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d14284100 | This paper describes the two algorithms we developed for the CoNLL 2008 Shared Task "Joint learning of syntactic and semantic dependencies". Both algorithms start parsing the sentence using the same syntactic parser.The first algorithm uses machine learning methods to identify the semantic dependencies in four stages: ... | Discriminative vs. Generative Approaches in Semantic Role Labeling |
d2481675 | This paper describes the latest developments in the PeEn-SMT system, specifically covering experiments with Grafix, an APE component developed for PeEn-SMT.The success of well-designed SMT systems has made this approach one of the most popular MT approaches. However, MT output is often seriously grammatically incorrect... | GRAFIX: Automated Rule-Based Post Editing System to Improve English-Persian SMT Output |
d802701 | This paper reports on a large-scale, end-toend relation and event extraction system. At present, the system extracts a total of 100 types of relations and events, which represents a much wider coverage than is typical of extraction systems. The system consists of three specialized pattem-based tagging modules, a high-p... | REES: A Large-Scale Relation and Event Extraction System |
d226262310 | Given the success of Transformer-based models, two directions of study have emerged: interpreting role of individual attention heads and down-sizing the models for efficiency. Our work straddles these two streams: We analyse the importance of basing pruning strategies on the interpreted role of the attention heads. We ... | On the weak link between importance and prunability of attention heads |
d3426165 | Grapheme-to-Phoneme (G2P) conversion is the task of predicting the pronunciation of a word given its graphemic or written form. It is a highly important part of both automatic speech recognition (ASR) and text-to-speech (TTS) systems. In this paper, we evaluate seven G2P conversion approaches: Adaptive Regularization o... | Comparison of Grapheme-to-Phoneme Conversion Methods on a Myanmar Pronunciation Dictionary |
d253628203 | Extracting relevant user behaviors through customer's transaction description is one of the ways to collect customer information. In the current text mining field, most of the researches are mainly study text classification, and only few study text clusters. Find the relationship between letters and words in the unstru... | |
d2913402 | Even though collaboration in peer learning has been shown to have a positive impact for students, there has been little research into collaborative peer learning dialogues. We analyze such dialogues in order to derive a model of knowledge co-construction that incorporates initiative and the balance of initiative. This ... | Impact of Initiative on Collaborative Problem Solving * |
d256739244 | This paper proposes a method for multilingual phoneme recognition in unseen, low resource languages. We propose a novel hierarchical multi-task classifier built on a hybrid convolution-transformer acoustic architecture where articulatory attribute and phoneme classifiers are optimized jointly.The model was evaluated on... | Hierarchical Multi-Task Transformers for Crosslingual Low Resource Phoneme Recognition |
d233189537 | In this paper, we challenge the assumption that political ideology is inherently built into text by presenting an investigation into the impact of experiential factors on annotator perceptions of political ideology. We construct an annotated corpus of U.S. political discussion, where in addition to ideology labels for ... | What Sounds "Right" to Me? Experiential Factors in the Perception of Political Ideology |
d225062658 | Recently, although deep learning has brought significant progress to semantic dependency parsing, the semantic annotation data is very expensive to label, and when a dependency parser with better performance in a single domain is migrated to other domains, its performance will decline largely. Therefore, in order to ma... | Semi-supervised Domain Adaptation for Semantic Dependency Parsing |
d21723747 | We propose a unified model combining the strength of extractive and abstractive summarization. On the one hand, a simple extractive model can obtain sentence-level attention with high ROUGE scores but less readable. On the other hand, a more complicated abstractive model can obtain word-level dynamic attention to gener... | A Unified Model for Extractive and Abstractive Summarization using Inconsistency Loss |
d1462388 | This demo presents LeXFlow, a workflow management system for crossfertilization of computational lexicons. Borrowing from techniques used in the domain of document workflows, we model the activity of lexicon management as a set of workflow types, where lexical entries move across agents in the process of being dynamica... | LeXFlow: a System for Cross-fertilization of Computational Lexicons |
