DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-21 are rejected under 35 U.S.C. 101 because the claims are directed toward an abstract idea without significantly more.
Claim 1, is rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (an abstract idea) and does not include additional elements that amount significantly more than the judicial exception.
Step 1
Claim 1 is directed toward a “method”, thus falls within a statutory category under the most recent guidelines of 35 U.S.C. 101.
Step 2A, Prong 1
Claim 1 recites steps for “accessing digitally stored corpus data and tokenizing the corpus data into sequences of tokens”; “based on matching the sequences of tokens to a digitally stored part-of-speech (POS) dictionary, generating a plurality of POS sequences; accessing a first treebank data set and storing a plurality of parses from the first treebank data set in a tree data structure in a memory of the computer system”; and “for each POS sequence of the plurality of POS sequences: using the tree data structure, identifying one or more candidate parses that match that POS sequence”; “based on a digitally stored lexical database, selecting a sentence corresponding to one candidate parse of the one or more candidate parses that is most semantically similar to that POS sequence”; “substituting, in the one candidate parse, words from that POS sequence, to form an updated parse”; and “digitally storing the updated parse in a second treebank data set.” These limitations collectively recite the collection, evaluation and translation of information, including language evaluation and translation. As characterized by the USPTO guidance and case law, such activities fall within the abstract-idea groupings of mental processes (e.g. observations, evaluations, and judgments that could be performed in the human mind or with pen and paper) and organizing /transmitting information. Reference can be made to latest patent eligibility guidelines. Accordingly, claim 1 recites an abstract idea.
Step 2A, Prong 2
The claim is implemented on a “a computer-implemented method executed using one or more processors of a computer system”. These are generic computer components performing their well-understood, routine, and conventional functions of storing and executing instructions, receiving requests, and sending content.
The claim does not recite any specific improvement to computer functionality (e.g., a particular translation algorithm, model architecture, data structure, memory organization, caching mechanism, latency-reduction technique, or network protocol that improves the operation of the computer or network). Nor does it effect a transformation of a physical article or use the abstract idea in any other manner that imposes a meaningful limit on the claim’s scope. Therefore, the claim does not integrate the abstract idea into a practical application under Step 2A, Prong 2.
Step 2B
Beyond the abstract idea, the additional elements are the generic “computer system,” and “one or more processors,” performing their conventional functions. Implementing the abstract idea on generic computer components does not amount to significantly more. Alice, 573 U.S. at 223–24).
The ordered combination of limitations mirrors the abstract idea itself performed using routine computer operations. There is no recited unconventional hardware, no technical improvement to the functioning of the computer itself, and no nonconventional arrangement of known components etc.
Accordingly, claim 1 does not include an “inventive concept” sufficient to transform the abstract idea into a patent-eligible application.
Therefore , claim 1 is directed to an abstract idea and does not recite additional elements that integrate the exception into a practical application or amount to significantly more than the exception itself. Claim 1 is therefore rejected under 35 U.S.C. § 101. Dependent claims 2-7 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea.
