The present teaching relates to entity linking. In one example, a text string is received. The text string is segmented to obtain a segmentation with a set of one or more segments of the text string. A set of entities are identified, with respect to the one or more segments, from a plurality of entities as linked to the one or more segments. The identifying is in accordance with a probabilistic model based on surface form information associated with the plurality of entities.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method, implemented on a computing device having at least one processor, storage, and a communication platform capable of connecting to a network for entity linking, comprising: receiving a text string; segmenting the text string to obtain a first set of one or more segments of the text string; and identifying, with respect to the first set of the one or more segments, a first set of entities from a plurality of entities as linked to the first set of the one or more segments in accordance with a probabilistic model based at least partially on previously submitted text strings associated with the plurality of entities. 2. The method of claim 1, wherein the identifying the first set of entities from the plurality of entities as linked to the first set of the one or more segments in accordance with the probabilistic model based at least partially on the previously submitted text strings associated with the plurality of entities comprises identifying the first set of entities from the plurality of entities as linked to the first set of the one or more segments in accordance with the probabilistic model based on an anchor text representing a link to a web page associated with an entity. 3. The method of claim 1, wherein the step of identifying comprises: computing, for each of the one or more segments and with respect to each of the plurality of entities, a probabilistic score P(e|s) for the segment based at least partially on one of the previously submitted text strings associated with the entity, wherein the probabilistic score P(e|s) is indicative of a likelihood that entity e is a linked entity given segment s. 4. The method of claim 3, further comprising: segmenting the text string to obtain a second set of one or more segments; identifying, with respect to the second set of one or more segments, a second set of entities from the plurality of entities as linked to the second set of one or more segments, in accordance with the probabilistic model based at least partially on the previously submitted text strings associated with the plurality of entities; and determining a set of linked entities based on the first set of entities and the second set of entities. 5. The method of claim 4, wherein the set of linked entities are determined by: maximizing aggregated probabilistic scores associated with one of the first set of the one or more segments and the second set of the one or more segments; or maximizing one of the probabilistic scores associated with one of the first set of the one or more segments and the second set of the one or more segments. 6. The method of claim 1, wherein the identifying is based, at least in part, on context of the text string. 7. The method of claim 6, wherein the probabilistic model includes a contextual relevance model based on which a context sensitive probabilistic score is computed for each entity; and the context sensitive probabilistic score is indicative of a likelihood that the entity is linked to a segment given the context of the text string. 8. The method of claim 7, wherein the context sensitive probabilistic score is determined based on a similarity between a first vector representing content associated with the entity and a second vector representing the context of the text string. 9. The method of claim 8, wherein the first vector is determined based on the content of a web page associated with the entity. 10. The method of claim 1, further comprising: determining, based on the identified linked entities, content sources where content related to the text string can be retrieved. 11. A method, implemented on a computing device having at least one processor, storage, and a communication platform capable of connecting to a network for providing search results, comprising: receiving a query; segmenting the query into one or more segments each of which includes at least some text; determining, with respect to the one or more segments, a set of entities from a plurality of entities as linked to the one or more segments in accordance with a probabilistic model based at least partially on previously submitted text strings associated with the plurality of entities; identifying content sources associated with the set of entities linked to the one or more segments; identifying search results from the content sources based on the query; and providing the search results as a response to the query. 12. A system for entity linking, comprising: a segmenting module configured to segment a text string to obtain a first set of one or more segments of the text string; and an entity identifying module coupled with the segmenting module and configured to identify, with respect to the first set of the one or more segments, a first set of entities from a plurality of entities as linked to the first set of the one or more segments in accordance with a probabilistic model based at least partially on previously submitted text strings associated with the plurality of entities. 13. The system of claim 12, wherein the identifying the first set of entities from the plurality of entities as linked to the first set of the one or more segments in accordance with the probabilistic model based at least partially on the previously submitted text strings associated with the plurality of entities comprises identifying the first set of entities from the plurality of entities as linked to the first set of the one or more segments in accordance with the probabilistic model based on an anchor text representing a link to a web page associated with an entity. 14. The system of claim 12, wherein the entity identifying module comprises: a probabilistic score calculator configured to compute, for each of the one or more segments and with respect to each of the plurality of entities, a probabilistic score P(e|s) for the segment based at least partially on one of the previously submitted text strings associated with the entity, wherein the probabilistic score P(e|s) is indicative of a likelihood that entity e is a linked entity given segment s. 15. The system of claim 14, wherein the segmenting module is further configured to segment the text string to obtain a second set of one or more segments; and the entity identifying module is further configured to identify, with respect to the second set of one or more segments, a second set of entities from the plurality of entities as linked to the second set of one or more segments, in accordance with the probabilistic model based at least partially on the previously submitted text strings associated with the plurality of entities, and determine a set of linked entities based on the first set of entities and the second set of entities. 16. The system of claim 15, wherein the entity identifying module comprises an entity selector configured to: maximize aggregated probabilistic scores associated with one of the first set of the one or more segments and the second set of the one or more segments; or maximize one of the probabilistic scores associated with one of the first set of the one or more segments and the second set of the one or more segments. 17. The system of claim 12, wherein the identifying is based, at least in part, on context of the text string. 18. The system of claim 17, wherein the probabilistic model includes a contextual relevance model based on which a context sensitive probabilistic score is computed for each entity; and the context sensitive probabilistic score is indicative of a likelihood that the entity is linked to a segment given the context of the text string. 19. The system of claim 18, wherein the context sensitive probabilistic score is determined based on a similarity between a first vector representing content associated with the entity and a second vector representing the context of the text string. 20. The system of claim 19, wherein the first vector is determined based on the content of a web page associated with the entity. 21. A machine-readable, non-transitory and tangible medium having data recorded thereon for entity linking, the medium, when read by the machine, causes the machine to perform the following steps: receiving a text string; segmenting the text string to obtain first set of one or more segments of the text string; and identifying, with respect to the first set of the one or more segments, a first set of entities from a plurality of entities as linked to the first set of the one or more segments in accordance with a probabilistic model based at least partially on previously submitted text strings associated with the plurality of entities. 22. The medium of claim 21, wherein the steps further comprise: segmenting the text string to obtain a second set of one or more segments; identifying, with respect to the second set of one or more segments, a second set of entities from the plurality of entities as linked to the second set of one or more segments, in accordance with the probabilistic model based at least partially on the previously submitted text strings associated with the plurality of entities; and determining a selected set of linked entities based on the first set of entities and the second set of entities.