# US 2013/0158979 A1 · System and Method for Identifying Phrases in Text > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2013/0158979 A1 - Document ID: US20130158979A1 - Status: Published application - Kind: A1 - Application number: 13/326,120 - Filed: 2011-12-14 - Published: 2013-06-20 - Earliest claimed: 2011-12-14 - Assignees: PureDiscovery Corporation - Inventors: Paul A. Jakubik - Web page: https://patentgrep.com/patent/US20130158979A1 ## CPC - G06F 40/40: Processing or translation of natural language (natural language analysis G06F40/20; semantic analysis G06F40/30) - G06F 40/211: Syntactic parsing, e.g. based on context-free grammar [CFG] or unification grammars - G06F 40/295: Named entity recognition - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract A method includes accessing text that includes a plurality of words, tagging each of the plurality of words with one of a plurality of parts of speech (POS) tags, and creating a plurality of tokens, each token comprising one of the plurality of words and its associated POS tag. The method further includes clustering one or more of the created tokens into a chunk of tokens, the one or more tokens clustered into the chunk of tokens based on the POS tags of the one or more tokens, and forming a phrase based on the chunk of tokens, the phrase comprising the words of the one or more tokens clustered into the chunk of tokens. ## Claims ### Claim 1 A system, comprising: one or more memory units; and one or more processing units operable to: access text comprising a plurality of words; tag each of the plurality of words with one of a plurality of parts of speech (POS) tags; create a plurality of tokens, each token comprising one of the plurality of words and its associated POS tag; cluster one or more of the created tokens into a chunk of tokens, the one or more tokens clustered into the chunk of tokens based on the POS tags of the one or more tokens; and form a phrase based on the chunk of tokens, the phrase comprising the words of the one or more tokens clustered into the chunk of tokens. ### Claim 2 (depends on 1) The system of claim 1, wherein the plurality of POS tags comprises: a POS tag for a proper noun that is a geographic name; a POS tag for a proper noun that is a name of a person; and a POS tag for a proper noun that is can be both a geographic name and a name of a person. ### Claim 3 (depends on 1) The system of claim 1, wherein tagging each of the plurality of words with one of the plurality of POS tags comprises utilizing a lexical analyzer to determine whether each of the plurality of words is certain type of entity, the certain type of entity chose from a plurality of entities comprising: an acronym; a plurality of initials; a uniform resource locator (URL); and an email address. ### Claim 4 (depends on 1) The system of claim 1, wherein tagging each of the plurality of words with one of the plurality of POS tags comprises searching a lexicon for each of the plurality of words, the lexicon mapping a known set of words to POS tags. ### Claim 5 (depends on 1) The system of claim 1, wherein tagging each of the plurality of words with one of the plurality of POS tags comprises applying a set of heuristics. ### Claim 6 (depends on 1) The system of claim 1, the one or more processing units further operable to provide a count of the number of the words in the text, the count based on the plurality of created tokens. ### Claim 7 (depends on 1) The system of claim 1, wherein clustering one or more of the created tokens into the chunk of tokens comprises clustering tokens having the same POS tags into the chunk of tokens. ### Claim 8 A computer-implemented method, comprising: accessing text by a processing system, the text comprising a plurality of words; tagging, by the processing system, each of the plurality of words with one of a plurality of parts of speech (POS) tags; creating, by the processing system, a plurality of tokens, each token comprising one of the plurality of words and its associated POS tag; clustering, by the processing system, one or more of the created tokens into a chunk of tokens, the one or more tokens clustered into the chunk of tokens based on the POS tags of the one or more tokens; and forming, by the processing system, a phrase based on the chunk of tokens, the phrase comprising the words of the one or more tokens clustered into the chunk of tokens. ### Claim 9 (depends on 8) The computer-implemented method of claim 8, wherein the plurality of POS tags comprises: a POS tag for a proper noun that is a geographic name; a POS tag for a proper noun that is a name of a person; and a POS tag for a proper noun that is can be both a geographic name and a name of a person. ### Claim 10 (depends on 8) The computer-implemented method of claim 8, wherein tagging each of the plurality of words with one of the plurality of POS tags comprises utilizing a lexical analyzer to determine whether each of the plurality of words is certain type of entity, the certain type of entity chose from a plurality of entities comprising: an acronym; a plurality of initials; a uniform resource locator (URL); and an email address. ### Claim 11 (depends on 8) The computer-implemented method of claim 8, wherein tagging each of the plurality of words with one of the plurality of POS tags comprises searching a lexicon for each of the plurality of words, the lexicon mapping a known set of words to POS tags. ### Claim 12 (depends on 8) The computer-implemented method of claim 8, wherein tagging each of the plurality of words with one of the plurality of POS tags comprises applying a set of heuristics. ### Claim 13 (depends on 8) The computer-implemented method of claim 8, further comprising providing a count of the number of the words in the text, the count based on the plurality of created tokens. ### Claim 14 (depends on 8) The computer-implemented method of claim 8, wherein clustering one or more of the created tokens into the chunk of tokens comprises clustering tokens having the same POS tags into the chunk of tokens. ### Claim 15 A non-transitory computer-readable medium comprising software, the software when executed by one or more processing units operable to perform operations comprising: accessing text comprising a plurality of words; tagging each of the plurality of words with one of a plurality of parts of speech (POS) tags; creating a plurality of tokens, each token comprising one of the plurality of words and its associated POS tag; clustering one or more of the created tokens into a chunk of tokens, the one or more tokens clustered into the chunk of tokens based on the POS tags of the one or more tokens; and forming a phrase based on the chunk of tokens, the phrase comprising the words of the one or more tokens clustered into the chunk of tokens. ### Claim 16 (depends on 15) The non-transitory computer-readable medium of claim 15, wherein the plurality of POS tags comprises: a POS tag for a proper noun that is a geographic name; a POS tag for a proper noun that is a name of a person; and a POS tag for a proper noun that is can be both a geographic name and a name of a person. ### Claim 17 (depends on 15) The non-transitory computer-readable medium of claim 15, wherein tagging each of the plurality of words with one of the plurality of POS tags comprises searching a lexicon for each of the plurality of words, the lexicon mapping a known set of words to POS tags. ### Claim 18 (depends on 15) The non-transitory computer-readable medium of claim 15, wherein tagging each of the plurality of words with one of the plurality of POS tags comprises applying a set of heuristics. ### Claim 19 (depends on 15) The non-transitory computer-readable medium of claim 15, further comprising providing a count of the number of the words in the text, the count based on the plurality of created tokens. ### Claim 20 (depends on 15) The non-transitory computer-readable medium of claim 15, wherein clustering one or more of the created tokens into the chunk of tokens comprises clustering tokens having the same POS tags into the chunk of tokens.