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Coreference resolution involves finding antecedents for anaphoric discourse entities, such as definite noun phrases. But many definite noun phrases are not anaphoric because their meaning can be un- derstood from …...

In this paper, we present a learning approach for coreference resolution of noun phrases in unrestricted text. The approach learns from a small, annotated corpus and the task in- cludes …...

In this paper we present a new, multi- lingual data-driven method for coreference resolution as implemented in the SWIZZLE system. The results obtained after training this system on a bilingual …...

The information extraction is to delimit in advance, as part of the specification of the task, the semantic range of the output and to filter information from large volumes of …...

This paper presents a constraint-based multi- agent strategy to coreference resolution of general noun phrases in unrestricted English text. For a given anaphor and all the preceding referring expressions as …...

This paper proposes a new approach for coreference resolution which uses the Bell tree to represent the search space and casts the coreference resolution problem as finding the best path …...

Traditionally, coreference resolution is done by mining the reference relationships be- tween NP pairs. However, an individual NP usually lacks adequate description informa- tion of its referred entity. In this …...

Entity detection and tracking (EDT) is the task of identifying textual mentions of real-world entities in documents, ex- tending the named entity detection and coreference resolution task by consider- ing …...

. 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 …...

In this paper, we view coreference reso- lution as a problem of ranking candidate partitions generated by different coref- erence systems. We propose a set of partition-based features to learn …...

In this paper, we study the impact of a group of features extracted automatically from machine-generated parse trees on coreference resolution. One focus is on designing syn- tactic features using …...

In this paper we describe a coreference resolution method that employs a classi- fication and a clusterization phase. In a novel way, the clusterization is produced as a graph cutting …...

We investigate methods to improve the re- call in coreference resolution by also trying to resolve those definite descriptions where no earlier mention of the referent shares the same lexical …...

Non-verbal modalities such as gesture can improve processing of spontaneous spoken language. For example, similar hand ges- tures tend to predict semantic similarity, so features that quantify gestural similarity can …...

A twin-model is proposed for coreference res- olution: a link component, modeling the coref- erential relationship between an anaphor and a candidate antecedent, and a creation com- ponent modeling the …...

Semantic relatedness is a very important fac- tor for the coreference resolution task. To obtain this semantic information, corpus- based approaches commonly leverage pat- terns that can express a specific …...

Traditional noun phrase coreference res- olution systems represent features only of pairs of noun phrases. In this paper, we propose a machine learning method that enables features over sets of …...

Standard pairwise coreference resolution systems are subject to errors resulting from their performing anaphora identifi- cation as an implicit part of coreference resolution. In this paper, we propose an integer …...

We present an unsupervised, nonparamet- ric Bayesian approach to coreference reso- lution which models both global entity iden- tity across a corpus as well as the sequen- tial anaphoric structure …...

Various types of structural information - e.g., about the type of constructions in which binding constraints apply, or about the structure of names - play a central role in coreference …...

Machine learning approaches to coreference resolution are typically supervised, and re- quire expensive labeled data. Some unsuper- vised approaches have been proposed (e.g., Haghighi and Klein (2007)), but they are …...

This paper investigates two strategies for im- proving coreference resolution: (1) training separate models that specialize in particu- lar types of mentions (e.g., pronouns versus proper nouns) and (2) using …...

In recent years there has been substantial work on the important problem of coreference res- olution, most of which has concentrated on the development of new models and algo- rithmic …...

We present a generative model for unsuper- vised coreference resolution that views coref- erence as an EM clustering process. For comparison purposes, we revisit Haghighi and Klein’s (2007) fully-generative Bayesian …...

There have been considerable attempts to incorporate semantic knowledge into coreference resolution systems: different knowledge sources such as WordNet and Wikipedia have been used to boost the per- formance. In …...

Recent work has shown that explicitly iden- tifying and filtering non-anaphoric mentions prior to coreference resolution can improve the performance of a coreference system. We present a novel approach to …...