d28841202 | Recent research in computational music research, including my own, has been greatly influenced by methods in computational linguistics. But I believe the influence could also go the other way: Music may offer some interesting lessons for language research, particularly with regard to the modeling of cognition. | Music, Language, and Computational Modeling: Lessons from the Key-Finding Problem |
d12066739 | We present SPARSAR, a system for the automatic analysis of poetry(and text) style which makes use of NLP tools like tokenizers, sentence splitters, NER (Name Entity Recognition) tools, and taggers. In addition the system adds syntactic and semantic structural analysis and prosodic modeling. We do a dependency mapping t... | SPARSAR: An Expressive Poetry Reader |
d11742913 | This paper proposes two decision trees for determining the meanings of the prepositional uses of over by using the contextual information. It first examines the meanings of the prepositional uses of over and then aims at identifying the contexts for interpreting the meanings. Some contexts are complementary features, a... | Decision Trees for Sense Disambiguation of Prepositions: Case of Over |
d8248505 | Social media outlets are providing new opportunities for harvesting valuable resources. We present a novel approach for mining data from Twitter for the purpose of building transliteration resources and systems. Such resources are crucial in translation and retrieval tasks. We demonstrate the benefits of the approach o... | Arabic to English Person Name Transliteration using Twitter |
d5317323 | This paper describes an approach to conceptual analysis and understanding of natural language in which linguistic knowledge centers on individual words, and the analysis mechanisms consist of interactions among distributed procedural experts representing that knowledge.Each word expert models the process of diagnosing ... | WORD EXPERT PARSING l |
d21821146 | Our proposed method is to use a Hidden Markov Model-based word segmenter and a Support Vector Machine-based chunker for Chinese word segmentation. Firstly, input sentences are analyzed by the Hidden Markov Model-based word segmenter. The word segmenter produces n-best word candidates together with some class informatio... | Combining Segmenter and Chunker for Chinese Word Segmentation |
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d53083290 | In contrast to the older writing system of the 19th century, modern Hawaiian orthography employs characters for long vowels and glottal stops. These extra characters account for about one-third of the phonemes in Hawaiian, so including them makes a big difference to reading comprehension and pronunciation. However, tra... | Recovering Missing Characters in Old Hawaiian Writing |
d13861243 | For highly inflectional languages, the number of morpho-syntactic descriptions (MSD), required to descriptionally cover the content of a word-form lexicon, tends to rise quite rapidly, approaching a thousand or even more set of distinct codes. For the purpose of automatic disambiguation of arbitrary written texts, usin... | Principled Hidden Tagset Design for Tiered Tagging of Hungarian |
d14569368 | Statistical machine translation (SMT) is based on the ability to effectively learn word and phrase relationships from parallel corpora, a process which is considerably more difficult when the extent of morphological expression differs significantly across the source and target languages. We present techniques that sele... | Bridging the Inflection Morphology Gap for Arabic Statistical Machine Translation |
d7371587 | T h e p a p e r d e s crib e s th e S w ed ish la n g u a g e c o m p o n e n t s u sed in th e S p o ken L a n g u a g e T r a n s la to r (S L T ) s y s te m . S L T is a m u lt i-c o m p o n e n t sy s te m fo r tr a n s la tio n o f s p o k e n E n g lish in t o s p o k e n S w ed ish . T h e la n g u a g e p ro ce... | Swedish Language Processing in the Spoken Language Translator |
d21708183 | There is a growing body of research focused on task-oriented instructor-manipulator dialogue, whereby one dialogue participant initiates a reference to an entity in a common environment while the other participant must resolve this reference in order to manipulate said entity. Many of these works are based on disparate... | KTH Tangrams: A Dataset for Research on Alignment and Conceptual Pacts in Task-Oriented Dialogue |
d2067306 | We present a simple but very effective approach to identifying high-quality data in noisy data sets for structured problems like parsing, by greedily exploiting partial structures. We analyze our approach in an annotation projection framework for dependency trees, and show how dependency parsers from two different para... | Data-Driven Dependency Parsing of New Languages Using Incomplete and Noisy Training Data |
d16700314 | In this paper, we describe MLSA, a publicly available multi-layered reference corpus for German-language sentiment analysis. The construction of the corpus is based on the manual annotation of 270 German-language sentences considering three different layers of granularity. The sentence-layer annotation, as the most coa... | MLSA -A Multi-layered Reference Corpus for German Sentiment Analysis |
