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d1269169 | This paper considers statistical parsing of Czech, which differs radically from English in at least two respects: (1) it is a highly inflected language, and (2) it has relatively free word order. These differences are likely to pose new problems for techniques that have been developed on English. We describe our experi... | A Statistical Parser for Czech* |
d17321205 | Morphological analysis must take into account the spelling-change processes of a language as well as its possible configurations of stems, affixes, and inflectional markings. The computational difficulty of the task can be clarified by investigating specific models of morphological processing. The use of finite-state m... | COMPUTATIONAL COMPLEXITY IN TWO-LEVEL MORPHOLOGY |
d5459895 | This paper introduces an efficient incremental LL(l) parsing algorithm for use in language-based editors that use the structure recognition approach. It fe atures very fine grained analysis and a unique approach to parse control and error recovery. It also presents incomplete LL(l) grammars as a way of dealing with the... | INCREMENTAL LL(l) PARSING IN LANGUAGE-BASED EDITORS |
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d252819332 | This paper describes our submission to the Social Media Mining for Health (SMM4H) 2022 Shared Task 8, aimed at detecting selfreported chronic stress on Twitter. Our approach leverages a pre-trained transformer model (RoBERTa) in combination with a Bidirectional Long Short-Term Memory (BiLSTM) network trained on a diver... | MANTIS at SMM4H'2022: Pre-Trained Language Models Meet a Suite of Psycholinguistic Features for the Detection of Self-Reported Chronic Stress |
d196211550 | Supplementing product information by extracting attribute values from title is a crucial task in e-Commerce domain. Previous studies treat each attribute only as an entity type and build one set of NER tags (e.g., BIO) for each of them, leading to a scalability issue which unfits to the large sized attribute system in ... | Scaling Up Open Tagging from Tens to Thousands: Comprehension Empowered Attribute Value Extraction from Product Title |
d19011769 | Microblog messages pose severe challenges for current sentiment analysis techniques due to some inherent characteristics such as the length limit and informal writing style. In this paper, we study the problem of extracting opinion targets of Chinese microblog messages. Such fine-grained word-level task has not been we... | Collective Opinion Target Extraction in Chinese Microblogs |
d491439 | This paper describes the system submitted for the Sentiment Analysis in Twitter Task of SEMEVAL 2014 and specifically the Message Polarity Classification subtask. We used a 2-stage pipeline approach employing a linear SVM classifier at each stage and several features including morphological features, POS tags based fea... | AUEB: Two Stage Sentiment Analysis of Social Network Messages |
d9169716 | We present a human judgments dataset and an adapted metric for evaluation of Arabic machine translation. Our mediumscale dataset is the first of its kind for Arabic with high annotation quality. We use the dataset to adapt the BLEU score for Arabic. Our score (AL-BLEU) provides partial credits for stem and morphologica... | A Human Judgment Corpus and a Metric for Arabic MT Evaluation |
d251466086 | Medical data annotation requires highly qualified expertise. Despite the efforts devoted to medical entity linking in different languages, available data is very sparse in terms of both data volume and languages. In this work, we establish benchmarks for cross-lingual medical entity linking using clinical reports, clin... | Medical Crossing: a Cross-lingual Evaluation of Clinical Entity Linking |
d465873 | We present methods for investigating processes of evolution in a language family by modeling relationships among the observed languages. The models aim to find regularities-regular correspondences in lexical data. We present an algorithm which codes the data using phonetic features of sounds, and learns longrange conte... | Modeling language evolution with codes that utilize context and phonetic features |
d14386564 | In this paper, we present a statistical approach to machine translation. We describe the application of our approach to translation from French to English and give preliminary results. Peter F. Brown et al. A Statistical Approach to Machine Translation Source Language Model S t TranslatiOnModel T Pr(S) x Pr(TIS) = Pr(S... | A STATISTICAL APPROACH TO MACHINE TRANSLATION |
d5598307 | The Japanese language has absorbed large numbers of loanwords from many languages, in particular English. As well as using single loanwords, compound nouns, multiword expressions (MWEs), etc. constructed from loanwords can be found in use in very large quantities. In this paper we describe a system which has been devel... | Segmentation and Translation of Japanese Multi-word Loanwords |