As the arm of NLP technologies extends beyond a small core of languages, tech- niques for working with instances of lan- guage data across hundreds to thousands of languages may …...

Traditional learning-based coreference re- solvers operate by training a mention- pair classifier for determining whether two mentions are coreferent or not. Two in- dependent lines of recent research have attempted …...

AbstractThe task of coreference resolution requires people or systems to decide when two referring expressions refer to the 'same' entity or event. In real text, this is often a difficult …...

AbstractThis paper presents the ADN-Classifier, an Automatic classification system of Spanish Deverbal Nominalizations aimed at identifying its semantic denotation (i.e. event, result, underspecified, or lexicalized). The classifier can be used …...

We propose a method to improve the trans- lation of pronouns by resolving their co- reference to prior mentions. We report re- sults using two different co-reference res- olution methods …...

BART (Versley et al., 2008) is a highly mod- ular toolkit for coreference resolution that supports state-of-the-art statistical approaches and enables efficient feature engineering. For the SemEval task 1 on …...

AbstractWe propose a methodology for a novel type of discourse annotation whose model is tuned to the analysis of a text as narrative. This is intended to be the basis …...

This paper explores the effect that dif- ferent corpus configurations have on the performance of a coreference resolution system, as measured by MUC, B3, and CEAF. By varying separately three …...

Coreference resolution is governed by syntac- tic, semantic, and discourse constraints. We present a generative, model-based approach in which each of these factors is modularly en- capsulated and learned in …...

Corry is a system for coreference resolution in English. It supports both local (Soon et al. (2001)-style) and global (Integer Linear Programming, Denis and Baldridge (2007)- style) models of coreference. …...

AbstractThis paper summarizes our work on creating a full-scale coreference resolution (CR) system for Italian, using BART ― an open-source modular CR toolkit initially developed for English corpora. We discuss …...

This paper proposes a dependency-driven scheme to dynamically determine the syn- tactic parse tree structure for tree ker- nel-based anaphoricity determination in coreference resolution. Given a full syntactic parse tree, …...

We describe a novel approach to coref- erence resolution which implements a global decision via hypergraph partition- ing. In constrast to almost all previ- ous approaches, we do not rely …...

A large body of prior research on coref- erence resolution recasts the problem as a two-class classification problem. How- ever, standard supervised machine learn- ing algorithms that minimize classifica- tion …...

This paper describes the participation of RelaxCor in the Semeval-2010 task number 1: “Coreference Resolution in Multiple Languages“. RelaxCor is a constraint-based graph partitioning ap- proach to coreference resolution solved …...

This paper presents the SemEval-2010 task on Coreference Resolution in Multi- ple Languages. The goal was to evaluate and compare automatic coreference reso- lution systems for six different languages (Catalan, …...

This paper presents SUCRE, a new soft- ware tool for coreference resolution and its feature engineering. It is able to sep- arately do noun, pronoun and full coref- erence resolution. …...

The research focus of computational coreference resolution has exhibited a shift from heuristic approaches to machine learning approaches in the past decade. This paper surveys the major milestones in supervised …...

Probabilistic models of sentence com- prehension are increasingly relevant to questions concerning human language processing. However, such models are of- ten limited to syntactic factors. This paper introduces a novel …...

We present UBIU, a language indepen- dent system for detecting full coreference chains, composed of named entities, pro- nouns, and full noun phrases which makes use of memory based learning …...

. This paper presents a listwise approach as an alternative to commonly used pair- wise approaches to the task of coreference resolution in multiple languages. In this listwise approach, all …...

We introduce an incremental entity- mention model for coreference resolution. Our experiments show that it is superior to a non-incremental version in the same en- vironment. The benefits of an …...

In this paper, we present an unsupervised framework that bootstraps a complete corefer- ence resolution (CoRe) system from word as- sociations mined from a large unlabeled cor- pus. We show …...

. This paper systematically explores the effectiveness of dependency and constituent-based syntactic information for anaphoricity determination. In particular, this paper proposes two ways to combine dependency and constituent-based syntactic information …...

