6. A subject-verb-object (SVO) chunked computing device, comprising; at least one processor; and memory storing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations comprising: identify a plurality of part of speech (PoS) tokens in an unstructured text; and determine a SVO chunked text directly from the plurality of PoS tokens using a machine learning chunker model, wherein the machine learning chunker model is trained on an SVO annotated training data, wherein the SVO annotated training data comprises a plurality of tokens, a plurality of corresponding PoS tags, and a plurality of corresponding SVO tags, the plurality of corresponding SVO tags comprises one or more of a subject tag, a verb tag, an object tag, or an object-subject tag, and the plurality of corresponding SVO tags is in beginninginside-other (BIO) format, and wherein the SVO annotated training data is generated based on a plurality of corresponding span information for the plurality of tokens by for each of a plurality of PoS tokens in each of a plurality of sets of syntactically related PoS tokens in a sentence, detecting a span information for a PoS token and tagging the PoS token as a subject, a verb, an object, or an object-subject based on the span information and a pervious tagging of the PoS token.
6. A subject-verb-object (SVO) chunked computing device, comprising; at least one processor; and memory storing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations comprising: identify a plurality of part of speech (PoS) tokens in an unstructured text; and determine a SVO chunked text directly from the plurality of PoS tokens using a machine learning chunker model, wherein the machine learning chunker model is trained on an SVO annotated training data, wherein the SVO annotated training data comprises a plurality of tokens, a plurality of corresponding PoS tags, and a plurality of corresponding SVO tags, the plurality of corresponding SVO tags comprises one or more of a subject tag, a verb tag, an object tag, or an object-subject tag, and the plurality of corresponding SVO tags is in beginninginside-other (BIO) format, and wherein the SVO annotated training data is generated based on a plurality of corresponding span information for the plurality of tokens by for each of a plurality of PoS tokens in each of a plurality of sets of syntactically related PoS tokens in a sentence, detecting a span information for a PoS token and tagging the PoS token as a subject, a verb, an object, or an object-subject based on the span information and a pervious tagging of the PoS token. 10. The SVO chunked computing device of claim 6 , wherein the machine learning chunker model determines the plurality of SVO chunked text directly from the plurality of PoS tokens without a set of heuristics or a set of rules.