d6844025 | Table is a very common presentation scheme, but few papers touch on table extraction in text data mining. This paper l'ocuscs on mining tables from large-scale HTML texts.Table filtering,recognition, interpretation, and presentation arc discussed. Heuristic rules and cell similarities arc employed to identify tables. ... | Mining Tables from Large Scale HTML Texts |
d10102597 | This paper describes a novel character tagging approach to Chinese word segmentation and named entity recognition (NER) for our participation in Bakeoff-4. 1 It integrates unsupervised segmentation and conditional random fields (CRFs) learning successfully, using similar character tags and feature templates for both wo... | Unsupervised Segmentation Helps Supervised Learning of Character Tagging for Word Segmentation and Named Entity Recognition |
d1234375 | Previous researches on Text-level discourse parsing mainly made use of constituency structure to parse the whole document into one discourse tree. In this paper, we present the limitations of constituency based discourse parsing and first propose to use dependency structure to directly represent the relations between e... | Text-level Discourse Dependency Parsing |
d13072792 | This article addresses the lack of common approaches for text simplification evaluation, by presenting the first attempt for a common evaluation metrics. The article proposes reading comprehension evaluation as a method for evaluating the results of Text Simplification (TS). An experiment, as an example application of ... | The C-Score -Proposing a Reading Comprehension Metrics as a Common Evaluation Measure for Text Simplification |
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d21687487 | In this paper, we present a new corpus that contains 943 homepages of scientific conferences, 14794 including subpages, with annotations of interesting information: name of a conference, its abbreviation, place, and several important dates; that is, submission, notification, and camera ready dates. The topics of confer... | Annotated Corpus of Scientific Conference's Homepages for Information Extraction |
d34700045 | To date, various Twitter-based event detection systems have been proposed. Most of their targets, however, share common characteristics. They are seasonal or global events such as earthquakes and flu pandemics. In contrast, this study targets unseasonal and local disease events. Our system investigates the frequencies ... | Multivariate Linear Regression of Symptoms-related Tweets for Infectious Gastroenteritis Scale Estimation |
d26397607 | We propose Object-oriented Neural Programming (OONP), a framework for semantically parsing documents in specific domains. Basically, OONP reads a document and parses it into a predesigned object-oriented data structure (referred to as ontology in this paper) that reflects the domain-specific semantics of the document. ... | Object-oriented Neural Programming (OONP) for Document Understanding |
d10642417 | We use χ 2 to investigate the context dependency of student affect in our computer tutoring dialogues, targeting uncertainty in student answers in 3 automatically monitorable contexts. Our results show significant dependencies between uncertain answers and specific contexts. Identification and analysis of these depende... | Exploring Affect-Context Dependencies for Adaptive System Development |
d7184744 | This paper presents an attempt at developing a technique of acquiring translation pairs of technical terms with sufficiently high precision from parallel patent documents. The approach taken in the proposed technique is based on integrating the phrase translation table of a state-of-the-art statistical phrasebased mach... | Integrating a Phrase-based SMT Model and a Bilingual Lexicon for Human in Semi-Automatic Acquisition of Technical Term Translation Lexicon |
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d7814136 | In this paper, we present a novel approach to incorporate source-side syntactic reordering patterns into phrase-based SMT. The main contribution of this work is to use the lattice scoring approach to exploit and utilize reordering information that is favoured by the baseline PBSMT system. By referring to the parse tree... | Improved Phrase-based SMT with Syntactic Reordering Patterns Learned from Lattice Scoring |
d248780052 | Decisions on state-level policies have a deep effect on many aspects of our everyday life, such as health-care and education access. However, there is little understanding of how these policies and decisions are being formed in the legislative process. We take a datadriven approach by decoding the impact of legislation... | Modeling U.S. State-Level Policies by Extracting Winners and Losers from Legislative Texts |
