Based on this training corpus, we can construct a tagger that can be used to label new sentences; and use the nltk.chunk.conlltags2tree() function to convert the tag sequences into a chunk tree.
NLTK provides a classifier that has already been trained to recognize named entities, accessed with the function nltk.ne_chunk() . If we set the parameter binary=Correct , then named entities are just tagged as NE ; otherwise, the classifier adds category labels such as PERSON, ORGANIZATION, and GPE.
seven.6 Relatives Removal
Once named entities have been identified in a text, we then want to extract the relations that exist between them. As indicated earlier, we will typically be looking for relations between specified types of named entity. One way of approaching this task is to initially look for all triples of the form (X, ?, Y), where X and Y are named entities of the required types, and ?
