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Found 24 papers, 10 papers with code
The CODI-CRAC 2022 Shared Task on Anaphora, Bridging, and Discourse Deixis in Dialogue
The CODI-CRAC 2022 Shared Task on Anaphora Resolution in Dialogues is the second edition of an initiative focused on detecting different types of anaphoric relations in conversations of different kinds.
The Universal Anaphora Scorer
It also supports the evaluation of split antecedent anaphora and discourse deixis, for which no tools existed.
The CODI-CRAC 2021 Shared Task on Anaphora, Bridging, and Discourse Deixis in Dialogue
In this paper, we provide an overview of the CODI-CRAC 2021 Shared-Task: Anaphora Resolution in Dialogue.
Multi-Objective Mobile Damped Wave Algorithm (MOMDWA): A Novel Approach For Quantum System Control
In this paper, we introduce a novel multi-objective optimization algorithm, the Multi-Objective Mobile Damped Wave Algorithm (MOMDWA), specifically designed to address complex quantum control problems.
Aggregating Crowdsourced and Automatic Judgments to Scale Up a Corpus of Anaphoric Reference for Fiction and Wikipedia Texts
Although several datasets annotated for anaphoric reference/coreference exist, even the largest such datasets have limitations in terms of size, range of domains, coverage of anaphoric phenomena, and size of documents included.
Scoring Coreference Chains with Split-Antecedent Anaphors
Anaphoric reference is an aspect of language interpretation covering a variety of types of interpretation beyond the simple case of identity reference to entities introduced via nominal expressions covered by the traditional coreference task in its most recent incarnation in ONTONOTES and similar datasets.
Stay Together: A System for Single and Split-antecedent Anaphora Resolution
Split-antecedent anaphora is rarer and more complex to resolve than single-antecedent anaphora; as a result, it is not annotated in many datasets designed to test coreference, and previous work on resolving this type of anaphora was carried out in unrealistic conditions that assume gold mentions and/or gold split-antecedent anaphors are available.
Multitask Learning-Based Neural Bridging Reference Resolution
can be achieved on full bridging resolution with this architecture.
Free the Plural: Unrestricted Split-Antecedent Anaphora Resolution
One limitation of virtually all coreference resolution models is the focus on single-antecedent anaphors.
Neural Coreference Resolution for Arabic
No neural coreference resolver for Arabic exists, in fact we are not aware of any learning-based coreference resolver for Arabic since (Bjorkelund and Kuhn, 2014).
Named Entity Recognition as Dependency Parsing
Named Entity Recognition (NER) is a fundamental task in Natural Language Processing, concerned with identifying spans of text expressing references to entities.
Ranked #2 on
Named Entity Recognition (NER)
on GENIA
Multi-task Learning Based Neural Bridging Reference Resolution
can be achieved on full bridging resolution with this architecture.
A Cluster Ranking Model for Full Anaphora Resolution
In this paper, we introduce an architecture to simultaneously identify non-referring expressions (including expletives, predicative s, and other types) and build coreference chains, including singletons.
Ranked #1 on
Coreference Resolution
on The ARRAU Corpus
A Mention-Pair Model of Annotation with Nonparametric User Communities
The model is also flexible enough to be used in standard annotation tasks for classification where it registers on par performance with the state of the art.
Neural Mention Detection
We then evaluate our models for coreference resolution by using mentions predicted by our best model in start-of-the-art coreference systems.
Crowdsourcing and Aggregating Nested Markable Annotations
One of the key steps in language resource creation is the identification of the text segments to be annotated, or markables, which depending on the task may vary from nominal chunks for named entity resolution to (potentially nested) noun phrases in coreference resolution (or mentions) to larger text segments in text segmentation.
A Crowdsourced Corpus of Multiple Judgments and Disagreement on Anaphoric Interpretation
The corpus, containing annotations for about 108, 000 markables, is one of the largest corpora for coreference for English, and one of the largest crowdsourced NLP corpora, but its main feature is the large number of judgments per markable: 20 on average, and over 2. 2M in total.
Semi-Supervised Methods for Out-of-Domain Dependency Parsing
Dependency parsing is one of the important natural language processing tasks that assigns syntactic trees to texts.
A Probabilistic Annotation Model for Crowdsourcing Coreference
The availability of large scale annotated corpora for coreference is essential to the development of the field.
Anaphora Resolution with the ARRAU Corpus
The most distinctive feature of the corpus is the annotation of a wide range of anaphoric relations, including bridging references and discourse deixis in addition to identity (coreference).
Dependency Language Models for Transition-based Dependency Parsing
In this paper, we present an approach to improve the accuracy of a strong transition-based dependency parser by exploiting dependency language models that are extracted from a large parsed corpus.
