Search Results for author: Heike Zinsmeister

Found 12 papers, 0 papers with code

Modeling Ambiguity with Many Annotators and Self-Assessments of Annotator Certainty

no code implementations COLING (LAW) 2020 Melanie Andresen, Michael Vauth, Heike Zinsmeister

We show that results of multiple annotations and average annotator certainty correlate, but many ambiguities can only be captured if several people contribute.

Sentence

Survey: Anaphora With Non-nominal Antecedents in Computational Linguistics: a Survey

no code implementations CL 2018 Varada Kolhatkar, Adam Roussel, Stefanie Dipper, Heike Zinsmeister

Most of the existing approaches to anaphora annotation and resolution focus on nominal-antecedent anaphora, classifying many of the cases where the antecedents are syntactically non-nominal as non-anaphoric.

Machine Translation Question Answering +1

Anaphora Resolution with the ARRAU Corpus

no code implementations WS 2018 Massimo Poesio, Yulia Grishina, Varada Kolhatkar, Nafise Moosavi, Ina Roesiger, Adam Roussel, Fabian Simonjetz, Alex Uma, ra, Olga Uryupina, Juntao Yu, Heike Zinsmeister

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).

Approximating Style by N-gram-based Annotation

no code implementations WS 2017 Melanie Andresen, Heike Zinsmeister

We present a study that exemplifies this process by a comparison of the German academic languages of linguistics and literary studies.

Authorship Attribution

The Use of Parallel and Comparable Data for Analysis of Abstract Anaphora in German and English

no code implementations LREC 2012 Stefanie Dipper, Melanie Seiss, Heike Zinsmeister

Motivated by the need to use a parallel resource for cross-linguistic feature induction in abstract anaphora resolution, this paper investigates properties of English and German texts in the Europarl corpus, taking into account both general features such as sentence length as well as task-dependent features such as the distribution of demonstrative noun phrases.

Abstract Anaphora Resolution Sentence +1

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