While world knowledge has been shown to improve learning-based coreference resolvers, the improvements were typically obtained by incorporating world knowledge into a fairly weak baseline resolver. Hence, it is not …...

Breaking away from traditional attempts at coreference resolution from discourse- only inputs, we try to do the same by constructing rich verb semantics from per- ceptual data, viz. a 2-D …...

In this paper we present an approach to large-scale coreference resolution for an ample set of human languages, with a par- ticular emphasis on time performance and precision. One of …...

An entity in a dialogue may be old, new, or mediated/inferrable with respect to the hearer’s beliefs. Knowing the information status of the entities participating in a dia- logue can …...

This paper presents an empirical study on the influence of singletons on the evalua- tion of coreference resolution systems. We present results on two English data sets used in the …...

The annotation of documents with linguis- tic information requires time-consuming and therefore expensive manual annota- tion. Especially, a complex task, like coreference resolution, needs large data sets for the training …...

This paper presents a mixed deterministic model for coreference resolution in the CoNLL-2012 shared task. We separate the two main stages of our model, mention detection and coreference resolution, into …...

This paper presents HITS’ coreference reso- lution system that participated in the CoNLL- 2012 shared task on multilingual unrestricted coreference resolution. Our system employs a simple multigraph representation of the …...

We present an active learning method for coreference resolution that is novel in three re- spects. (i) It uses bootstrapped neighborhood pooling, which ensures a class-balanced pool even though gold …...

We present a novel adaptive clustering model for coreference resolution in which the expert rules of a state of the art deterministic sys- tem are used as features over pairs …...

This paper describes the UniTN/Essex sub- mission to the CoNLL-2012 Shared Task on the Multilingual Coreference Resolution. We have extended our CoNLL-2011 submission, based on BART, to cover two additional …...

We describe our system for the CoNLL-2012 shared task, which seeks to model corefer- ence in OntoNotes for English, Chinese, and Arabic. We adopt a hybrid approach to coreference resolution, …...

AbstractThis paper describes an empirical study of coreference in spoken vs. written text. We focus on the comparison of two particular text types, interviews and popular science texts, as instances …...

This paper presents the first systematic study of the coreference resolution problem in a general inference-based discourse processing framework. Employing the mode of inference called weighted abduction, we propose a …...

This paper describes our contribution to the CoNLL 2012 Shared Task.1 We present a novel decoding algorithm for coreference res- olution which is combined with a standard pair-wise coreference resolver …...

We propose an adaptive ensemble method to adapt coreference resolution across domains. This method has three features: (1) it can op- timize for any user-specified objective mea- sure; (2) it …...

We describe an approach to coreference resolution that relies on the intuition that easy decisions should be made early, while harder decisions should be left for later when more information …...

We introduce a novel coreference resolution system that models entities and events jointly. Our iterative method cautiously constructs clusters of entity and event mentions using lin- ear regression to model …...

Coreference resolution, which aims at correctly linking meaningful expressions in text, is a much challenging problem in Natural Language Processing community. This paper describes the multilingual coreference modeling system of …...

We explore the interplay of knowledge and structure in co-reference resolution. To inject knowledge, we use a state-of-the-art system which cross-links (or “grounds”) expressions in free text to Wikipedia. We …...

Although first names and nicknames in the United States have been well documented, there has been almost no quantitative analysis on the usage and association of these names amongst themselves. …...

Coreference resolution systems can benefit greatly from inclusion of global context, and a number of recent approaches have demonstrated improvements when precom- puting an alignment to external knowledge sources. However, …...

Coreference resolution metrics quantify errors but do not analyze them. Here, we consider an automated method of categorizing errors in the output of a coreference system into intu- itive underlying …...

Quote attribution is the task of identify- ing the speaker of each quote within a document. While recent research has es- tablished large-scale corpora for this task, these corpora are …...

Coreference resolution plays a critical role in discourse analysis. This paper focuses on exploiting zero pronouns to improve Chi- nese coreference resolution. In particular, a simplified semantic role labeling framework …...

