POSID combines regex, Word2Vec, WordNet, and SBERT zero-shot classification with POS-tag heuristics to extract person attributes from incident reports, reaching 0.90 F1 for clothes attribute-value pairs on the new InciText dataset.
Sentence-bert: Sentence embeddings using siamese bert-networks,
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A Modular Unsupervised Framework for Attribute Recognition from Unstructured Text
POSID combines regex, Word2Vec, WordNet, and SBERT zero-shot classification with POS-tag heuristics to extract person attributes from incident reports, reaching 0.90 F1 for clothes attribute-value pairs on the new InciText dataset.