Impact of Coreference Resolution on Slot Filling
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Summary
The strengths and weaknesses of automatic coreference resolution systems are illustrated and experimental results to show that they improve performance in the slot filling end-to-end setting are provided.
- Type
- preprint
- Published
- 2017-10-26
- Cited by
- 3
- References
- 16
- Access
- Open access
- OpenAlex
- https://openalex.org/W2765988220
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:35967684
Keywords
Coreference, Computer science, Resolution (logic), Task (project management), Natural language processing
References
- Using Mined Coreference Chains as a Resource for a Semantic Task
- Knowledge Base Population: Successful Approaches and Challenges
- The Stanford CoreNLP Natural Language Processing Toolkit
- Deterministic Coreference Resolution Based on Entity-Centric, Precision-Ranked Rules
- Stanford's Distantly Supervised Slot Filling Systems for KBP 2014
- Challenges in the Knowledge Base Population Slot Filling Task
- Analysing recall loss in named entity slot filling
- CIS at TAC Cold Start 2015: Neural Networks and Coreference Resolution for Slot Filling
- Effective Slot Filling Based on Shallow Distant Supervision Methods
- Coreference Resolution : Current Trends and Future Directions