Performance

We present a comparative analysis of the performance of a statistics-based system for the formation of semantic groups of adjectives when various sources of linguistic knowledge are introduced. We identify …...

An ongoing debate in text understanding efforts centers on the use of pattern-matching techniques, which some have characterized as "designed to ignore as much text as possible," versus approaches which …...

Pronunciation-by-analogy (PbA) is an emer- ging technique for text-phoneme conversion based on a psychological model of read- ing aloud. This paper explores the impact of certain basic implementational choices on …...

We present a trainable model for identify- ing sentence boundaries in raw text. Given a corpus annotated with sentence bound- aries, our model learns to classify each oc- currence of., …...

AbstractIn this paper we describe a language recognition algorithm for multilingual documents that is based on mixed-order n-grams, Markov chains, maximum likelihood, and dynamic programming. We present the results of …...

We present a corpus-based study of the se- quential ordering among premodifiers in noun phrases. This information is important for the fluency of generated text in practical appli- cations. We …...

This paper presents a method that as- sists in maintaining a rule-based named-entity recognition and classifi- cation system. The underlying idea is to use a separate system, constructed with the …...

This paper proposes a Hidden Markov Model (HMM) and an HMM-based chunk tagger, from which a named entity (NE) recognition (NER) system is built to recognize and classify names, times …...

We compare two approaches for describing and gen- erating bodies of rules used for natural language parsing. In today’s parsers rule bodies do not ex- ist a priori but are …...

We present a prototype natural-language problem-solving application for a financial services call center, developed as part of the Amitiés multilingual human-computer dialogue project. Our automated dialogue system, based on empirical …...

. Although effective for antecedent determination, the tradi- tional twin-candidate model can not prevent the invalid resolution of non-anaphors without additional measures. In this paper we propose a modified learning …...

AbstractThis paper introduces the Multilingual Information Service System being implemented for the Beijing Olympics. Multilingual machine translation is an important component in this system. This real world application asks for …...

This paper defines a generative probabilis- tic model of parse trees, which we call PCFG-LA. This model is an extension of PCFG in which non-terminal symbols are augmented with latent …...

In order to achieve the long-range goal of semantic interpretation of noun com- pounds, it is often necessary to first de- termine their syntactic structure. This pa- per describes an …...

In this paper we show that generative models are competitive with and some- times superior to discriminative models, when both kinds of models are allowed to learn structures that are …...

Given the growing complexity of tasks that spoken dialogue systems are trying to handle, Reinforcement Learning (RL) has been increasingly used as a way of au- tomatically learning the best …...

Word alignment using recency-vector based approach has recently become pop- ular. One major advantage of these tech- niques is that unlike other approaches they perform well even if the size …...

Question answering on speech transcripts (QAst) is a pilot track of the CLEF com- petition. In this paper we present our con- tribution to QAst, which is centred on a …...

We present Pro3Gres, a deep-syntactic, fast dependency parser that combines a hand- written competence grammar with proba- bilistic performance disambiguation and that has been used in the biomedical domain. We …...

This paper presents a new unsupervised algo- rithm (WordEnds) for inferring word bound- aries from transcribed adult conversations. Phone ngrams before and after observed pauses are used to bootstrap a …...

This paper proposes a probabilistic model for associative anaphora resolution in Japanese. Associative anaphora is a type of bridging anaphora, in which the anaphor and its antecedent are not coref- …...

This paper presents a method for automatic topic identification using an encyclopedic graph derived from Wikipedia. The sys- tem is found to exceed the performance of previously proposed machine learning …...

Post-editing (PE) is still a new activity for many translators. The lack of training, clear and consistent guidelines and inter- national standards may cause difficulties in the transition from translation …...

Most supervised language processing sys- tems show a significant drop-off in per- formance when they are tested on text that comes from a domain significantly different from the domain of …...

We use web-scale N-grams in a base NP parser that correctly analyzes 95.4% of the base NPs in natural text. Web-scale data improves performance. That is, there is no data …...