d74975 | Deletion of dimensions of textual similarity for the exploration of collections of accident reports in aviationIn this paper we study the relationship between external classification and textual similarity in collections of incident reports. Our goal is to complement the existing classification-based analysis strategie... | Effacement de dimensions de similarité textuelle pour l'exploration de collections de rapports d'incidents aéronautiques |
d6309434 | DIRNDL is a spoken and written corpus based on German radio news, which features coreference and information-status annotation (including bridging anaphora and their antecedents), as well as prosodic information. We have recently extended DIRNDL with a finegrained two-dimensional information status labeling scheme. We ... | The Extended DIRNDL Corpus as a Resource for Automatic Coreference and Bridging Resolution |
d10994429 | We study a novel architecture for syntactic SMT. In contrast to the dominant approach in the literature, the system does not rely on translation rules, but treat translation as an unconstrained target sentence generation task, using soft features to capture lexical and syntactic correspondences between the source and t... | Syntactic SMT Using a Discriminative Text Generation Model |
d15691181 | In this paper, we present an approach for merging fine-grained verb senses of Hindi WordNet. Senses are merged based on gloss similarity score. We explore the use of word embeddings for gloss similarity computation and compare with various WordNet based gloss similarity measures.Our results indicate that word embedding... | Merging Verb Senses of Hindi WordNet using Word Embeddings |
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d195065610 | This paper summarizes our work on analysis of cross linguistic variations in discourse relations for Indo-Aryan language Hindi and Dravid ian languages Malayalam and Tamil. In this paper we have also presented an automat ic discourse relation identifier, wh ich gave encouraging results. Analysis of the results showed t... | Cross Linguistic Variations in Discourse Relations among Indian Languages |
d16207472 | This paper presents a novel approach for parallel data generation using machine translation and quality estimation. Our study focuses on pivot-based machine translation from English to Croatian through Slovene. We generate an English-Croatian version of the Europarl parallel corpus based on the English-Slovene Europarl... | Quality Estimation for Synthetic Parallel Data Generation |
d8201148 | Automatic construction of knowledge graphs (KGs) from unstructured text has received considerable attention in recent research, resulting in the construction of several KGs with millions of entities (nodes) and facts (edges) among them. Unfortunately, such KGs tend to be severely sparse in terms of number of facts know... | An Entity-centric Approach for Overcoming Knowledge Graph Sparsity |
d14701636 | In this paper, we propose a new probabilistic GLR parsing method that can solve the problems of conventional methods. Our proposed Conditional Action Model uses Surface Phrasal Types (SPTs) encoding the functional word sequences of the sub-trees for describing structural characteristics of the partial parse. And, the p... | GLR PARSER WITH CONDITIONAL ACTION MODEL USING SURFACE PHRASAL TYPES FOR KOREAN |
d5313088 | Luke is a knowledge editor designed to support two tasks; the first is editing the classes and relations in a knowledge base. The second is editing and maintaining the semantic mapping knowledge neccesery to allow a natural language interface to understand sentences with respect to that knowledge base. In order to emph... | LUKE: AN EXPERIMENT IN THE EARLY INTEGRATION OF NATURAL LANGUAGE PROCESSING |
d227231238 | This paper presents a "road map" for the annotation of semantic categories in typologically diverse languages, with potentially few linguistic resources, and often no existing computational resources. Past semantic annotation efforts have focused largely on high-resource languages, or relatively low-resource languages ... | Cross-lingual annotation: a road map for low-and no-resource languages |
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d258486868 | The identification of Verbal Multiword Expressions (VMWEs) presents a greater challenge compared to non-verbal MWEs due to their higher surface variability. VMWEs are linguistic units that exhibit varying levels of semantic opaqueness and pose difficulties for computational models in terms of both their identification ... | |
d6530117 | Ukwabelana -An open-source morphological Zulu corpus | |
