# US 2014/0156264 A1 · Open language learning for information extraction

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- Number: US 2014/0156264 A1
- Document ID: US20140156264A1
- Status: Published application
- Kind: A1
- Application number: 14/083,261
- Filed: 2013-11-18
- Published: 2014-06-05
- Earliest claimed: 2012-11-19
- Applicants: University of Washington through it Center for Commercialization
- Inventors: Oren Etzioni; Robert E. Bart; Mausam; Michael D. Schmitz; Stephen G. Doderland
- Web page: https://patentgrep.com/patent/US20140156264A1

## CPC

- G06F 40/211: Syntactic parsing, e.g. based on context-free grammar [CFG] or unification grammars
- G06F 40/205: Parsing
- G06F 40/289: Phrasal analysis, e.g. finite state techniques or chunking
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)

## Abstract

A system for extracting relational tuples from sentences is provided. The system includes a bootstrapper, an open pattern learner, and a pattern matcher. The bootstrapper 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. The open pattern learner learns, from the seed tuples and sentence pairs, open patterns that encode ways in which relational tuples may be expressed in a sentence, The pattern matcher 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.

## Claims

### Claim 1

A method for learning open patterns within a corpus of text, the method comprising:
providing seed tuples and associated sentences, the seed tuples having arguments and relations, each argument and relation having one or more words;
for each seed tuple and associated sentence,
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, the dependency path having a relation node; and
annotating the relation node with the word of the relation and a part-of-speech constraint; and
replacing the relation word of the seed tuple with a relation symbol to create an extraction template;
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,
collecting candidate patterns based on syntactic restrictions on the relation word; and
converting lexical constraints of the collected candidate patterns into a list of words of sentences with the candidate pattern to generate an open pattern.

### Claim 2 (depends on 1)

The method of claim 1 wherein the creating of an extraction template includes normalizing verbs to “be”.

### Claim 3 (depends on 1)

The method of claim 1 when a candidate pattern is not a syntactic pattern, generalizing the list of word to other similar words.

### Claim 4 (depends on 1)

The method of claim 1 including sorting the open patterns based on frequency of occurrence in the sentences and matching the open patterns as sorted to a sentence.

### Claim 5 (depends on 1)

The method of claim 1 including extracting a relational tuple from a sentence by:
matching an open pattern with a dependency parse of a sentence;
identifying base nodes of the dependency parse for the arguments and the relation of the extraction template of the matching open pattern; and
expanding the arguments and the relation to include information relevant to the extraction to form the relational tuple based on the extraction template.

### Claim 6 (depends on 5)

The method of claim 5 including performing context analysis to handle extractions that are not asserted as factual in a sentence.

### Claim 7 (depends on 6)

The method of claim 6 wherein performing context analysis includes adding an attribution field to the relational tuple to indicate who is asserting the relation.

### Claim 8 (depends on 6)

The method of claim 6 wherein performing context analysis includes adding a clausal modifier field to the relational tuple when truth of the relation is conditional.

### Claim 9

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.

### Claim 10 (depends on 9)

The system of claim 9 wherein open pattern learner creates a candidate pattern by:
for each seed tuple and sentence pair,
extracting a dependency path of the sentence connecting the words of the arguments and the relation of the seed tuple, the dependency path having a relation node; and
annotating the relation node 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,
collecting candidate patterns based on syntactic restrictions on the relation word; and
converting lexical constraints of the collected candidate patterns into a list of words of sentences with the candidate pattern to generate an open pattern.

### Claim 11 (depends on 10)

The system of claim 10 wherein the open pattern learner further replaces the relation word of the seed tuple with a relation symbol to create an extraction template.

### Claim 12 (depends on 11)

The system of claim 11 wherein the open pattern learner further normalize verbs to “be” in an extraction template.

### Claim 13 (depends on 9)

The system of claim 9 including a context analyzer that adds an attribution field to the relational tuple to indicate who is asserting the relation and adds a clausal modifier field to the relational tuple when truth of the relation is conditional.

### Claim 14

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.

### Claim 15 (depends on 14)

The method of claim 14 including extracting a relational tuple from a sentence by:
matching an open pattern with a dependency parse of a sentence;
identifying base nodes of the dependency parse for the arguments and the relation of the extraction template of the matching open pattern; and
expanding the arguments and the relation to include information relevant to the extraction to form the relational tuple based on the extraction template.

### Claim 16 (depends on 15)

The method of claim 15 including performing context analysis to handle extractions that are not asserted as factual in a sentence.

### Claim 17 (depends on 16)

The method of claim 16 wherein performing context analysis includes adding an attribution field to the relational tuple to indicate who is asserting the relation.

### Claim 18 (depends on 16)

The method of claim 16 wherein performing context analysis includes adding a clausal modifier field to the relational tuple when truth of the relation is conditional.

### Claim 19 (depends on 14)

The method of claim 14 including replacing the relation word of the seed tuple with a relation symbol to create an extraction template.

### Claim 20 (depends on 19)

The method of claim 19 including normalizing verbs to “be” in an extraction template.