AbstractIn this paper, we present several ways to measure and evaluate the annotation and annotators, proposed and used during the building of the Czech part of the Prague Czech-English Dependency …...

We explore the relation between word sense subjectivity and cross-lingual lexical substitu- tion, following the intuition that good substi- tutions will transfer a word’s (contextual) sen- timent from the source …...

We demonstrate how supervised discrimina- tive machine learning techniques can be used to automate the assessment of ‘English as a Second or Other Language’ (ESOL) examina- tion scripts. In particular, …...

This paper describes efforts towards the development of an Arabic to Italian SMT system for the news domain. Since only very little parallel data are available for this language pair, …...

Extensive knowledge bases of entailment rules between predicates are crucial for applied se- mantic inference. In this paper we propose an algorithm that utilizes transitivity constraints to learn a globally-optimal …...

The well-studied supervised Relation Extraction algorithms require training data that is accurate and has good coverage. To obtain such a gold standard, the common practice is to do independent double …...

This paper describes the evaluation of differ- ent kinds of textual features for the Cross- Lingual Textual Entailment Task of SemEval 2013. We have counted the number of N- grams …...

Traditional approaches to the task of ACE event extraction usually rely on sequential pipelines with multiple stages, which suf- fer from error propagation since event trig- gers and arguments are …...

This paper describes a temporal expression identification and normalization system, Man- TIME, developed for the TempEval-3 chal- lenge. The identification phase combines the use of conditional random fields along with …...

Mining opinion targets is a fundamen- tal and important task for opinion min- ing from online reviews. To this end, there are usually two kinds of methods: syntax based and …...

We approach the typed-similarity task using a range of heuristics that rely on information from the appropriate metadata fields for each type of similarity. In addition we train a linear …...

AbstractThis paper presents two improvements of language models based on Restricted Boltzmann Machine (RBM) for large machine translation tasks. In contrast to other continuous space approach, RBM based models can …...

We experiment graph-based Semi- Supervised Learning (SSL) of Conditional Random Fields (CRF) for the application of Spoken Language (SLU) on unaligned data.Understanding The aligned labels for examples are obtained using …...

We describe a state-of-the-art automatic system that can acquire subcategorisation frames from raw text for a free word-order language. We use it to construct a subcate- gorisation lexicon of German …...

This article tackles the Authorship Attri- bution task according to the language in- dependence issue. We propose an alterna- tive of variable length character n-grams features in supervised methods: maximal …...

In this paper we describe a semi-automated approach to extend morphological lexicons by defining the prediction of the correct inflectional paradigm and the lemma for an unknown word as a …...

We present a transition-based arc-eager model to parse spinal trees, a dependency- based representation that includes phrase- structure information in the form of con- stituent spines assigned to tokens. As …...

Semantic Textual Similarity measures similar- ity between pair of texts, even though the sim- ilar context is projected using different words. This work attempted to incorporate the con- text space …...

A common model for question answering (QA) is that a good answer is one that is closely related to the question, where re- latedness is often determined using general- purpose …...

This paper introduces STEM and LAMB, em- beddings trained for stems and lemmata in- stead of for surface forms. For morpholog- ically rich languages, they perform signif- icantly better than …...

AbstractJoint inference approaches such as Integer Linear Programming (ILP) and Markov Logic Networks (MLNs) have recently been successfully applied to many natural language processing (NLP) tasks, often outperforming their pipeline …...

Learning embeddings of words and knowledge base elements is a promising approach for open domain question answering. Based on the remark that relations and entities are distinct object types lying …...

This paper presents our participation to the Se- mEval “Task 13: Taxonomy Extraction Evalu- ation (TExEval-2)” (Bordea et al., 2016). This year, we propose the combination of recent se- mantic …...

Relation extraction models based on deep learning have been attracting a lot of at- tention recently. Little research is carried out to reduce their need of labeled training data. In …...

