作者: Ancillary 時間: 2025-3-21 23:21 作者: Oratory 時間: 2025-3-22 03:34
https://doi.org/10.1057/9781403980564art systems that are purely based on machine learning. We finish the chapter by outlining a checklist-based approach on choosing, integrating and adapting a coreference system for a putative new application context.作者: 難理解 時間: 2025-3-22 08:05
Monika J?ckle,Sandra Eck,Kyra Schneiderdels over the years. In particular, there is a gradual shift from local modelstowards global models,which seek to address the weaknesses of local models by exploiting additional information beyond that of the local context. In this chapter, we will discuss these advanced models for coreference resolution.作者: 法官 時間: 2025-3-22 10:15
Problemstellung und Forschungsperspektive,scale machine learning approaches. We describe the drawbacks and advantages of the different algorithms, focusing mostly on English anaphora resolution. We pay special attention to recent methods for extracting agreement information directly from large volumes of raw text.作者: 隱藏 時間: 2025-3-22 13:45
https://doi.org/10.1007/978-3-531-91200-4e resolution helps to improve the quality of selected content even if coreference resolution systems are still far from perfect. Both single-document and multi-document summarization branches are discussed. Then we focus on post-processing techniques to improve the referential clarity and coherence of extracted summaries.作者: MANIA 時間: 2025-3-22 18:33
2192-032X arch advances.Includes a comprehensive introduction to the f.This book lays out a path leading from the linguistic and cognitive basics, to classical rule-based and machine learning algorithms, to today’s state-of-the-art approaches, which use advanced empirically grounded techniques, automatic know作者: Biofeedback 時間: 2025-3-22 22:07
https://doi.org/10.1057/9781403980564tic representation of a document to be analyzed. This chapter focuses on the preprocessing technology, taking into consideration a variety of external tools needed to create such representations, and shows how to combine them in a ., in order to extract mentions of entities in a given document, describing their linguistic properties.作者: 魔鬼在游行 時間: 2025-3-23 03:42
https://doi.org/10.1007/978-3-531-91200-4however, the question of semantic constraints and preferences and its operationalization in a system that performs anaphora resolution, is more complex and a larger variety of solutions can be found in practice.作者: Repetitions 時間: 2025-3-23 06:16
Preprocessing Technologytic representation of a document to be analyzed. This chapter focuses on the preprocessing technology, taking into consideration a variety of external tools needed to create such representations, and shows how to combine them in a ., in order to extract mentions of entities in a given document, describing their linguistic properties.作者: cathartic 時間: 2025-3-23 11:27
Using Lexical and Encyclopedic Knowledgehowever, the question of semantic constraints and preferences and its operationalization in a system that performs anaphora resolution, is more complex and a larger variety of solutions can be found in practice.作者: Dorsal-Kyphosis 時間: 2025-3-23 16:24
https://doi.org/10.1007/978-3-030-46870-5corpora are presented in a uniform and well-structured way. Moreover, three useful, widely used and freely available annotation tools (CALLISTO, MMAX2, and Palinka) will be described. They can be employed if own annotation work turns out to be indispensable.作者: Override 時間: 2025-3-23 21:33 作者: expansive 時間: 2025-3-23 22:57 作者: 無效 時間: 2025-3-24 06:20 作者: 憤憤不平 時間: 2025-3-24 07:33 作者: 條街道往前推 時間: 2025-3-24 11:58
The Mention-Pair Model by clustering these pairwise decisions. This chapter reviews the main building blocks of the mention-pair model: the construction of positive and negative instances and the related problem of data set skewness, the selection of informative features, and the choice of machine learner and clustering mechanism.作者: 不發(fā)音 時間: 2025-3-24 17:12
Linguistic and Cognitive Evidence About Anaphoraaints and preferences) will be identified that are deemed relevant for interpreting anaphoric expressions, and it will be looked at evidence from corpora and psycholinguistics in favor of these factors. This includes a description of the main models of local focus, distinguishing between discrete and activation-based approaches.作者: 持久 時間: 2025-3-24 20:14 作者: Albinism 時間: 2025-3-25 02:16 作者: acquisition 時間: 2025-3-25 04:32
Advanced Machine Learning Models for Coreference Resolutiondels over the years. In particular, there is a gradual shift from local modelstowards global models,which seek to address the weaknesses of local models by exploiting additional information beyond that of the local context. In this chapter, we will discuss these advanced models for coreference resolution.作者: Conjuction 時間: 2025-3-25 09:04
Extracting Anaphoric Agreement Properties from Corporascale machine learning approaches. We describe the drawbacks and advantages of the different algorithms, focusing mostly on English anaphora resolution. We pay special attention to recent methods for extracting agreement information directly from large volumes of raw text.作者: eustachian-tube 時間: 2025-3-25 15:15
Coreference Applications to Summarizatione resolution helps to improve the quality of selected content even if coreference resolution systems are still far from perfect. Both single-document and multi-document summarization branches are discussed. Then we focus on post-processing techniques to improve the referential clarity and coherence of extracted summaries.作者: 碳水化合物 時間: 2025-3-25 18:37
