional ran- dom fields (CRF) and its application to part- of-speech (POS) tagging. The algorithm uses a similarity graph to …...

This paper presents an algorithm for unsu- pervised co-occurrence based parsing that improves and extends existing approaches. The proposed algorithm induces a context- free grammar of the language in question …...

The connection between part-of-speech (POS) categories and morphological properties is well-documented in linguistics but underuti- lized in text processing systems. This pa- per proposes a novel model for morphologi- cal …...

This study presents a novel method that measures English language learners’ syntac- tic competence towards improving automated speech scoring systems. In contrast to most previous studies which focus on the …...

AbstractThe following paper presents a lexical analysis component as implemented in the PANACEA project. The goal is to automatically extract lexicon entries from crawled corpora, in an attempt to use …...

Most existing theory of structured prediction assumes exact inference, which is often in- tractable in many practical problems. This leads to the routine use of approximate infer- ence such as …...

We present a flexible formulation of semi- supervised learning for structured mod- els, which seamlessly incorporates graph- based and more general supervision by ex- tending the posterior regularization (PR) framework. …...

Part-of-speech information is a pre-requisite in many NLP algorithms. However, Twitter text is difficult to part-of-speech tag: it is noisy, with linguistic errors and idiosyncratic style. We present a detailed …...

We describe our approach for the SemEval-2014 task 9: Sentiment Analy- sis in Twitter. We make use of an en- semble learning method for sentiment classification of tweets that relies …...

Analyses of filler-gap dependencies usu- ally involve complex syntactic rules or heuristics; however recent results suggest that filler-gap comprehension begins ear- lier than seemingly simpler constructions such as ditransitives or …...

AbstractCrowdsourcing has been used recently as an alternative to traditional costly annotation by many natural language processing groups. In this paper, we explore the use of Amazon Mechanical Turk (AMT) …...

AbstractInformation Extraction is an important task in Natural Language Processing, consisting of finding a structured representation for the information expressed in natural language text. Two key steps in information extraction …...

AbstractThis paper discusses a Thai corpus, TaLAPi, fully annotated with word segmentation (WS), part-of-speech (POS) and named entity (NE) information with the aim to provide a high-quality and sufficiently large …...

AbstractAt CEA LIST, we have decided to release our multilingual analyzer LIMA as Free software. As we were not proprietary of all the language resources used we had to select …...

We present a method that improves data selection by combining a hybrid word/part-of-speech representation for corpora, with the idea of distinguishing between rare and frequent events. We validate our approach …...

Although entity linking is a widely re- searched topic, the same cannot be said for entity linking geared for languages other than English. Several limitations includ- ing syntactic features and …...

It is well-known that readers are less likely to fixate their gaze on closed class syn- tactic categories such as prepositions and pronouns. This paper investigates to what extent the …...

State-of-the-art sequence labeling systems traditionally require large amounts of task- specific knowledge in the form of hand- crafted features and data pre-processing. In this paper, we introduce a novel neu- …...

AbstractIn this paper, we investigate unsupervised and semi-supervised methods for part-of-speech (PoS) tagging in the context of historical German text. We locate our research in the context of Digital Humanities …...

Neural machine translation has recently achieved impressive results, while using little in the way of external linguistic in- formation. In this paper we show that the strong learning capability of …...

This paper describes a classification system that participated in SemEval-2016 Task 4: Sentiment Analysis in Twitter. The proposed approach competed in subtasks A, B, and C, which involved tweet polarity …...

We propose a fast and scalable method for semi-supervised learning of sequence models, based on anchor words and moment matching. Our method can handle hidden Markov mod- els with feature-based …...

AbstractIn this work we present the open source hunvec framework for sequential tagging, built upon Theano and Pylearn2. The underlying statistical model, which connects linear CRF-s with neural networks, was …...

AbstractThe article describes the current status of a large national project, CoRoLa, aiming at building a reference corpus for the contemporary Romanian language. Unlike many other national corpora, CoRoLa contains …...

Linguistic resources such as part-of- speech (POS) tags have been extensively used in statistical machine translation (SMT) frameworks and have yielded bet- ter performances. However, usage of such linguistic annotations …...

AbstractThis article describes our proposed system named LIM-LIG. This system is designed for SemEval 2017 Task1: Semantic Textual Similarity (Track1). LIM-LIG proposes an innovative enhancement to word embedding-based model devoted …...

AbstractThe widespread use of word embeddings is associated with the recent successes of many natural language processing (NLP) systems. The key approach of popular models such as word2vec and GloVe …...

This paper introduces EFLLex, an innovative lexical resource that describes the use of 15,280 English words in pedagogical materials across the proficiency levels of the European Framework of Reference for …...

In recent years, machine learning methods beyond the confines of conventional super- vised learning have been used along with deep learning methods and intensively investigated. Fine-tuning, which improves the performance …...

We present TIGER 2.2-doc – a new set of annotations for the German TIGER corpus. The set moves the corpus to a document level. It includes a full mapping of …...