AbstractLike most of the languages which have only recently started being investigated for the Natural Language Processing (NLP) tasks, Amazigh lacks annotated corpora and tools and still suffers from the …...

AbstractRecent neural models have shown significant progress on the problem of generating short descriptive texts conditioned on a small number of database records. In this work, we suggest a slightly …...

AbstractWe present and apply two methods for addressing the problem of selecting relevant training data out of a general pool for use in tasks such as machine translation. Building on …...

AbstractWord embeddings are supposed to provide easy access to semantic relations such as “male of” (man–woman). While this claim has been investigated for concepts, little is known about the distributional …...

AbstractThis paper evaluates different techniques for building a supervised, multilanguage keyphrase extraction pipeline for languages which lack a gold standard. Starting from an unsupervised English keyphrase extraction pipeline, we implement …...

AbstractThis paper proposes to tackle the AMR parsing bottleneck by improving two components of an AMR parser: concept identification and alignment. We first build a Bidirectional LSTM based concept identifier …...

AbstractIn this work, we study the problem of part-of-speech tagging for Tweets. In contrast to newswire articles, Tweets are usually informal and contain numerous out-of-vocabulary words. Moreover, there is a …...

AbstractShared Task 1 at SemEval-2017 deals with assessing the semantic similarity between sentences, either in the same or in different languages. In our system submission, we employ multilingual word representations, …...

AbstractSemantic Textual Similarity (STS) measures the meaning similarity of sentences. Applications include machine translation (MT), summarization, generation, question answering (QA), short answer grading, semantic search, dialog and conversational systems. The …...

AbstractIn this paper we present our contribution to SemEval-2018, a classifier for classifying multi-label emotions of Arabic and English tweets. We attempted “Affect in Tweets”, specifically Task E-c: Detecting Emotions …...

AbstractThe first stage of every knowledge base question answering approach is to link entities in the input question. We investigate entity linking in the context of question answering task and …...

AbstractTo bridge the gap between Machine Reading Comprehension (MRC) models and human beings, which is mainly reflected in the hunger for data and the robustness to noise, in this paper, …...

AbstractVariational auto-encoders (VAEs) are widely used in natural language generation due to the regularization of the latent space. However, generating sentences from the continuous latent space does not explicitly model …...

AbstractCross-lingual word embeddings (CLEs) facilitate cross-lingual transfer of NLP models. Despite their ubiquitous downstream usage, increasingly popular projection-based CLE models are almost exclusively evaluated on bilingual lexicon induction (BLI). Even …...

AbstractDespite the advancement of question answering (QA) systems and rapid improvements on held-out test sets, their generalizability is a topic of concern. We explore the robustness of QA models to …...

AbstractSource Code Summarization is the task of writing short, natural language descriptions of source code. The main use for these descriptions is in software documentation e.g. the one-sentence Java method …...

AbstractNeural word representations are at the core of many state-of-the-art natural language processing models. A widely used approach is to pre-train, store and look up word or character embedding matrices. …...

AbstractOur submission for Task 1 ‘Cross-lingual Semantic Parsing with UCCA’ at SemEval-2018 is a feed-forward neural network that builds upon an existing state-of-the-art transition-based directed acyclic graph parser. We replace …...

AbstractDetection of some types of toxic language is hampered by extreme scarcity of labeled training data. Data augmentation – generating new synthetic data from a labeled seed dataset – can …...

AbstractKnowledge Graph Completion (KGC) aims at automatically predicting missing links for large-scale knowledge graphs. A vast number of state-of-the-art KGC techniques have got published at top conferences in several research …...

AbstractThis paper introduces BD2BB, a novel language and vision benchmark that requires multimodal models combine complementary information from the two modalities. Recently, impressive progress has been made to develop universal …...

AbstractThis paper describes the winning contribution to SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection (Subtask 2) handed in by team UG Student Intern. We present an ensemble model that …...

