1. A computer-implemented process, comprising: receiving, in a computer memory: data identifying entities described in a document, wherein the document includes a plurality of tokens appearing in an order in the document, and data defining sentiment values assigned to the tokens in the document; and processing the data in the computer memory with a processor to assign a sentiment value to one of the identified entities in the document, by: applying a filter to a sequence of the sentiment values corresponding to a sequence of the tokens in the order the tokens appear in the document, the filter having a width defined by a number of tokens, the entity having a position in the sequence of tokens, the filter providing a combination of contributions of the sentiment values associated with the tokens surrounding the position of the entity in the document within the width of the filter.
1. A computer-implemented process, comprising: receiving, in a computer memory: data identifying entities described in a document, wherein the document includes a plurality of tokens appearing in an order in the document, and data defining sentiment values assigned to the tokens in the document; and processing the data in the computer memory with a processor to assign a sentiment value to one of the identified entities in the document, by: applying a filter to a sequence of the sentiment values corresponding to a sequence of the tokens in the order the tokens appear in the document, the filter having a width defined by a number of tokens, the entity having a position in the sequence of tokens, the filter providing a combination of contributions of the sentiment values associated with the tokens surrounding the position of the entity in the document within the width of the filter. 7. The computer-implemented process of claim 1 , further comprising: receiving, in the computer memory, data defining a sentiment model; processing the data in the computer memory with a processor to assign a sentiment value to each phrase in the document according to the sentiment model.