d1905325 | We present results on the relation discovery task, which addresses some of the shortcomings of supervised relation extraction by applying minimally supervised methods. We describe a detailed experimental design that compares various configurations of conceptual representations and similarity measures across six differe... | Comparison of Similarity Models for the Relation Discovery Task |
d15123272 | In statistical machine translation, the generation of a translation hypothesis is computationally expensive. If arbitrary wordreorderings are permitted, the search problem is NP-hard. On the other hand, if we restrict the possible word-reorderings in an appropriate way, we obtain a polynomial-time search algorithm.In t... | A Comparative Study on Reordering Constraints in Statistical Machine Translation |
d18473670 | We describe the submission of the SAP Research & Innovation team to the Se-mEval 2014 Task 4: Aspect-Based Sentiment Analysis (ABSA). Our system follows a constrained and supervised approach for aspect term extraction, categorization and sentiment classification of online reviews and the details are included in this pa... | SAP-RI: A Constrained and Supervised Approach for Aspect-Based Sentiment Analysis |
d17876020 | We present analyses showing that HMEANT is a reliable, accurate and fine-grained semantic frame based human MT evaluation metric with high inter-annotator agreement (IAA) and correlation with human adequacy judgments, despite only requiring a minimal training of about 15 minutes for lay annotators. Previous work shows ... | On the reliability and inter-annotator agreement of human semantic MT evaluation via HMEANT |
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d8813310 | IMPLEMENTING THE GENERALIZED WORD ORDER GRAMMARS OF CHOMSKY AND DIDERICHSEN | |
d256461137 | Although attention weights have been commonly used as a means to provide explanations for deep learning models, the approach has been widely criticized due to its lack of faithfulness. In this work, we present a simple approach to compute the newly proposed metric AtteFa, which can quantitatively represent the degree o... | How (Un)Faithful is Attention? |
d256461387 | Named Entity Recognition (NER) is an important task in Natural Language Processing with applications in many domains. While the dominant paradigm of NER is sequence labelling, span-based approaches have become very popular in recent times but are less well understood. In this work, we study different aspects of span-ba... | Named Entity Recognition as Structured Span Prediction |
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d248779951 | Cancer immunology research involves several important cell and protein factors. Extracting the information of such cells and proteins and the interactions between them from text are crucial in text mining for cancer immunology research. However, there are few available datasets for these entities, and the amount of ann... | Named Entity Recognition for Cancer Immunology Research Using Distant Supervision |
d15243221 | We introduce and describe ongoing work in our Indonesian dependency treebank. We described characteristics of the source data as well as describe our annotation guidelines for creating the dependency structures. Reported within are the results from the start of the Indonesian dependency treebank. | Indonesian Dependency Treebank: Annotation and Parsing |
d259833818 | Argumentation is an important means of communication. For describing especially arguments about consequences, the notion of effect relations has been introduced recently. We propose a method to extract effect relations from large text resources and apply it on encyclopedic and argumentative texts. By connecting the ext... | Effect Graph: Effect Relation Extraction for Explanation Generation |
d10736122 | Synchronous Hyperedge ReplacementGraph Grammars (SHRG) can be used to translate between strings and graphs. In this paper, we study the capacity of these grammars to create non-projective dependency graphs. As an example, we use languages that contain cross serial dependencies.Lexicalized hyperedge replacement grammars... | Hyperedge Replacement and Nonprojective Dependency Structures |
d1353004 | The inclusion of morphological features provides very useful information that helps to enhance the results when parsing morphologically rich languages. MaltOptimizer is a tool, that given a data set, searches for the optimal parameters, parsing algorithm and optimal feature set achieving the best results that it can fi... | Effective Morphological Feature Selection with MaltOptimizer at the SPMRL 2013 Shared Task |
d352962 | This paper presents methodological and theoretical principles for constructing a machine translation system between Korean and Japanese. We focus our discussion on the real time computing problem of the machine translation system. This problem is characterized in the time and space complexity during the machine transla... | A Principle-based Korean/Japanese Machine Translation System: NARA |
