Papers Coreference Resolution
“Coreference Resolution” 태그가 달린 논문 924편 · 필터 해제
GenderQuant: Quantifying Mention-Level Genderedness
Language is gendered if the context surrounding a mention is suggestive of a particular binary gender for that mention. Detecting the different ways in which language is gendered is an important task since gendered langu…
Articlescoreference-resolutionCoreference ResolutionEvaluation of named entity coreference
In many NLP applications like search and information extraction for named entities, it is necessary to find all the mentions of a named entity, some of which appear as pronouns (she, his, etc.) or nominals (the professor…
coreference-resolutionCoreference ResolutionNeural Coreference Resolution with Limited Lexical Context and Explicit Mention Detection for Oral French
We propose an end-to-end coreference resolution system obtained by adapting neural models that have recently improved the state-of-the-art on the OntoNotes benchmark to make them applicable to other paradigms for this ta…
coreference-resolutionCoreference ResolutionCross-lingual Incongruences in the Annotation of Coreference
In the present paper, we deal with incongruences in English-German multilingual coreference annotation and present automated methods to discover them. More specifically, we automatically detect full coreference chains in…
coreference-resolutionCoreference ResolutionTranslationDeep Cross-Lingual Coreference Resolution for Less-Resourced Languages: The Case of Basque
In this paper, we present a cross-lingual neural coreference resolution system for a less-resourced language such as Basque. To begin with, we build the first neural coreference resolution system for Basque, training it …
coreference-resolutionCoreference ResolutionAttention Is (not) All You Need for Commonsense Reasoning
The recently introduced BERT model exhibits strong performance on several language understanding benchmarks. In this paper, we describe a simple re-implementation of BERT for commonsense reasoning. We show that the atten…
AllCoreference ResolutionNatural Language UnderstandingSentence Level Representation And Language Models In The Task Of Coreference Resolution For Russian
Coreference Resolution (CR) is one of the most difficult tasks in the field of Natural Language Processing due to the lack of deeply and comprehensively understanding the semantic meaning of the mention in not only the s…
coreference-resolutionCoreference ResolutionSentenceIncorporating Context and External Knowledge for Pronoun Coreference Resolution
Linking pronominal expressions to the correct references requires, in many cases, better analysis of the contextual information and external knowledge. In this paper, we propose a two-layer model for pronoun coreference …
coreference-resolutionCoreference ResolutionA Surprisingly Robust Trick for Winograd Schema Challenge
The Winograd Schema Challenge (WSC) dataset WSC273 and its inference counterpart WNLI are popular benchmarks for natural language understanding and commonsense reasoning. In this paper, we show that the performance of th…
Common Sense ReasoningCoreference ResolutionLanguage ModelingLanguage Modelling+3SP-10K: A Large-scale Evaluation Set for Selectional Preference Acquisition
Selectional Preference (SP) is a commonly observed language phenomenon and proved to be useful in many natural language processing tasks. To provide a better evaluation method for SP models, we introduce SP-10K, a large-…
coreference-resolutionCoreference ResolutionSocialIQA: Commonsense Reasoning about Social Interactions
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 o…
Common Sense ReasoningCoreference ResolutionMultiple-choiceQuestion Answering+1Unsupervised Deep Structured Semantic Models for Commonsense Reasoning
Commonsense reasoning is fundamental to natural language understanding. While traditional methods rely heavily on human-crafted features and knowledge bases, we explore learning commonsense knowledge from a large amount …
Common Sense ReasoningCoreference ResolutionNatural Language UnderstandingSentenceCLEVR-Dialog: A Diagnostic Dataset for Multi-Round Reasoning in Visual Dialog
Visual Dialog is a multimodal task of answering a sequence of questions grounded in an image, using the conversation history as context. It entails challenges in vision, language, reasoning, and grounding. However, study…
coreference-resolutionCoreference ResolutionDiagnosticVisual DialogLanguage Models are Unsupervised Multitask Learners
Natural language processing tasks, such as question answering, machine translation, reading comprehension, and summarization, are typically approached with supervised learning on taskspecific datasets. We demonstrate th…
Common Sense ReasoningCoreference ResolutionData-to-Text GenerationDialogue State Tracking+12SDNet: Contextualized Attention-based Deep Network for Conversational Question Answering
Conversational question answering (CQA) is a novel QA task that requires understanding of dialogue context. Different from traditional single-turn machine reading comprehension (MRC) tasks, CQA includes passage comprehen…
Conversational Question AnsweringCoreference ResolutionMachine Reading ComprehensionQuestion Answering+2CIS at TAC Cold Start 2015: Neural Networks and Coreference Resolution for Slot Filling
This paper describes the CIS slot filling system for the TAC Cold Start evaluations 2015. It extends and improves the system we have built for the evaluation last year. This paper mainly describes the changes to our last…
coreference-resolutionCoreference ResolutionGeneral Classificationslot-filling+1How Reasonable are Common-Sense Reasoning Tasks: A Case-Study on the Winograd Schema Challenge and SWAG
Recent studies have significantly improved the state-of-the-art on common-sense reasoning (CSR) benchmarks like the Winograd Schema Challenge (WSC) and SWAG. The question we ask in this paper is whether improved performa…
Common Sense ReasoningCoreference ResolutionThe Knowref Coreference Corpus: Removing Gender and Number Cues for Difficult Pronominal Anaphora Resolution
We 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 …
Common Sense Reasoningcoreference-resolutionCoreference ResolutionData Augmentation+2Team GESIS Cologne: An all in all sentence-based approach for FEVER
In this system description of our pipeline to participate at the Fever Shared Task, we describe our sentence-based approach. Throughout all steps of our pipeline, we regarded single sentences as our processing unit. In o…
AllCoreference ResolutionSentenceExpletives in Universal Dependency Treebanks
Although treebanks annotated according to the guidelines of Universal Dependencies (UD) now exist for many languages, the goal of annotating the same phenomena in a cross-linguistically consistent fashion is not always m…
Coreference ResolutionQuestion Answering