Usually used for sentence parsing, either grammatical, or Named Entity Recognition (NER) to understand keywords contained within text.
Arguments
- string
a string to be classified
- aggregation_strategy
(Default: simple). There are several aggregation strategies.
none: Every token gets classified without further aggregation.
simple: Entities are grouped according to the default schema (B-, I- tags get merged when the tag is similar).
first: Same as the simple strategy except words cannot end up with different tags. Words will use the tag of the first token when there is ambiguity.
average: Same as the simple strategy except words cannot end up with different tags. Scores are averaged across tokens and then the maximum label is applied.
max: Same as the simple strategy except words cannot end up with different tags. Word entity will be the token with the maximum score.