Text-Token Predictor Feature
(Redirected from Text Token-based Feature)
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A Text-Token Predictor Feature is a predictor feature function that is based on information about a text-token.
- Context:
- It can range from being a Language-Dependent Predictor Feature to being a Language-Independent Predictor Feature.
- It can (typically) be a Categorical Predictor Feature.
- It can (often) be used as:
- an Text Tagging Predictor Feature, such as a POS Feature.
- a Text Segmentation Predictor Feature, such as a Concept Mention Identification Feature.
- Example(s):
- a Low-level Text Token Predictor Feature.
- a Text Token hasCapitalLetter Feature, such as [math]\displaystyle{ f }[/math](hasCapital("Markov”)) ⇒ 1
- a Text Token Dictionary Match Feature, such as [math]\displaystyle{ f }[/math](equals("Markov”,"Jordan”)) ⇒ 0
- a Text Token Character Pattern Feature, such as [math]\displaystyle{ f }[/math](charPattern("Machine-223") ⇒ "Aaaaaaa-000" (Collins, 2002).
- a Character n-Gram Feature, such as [math]\displaystyle{ f }[/math](“rko”, “Markov”) ⇒
true
.
- a High-level Text Token Predictor Feature.
- a Text Token Part-of-Speech Role Feature, such as [math]\displaystyle{ f }[/math](POS(NNS, “tokens”) ⇒ 1
- a Low-level Text Token Predictor Feature.
- Counter-Example(s):
- See: NER Predictor Feature.