d252091127 | In this paper, we evaluate in a case study whether semantic role labelling (SRL) can be reliably used for verb-based sentiment inference (SI). SI strives to identify polar relations (against, in-favour-of) between discourse entities. We took 300 sentences with 10 different verbs that show verb alternations or are ambig... | Semantic Role Labeling for Sentiment Inference: A Case Study |
d8888540 | NLP models have many and sparse features, and regularization is key for balancing model overfitting versus underfitting. A recently repopularized form of regularization is to generate fake training data by repeatedly adding noise to real data. We reinterpret this noising as an explicit regularizer, and approximate it w... | Feature Noising for Log-linear Structured Prediction |
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d6225233 | 1Practical natural language interfaces must exhibit robust bei~aviour in the presence of extragrammaticat user input. This paper classifies different types of grammatical deviations and related phenomena at the lexical and sentential levels, discussing recovery strategies tailored to specific phenomena in the classific... | Coping with Extragrarnmaticality |
d3037733 | This paper introduces a new method for identifying named-entity (NE) transliterations within bilingual corpora. Current state-of-theart approaches usually require annotated data and relevant linguistic knowledge which may not be available for all languages. We show how to effectively train an accurate transliteration c... | Active Sample Selection for Named Entity Transliteration |
d6156475 | This paper describes an evaluation of an existing technique that locates sentences containing descriptions of a query word or phrase. The experiments expand on previous tests by exploring the effectiveness of the system when searching from a much larger document collection. The results showed the system working signifi... | Large scale testing of a descriptive phrase finder |
d17617272 | We propose a new unsupervised learning model, hidden softmax sequence model (HSSM), based on Boltzmann machine for dialogue structure analysis. The model employs three types of units in the hidden layer to discovery dialogue latent structures: softmax units which represent latent states of utterances; binary units whic... | Hidden Softmax Sequence Model for Dialogue Structure Analysis |
d14089470 | This paper presents Rule based Urdu Stemmer. In this technique rules are applied to remove suffix and prefix from the inflected words. Urdu is well spoken language all over the world but less work has been done on Urdu stemming. Stemmer helps us to find the root of the inflected word. Various possibilities of inflected... | Rule Based Urdu Stemmer |
d37608217 | Using 2D Formant Distribution to Build Speaker Models and Its Application in Speaker Verification | |
d11072864 | The number and sizes of parallel corpora keep growing, which makes it necessary to have automatic methods of processing them: combining, checking and improving corpora quality, etc. We here introduce a method which enables performing many of these by exploiting overlapping parallel corpora. The method finds the corresp... | Experiments on Processing Overlapping Parallel Corpora |
d2988891 | In this paper, we present a hybrid method for Chinese and Japanese word segmentation. Word-level information is useful for analysis of known words, while character-level information is useful for analysis of unknown words, and the method utilizes both these two types of information in order to effectively handle known ... | Chinese and Japanese Word Segmentation Using Word-Level and Character-Level Information |
d27773855 | Spoken Language Understanding (SLU) is a key component of goal oriented dialogue systems that would parse user utterances into semantic frame representations. Traditionally SLU does not utilize the dialogue history beyond the previous system turn and contextual ambiguities are resolved by the downstream components. In ... | Sequential Dialogue Context Modeling for Spoken Language Understanding |
d10127544 | How abstract knowledge is organised is a key question in cognitive science, and has clear repercussions for the design of artifical lexical resources, but is poorly understood. We present fMRI results for an experiment where participants imagined situations associated with abstract words, when cued with a visual word s... | On Discriminating fMRI Representations of Abstract WordNet Taxonomic Categories |
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d3061213 | We present TMop, the first open-source tool for automatic Translation Memory (TM) cleaning. The tool implements a fully unsupervised approach to the task, which allows spotting unreliable translation units (sentence pairs in different languages, which are supposed to be translations of each other) without requiring lab... | TMop: a Tool for Unsupervised Translation Memory Cleaning |
d10477775 | We present a valency lexicon for Latin verbs extracted from the Index Thomisticus Treebank, a syntactically annotated corpus of Medieval Latin texts by Thomas Aquinas. In our corpus-based approach, the lexicon reflects the empirical evidence of the source data. Verbal arguments are induced directly from annotated data.... | The Development of the Index Thomisticus Treebank Valency Lexicon |