Many errors in coreference resolution come from semantic mismatches due to inadequate world knowledge. Errors in named-entity linking (NEL), on the other hand, are of- ten caused by superficial modeling …...

Learning a hierarchy of specialized pairwise models for coreference resolution This paper proposes a new method for significantly improving the performance of pairwise coreference models. Given a set of indicators, …...

Coreference resolution systems rely heav- ily on string overlap (e.g., Google Inc. and Google), performing badly on mentions with very different words (opaque mentions) like Google and the search giant. …...

A discourse typically involves numerous en- tities, but few are mentioned more than once. Distinguishing discourse entities that die out after just one mention (singletons) from those that lead longer …...

AbstractWe present a joint model of three core tasks in the entity analysis stack: coreference resolution (within-document clustering), named entity recognition (coarse semantic typing), and entity linking (matching to Wikipedia …...

We address the problem of automatically attributing quotations to speakers, which has great relevance in text mining and me- dia monitoring applications. While cur- rent systems report high accuracies for …...

This paper presents a first version of LinkPeople, an entity-centric system for coreference reso- lution of person entities. The approach combines (i) a multi-pass architecture which takes advan- tage of …...

In this study, we perform an investigation of coreference resolution in the biomed- ical literature. We compare a state-of- the-art general system with a purpose- built system, demonstrating that the …...

AbstractCoreference resolution (CR) is a current problem in natural language processing (NLP) research and it is a key task in applications such as question answering, text summarization and information extraction …...

AbstractIn this paper we investigate how different dependency representations of a treebank influence the accuracy of the dependency parser trained on this treebank and the impact on several parser applications: …...

AbstractIn this paper, we present our attempt at annotating procedural texts with a flow graph as a representation of understanding. The domain we focus on is cooking recipe. The flow …...

We investigate different ways of learning structured perceptron models for coref- erence resolution when using non-local features and beam search. Our experi- mental results indicate that standard tech- niques such …...

We propose an algorithm for coreference resolution based on analogy with shift-reduce pars- ing. By reconceptualising the task in this way, we unite ranking- and cluster-based approaches to coreference resolution, …...

AbstractDIRNDL 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 …...

Distant supervision has become the lead- ing method for training large-scale rela- tion extractors, with nearly universal adop- tion in recent TAC knowledge-base pop- ulation competitions. However, there are still …...

In this paper we present a novel method for unsupervised coreference resolution. We introduce a precision-oriented inference method that scores a candidate entity of a mention based on the most …...

Domain adaptation is a challenge for super- vised NLP systems because of expensive and time-consuming manual annotated re- sources. We present a novel method to adapt a supervised coreference resolution …...

Efficient music information retrieval (MIR) require to have meta information about music along with content based information in the knowledge base. Dis- cussion forums on music are rich sources of …...

We explore the impact of adding distri- butional knowledge to a state-of-the-art coreference resolution system. By inte- grating features based on word and context expansions from a distributional thesaurus (DT), …...

AbstractMachine learning approaches to coreference resolution vary greatly in the modeling of the problem: while early approaches operated on the mention pair level, current research focuses on ranking architectures and …...

Discourse deixis is a linguistic phenomenon in which pronouns have verbal or clausal, rather than nominal, antecedents. Studies have esti- mated that between 5% and 10% of pronouns in non-conversational …...

Coreference resolution is a key problem in natural language understanding that still es- capes reliable solutions. One fundamental dif- ficulty has been that of resolving instances involving pronouns since they …...

Context representations are central to vari- ous NLP tasks, such as word sense disam- biguation, named entity recognition, co- reference resolution, and many more. In this work we present a …...

Wikipedia is a resource of choice ex- ploited in many NLP applications, yet we are not aware of recent attempts to adapt coreference resolution to this resource. In this work, …...

Coreference resolution systems are typically trained with heuristic loss functions that re- quire careful tuning. In this paper we in- stead apply reinforcement learning to directly optimize a neural mention-ranking …...

