Abstract
This paper addresses the automatic recognition of telicity, an aspectual notion. A telic event includes a natural endpoint (“she walked home”), while an atelic event does not (“she walked around”). Recognizing this difference is a prerequisite for temporal natural language understanding. In English, this classification task is difficult, as telicity is a covert linguistic category. In contrast, in Slavic languages, aspect is part of a verb’s meaning and even available in machine-readable dictionaries. Our contributions are as follows. We successfully leverage additional silver standard training data in the form of projected annotations from parallel English-Czech data as well as context information, improving automatic telicity classification for English significantly compared to previous work. We also create a new data set of English texts manually annotated with telicity.- Anthology ID:
- D17-1271
- Volume:
- Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing
- Month:
- September
- Year:
- 2017
- Address:
- Copenhagen, Denmark
- Editors:
- Martha Palmer, Rebecca Hwa, Sebastian Riedel
- Venue:
- EMNLP
- SIG:
- SIGDAT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 2559–2565
- Language:
- URL:
- https://aclanthology.org/D17-1271
- DOI:
- 10.18653/v1/D17-1271
- Cite (ACL):
- Annemarie Friedrich and Damyana Gateva. 2017. Classification of telicity using cross-linguistic annotation projection. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pages 2559–2565, Copenhagen, Denmark. Association for Computational Linguistics.
- Cite (Informal):
- Classification of telicity using cross-linguistic annotation projection (Friedrich & Gateva, EMNLP 2017)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-2/D17-1271.pdf
- Code
- annefried/telicity