d252624559 | This paper is primarily devoted to describing the preparation phase of a large-scale comparative study based on naturalistic linguistic data drawn from multiple sign language corpora. To provide an example, I am using my current project on manual gestural elements in Polish Sign Language, German Sign Language, and Russ... | -BY-NC 4.0 Making Sign Language Corpora Comparable: A Study of Palm-Up and Throw-Away in Polish Sign Language, German Sign Language, and Russian Sign Language |
d402181 | Shallow semantic parsing, the automatic identification and labeling of sentential constituents, has recently received much attention. Our work examines whether semantic role information is beneficial to question answering. We introduce a general framework for answer extraction which exploits semantic role annotations i... | Using Semantic Roles to Improve Question Answering |
d14937262 | We present the components of a processing chain for the creation, visualization, and validation of lexical resources (formed of terms and relations between terms). The core of the chain is a component for building lexical networks relying on Harris' distributional hypothesis applied on the syntactic dependencies produc... | Towards an environment for the production and the validation of lexical semantic resources |
d14979669 | This paper presents an evaluation of four shallow parsers The interest of each of these parsers led us to imagine a parameterized multiplexer for syntactic information based on the principle of merging the common boundaries of the outputs given by each of these programs. The question of evaluating the parsers as well a... | An evaluation of different symbolic shallow parsing techniques |
d7116703 | The extraction of flat concepts out of a given word sequence is usually one of the first steps in building a spoken language understanding (SLU) or dialogue system. This paper explores five different modelling approaches for this task and presents results on a French state-ofthe-art corpus, MEDIA. Additionally, two log... | A Comparison of Various Methods for Concept Tagging for Spoken Language Understanding |
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d259370768 | Although recent neural models for coreference resolution have led to substantial improvements on benchmark datasets, transferring these models to new target domains containing out-of-vocabulary spans and requiring differing annotation schemes remains challenging. Typical approaches involve continued training on annotat... | Annotating Mentions Alone Enables Efficient Domain Adaptation for Coreference Resolution |
d21726955 | In recent years, temporal tagging, i.e., the extraction and normalization of temporal expressions, has become a vibrant research area. Several tools have been made available, and new strategies have been developed. Due to domain-specific challenges, evaluations of new methods should be performed on diverse text types. ... | KRAUTS: A German Temporally Annotated News Corpus |
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d28533405 | This paper explores the automatic learning of distributed representations of the target's context for semantic frame labeling with target-based neural model. We constrain the whole sentence as the model's input without feature extraction from the sentence. This is different from many previous works in which local featu... | Semantic Frame Labeling with Target-based Neural Model |
d22319731 | This paper describes our submission to SemEval-2017 Task 3 Subtask D, "Question Answer Ranking in Arabic Community Question Answering". In this work, we applied a supervised machine learning approach to automatically re-rank a set of QA pairs according to their relevance to a given question. We employ features based on... | GW QA at SemEval-2017 Task 3: Question Answer Re-ranking on Arabic Fora |
d7212585 | Previous work on dialog act (DA) classification has investigated different methods, such as hidden Markov models, maximum entropy, conditional random fields, graphical models, and support vector machines. A few recent studies explored using deep learning neural networks for DA classification, however, it is not clear y... | Using Context Information for Dialog Act Classification in DNN Framework |
d5674957 | This paper explores a divisive hierarchical clustering algorithm based on the wellknown Obligatory Contour Principle in phonology. The purpose is twofold: to see if such an algorithm could be used for unsupervised classification of phonemes or graphemes in corpora, and to investigate whether this purported universal co... | A phoneme clustering algorithm based on the obligatory contour principle |