AbstractIn this paper we analyze the effectiveness of using linguistic knowledge from coreference and anaphora resolution for improving the performance for supervised keyphrase extraction. In order to verify the impact …...

Coreference resolution for event men- tions enables extraction systems to process document-level information. Current sys- tems in this area base their decisions on rich semantic features from various knowledge bases, …...

AbstractWe present a novel approach to automated question generation that improves upon prior work both from a technology perspective and from an assessment perspective. Our system is aimed at engaging …...

A long-standing challenge in coreference resolution has been the incorporation of entity-level information – features defined over clusters of mentions instead of men- tion pairs. We present a neural net- …...

AbstractThis paper presents a data-driven co-reference resolution system for German that has been adapted from IMS HotCoref, a co-reference resolver for English. It describes the difficulties when resolving co-reference in …...

AbstractThis paper explores the incorporation of lexico-semantic heuristics into a deterministic Coreference Resolution (CR) system for classifying named entities at document-level. The highest precise sieves of a CR tool are …...

There is a significant gap between the per- formance of a coreference resolution system on gold mentions and on system mentions. This gap is due to the large and unbalanced …...

AbstractWe describe challenges and advantages unique to coreference resolution in the biomedical domain, and a sieve-based architecture that leverages domain knowledge for both entity and event coreference resolution. Domain-general coreference …...

AbstractDespite the popularity of coreference resolution as a research topic, the overwhelming majority of the work in this area focused so far on single antecedence coreference only. Multiple antecedent coreference …...

AbstractThis paper presents WikiCoref, an English corpus annotated for anaphoric relations, where all documents are from the English version of Wikipedia. Our annotation scheme follows the one of OntoNotes with …...

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

AbstractThis paper presents a collaborative partitioning algorithm—a novel ensemble-based approach to coreference resolution. Starting from the all-singleton partition, we search for a solution close to the ensemble’s outputs in terms …...

AbstractAn interesting aspect of structured prediction is the evaluation of an output structure against the gold standard. Especially in the loss-augmented setting, the need of finding the max-violating constraint has …...

AbstractWe introduce the first end-to-end coreference resolution model and show that it significantly outperforms all previous work without using a syntactic parser or hand-engineered mention detector. The key idea is …...

AbstractA common reason for errors in coreference resolution is the lack of semantic information to help determine the compatibility between mentions referring to the same entity. Distributed representations, which have …...

Continuous representations for words or phrases, trained on large unlabeled corpora are proved very useful for many natural language processing tasks. While these vector representations capture many fine-grained syntactic and …...

AbstractAnimacy is a necessary property for a referent to be an agent, and thus animacy detection is useful for a variety of natural language processing tasks, including word sense disambiguation, …...

This paper presents the integration of RelaxCor into FreeLing. RelaxCor is a coreference resolution system based on constraint satisfaction that ranked second in the CoNLL-2011 shared task. FreeLing is an …...

The paper presents several configurations of deep neural networks aimed at the task of coreference resolution for Polish. Starting with the basic feature set and standard word embedding vector size …...

AbstractCoreference resolution is an important task for natural language understanding, and the resolution of ambiguous pronouns a longstanding challenge. Nonetheless, existing corpora do not capture ambiguous pronouns in sufficient volume …...

In this paper we introduce SzegedKoref, a Hungarian corpus in which coreference relations are manually annotated. For annotation, we selected some texts of Szeged Treebank, the biggest treebank of Hungarian …...

AbstractThis paper analyzes arguably the most challenging yet under-explored aspect of resolution tasks such as coreference resolution and entity linking, that is the resolution of plural mentions. Unlike singular mentions …...

AbstractWe propose a triad-based neural network system that generates affinity scores between entity mentions for coreference resolution. The system simultaneously accepts three mentions as input, taking mutual dependency and logical …...

AbstractExtensive research has recently shown that recurrent neural language models are able to process a wide range of grammatical phenomena. How these models are able to perform these remarkable feats …...

