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Transforming Wikipedia into Named Entity Training Data
Statistical named entity recognisers require costly hand-labelled training data and, as a result, most existing corpora are small. We exploit Wikipedia to create a massive corpus of named entity annotated …...
Analysing Wikipedia and Gold-Standard Corpora for NER Training
Named entity recognition (NER) for En- glish typically involves one of three gold standards: MUC, CoNLL, or BBN, all created by costly manual annotation. Recent work has used Wikipedia to …...
Fine-Grained Entity Type Classification by Jointly Learning Representations and Label Embeddings
AbstractFine-grained entity type classification (FETC) is the task of classifying an entity mention to a broad set of types. Distant supervision paradigm is extensively used to generate training data for …...
An Empirical Study on Multiple Information Sources for Zero-Shot Fine-Grained Entity Typing
AbstractAuxiliary information from multiple sources has been demonstrated to be effective in zero-shot fine-grained entity typing (ZFET). However, there lacks a comprehensive understanding about how to make better use of …...