This paper describes statistical analyses of missing translations in simultaneous interpretations. Eighty-eight lectures from English-to- Japanese interpretation data from a large-scale bilingual speech corpus were used for the analyses. Word-level …...

The first 100 days corpus is a curated corpus of the first 100 days of the United States of America’s President and the Senate. During the first 100 days, the …...

AbstractCross-lingual transfer is an effective way to build syntactic analysis tools in low-resource languages. However, transfer is difficult when transferring to typologically distant languages, especially when neither annotated target data …...

AbstractThe performance of a Part-of-speech (POS) tagger is highly dependent on the domain of the processed text, and for many domains there is no or only very little training data …...

AbstractFor most of the world’s languages, no primary data are available, even as many languages are disappearing. Throughout the last two decades, however, language documentation projects have produced substantial amounts …...

AbstractData augmentation techniques have been widely used to improve machine learning performance as they facilitate generalization. In this work, we propose a novel augmentation method to generate high quality synthetic …...

AbstractThis paper seeks to uncover patterns of sound change across Indo-Aryan languages using an LSTM encoder-decoder architecture. We augment our models with embeddings represent-ing language ID, part of speech, and …...

AbstractLanguage recognition has been significantly advanced in recent years by means of modern machine learning methods such as deep learning and benchmarks with rich annotations. However, research is still limited …...

AbstractA Mathematical Word Problem (MWP) differs from a general textual representation due to the fact that it is comprised of numerical quantities and units, in addition to text. Therefore, MWP …...

AbstractEzafe is a grammatical particle in some Iranian languages that links two words together. Regardless of the important information it conveys, it is almost always not indicated in Persian script, …...

For simultaneous interpretation, it is very important to identify appropriate segmentation boundaries so that the source text can be translated accurately and promptly. This paper proposes four different segmentation methods …...

AbstractThe research presented in this paper aims at enriching the manually morphosyntactically annotated part of National Corpus of Polish (NKJP1M) with a syntactic layer, i.e. dependency trees of sentences, and …...

AbstractThe most straightforward approach to joint word segmentation (WS), part-of-speech (POS) tagging, and constituent parsing is converting a word-level tree into a char-level tree, which, however, leads to two severe …...

Multilingual language models have been a crucial breakthrough as they considerably re- duce the need of data for under-resourced languages. Nevertheless, the superiority of language-specific models has already been proven …...

AbstractThe current natural language processing is strongly focused on raising accuracy. The progress comes at a cost of super-heavy models with hundreds of millions or even billions of parameters. However, …...

AbstractProbing experiments investigate the extent to which neural representations make properties—like part-of-speech—predictable. One suggests that a representation encodes a property if probing that representation produces higher accuracy than probing a …...

AbstractCode-Mixing (CM) is a common phenomenon in multilingual societies. CM plays a significant role in technology and medical fields where terminologies in the native language are not available or known. …...

AbstractPretraining-based neural network models have demonstrated state-of-the-art (SOTA) performances on natural language processing (NLP) tasks. The most frequently used sentence representation for neural-based NLP methods is a sequence of subwords …...

AbstractMost combinations of NLP tasks and language varieties lack in-domain examples for supervised training because of the paucity of annotated data. How can neural models make sample-efficient generalizations from task–language …...

AbstractActive learning (AL) uses a data selection algorithm to select useful training samples to minimize annotation cost. This is now an essential tool for building low-resource syntactic analyzers such as …...

AbstractA sufficient amount of annotated data is usually required to fine-tune pre-trained language models for downstream tasks. Unfortunately, attaining labeled data can be costly, especially for multiple language varieties and …...

AbstractSocial media data such as Twitter messages (“tweets”) pose a particular challenge to NLP systems because of their short, noisy, and colloquial nature. Tasks such as Named Entity Recognition (NER) …...

AbstractThis work explores techniques to predict Part-of-Speech (PoS) tags from neural signals measured at millisecond resolution with electroencephalography (EEG) during text reading. We first show that information about word length, …...

AbstractWhile pre-trained language models play a vital role in modern language processing tasks, but not every language can benefit from them. Most existing research on pre-trained language models focuses primarily …...

AbstractLanguages are continuously undergoing changes, and the mechanisms that underlie these changes are still a matter of debate. In this work, we approach language evolution through the lens of causality …...

AbstractModels based on bidirectional encoder representations from transformers (BERT) produce state of the art (SOTA) results on many natural language processing (NLP) tasks such as named entity recognition (NER), part-of-speech …...

AbstractThis work proposes an approach to use Part-Of-Speech (POS) information to automatically detect context-dependent Translation Units (TUs) from a Translation Memory database pertaining to the customer support domain. In line …...

Abstract“Implicit sentiment modeling in aspect-based sentiment analysis is a challenging problem due tocomplex expressions and the lack of opinion words in sentences. Recent efforts focusing onimplicit sentiment in ABSA mostly …...

AbstractThis paper describes the submission to SemEval-2023 Task 2: Multilingual Complex Named Entity Recognition (MultiCoNER II) by team SAB. This task aims to encourage growth in the field of Named …...