d1409410 | We describe a system which ranks humanprovided paraphrases of noun compounds, where the frequency with which a given paraphrase was provided by human volunteers is the gold standard for ranking. Our system assigns a score to a paraphrase of a given compound according to the number of times it has co-occurred with other... | UCD-PN: Selecting General Paraphrases Using Conditional Probability |
d13974751 | This paper discusses the building of the first Bulgarian-Polish-Lithuanian (for short, BG-PL-LT) experimental corpus. The BG-PL-LT corpus (currently under development only for research) contains more than 3 million words and comprises two corpora: parallel and comparable. The BG-PL-LT parallel corpus contains more than... | Multilingual Resources, Technologies and Evaluation for Central and Eastern European Languages |
d29978426 | With the supply of 8 closely interpreted dialectometrical maps, this paper analyses the linguistic change of the geolinguistic deep structures in Northern France (Domaine d'Oïl) between 1300 and 1900. As a matter of fact, the result will show -with one exception -the great stability of these deep structures. | On the geolinguistic change in Northern France between 1300 and 1900: a dialectometrical inquiry |
d5584560 | We introduce a novel Bayesian approach for deciphering complex substitution ciphers. Our method uses a decipherment model which combines information from letter n-gram language models as well as word dictionaries. Bayesian inference is performed on our model using an efficient sampling technique. We evaluate the qualit... | Bayesian Inference for Zodiac and Other Homophonic Ciphers |
d15196995 | VERBMOBIL as a long-term project of the Federal Ministry of Education, Science, Research and Technology aims at developing a mobile translation system for spontaneous speech. The source-language input consists of human speech (English, German or Japanese), the translation (bidirectional English-German and Japanese-Germ... | End-to-End Evaluation of Machine Interpretation Systems: A Graphical Evaluation Tool |
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d9502230 | People often use social media to discuss opinions, including political ones. We refer to relevant topics in these discussions as political issues, and the alternate stands towards these topics as political positions. We present a Political Issue Extraction (PIE) model that is capable of discovering political issues and... | Political Issue Extraction Model: A Novel Hierarchical Topic Model That Uses Tweets By Political And Non-Political Authors |
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d14755119 | This paper discusses the role of morphological and syntactic information in the automatic acquisition of semantic classes for Catalan adjectives, using decision trees as a tool for exploratory data analysis. We show that a simple mapping from the derivational type to the semantic class achieves 70.1% accuracy; syntacti... | Morphology vs. Syntax in Adjective Class Acquisition |
d250390866 | We present a cleansed version of the Modern Greek branch of the multilingual lexicon HURTLEX. 1 The new version contains 737 offensive words. We worked bottom-up in two annotation rounds and developed detailed diagnostics of "offensiveness" by cross-classifying words on three dimensions: context, reference, and themat... | Cleansing and expanding the HURTLEX(EL) with a multidimensional categorization of offensive words |
d227231162 | We propose an open-world knowledge graph completion model that can be combined with common closed-world approaches (such as ComplEx) and enhance them to exploit text-based representations for entities unseen in training. Our model learns relation-specific transformation functions from text-based embedding space to grap... | Relation Specific Transformations for Open World Knowledge Graph Completion |
d16671536 | We propose a language production model that uses dynamic discourse information to account for speakers' choices of referring expressions. Our model extends previous rational speech act models (Frank and Goodman, 2012) to more naturally distributed linguistic data, instead of assuming a controlled experimental setting. ... | Why discourse affects speakers' choice of referring expressions |
d5246477 | Tagging as the most crucial annotation of language resources can still be challenging when the corpus size is big and when the corpus data is not homogeneous. The Chinese Gigaword Corpus is confounded by both challenges. The corpus contains roughly 1.12 billion Chinese characters from two heterogeneous sources: respect... | Uniform and Effective Tagging of a Heterogeneous Giga-word Corpus |
d712309 | In this study, we applied a deep LSTM structure to classify dialogue acts (DAs) in open-domain conversations. We found that the word embeddings parameters, dropout regularization, decay rate and number of layers are the parameters that have the largest effect on the final system accuracy. Using the findings of these ex... | Dialogue Act Classification in Domain-Independent Conversations Using a Deep Recurrent Neural Network |