Theorie und Praxis der Diskursforschung results. Conceptually, and from an engineering perspective, the ILP formulation is very simple and it provides system designers with a lot of flexibility in incorporating knowledge. Indeed, this is where we believe future research should focus.作者: 我不怕犧牲 時間: 2025-3-25 20:59 作者: 圍裙 時間: 2025-3-26 01:43 作者: conference 時間: 2025-3-26 04:54 作者: 我們的面粉 時間: 2025-3-26 11:10
https://doi.org/10.1007/978-3-030-46870-5ated Corpora and Annotation Tools”) led to the development of the first systems able to operate on a larger scale, and to a widening of the range of anaphoric expressions handled. The fundamental property of these systems was the ability to carry out resolution on the basis of imperfect information 作者: febrile 時間: 2025-3-26 16:40
Early Approaches to Anaphora Resolution: Theoretically Inspired and Heuristic-Basedated Corpora and Annotation Tools”) led to the development of the first systems able to operate on a larger scale, and to a widening of the range of anaphoric expressions handled. The fundamental property of these systems was the ability to carry out resolution on the basis of imperfect information 作者: Debark 時間: 2025-3-26 19:20 作者: MUTED 時間: 2025-3-26 22:23
Linguistic and Cognitive Evidence About Anaphoraecovered in context—in particular, which information is used. In this chapter we discuss this evidence. Respective key concepts will be defined, including the main types of relations between anaphor and antecedent and the formal notion of discourse model. Moreover, the most important factors (constr作者: 退潮 時間: 2025-3-27 03:05 作者: 惰性氣體 時間: 2025-3-27 05:58
Annotated Corpora and Annotation Toolsrehensive survey of annotated corpora will be given, which ranges from the corpora and guidelines developed for the Message Understanding Conferences MUC-6 (1996) and MUC-7 (1998), which have been seminal to the field, to the resources that have been recently made available as part of the 2010 SemEv作者: 失誤 時間: 2025-3-27 10:27
Evaluation Metricse of sub-problems, such as: (1) What is the evaluation unit (entities or links); if entities, is entity-alignment needed? if links, how to handle single-mention entities? (2) How to deal with the fact that the response mention set may differ from that of the key mention set? We will review the preva作者: AGONY 時間: 2025-3-27 17:04 作者: 痛打 時間: 2025-3-27 20:24 作者: GNAT 時間: 2025-3-27 23:06
Off-the-Shelf Toolsognition. In this chapter, we will present the properties that are most important for the integration of coreference systems into a larger context, then describe the BART system, the dCoref system that is part of Stanford’s CoreNLP suite, as well as IMSCoref and HOTCoref as examples of state-of-the-作者: 毗鄰 時間: 2025-3-28 04:51 作者: manifestation 時間: 2025-3-28 09:32 作者: CRACY 時間: 2025-3-28 12:01 作者: 不如樂死去 時間: 2025-3-28 15:53 作者: 膽小鬼 時間: 2025-3-28 20:40 作者: resistant 時間: 2025-3-29 00:26
Using Lexical and Encyclopedic Knowledgeanaphors and for anaphoric definite descriptions – beyond the baseline level. In contrast to hard criteria such as binding and agreement constraints, however, the question of semantic constraints and preferences and its operationalization in a system that performs anaphora resolution, is more comple作者: outskirts 時間: 2025-3-29 06:20 作者: 輕率的你 時間: 2025-3-29 09:03
https://doi.org/10.1007/978-3-030-46870-5ecovered in context—in particular, which information is used. In this chapter we discuss this evidence. Respective key concepts will be defined, including the main types of relations between anaphor and antecedent and the formal notion of discourse model. Moreover, the most important factors (constr作者: A簡潔的 時間: 2025-3-29 13:56 作者: monogamy 時間: 2025-3-29 19:06
https://doi.org/10.1007/978-3-030-46870-5rehensive survey of annotated corpora will be given, which ranges from the corpora and guidelines developed for the Message Understanding Conferences MUC-6 (1996) and MUC-7 (1998), which have been seminal to the field, to the resources that have been recently made available as part of the 2010 SemEv作者: 聽寫 時間: 2025-3-29 21:30 作者: 怎樣才咆哮 時間: 2025-3-30 00:22
Participant-Observation as a Research Methodn the same datasets and annotations, and are evaluated on the same test set and using the same scoring software, thus making it possible to compare the different participating systems. More specifically, we overview the Message Understanding Conference (MUC), the Automatic Content Extraction program作者: 搖曳 時間: 2025-3-30 05:51 作者: 手工藝品 時間: 2025-3-30 11:03
https://doi.org/10.1057/9781403980564ognition. In this chapter, we will present the properties that are most important for the integration of coreference systems into a larger context, then describe the BART system, the dCoref system that is part of Stanford’s CoreNLP suite, as well as IMSCoref and HOTCoref as examples of state-of-the-作者: Brittle 時間: 2025-3-30 15:42
Participant-Observation as a Research Method in the mid-1990s and further developed into a more generic resolver by Soon et?al. in 2001 and many others, the simple model still remains a popular benchmark in the learning-based resolution research. The mention-pair model recasts the coreference resolution problem as a classification task in whi作者: indicate 時間: 2025-3-30 19:47
Monika J?ckle,Sandra Eck,Kyra Schneider modeling perspective: its focus on making local coreference decisions involving only two mentions and their contexts makes it even less expressive than the coreference systems developed in the pre-statistical NLP era. Realizing its weaknesses, researchers have developed many advanced coreference mo作者: 歸功于 時間: 2025-3-30 22:47 作者: 多樣 時間: 2025-3-31 02:53 作者: Mendicant 時間: 2025-3-31 05:26 作者: 巫婆 時間: 2025-3-31 09:44 作者: Exposition 時間: 2025-3-31 14:42 作者: CRUDE 時間: 2025-3-31 20:30
