9. A method implemented on a computer comprising a processor, and for performing actions on a multi-term text unit based on a derived semantic attribute or attribute value, the method comprising: receiving a text content comprising multiple text units, each text unit comprising at least a portion of a phrase or a sentence consisting of multiple terms, each term comprising a word or a phrase in a language; identifying, in the text content, a text unit, wherein the text unit comprises a first term and a second term; obtaining a derived semantic attribute or attribute value for the text unit as a whole based on the first term and the second term, wherein an example of the derived semantic attribute or attribute value comprises at least a positive or negative sentiment or opinion value; and performing an action on the text unit based on the derived semantic attribute or attribute value, wherein the action includes extracting the text unit for display or storage, marking the text unit for display in a format that is different from the display format of the text elements adjacent to the text unit in the text content, or displaying the text unit in a format that is different from the display format of the text elements adjacent to the text unit in the text content; wherein the steps for obtaining the derived semantic attribute or attribute value for the text unit as a whole include the following: identifying a first semantic attribute and a second semantic attribute, wherein the embodiments of the first semantic attribute and the second semantic attribute include an attribute name or description, a meaning carried by one or more terms in the language, an attribute type or attribute value, wherein neither the first semantic attribute nor the second semantic attribute refers to a positive or negative sentiment or opinion value; identifying the first term in the text unit, wherein the first term is associated with the first semantic attribute, or is associated with a label indicating the first semantic attribute, or is a member of a first group of terms in which at least some of the terms are associated with the first semantic attribute; identifying the second term in the text unit, wherein the second term is associated with the second semantic attribute, or is associated with a label indicating the second semantic attribute, or is a member of a second group of terms in which at least some of the terms are associated with the second semantic attribute; determining the derived semantic attribute or attribute value for the text unit as a whole based on the first term and the second term, and the first semantic attribute and the second semantic attribute.
9. A method implemented on a computer comprising a processor, and for performing actions on a multi-term text unit based on a derived semantic attribute or attribute value, the method comprising: receiving a text content comprising multiple text units, each text unit comprising at least a portion of a phrase or a sentence consisting of multiple terms, each term comprising a word or a phrase in a language; identifying, in the text content, a text unit, wherein the text unit comprises a first term and a second term; obtaining a derived semantic attribute or attribute value for the text unit as a whole based on the first term and the second term, wherein an example of the derived semantic attribute or attribute value comprises at least a positive or negative sentiment or opinion value; and performing an action on the text unit based on the derived semantic attribute or attribute value, wherein the action includes extracting the text unit for display or storage, marking the text unit for display in a format that is different from the display format of the text elements adjacent to the text unit in the text content, or displaying the text unit in a format that is different from the display format of the text elements adjacent to the text unit in the text content; wherein the steps for obtaining the derived semantic attribute or attribute value for the text unit as a whole include the following: identifying a first semantic attribute and a second semantic attribute, wherein the embodiments of the first semantic attribute and the second semantic attribute include an attribute name or description, a meaning carried by one or more terms in the language, an attribute type or attribute value, wherein neither the first semantic attribute nor the second semantic attribute refers to a positive or negative sentiment or opinion value; identifying the first term in the text unit, wherein the first term is associated with the first semantic attribute, or is associated with a label indicating the first semantic attribute, or is a member of a first group of terms in which at least some of the terms are associated with the first semantic attribute; identifying the second term in the text unit, wherein the second term is associated with the second semantic attribute, or is associated with a label indicating the second semantic attribute, or is a member of a second group of terms in which at least some of the terms are associated with the second semantic attribute; determining the derived semantic attribute or attribute value for the text unit as a whole based on the first term and the second term, and the first semantic attribute and the second semantic attribute. 12. The method of claim 9 , further comprising: identifying a grammatical attribute associated with the first term or with the second term, wherein the grammatical attribute includes at least the grammatical roles of a subject, an object, a head, a modifier, and parts of speech of a noun, a verb, a preposition, an adjective, and adverb, wherein the derived semantic attribute or attribute value is determined based on the grammatical attribute.