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d17827598 | Urdu language raises several challenges to Natural Language Processing (NLP) largely due to its rich morphology. In this language, morphological processing becomes particularly important for Information Retrieval (IR). The core tool of IR is a Stemmer which reduces a word to its stem form. Due to the diverse nature of ... | Challenges in Developing a Rule based Urdu Stemmer |
d3002688 | This paper describes a cellular-telephonebased text-to-text translation system developed at Transclick, Inc. The application translates messages bidirectionally in English, French, German, Italian, Spanish and Portuguese. This paper describes design features uniquely suited to hand-held-device based translation systems... | Usability Considerations for a Cellular-based Text Translator |
d12127070 | This paper reports on a study of semantic role tagging in Chinese, in the absence of a parser. We investigated the effect of using only lexical information in statistical training; and proposed to identify the relevant headwords in a sentence as a first step to partially locate the corresponding constituents to be labe... | Semantic Role Tagging for Chinese at the Lexical Level |
d216804955 | A wide range of applications, from social media to scientific literature analysis, involve graphs in which documents are connected by links. We introduce a topic model for link prediction based on the intuition that linked documents will tend to have similar topic distributions, integrating a max-margin learning criter... | Birds of a Feather Linked Together: A Discriminative Topic Model using Link-based Priors |
d1587075 | On the example of the recent edition of the Frequency Dictionary of Czech we describe and explain some new general principles that should be followed for getting better results for practical uses of frequency dictionaries. It is mainly adopting average reduced frequency instead of absolute frequency for ordering items.... | New Approach to Frequency Dictionaries -Czech Example |
d9943147 | We present a new approach to paratactic content aggregation in the context of generating hypertext summaries of OLAP and data mining discoveries. Two key properties make this approach innovative and interesting: (1) it encapsulates aggregation inside the sentence planning component, and(2)it relies on a domain independ... | Content Aggregation in Natural Language Hypertext Summarization of OLAP and Data Mining Discoveries |
d202541036 | Neural networks are part of many contemporary NLP systems, yet their empirical successes come at the price of vulnerability to adversarial attacks. Previous work has used adversarial training and data augmentation to partially mitigate such brittleness, but these are unlikely to find worst-case adversaries due to the c... | Achieving Verified Robustness to Symbol Substitutions via Interval Bound Propagation |
d63423276 | In this paper, we describe the "FBK English-Spanish Automatic Post-editing (APE)" systems submitted to the APE shared task at the WMT 2015. We explore the most widely used statistical APE technique (monolingual) and its most significant variant (context-aware). In this exploration, we introduce some novel task-specific... | The FBK Participation in the WMT15 Automatic Post-editing Shared Task |
d235482401 | A Preliminary Study on Deep Learning Neural Networks-based Multi-Model Sentiment Detection | |
d15680042 | During the recent Dialog State Tracking Challenge (DSTC), a fundamental question was raised: "Would better performance in dialog state tracking translate to better performance of the optimized policy by reinforcement learning?" Also, during the challenge system evaluation, another nontrivial question arose: "Which eval... | Extrinsic Evaluation of Dialog State Tracking and Predictive Metrics for Dialog Policy Optimization |
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d6396023 | The principle known as 'free indexation' plays an important role in the determination of the referential properties of noun phrases in the principleand-parameters language framework. First, by investigating the combinatorics of free indexation, we show that the problem of enumerating all possible indexings requires exp... | Free Indexation: Combinatorial Analysis and A Compositional Algorithm* |
d15488392 | The rapidly growing biomedical literature has been a challenging target for natural language processing algorithms. One of the tasks these algorithms focus on is called named entity recognition (NER), often employed to tag gene mentions.Here we describe a new approach for this task, an approach that uses graphbased sem... | Graph-based Semi-supervised Gene Mention Tagging |
