Proceedings of the Workshop on Coreference Resolution Beyond OntoNotes (CORBON 2016) 2016
DOI: 10.18653/v1/w16-0711
|View full text |Cite
|
Sign up to set email alerts
|

Error analysis for anaphora resolution in Russian: new challenging issues for anaphora resolution task in a morphologically rich language

Abstract: This paper presents a quantitative and qualitative error analysis of Russian anaphora resolvers which participated in the RU-EVAL event. Its aim is to identify and characterize a set of challenging errors common to stateof-the-art systems dealing with Russian. We examined three types of pronouns: 3rd person pronouns, reflexive and relative pronouns. The investigation has shown that a high level of grammatical ambiguity, specific features of reflexive pronouns, free word order and special cases of non-referenti… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
6
0
1

Year Published

2019
2019
2021
2021

Publication Types

Select...
3
1
1

Relationship

0
5

Authors

Journals

citations
Cited by 9 publications
(7 citation statements)
references
References 4 publications
0
6
0
1
Order By: Relevance
“…In Russian, to express the idea of sentence 20a the pronoun sam would be used, which has the same form for animate and inanimate entities. In contrast to English, Russian reflexive pronouns do not agree with their antecedent in number and gender, nor do they express animacy (Toldova et al, 2016). So the error, again, can be caused by the influence of the learners' native language.…”
Section: (B) This Beliefs and Expectations Produce Norms That Powerfumentioning
confidence: 91%
“…In Russian, to express the idea of sentence 20a the pronoun sam would be used, which has the same form for animate and inanimate entities. In contrast to English, Russian reflexive pronouns do not agree with their antecedent in number and gender, nor do they express animacy (Toldova et al, 2016). So the error, again, can be caused by the influence of the learners' native language.…”
Section: (B) This Beliefs and Expectations Produce Norms That Powerfumentioning
confidence: 91%
“…Mixed Polish coreferences resolution approach combines neural networks architecture with the sieve-based approach [48]. For Russian, RU-EVAL-2014 [49] was an evaluation campaign of anaphora and coreferences resolution tools that employed a wide variety of approaches. The evaluation was performed on Russian Coreference Corpus (RuCur).…”
Section: Related Workmentioning
confidence: 99%
“…For Russian, RU-EVAL-2014 [49] was an evaluation campaign of anaphora and coreferences resolution tools that employed a wide variety of approaches. The evaluation was performed on Russian Coreference Corpus (RuCur).…”
Section: Related Workmentioning
confidence: 99%
“…Российские ученые [15] сравнивают шесть программных систем обнаружения анафоры. Для автоматизации процесса поиска в системах использовались методы машинного обучения, морфологические и синтаксические анализаторы, онтологии и правила.…”
Section: обзор смежных работunclassified