Heuristic Algorithm for Zero Subject Detection in Polish

Kaczmarek, Adam; Marcińczuk, Michał

doi:10.1007/978-3-319-24033-6_43

Cited by 5 publications

(2 citation statements)

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“…Kopeć (2014) has presented a machine learning approach and has shown that the performance of dependency parsing itself for this problem is even lower than the majority baseline. Another heuristic approach, referred to as Minos, has been formulated by Kaczmarek and Marcińczuk (2015b) and has achieved state-of-the-art results. This study also provides an in-depth analysis of verb classification in Polish from the perspective of zero subject detection.…”

Section: Related Workmentioning

confidence: 99%

“…One is the improvement of zero subject detection, which we plan to achieve by combining a machine learning approach with knowledge incorporated in the current state-ofthe art heuristic approach (Kaczmarek & Marcińczuk, 2015b). Another aspect is the improvement of coreference resolution for other mentions, as we have shown that it has a significant impact on the final results.…”

Section: Future Workmentioning

confidence: 99%

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A preliminary study in zero anaphora coreference resolution for Polish

Kaczmarek

Marcińczuk

2017

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Zero anaphora is an element of the coreference resolution task that has not yet been directly addressed in Polish and, in most studies, it has been left as the most challenging aspect for further investigation. This article presents an initial study of this problem. The preparation of a machine learning approach, alongside engineering features based on linguistic study of the KPWr corpus, is discussed. This study utilizes existing tools for Polish coreference resolution as sources of partial coreferential clusters containing pronoun, noun and named entity mentions. They are also used as baseline zero coreference resolution systems for comparison with our system. The evaluation process is focused not only on clustering correctness, without taking into account types of mentions, using standard CoNLL-2012 measures, but also on the informativeness of the resulting relations. According to the annotation approach used for coreference to the KPWr corpus, only named entities are treated as mentions that are informative enough to constitute a link to real world objects. Consequently, we provide an evaluation of informativeness based on found links between zero anaphoras and named entities. For the same reason, we restrict coreference resolution in this study to mention clusters built around named entities.

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Section: Related Workmentioning

confidence: 99%

Section: Future Workmentioning

confidence: 99%