d252819268 | The World Health Organization has emphasised the need of stepping up suicide prevention efforts to meet the United Nation's Sustainable Development Goal target of 2030 (Goal 3: Good health and well-being). We address the challenging task of personality subtyping from suicide notes. Most research on personality subtypin... | EM-PERSONA: EMotion-assisted Deep Neural Framework for PERSONAlity Subtyping from Suicide Notes |
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d61218567 | Cette étude s'insère dans le projet VOILADIS (VOIsinage Lexical pour l'Analyse du DIScours), qui a pour objectif d'exploiter des marques de cohésion lexicale pour mettre au jour des phénomènes discursifs. Notre propos est de montrer la pertinence d'une ressource, construite par l'analyse distributionnelle automatique d... | Détection de la cohésion lexicale par voisinage distributionnel : application à la segmentation thématique |
d222176890 | Attention is a key component of Transformers, which have recently achieved considerable success in natural language processing. Hence, attention is being extensively studied to investigate various linguistic capabilities of Transformers, focusing on analyzing the parallels between attention weights and specific linguis... | Attention is Not Only a Weight: Analyzing Transformers with Vector Norms |
d34456947 | Walk Thru Text and Keys Walk Thru Text for Information Extraction Key for Template Element Key for Template Relation Key for Scenario Template Walk Thru Text for Named Entity Key for Named Entity Walk Thru Text for Coreference Key for Coreference Template Element Key | |
d233474003 | We test the hypothesis that in some languages the lexicon is stratified(Itô and Mester, 1995a)and that multiple phonotactic subgrammars based on gradiently measured phonotactics not only reduce average phoneme uncertainty, but align well with proposed lexical strata that are based on categorical constraint ranking diff... | Lexical strata and phonotactic perplexity minimization |
d32922893 | This paper describes a program for handling "scope ambiguities" in individual English sentences. The program operates on initial logical translations, generated by a parser/translator, in which "unscoped elements" such as quantifiers, coordinators and negation are left in place to be extracted and positioned by the sco... | HANDLING SCOPE AMBIGUITIES IN ENGLISH |
d241583483 | Training large language models can consume a large amount of energy. We hypothesize that the language model's configuration impacts its energy consumption, and that there is room for power consumption optimisation in modern large language models. To investigate these claims, we introduce a power consumption factor to t... | Hyperparameter Power Impact in Transformer Language Model Training |
d11064772 | Room 820. MH" Artificial Intelligence I ~lb Cambridge. MA 02139 AIISTRACI" Natural langt~ages are often assumed to be constrained so that they are either easily learnable or parsdble, but few studies have investigated the conrtcction between these two "'functional'" demands, Without a fonnal model of pamtbility or lear... | |
d250390827 | In this description paper we outline the system architecture submitted to Task 4, Subtask 1 at SemEval-2022. We leverage the generative power of state-of-the-art generative pretrained transformer models to increase training set size and remedy class imbalance issues. Our best submitted system is trained on a synthetica... | MS@IW at SemEval-2022 Task 4: Patronising and Condescending Language Detection with Synthetically Generated Data |
d977897 | Speech-enabled dialogue systems have the potential to enhance the ease with which blind individuals can interact with the Web beyond what is possible with screen readers -the currently available assistive technology which narrates the textual content on the screen and provides shortcuts to navigate the content. In this... | Dialogue Act Modeling for Non-Visual Web Access |
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d128296356 | We introduce SOCIAL IQA, the first largescale benchmark for commonsense reasoning about social situations. SOCIAL IQA contains 38,000 multiple choice questions for probing emotional and social intelligence in a variety of everyday situations (e.g., Q: "Jordan wanted to tell Tracy a secret, so Jordan leaned towards Trac... | SOCIAL IQA: Commonsense Reasoning about Social Interactions |
d11395323 | OLISSIPO (Omnis Latinitatis Instrumentum Secundum Scholarum Instructionis Propositum Ordinatum) is a prototype developed by the Centro de Estudos Clássicos of the University of Lisbon and the Istituto di Linguistica Computazionale of CNR in Pisa, thanks to a common research project in the framework of the scientific ag... | THE OLISSIPO AND LECTIO PROJECTS |
d219308595 | ||
