Refine
Document Type
- Conference Proceeding (3)
- Article (1)
Has Fulltext
- yes (4)
Keywords
- Korpus <Linguistik> (3)
- Textsorte (2)
- dependency parsing (2)
- genre and register variation (2)
- parser adaptation (2)
- Automatische Sprachanalyse (1)
- Deutsch (1)
- Grammatik (1)
- HPSG (1)
- Head-driven phrase structure grammar (1)
Publicationstate
- Veröffentlichungsversion (4) (remove)
Reviewstate
- Peer-Review (4) (remove)
In this paper, we deal with register-driven variation from a probabilistic perspective, as proposed in Schäfer, Bildhauer, Pankratz, Müller (2022). We compare two approaches to analyse this variation within HPSG. On the one hand, we consider a multiple-grammar approach and combine it with the architecture proposed in the CoreGram project Müller (2015) - discussing its advantages and disadvantages. On the other hand, we take into account a single-grammar approach and argue that it appears to be superior due to its computational efficiency and cognitive plausibility.
In the NLP literature, adapting a parser to new text with properties different from the training data is commonly referred to as domain adaptation. In practice, however, the differences between texts from different sources often reflect a mixture of domain and genre properties, and it is by no means clear what impact each of those has on statistical parsing. In this paper, we investigate how differences between articles in a newspaper corpus relate to the concepts of genre and domain and how they influence parsing performance of a transition-based dependency parser. We do this by applying various similarity measures for data point selection and testing their adequacy for creating genre-aware parsing models.
In the NLP literature, adapting a parser to new text with properties different from the training data is commonly referred to as domain adaptation. In practice, however, the differences between texts from different sources often reflect a mixture of domain and genre properties, and it is by no means clear what impact each of those has on statistical parsing. In this paper, we investigate how differences between articles in a newspaper corpus relate to the concepts of genre and domain and how they influence parsing performance of a transition-based dependency parser. We do this by applying various similarity measures for data point selection and testing their adequacy for creating genre-aware parsing models.
Dieses Papier diskutiert informationsstrukturelle Aspekte der mehrfachen Vorfeldbesetzung im Deutschen. Auf der Grundlage einer größtenteils aus den IDS-Korpora extrahierten Belegsammlung werden Diskursgegebenheit, Fokus- und Topikstatus (vor allem) des Vorfeldmaterials beschrieben und in Bezug zu entsprechenden Aussagen in der Literatur gesetzt. Neben informationsstrukturellen Faktoren werden im letzten Abschnitt mögliche weitere Faktoren angesprochen, die mehrfache Vorfeldbesetzung favorisieren könnten. Zudem werden für einen begrenzten Ausschnitt des Deutschen erstmals Zahlen vorgelegt, die das Verhältnis von mehrfacher Vorfeldbesetzung zur ähnlichen, aber als „kanonischer“ geltenden Besetzung des Vorfelds mit einer (möglicherweise partiellen) Verbalphrase illustrieren.