d6205777 | We present an update to UDPipe 1.0(Straka et al., 2016), a trainable pipeline which performs sentence segmentation, tokenization, POS tagging, lemmatization and dependency parsing. We provide models for all 50 languages of UD 2.0, and furthermore, the pipeline can be trained easily using data in CoNLL-U format.For the ... | Tokenizing, POS Tagging, Lemmatizing and Parsing UD 2.0 with UDPipe |
d43481313 | RESUME ____________________________________________________________________________________________________________Cet article s'intéresse aux conversations téléphoniques d'un Centre d'Appels EDF, automatiquement découpées en « tours de parole » et automatiquement transcrites. Il fait apparaître une relation entre la l... | La longueur des tours de parole comme critère de sélection de conversations dans un centre d'appels |
d3470796 | In this paper we describe a method to morphologically segment highly agglutinating and inflectional languages from Dravidian family. We use nested Pitman-Yor process to segment long agglutinated words into their basic components, and use a corpus based morpheme induction algorithm to perform morpheme segmentation. We t... | Unsupervised learning of agglutinated morphology using nested Pitman-Yor process based morpheme induction algorithm |
d245442676 | It is with great sadness that we report the passing of Martin Kay in August 2021. Martin was a pioneer and intellectual trailblazer in computational linguistics. He was also a close friend and colleague of many years.Martin was a polyglot undergraduate student of modern and medieval languages at Cambridge University, w... | Obituary under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license |
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d257154238 | In recent years, researchers have developed question-answering based approaches to automatically evaluate system summaries, reporting improved validity compared to word overlapbased metrics like ROUGE, in terms of correlation with human ratings of criteria including fluency and hallucination. In this paper, we take a c... | Evaluating the Examiner: The Perils of Pearson Correlation for Validating Text Similarity Metrics |
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d256460980 | Entity linking, the task of linking potentially ambiguous mentions in texts to corresponding knowledge-base entities, is an important component for language understanding. We address two challenge in entity linking: how to leverage wider contexts surrounding a mention, and how to deal with limited training data. We pro... | Unsupervised Entity Linking with Guided Summarization and Multiple-Choice Selection |
d62267053 | Interpreting fully natural speech is an important goal for spoken language understanding systems. However, while corpus studies have shown that about 10% of spontaneous utterances contain self-corrections, or RE-PAIRS, little is known about the extent to which cues in the speech signal may facilitate repair processing.... | A SPEECH-FIRST MODEL FOR REPAIR DETECTION AND CORRECTION |
d248780342 | This paper describes a novel framework to estimate the data quality of a collection of product descriptions to identify required relevant information for accurate product listing classification for tax-code assignment. Our Data Quality Estimation (DQE) framework consists of a Question Answering (QA) based attributevalu... | Data Quality Estimation Framework for Faster Tax Code Classification |
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d14967295 | This paper is concerned with the possibility of quantifying and comparing the productivity of similar yet distinct syntactic constructions, predicting the likelihood of encountering unseen lexemes in their unfilled slots. Two examples are explored: variants of comparative correlative constructions (CCs, e.g. the faster... | Quantifying Constructional Productivity with Unseen Slot Members |
d248780538 | Existing visual grounding datasets are artificially made, where every query regarding an entity must be able to be grounded to a corresponding image region, i.e., answerable. However, in real-world multimedia data such as news articles and social media, many entities in the text cannot be grounded to the image, i.e., u... | Flexible Visual Grounding |
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d252624440 | We analyzed negative headshake found in the online corpus of Russian Sign Language. We found that negative headshake can co-occur with negative manual signs, although most of these signs are not accompanied by it. We applied OpenFace, a Computer Vision toolkit, to extract head rotation measurements from video recording... | -BY-NC 4.0 Phonetics of Negative Headshake in Russian Sign Language: A Small-Scale Corpus Study |
d11849431 | This paper investigates the impact on French dependency parsing of lexical generalization methods beyond lemmatization and morphological analysis. A distributional thesaurus is created from a large text corpus and used for distributional clustering and WordNet automatic sense ranking. The standard approach for lexical ... | Probabilistic Lexical Generalization for French Dependency Parsing |
