Rajiv Baronia

Vineeth Thanikonda Munirathnam

Jack Porter

Suzanne M Kirch

Soundararajan Velu

Semantic frame identification involves associating identified target words in the sentential context of their natural language source with semantic frames from a frame lexical database. The disclosed invention leverages the CapsNet architecture for improved semantic frame identification of a target word in a natural language input. This includes deriving the features of a target word identified in the sentence and extracting the features of the word units and the thematic words around the target word. Through dynamic routing of capsules, the CapsNet is able to filter the candidate frames for the target word to reduce the search space and apply the CapsNet prediction to identify a frame from a frame lexical database.

Semantic frame identification using capsule networks

Named Entity Recognition is the identification and classification of named entities within a document. Nested NEs occur when an NE is contained within another NE. The disclosed invention leverages the CapsNet architecture for improved nested NE identification and classification. This includes deriving the features of an input text. The derived features are used to identify and classify any named entities in the text. The system is further configured to identify named entities in the text and perform clustering to group named entities. The disclosed CapsNet considers the context of the whole text to activate higher capsule layers in order to identify the named entities and classify them. The teachings of this invention are applicable to other NER models to improve nested NE identification and classification.

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San Ramon, CA, United States of America

Rajiv Baronia