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I'm trying to extract triplet subject, predicate, and object from sentence. I need more references on how to do this.
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Aspect Sentiment Triplet Extraction (ASTE) aims to extract triplets from sentences, where each triplet includes an entity, its associated sentiment, and the opinion span explaining the reason for the sentiment.
Let's take a look at a few examples. Sharon sang the song. “Sharon” is the subject. The verb is “sang” and the direct object of the verb is “the song.” This makes the entire predicate of the sentence “sang the song.”
According to the approach presented in [1], a triplet in a text sentence is defined as a relation between subject and object, the relation being the predicate.The aim here is to extract sets of the form {subject, predicate, object} out of syntactically parsed sentences.The triple is a minimal representation for ...
Subject, predicate, and objects are the three different components when breaking down a sentence. The subject is the "who" or "what" of the sentence, the predicate is the verb, and the object is any noun or concept that is part of the action of the subject.
The most basic way to do this, with acceptable result is to do shallow parsing and then extracting NOUN-VERB-NOUN triples. This should work for all SVO (subject–verb–object) languages like English. Some tuning may be required to extract only the first triple from a sentence, or not extract in case of comas. It is a very fast solution, because shallow POS tagging usually is O(n) - 0.01 per sentence, instead of deep parsing(Open NLP, Stanford Parser) which is O(n^3) - 0.4 sec per sentence.
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