Open language learning for information extraction

A system for extracting relational tuples from sentences, the relational tuples having arguments and relations, the system comprising:

• a bootstrapper that generates training data by, for each of a plurality of seed tuples, identifying sentences of a corpus that contains the words of the seed tuple such that the seed tuple and an identified sentence form a seed tuple and sentence pair;
• an open pattern learner that learns, from the seed tuples and sentence pairs, open patterns that encode ways in which relational tuples may be expressed in a sentence;
• and
• a pattern matcher that matches the open patterns to a dependency parse of a sentence, identifies base nodes of the dependency parse for the arguments and relation for the relational tuple that the open pattern encodes, and expands the arguments and relation of the relational tuple.

A method for learning open patterns within a corpus of text, the method comprising:

• for seed tuple and sentence pairs, creating a candidate pattern by:
• extracting a dependency path of the sentence connecting the words of the arguments and the relation of the seed tuple;
• and
• annotating dependency path with the word of the relation and a part-of-speech constraint;
• and
• when a candidate pattern is a syntactic pattern, generalizing the candidate pattern to unseen relations and preposition to generate an open pattern;
• and
• when a candidate pattern is not a syntactic pattern, converting lexical constraints of the candidate patterns with similar syntactic restrictions on the relation word into a list of words of sentences with the candidate pattern to generate an open pattern.