AbstractWe evaluate several publicly available off-the-shelf (commercial and research) automatic speech recognition (ASR) systems across diverse dialogue domains (in US-English). Our evaluation is aimed at non-experts with limited experience in …...

AbstractIn the literature, the research on abstract meaning representation (AMR) parsing is much restricted by the size of human-curated dataset which is critical to build an AMR parser with good …...

AbstractThe incorporation of data augmentation method in grammatical error correction task has attracted much attention. However, existing data augmentation methods mainly apply noise to tokens, which leads to the lack …...

AbstractIn this paper we present the WIPRO-RIT systems submitted to the Similar Language Translation shared task at WMT 2020. The second edition of this shared task featured parallel data from …...

AbstractRecently, many works have tried to augment the performance of Chinese named entity recognition (NER) using word lexicons. As a representative, Lattice-LSTM has achieved new benchmark results on several public …...

AbstractSince at least half of the world’s 6000 plus languages will vanish during the 21st century, language documentation has become a rapidly growing field in linguistics. A fundamental challenge for …...

AbstractState-of-the-art systems for argumentation mining are supervised, thus relying on training data containing manually annotated argument components and the relationships between them. To eliminate the reliance on annotated data, we …...

AbstractThe goal of argumentation mining is to automatically extract argumentation structures from argumentative texts. Most existing methods determine argumentative relations by exhaustively enumerating all possible pairs of argument components, which …...

Previous studies have argued that pre-trained language models encode commonsense rela- tional knowledge (e.g. that apples are ed- ible). However, simultaneous work has re- vealed that such models are often …...

Cross-language entity linking grounds men- tions written in several languages to a mono- lingual knowledge base. We use a simple neu- ral ranking architecture for this task that uses multilingual …...

AbstractThe research community has proposed copious modifications to the Transformer architecture since it was introduced over three years ago, relatively few of which have seen widespread adoption. In this paper, …...

AbstractRelative position embedding (RPE) is a successful method to explicitly and efficaciously encode position information into Transformer models. In this paper, we investigate the potential problems in Shaw-RPE and XL-RPE, …...

ive Summarization by Incorporating Answer Relevance Dan Su∗, Tiezheng Yu∗, Pascale Fung Center for Artificial Intelligence Research (CAiRE) Department of Electronic and Computer Engineering The Hong Kong University of Science …...

AbstractThis paper describes the first report on cross-lingual transfer for semantic dependency parsing. We present the insight that there are twodifferent kinds of cross-linguality, namely sur-face level and mantic level, …...

AbstractRumors are rampant in the era of social media. Conversation structures provide valuable clues to differentiate between real and fake claims. However, existing rumor detection methods are either limited to …...

AbstractDue to the popularity of intelligent dialogue assistant services, speech emotion recognition has become more and more important. In the communication between humans and machines, emotion recognition and emotion analysis …...

Named Entity Recognition (NER) is a fun- damental and widely used task in natural language processing (NLP), which is gener- ally trained on the human-annotated corpus. However, data annotation is …...

AbstractWe propose TuringAdvice, a new challenge task and dataset for language understanding models. Given a written situation that a real person is currently facing, a model must generate helpful advice …...

AbstractFor text-level discourse analysis there are various discourse schemes but relatively few labeleddata because discourse research is still immature and it is labor-intensive to annotate the innerlogic of a text. …...

AbstractWe describe the UTFPR systems submitted to the Lexical Complexity Prediction shared task of SemEval 2021. They perform complexity prediction by combining classic features, such as word frequency, n-gram frequency, …...

AbstractA significant challenge in developing translation systems for the world’s ∼7,000 languages is that very few have sufficient data for state-of-the-art techniques. Transfer learning is a promising direction for low-resource …...

AbstractCurrent question answering (QA) systems primarily consider the single-answer scenario, where each question is assumed to be paired with one correct answer. However, in many real-world QA applications, multiple answer …...

AbstractGiven the challenges and complexities introduced while dealing with Dialect Arabic (DA) variations, Transformer based models, e.g., BERT, outperformed other models in dealing with the DA identification task. However, to …...

