Automated Sentence-Level NLP Task
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An Automated Sentence-Level NLP Task is an NLP task that is a sentence-level analysis task (whose inputs are sentences).
- Context:
- It can (typically) involve Sentence Structure Analysis and Sentence Meaning Extraction.
- It can (often) require Sentence Boundary Detection and Sentence Preprocessing.
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- It can range from being a Simple Sentence Analysis to being a Complex Sentence Analysis.
- It can range from being a Rule-Based Sentence Processing to being a Machine Learning Sentence Processing.
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- It can be solved by a Sentence-Level NLP System.
- It can be part of a Natural Language Processing Pipeline.
- It can require understanding of Sentence-Level Context.
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- Example(s):
- Text Parsing Tasks, which analyze sentence structure.
- SRL Tasks, which identify semantic roles.
- Sentence-Level Text Error Corrections, which fix grammatical mistakes.
- Sentence Classification Tasks, which categorize sentences.
- Sentence Similarity Tasks, which compare sentence meanings.
- Sentence Generation Tasks, which produce grammatical sentences.
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- Counter-Example(s):
- Paragraph-Level NLP, which processes larger text units.
- Document-Level NLP, which analyzes full documents.
- Word-Level NLP, which focuses on individual words.
- Character-Level NLP, which processes text characters.
- See: Sentence-Level Analysis, Natural Language Processing, Linguistic Analysis.
References
2016
- (Schmaltz et al., 2016) ⇒ Allen Schmaltz, Yoon Kim, Alexander M Rush, and Stuart Shieber. (2016). “Sentence-Level Grammatical Error Identification As Sequence-to-Sequence Correction.” In: Proceedings of the 11th Workshop on Innovative Use of NLP for Building Educational Applications.
- QUOTE: ... Evaluation is at the sentence level, but the paragraph-level context for each sentence is also provided. The paragraphs, themselves, are shuffled so that full article context is not available. A coarse academic field category is also provided for each paragraph. Our models described below do not make use of the paragraph context nor the field category, and they treat each sentence independently. ...
... As part of pre-processing, we treat each sentence independently, discarding paragraph context (which sentences, if any, were present in the same paragraph) and domain information, which is a coarse grouping by the field of the original journal (Engineering, Computer Science, Mathematics, Physics, etc.). …
- QUOTE: ... Evaluation is at the sentence level, but the paragraph-level context for each sentence is also provided. The paragraphs, themselves, are shuffled so that full article context is not available. A coarse academic field category is also provided for each paragraph. Our models described below do not make use of the paragraph context nor the field category, and they treat each sentence independently. ...