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CUNY-BLENDER TAC-KBP2010 Entity Linking and Slot Filling System Description
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Citations
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References
2010
Year
Cuny-blender TeamEngineeringSemantic WebCorpus LinguisticsText MiningNatural Language ProcessingRegular Entity LinkingInformation RetrievalData ScienceComputational LinguisticsManagementData IntegrationLinked DataNamed-entity RecognitionData ManagementMachine TranslationEntity DisambiguationNlp TaskComputer ScienceInformation ManagementRetrieval Augmented GenerationRelationship ExtractionRegular Slot FillingLinguistics
The CUNY-BLENDER team participated in the following tasks in TAC-KBP2010: Regular Entity Linking, Regular Slot Filling and Surprise Slot Filling task (per:disease slot). In the TAC-KBP program, the entity linking task is considered as independent from or a pre-processing step of the slot filling task. Previous efforts on this task mainly focus on utilizing the entity surface information and the sentence/document-level contextual information of the entity. Very little work has attempted using the slot filling results as feedback features to enhance entity linking. In the KBP2010 evaluation, the CUNY-BLENDER entity linking system explored the slot filling attributes that may potentially help disambiguate entity mentions. Evaluation results show that this feedback approach can achieve 9.1% absolute improvement on micro-average accuracy over the baseline using vector space model.
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