d11034156 | This paper reports the description and performance of our system, FBK-HLT, participating in the SemEval 2015, Task #2 "Semantic Textual Similarity", English subtask. We submitted three runs with different hypothesis in combining typical features (lexical similarity, string similarity, word n-grams, etc) with syntactic ... | FBK-HLT: A New Framework for Semantic Textual Similarity |
d8024419 | With the growing popularity of Japanese learning, a large number of learning support tools or systems have been developed to help Japanese learners in various situations. We have particularly noticed the increasing necessity of systems developed as web applications, most of which are free and easily accessed, and hence... | A Japanese Learning Support System Matching Individual Abilities |
d6402709 | This paper is on dividing non-separated language sentences (whose words are not separated from each other with a space or other separaters) into morphemes using statistical information, not grammatical information which is often used in NLP. In this paper we describe our method and experimental result on Japanese and C... | SE(IMENTING A SENTENf,I¢ INTO MOItl)IIEM1,;S USING STNI'ISTIC INFOI{MATION BI,TFWEEN WORI)S |
d239890007 | Specialized press and professional information channels influence beliefs on economic outlook or prospects for financial markets by drawing attention on particular events, and disseminating domain expert opinions. Analyzing this textual data allows for a better understanding of investors' beliefs and detecting key indi... | Annotation model and corpus for opinion detection in economic and financial narratives |
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d17754705 | This paper proposes the impacts of event and event actor alignment in English and Bengali phrase based Statistical Machine Translation (PB-SMT) System. Initially, events and event actors are identified from English and Bengali parallel corpus. For events and event actor identification in English we proposed a hybrid te... | Event and Event Actor Alignment in Phrase Based Statistical Machine Translation |
d5193589 | The pseudo-passive is peculiar in that (i) the DP that appears to be the complement of a preposition undergoes passivization, and (ii) it is semantically characterized by the fact that it describes a resultant state or a characteristic of the Theme. The first peculiarity can be explained if the DP is not the complement... | Pseudo-Passives as Adjectival Passives |
d3062643 | Using SVMs for named entity recognition, we are often confronted with the multi-class problem. Larger as the number of classes is, more severe the multiclass problem is. Especially, one-vs-rest method is apt to drop the performance by generating severe unbalanced class distribution. In this study, to tackle the problem... | Two-Phase Biomedical NE Recognition based on SVMs |
d33353746 | In this paper we conduct an initial study on the dialects of Romanian. We analyze the differences between Romanian and its dialects using the Swadesh list. We analyze the predictive power of the orthographic and phonetic features of the words, building a classification problem for dialect identification. | A Computational Perspective on the Romanian Dialects |
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d32007803 | Sentiment analysis is the computational task of extracting sentiment from a text document -for example whether it expresses a positive, negative or neutral opinion. Various approaches have been introduced in recent years, using a range of different techniques to extract sentiment information from a document. Measuring ... | A Calibration Method for the Evaluation of Sentiment Analysis |
d8473142 | We describe the compilation of a large corpus of French-Dutch sentence pairs from official Belgian documents which are available in the online version of the publication Belgisch Staatsblad/Moniteur belge, and which have been published between 1997 and 2006. After downloading files in batch, we filtered out documents w... | Belgisch Staatsblad Corpus: Retrieving French-Dutch Sentences from Official Documents |
d19558838 | Vector representations of word meaning have found many applications in the field of natural language processing. Word vectors intuitively represent the average context in which a given word tends to occur, but they cannot explicitly model the diversity of these contexts. Although region representations of word meaning ... | Modeling Context Words as Regions: An Ordinal Regression Approach to Word Embedding |
d6260053 | Danish is a major Scandinavian language spoken daily by around six million people. However, it lacks a unified, open set of NLP tools. This demonstration will introduce DKIE, an extensible open-source toolkit for processing Danish text. We implement an information extraction architecture for Danish within GATE, includi... | DKIE: Open Source Information Extraction for Danish |
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