AbstractWe apply BERT to coreference resolution, achieving a new state of the art on the GAP (+11.5 F1) and OntoNotes (+3.9 F1) benchmarks. A qualitative analysis of model predictions indicates …...

AbstractRecent neural network models have significantly advanced the task of coreference resolution. However, current neural coreference models are usually trained with heuristic loss functions that are computed over a sequence …...

Modeling anaphora resolution is critical for proper pronoun translation in neural machine translation. Recently it has been addressed by context-aware models with varying success. In this work, we pro- pose …...

AbstractIn order for coreference resolution systems to be useful in practice, they must be able to generalize to new text. In this work, we demonstrate that the performance of the …...

AbstractWe introduce a new benchmark for coreference resolution and NLI, KnowRef, that targets common-sense understanding and world knowledge. Previous coreference resolution tasks can largely be solved by exploiting the number …...

AbstractThe common practice in coreference resolution is to identify and evaluate the maximum span of mentions. The use of maximum spans tangles coreference evaluation with the challenges of mention boundary …...

AbstractPronoun resolution is a major area of natural language understanding. However, large-scale training sets are still scarce, since manually labelling data is costly. In this work, we introduce WikiCREM (Wikipedia …...

AbstractCoreference resolution is the task of identifying all mentions in a text that refer to the same real-world entity. Collecting sufficient labelled data from expert annotators to train a high-performance …...

AbstractWe improve upon pairwise annotation for active learning in coreference resolution, by asking annotators to identify mention antecedents if a presented mention pair is deemed not coreferent. This simple modification, …...

AbstractThe performance of standard coreference resolution is known to drop significantly on Twitter texts. We improve the performance of the (Lee et al., 2018) system, which is originally trained on …...

AbstractWe present a freely available, genre-balanced English web corpus totaling 4M tokens and featuring a large number of high-quality automatic annotation layers, including dependency trees, non-named entity annotations, coreference resolution, …...

AbstractThe meaning of natural language text is supported by cohesion among various kinds of entities, including coreference relations, predicate-argument structures, and bridging anaphora relations. However, predicate-argument structures for nominal predicates …...

AbstractWe present the first large scale corpus for entity resolution in email conversations (CEREC). The corpus consists of 6001 email threads from the Enron Email Corpus containing 36,448 email messages …...

AbstractWe present a voice-based conversational agent which combines the robustness of chatbots and the utility of question answering (QA) systems. Indeed, while data-driven chatbots are typically user-friendly but not goal-oriented, …...

AbstractIn this paper, we present CorefQA, an accurate and extensible approach for the coreference resolution task. We formulate the problem as a span prediction task, like in question answering: A …...

AbstractLanguage models (LMs) trained on large quantities of text have been claimed to acquire abstract linguistic representations. Our work tests the robustness of these abstractions by focusing on the ability …...

AbstractInformation extraction from unstructured texts plays a vital role in the field of natural language processing. Although there has been extensive research into each information extraction task (i.e., entity linking, …...

AbstractRecently, end-to-end neural network-based approaches have shown significant improvements over traditional pipeline-based models in English coreference resolution. However, such advancements came at a cost of computational complexity and recent works …...

AbstractNow that the performance of coreference resolvers on the simpler forms of anaphoric reference has greatly improved, more attention is devoted to more complex aspects of anaphora. One limitation of …...

AbstractCoreference resolution aims at identifying and grouping all mentions referring to the same entity. In French, most systems run different setups, making their comparison difficult. In this paper, we present …...

AbstractDramatic texts are a highly structured literary text type. Their quantitative analysis so far has relied on analysing structural properties (e.g., in the form of networks). Resolving coreferences is crucial …...

AbstractWe investigate modeling coreference resolution under a fixed memory constraint by extending an incremental clustering algorithm to utilize contextualized encoders and neural components. Given a new sentence, our end-to-end algorithm …...

AbstractLong document coreference resolution remains a challenging task due to the large memory and runtime requirements of current models. Recent work doing incremental coreference resolution using just the global representation …...

