AMR Beyond the Sentence: the Multi-sentence AMR corpus
Tim O’Gorman, Michael Regan, Kira Griffitt, Ulf Hermjakob, Kevin Knight, Martha Palmer
Abstract
There are few corpora that endeavor to represent the semantic content of entire documents. We present a corpus that accomplishes one way of capturing document level semantics, by annotating coreference and similar phenomena (bridging and implicit roles) on top of gold Abstract Meaning Representations of sentence-level semantics. We present a new corpus of this annotation, with analysis of its quality, alongside a plausible baseline for comparison. It is hoped that this Multi-Sentence AMR corpus (MS-AMR) may become a feasible method for developing rich representations of document meaning, useful for tasks such as information extraction and question answering.- Anthology ID:
- C18-1313
- Volume:
- Proceedings of the 27th International Conference on Computational Linguistics
- Month:
- August
- Year:
- 2018
- Address:
- Santa Fe, New Mexico, USA
- Editors:
- Emily M. Bender, Leon Derczynski, Pierre Isabelle
- Venue:
- COLING
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 3693–3702
- Language:
- URL:
- https://aclanthology.org/C18-1313
- DOI:
- Cite (ACL):
- Tim O’Gorman, Michael Regan, Kira Griffitt, Ulf Hermjakob, Kevin Knight, and Martha Palmer. 2018. AMR Beyond the Sentence: the Multi-sentence AMR corpus. In Proceedings of the 27th International Conference on Computational Linguistics, pages 3693–3702, Santa Fe, New Mexico, USA. Association for Computational Linguistics.
- Cite (Informal):
- AMR Beyond the Sentence: the Multi-sentence AMR corpus (O’Gorman et al., COLING 2018)
- PDF:
- https://preview.aclanthology.org/teach-a-man-to-fish/C18-1313.pdf