Abstract
Spatial relation extraction from generic text is a challenging problem due to the ambiguity of the prepositions spatial meaning as well as the nesting structure of the spatial descriptions. In this work, we highlight the difficulties that the anaphora can make in the extraction of spatial relations. We use external multi-modal (here visual) resources to find the most probable candidates for resolving the anaphoras that refer to the landmarks of the spatial relations. We then use global inference to decide jointly on resolving the anaphora and extraction of the spatial relations. Our preliminary results show that resolving anaphora improves the state-of-the-art results on spatial relation extraction.- Anthology ID:
- W18-1407
- Volume:
- Proceedings of the First International Workshop on Spatial Language Understanding
- Month:
- June
- Year:
- 2018
- Address:
- New Orleans
- Editors:
- Parisa Kordjamshidi, Archna Bhatia, James Pustejovsky, Marie-Francine Moens
- Venue:
- SpLU
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 53–62
- Language:
- URL:
- https://aclanthology.org/W18-1407
- DOI:
- 10.18653/v1/W18-1407
- Cite (ACL):
- Umar Manzoor and Parisa Kordjamshidi. 2018. Anaphora Resolution for Improving Spatial Relation Extraction from Text. In Proceedings of the First International Workshop on Spatial Language Understanding, pages 53–62, New Orleans. Association for Computational Linguistics.
- Cite (Informal):
- Anaphora Resolution for Improving Spatial Relation Extraction from Text (Manzoor & Kordjamshidi, SpLU 2018)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/W18-1407.pdf
- Data
- Visual Genome