AbstractHumans do not make inferences over texts, but over models of what texts are about. When annotators are asked to annotate coreferent spans of text, it is therefore a somewhat …...

AbstractWe propose a multi task learning-based neural model for resolving bridging references tackling two key challenges. The first challenge is the lack of large corpora annotated with bridging references. To …...

AbstractMention detection is an important preprocessing step for annotation and interpretation in applications such as NER and coreference resolution, but few stand-alone neural models have been proposed able to handle …...

AbstractWord embeddings are the standard model for semantic and syntactic representations of words. Unfortunately, these models have been shown to exhibit undesirable word associations resulting from gender, racial, and religious …...

AbstractCoreference resolution (CR) aims to find all spans of a text that refer to the same entity. The F1-Scores on these task have been greatly improved by new developed End2End-approaches …...

AbstractThis paper analyzes the impact of higher-order inference (HOI) on the task of coreference resolution. HOI has been adapted by almost all recent coreference resolution models without taking much investigation …...

AbstractIn order to alleviate the shortage of multi-domain data and to capture discourse phenomena for task-oriented dialogue modeling, we propose RiSAWOZ, a large-scale multi-domain Chinese Wizard-of-Oz dataset with Rich Semantic …...

AbstractCorrectly resolving textual mentions of people fundamentally entails making inferences about those people. Such inferences raise the risk of systemic biases in coreference resolution systems, including biases that can harm …...

AbstractA standard way to address different NLP problems is by first constructing a problem-specific dataset, then building a model to fit this dataset. To build the ultimate artificial intelligence, we …...

AbstractIn response to (i) inconclusive results in the literature as to the properties of coreference chains in written versus spoken language, and (ii) a general lack of work on automatic …...

AbstractCoreference resolution is an NLP task to find out whether the set of referring expressions belong to the same concept in discourse. A multi-pass sieve is a deterministic coreference model …...

AbstractCoreference resolution is an important compo-nent in analyzing narrative text from admin-istrative data (e.g., clinical or police sources).However, existing coreference models trainedon general language corpora suffer from poortransferability due to …...

Screenplays refer to characters using differ- ent names, pronouns, and nominal expres- sions. We need to resolve these mentions to the correct referent character for better story understanding and holistic …...

The automated transcription of spoken lan- guage, and meetings, in particular, is be- coming more widespread as automatic speech recognition systems are becoming more accu- rate. This trend has significantly …...

AbstractCoreference resolution is essential for natural language understanding and has been long studied in NLP. In recent years, as the format of Question Answering (QA) became a standard for machine …...

AbstractAnaphora and ellipses are two common phenomena in dialogues. Without resolving referring expressions and information omission, dialogue systems may fail to generate consistent and coherent responses. Traditionally, anaphora is resolved …...

Coreference resolution has been mostly in- vestigated within a single document scope, showing impressive progress in recent years based on end-to-end models. However, the more challenging task of cross-document (CD) …...

AbstractAlthough parsing to Abstract Meaning Representation (AMR) has become very popular and AMR has been shown effective on the many sentence-level downstream tasks, little work has studied how to generate …...

AbstractPerforming event and entity coreference resolution across documents vastly increases the number of candidate mentions, making it intractable to do the full n2 pairwise comparisons. Existing approaches simplify by considering …...

AbstractExternal syntactic and semantic information has been largely ignored by existing neural coreference resolution models. In this paper, we present a heterogeneous graph-based model to incorporate syntactic and semantic structures …...

We consider a joint information extraction (IE) model, solving named entity recognition, coreference resolution and relation extraction jointly over the whole document. In particu- lar, we study how to inject …...

AbstractCharacter linking, the task of linking mentioned people in conversations to the real world, is crucial for understanding the conversations. For the efficiency of communication, humans often choose to use …...

AbstractVisual dialog is a vision-language task where an agent needs to answer a series of questions grounded in an image based on the understanding of the dialog history and the …...