AbstractRecent graph-based models for joint multiple intent detection and slot filling have obtained promising results through modeling the guidance from the prediction of intents to the decoding of slot filling. …...

AbstractContinual learning is essential for real-world deployment when there is a need to quickly adapt the model to new tasks without forgetting knowledge of old tasks. Existing work on continual …...

AbstractA Visual Question Answering (VQA) model processes images and questions simultaneously with rich semantic information. The attention mechanism can highlight fine-grained features with critical information, thus ensuring that feature extraction …...

AbstractEmotion recognition in conversation (ERC) aims to analyze the speaker’s state and identify their emotion in the conversation. Recent works in ERC focus on context modeling but ignore the representation …...

AbstractAutomated scientific fact checking is difficult due to the complexity of scientific language and a lack of significant amounts of training data, as annotation requires domain expertise. To address this …...

AbstractRecently, aspect sentiment quad prediction (ASQP) has become a popular task in the field of aspect-level sentiment analysis. Previous work utilizes a predefined template to paraphrase the original sentence into …...

AbstractThis paper presents the phonological, morphological, and syntactic distinctions between formal and informal Persian, showing that these two variants have fundamental differences that cannot be attributed solely to pronunciation discrepancies. …...

AbstractCurrently, Medical Subject Headings (MeSH) are manually assigned to every biomedical article published and subsequently recorded in the PubMed database to facilitate retrieving relevant information. With the rapid growth of …...

AbstractIn conversational question answering (CQA), the task of question rewriting (QR) in context aims to rewrite a context-dependent question into an equivalent self-contained question that gives the same answer. In …...

AbstractBERT models used in specialized domains all seem to be the result of a simple strategy: initializing with the original BERT and then resuming pre-training on a specialized corpus. This …...

AbstractDeep NLP models have been shown to be brittle to input perturbations. Recent work has shown that data augmentation using counterfactuals — i.e. minimally perturbed inputs — can help ameliorate …...

AbstractThe task of converting a natural language question into an executable SQL query, known as text-to-SQL, is an important branch of semantic parsing. The state-of-the-art graph-based encoder has been successfully …...

AbstractIn linguistics, a sememe is defined as the minimum semantic unit of languages. Sememe knowledge bases (KBs), which are built by manually annotating words with sememes, have been successfully applied …...

AbstractMulti-vector retrieval methods combine the merits of sparse (e.g. BM25) and dense (e.g. DPR) retrievers and have achieved state-of-the-art performance on various retrieval tasks. These methods, however, are orders of …...

AbstractFigurative language is commonplace in natural language, and while making communication memorable and creative, can be difficult to understand. In this work, we investigate the robustness of Question Answering (QA) …...

AbstractIn our article, we present the systems developed for SemEval-2023 Task 3, which aimed to evaluate the ability of Natural Language Processing (NLP) systems to detect genres and persuasion techniques …...

AbstractNeural reasoning accuracy improves when generating intermediate reasoning steps. However, the source of this improvement is yet unclear. Here, we investigate and factorize the benefit of generating intermediate steps for …...

AbstractNeural machine translation (NMT) has achieved state-of-art performance in high-resource language pairs, but the performance of NMT drops in low-resource conditions. Morphologically rich languages are yet another challenge in NMT. …...

AbstractHate speech is a surely relevant problem in Brazil. Nevertheless, its regulation is not effective due to the difficulty to identify, quantify and classify offensive comments. Here, we introduce a …...

AbstractChain-of-thought prompting (e.g., “Let’s think step-by-ste”) primes large language models to verbalize rationalization for their predictions. While chain-of-thought can lead to dramatic performance gains, benefits appear to emerge only for …...

AbstractWe introduce the StatCan Dialogue Dataset consisting of 19,379 conversation turns between agents working at Statistics Canada and online users looking for published data tables. The conversations stem from genuine …...