d252624723 | Five participants, each located in distinct locations (USA, Canada, South Africa, Scotland and (South East) England), identified the selfdetermined social class of a corpus of 227 speakers (born 1986-2001; from South East England) based on 10-second passage readings. This pilot study demonstrates the potential for usin... | Crowdsourced Participants' Accuracy at Identifying the Social Class of Speakers from South East England |
d44155936 | We present KOI (Knowledge of Incidents), a system that given news articles as input, builds a knowledge graph (KOI-KG) of incidental events. KOI-KG can then be used to efficiently answer questions such as "How many killing incidents happened in 2017 that involve Sean?" The required steps in building the KG include: (i)... | KOI at SemEval-2018 Task 5: Building Knowledge Graph of Incidents |
d5321936 | This paper presents the results of a joint effort of a group of multimodality researchers and tool developers to improve the interoperability between several tools used for the annotation of multimodality. We propose a multimodal annotation exchange format, based on the annotation graph formalism, which is supported by... | An exchange format for multimodal annotations |
d2468776 | In this paper, we propose a new sequential labeling scheme, double sequential labeling, that we apply it on Chinese parsing. The parser is built with conditional random field (CRF) sequential labeling models. One focuses on the beginning of a phrase and the phrase type, while the other focuses on the end of a phrase. O... | Sentence Parsing with Double Sequential Labeling in Traditional Chinese Parsing Task |
d10776665 | We present an overview of TARSQI, a modular system for automatic temporal annotation that adds time expressions, events and temporal relations to news texts. | Automating Temporal Annotation with TARSQI |
d2505580 | We present a computational analysis of the language of drug users when talking about their drug experiences. We introduce a new dataset of over 4,000 descriptions of experiences reported by users of four main drug types, and show that we can predict with an F1-score of up to 88% the drug behind a certain experience. We... | A Computational Analysis of the Language of Drug Addiction |
d6963628 | The paper describes problems in disambiguating the morphological analysis of Bantu languages by using Swahili as a test language. The main factors of ambiguity in this language group can be traced to the noun class structure on one hand and to the bi-directional word-formation on the other. In analyzing word-forms, the... | Disambiguation of morphological analysis in Bantu languages |
d933983 | We present CSNIPER (Corpus Sniper), a tool that implements (i) a web-based multiuser scenario for identifying and annotating non-canonical grammatical constructions in large corpora based on linguistic queries and (ii) evaluation of annotation quality by measuring inter-rater agreement. This annotationby-query approach... | CSNIPER Annotation-by-query for non-canonical constructions in large corpora |
d13244912 | Chinese is written without word delimiters so word segmentation is generally considered a key step in processing Chinese texts. This paper presents a new statistical approach to segment Chinese sequences into words based on contextual entropy on both sides of a bigram. It is used to capture the dependency with the left... | Chinese Word Segmentation Based on Contextual Entropy |
d868646 | In this paper, we describe our submissions to the WMT17 Multimodal Translation Task. For Task 1 (multimodal translation), our best scoring system is a purely textual neural translation of the source image caption to the target language. The main feature of the system is the use of additional data that was acquired by s... | CUNI System for the WMT17 Multimodal Traslation Task |
d252411758 | This paper describes the Bilinguals in the Midwest (BILinMID) Corpus, a comparable text corpus of the Spanish and English spoken in the US Midwest by various types of bilinguals. Unlike other areas within the US where language contact has been widely documented (e.g., the Southwest), Spanish-English bilingualism in the... | BILinMID: A Spanish-English Corpus of the US Midwest |
d378229 | Access to expressions of subjective personal posts increased with the popularity of Social Media. However, most of the work in sentiment analysis focuses on predicting only valence from text and usually targeted at a product, rather than affective states. In this paper, we introduce a new data set of 2895 Social Media ... | Modelling Valence and Arousal in Facebook posts |
d7305269 | The Task DomainHere we address the problem of mapping phrase meanings into their conceptual representations. Figurative phrases are pervasive in human communication, yet they are difficult to explain theoretically. In fact, the ability to handle idiosyncratic behavior of phrases should be a criterion for any theory of ... | Encodinl~ and Acquiring Meanings for-Figurative Phrases * |
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