Ultimately this means two things will happen: first, legitimate, Wall Street-based token entities will begin using more expensive and vetted services and the ICO scammers will keep spamming us with ladies in bikinis.
Since we try to minimise both predictors their error is back-propagated through the graph, creating a reinforcing loop with two effects: (1) it theoretically encourages the part-detected to better pay more attention to single-token entities and (2) it helps the beginning-detector attend to entity parts.
Since IOB12E captures not only the first word (B1), but also the word that follows it (B2), it may have trouble with the recognition of two-token entities, in which the second word serves both as B2 and the end, or is an independent entity itself.
* NE: single-token chemical entity.
As established by P Corbett, C Batchelor and S Teufel [21] and S Eltyeb and N Salim [20], tokenization is an important issue in CHEMDNER systems, and a customized tokenizer can provide clear advantages in the handling of multi-token chemical entities.
Given these assignments, multi-token named entities can be constructed.
Multi-token named entities, e.g. "ethyl acetate", that occur within the input text are then identified by regex-style matching of chemical tokens to a set of pre-specified pattern definitions such as "*yl *ate".
On the bright side, our analyses of the tokenised CHEMDNER corpus showed a near-complete absence of tokens overlapping several entities, making it possible to accurately reconstruct large entity tokens by stitching several fragments together.
These metrics were computed both at entity and token levels [ 54].
In other words, the terms of place, transition, arc, and token are named as entity, process, connector, and content respectively.