AbstractAcademic neural models for coreference resolution (coref) are typically trained on a single dataset, OntoNotes, and model improvements are benchmarked on that same dataset. However, real-world applications of coref depend …...

State of the art end-to-end coreference reso- lution models use expensive span representa- tions and antecedent prediction mechanisms. These approaches are expensive both in terms of their memory requirements as …...

AbstractCoreference resolution is key to many natural language processing tasks and yet has been relatively unexplored in Sign Language Processing. In signed languages, space is primarily used to establish reference. …...

AbstractZero pronoun resolution aims at recognizing dropped pronouns and pointing out their anaphoric mentions, while non-zero coreference resolution targets at clustering mentions referring to the same entity. Existing efforts often …...

AbstractWinograd schemas are a well-established tool for evaluating coreference resolution (CoR) and commonsense reasoning (CSR) capabilities of computational models. So far, schemas remained largely confined to English, limiting their utility …...

AbstractRecent coreference resolution models rely heavily on span representations to find coreference links between word spans. As the number of spans is O(n2) in the length of text and the …...

AbstractLabeled data for the task of Coreference Resolution is a scarce resource, requiring significant human effort. While state-of-the-art coreference models rely on such data, we propose an approach that leverages …...

AbstractIn recent years, there has been an increasing awareness that many NLP systems incorporate biases of various types (e.g., regarding gender or race) which can have significant negative consequences. At …...

AbstractSpeaker identification (SI) in texts aims to identify the speaker(s) for each utterance in texts. Previous studies divide SI into several sub-tasks (e.g., quote extraction, named entity recognition, gender identification, …...

AbstractModern approaches in Natural Language Processing (NLP) require, ideally, large amounts of labelled data for model training. However, new language resources, for example, for Named Entity Recognition (NER), Co-reference Resolution …...

AbstractThe state-of-the-art models for coreference resolution are based on independent mention pair-wise decisions. We propose a modelling approach that learns coreference at the document-level and takes global decisions. For this …...

AbstractIn recent years, transformer-based coreference resolution systems have achieved remarkable improvements on the CoNLL dataset. However, how coreference resolvers can benefit from discourse coherence is still an open question. In …...

AbstractTwo of the most fundamental issues in Natural Language Understanding (NLU) at present are: (a) how it can established whether deep learning-based models score highly on NLU benchmarks for the …...

AbstractThis paper suggests a direction of coreference resolution for online decoding on actively generated input such as dialogue, where the model accepts an utterance and its past context, then finds …...

AbstractAs using they/them as personal pronouns becomes increasingly common in English, it is important that coreference resolution systems work as well for individuals who use personal “they” as they do …...

AbstractWe propose a new paradigm for zero-shot learners that is format agnostic, i.e., it is compatible with any format and applicable to a list of language tasks, such as text …...

AbstractGiven a sentence “Abby told Brittney that she upset Courtney”, one would struggle to understand who “she” refers to, and ask for clarification. However, if the word “upset” were replaced …...

AbstractAlthough recent neural models for coreference resolution have led to substantial improvements on benchmark datasets, it remains a challenge to successfully transfer these models to new target domains containing many …...

AbstractMost recent coreference resolution systems use search algorithms over possible spans to identify mentions and resolve coreference. We instead present a coreference resolution system that uses a text-to-text (seq2seq) paradigm …...

AbstractBias-measuring datasets play a critical role in detecting biased behavior of language models and in evaluating progress of bias mitigation methods. In this work, we focus on evaluating gender bias …...

AbstractMachine translation (MT) requires a wide range of linguistic capabilities, which current end-to-end models are expected to learn implicitly by observing aligned sentences in bilingual corpora. In this work, we …...

AbstractLarge-scale, high-quality corpora are critical for advancing research in coreference resolution. However, existing datasets vary in their definition of coreferences and have been collected via complex and lengthy guidelines that …...

AbstractOntonotes has served as the most important benchmark for coreference resolution. However, for ease of annotation, several long documents in Ontonotes were split into smaller parts. In this work, we …...