The Independent claim 15 is directed toward a computer system that recite(s) the instructions for “accessing digitally stored corpus data and tokenizing the corpus data into sequences of tokens”; “based on matching the sequences of tokens to a digitally stored part-of-speech (POS) dictionary, generating a plurality of POS sequences; accessing a first treebank data set and storing a plurality of parses from the first treebank data set in a tree data structure in a memory of the computer system”; and “for each POS sequence of the plurality of POS sequences: using the tree data structure, identifying one or more candidate parses that match that POS sequence”; “based on a digitally stored lexical database, selecting a sentence corresponding to one candidate parse of the one or more candidate parses that is most semantically similar to that POS sequence”; “substituting, in the one candidate parse, words from that POS sequence, to form an updated parse”; and “digitally storing the updated parse in a second treebank data set.” All the steps can be performed by a human being using pen and paper. These limitations collectively recite the collection, evaluation of information, including language evaluation. As characterized by the USPTO guidance and case law, such activities fall within the abstract-idea groupings of mental processes (e.g. observations, evaluations, and judgments that could be performed in the human mind or with pen and paper) and organizing /transmitting information. Reference can be made to latest patent eligibility guidelines. Accordingly, claim 15 recites an abstract idea.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. With respect to integration of the abstract idea into a practical application, the additional element of using a generic computing device the determining and data gathering steps amount to no more than mere instructions to apply the exception using a generic computer. The current specification on paragraph 0058, clearly specifies that “… a computing device 102 is communicatively coupled via a network 120 to a text and image processor 140. In one embodiment, computing device 102 may include a client-type computing device such as a personal computer, laptop, tablet, smartphone, or notebook computer. For purposes of illustrating a clear example, a single computing device 102, network 120, and text and image processor 140 are shown in FIG. 1, but practical embodiments may include thousands to millions of computing devices 102 distributed over a wide geographic area or over the globe, and hundreds to thousands of instances of text and image processor 140 to serve requests and computing requirements of the computing devices.”, and at paragraph 0105, “ Computer system 400 further includes non-volatile memory such as read-only memory (ROM) 308 or other static storage devices coupled to I/O subsystem 402 for storing information and instructions for processor 404. The ROM 408 may include various forms of programmable ROM (PROM), such as erasable PROM (EPROM) or electrically erasable PROM (EEPROM). A unit of persistent storage 410 may include various forms of non-volatile RAM (NVRAM), such as FLASH memory, solid-state storage, magnetic disk, or optical disks such as CD-ROM or DVD-ROM and may be coupled to I/O subsystem 402 for storing information and instructions. Storage 410 is an example of a non-transitory computer-readable medium that may be used to store instructions and data, which, when executed by the processor 404, causes performing computer-implemented methods to execute the techniques herein.” The additional elements have been considered both individually and as an ordered combination in the significantly more consideration. The inclusion of the computer or memory and controller to perform the selecting and generating steps amount to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using a generic computing device cannot provide an inventive concept. Therefore, claim 15 as drafted is not patent eligible. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea.
Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation. Independent claim 15 is therefore not drawn to eligible subject matter as they are directed to an abstract idea without significantly more. Claims 16-21 are dependent claims and do not contain subject matter that can be overcome the rejection of independent claim 15.
Claims 8-14 are directed toward a non-transitory computer readable medium with instructions to implement the method of claims 1-7 and are rejected under similar rationale.
All dependent claims when analyzed as a whole are held to be patent ineligible under 35 U.S.C. §101 because any additional recited limitations fail to establish that the claims are not directed to an abstract idea for the same reasons already recited for the independent claims.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-21 are rejected under 35 U.S.C. 102(a1) as being anticipated by Parng et al., (US 2020/0097549 A1).
As per claims 1, 8 and 15, Parng et al., teach a computer-implemented method/a non-transitory computer readable medium with instruction to implement the method/system, executed using one or more processors of a computer system, the computer-implemented method comprising:
accessing digitally stored corpus data and tokenizing the corpus data into sequences of tokens (0026);
based on matching the sequences of tokens to a digitally stored part-of-speech (POS) dictionary, generating a plurality of POS sequences (0026);
accessing a first treebank data set and storing a plurality of parses from the first treebank data set in a tree data structure in a memory of the computer system (0023); and
for each POS sequence of the plurality of POS sequences: using the tree data structure, identifying one or more candidate parses that match that POS sequence (0037, 0061-0063);
based on a digitally stored lexical database, selecting a sentence corresponding to one candidate parse of the one or more candidate parses that is most semantically similar to that POS sequence (0061-0063);
substituting, in the one candidate parse, words from that POS sequence, to form an updated parses (0043); and
digitally storing the updated parse in a second treebank data set (0037, 0043).
As per claims 2, 9 and 16, Parng et al., teach the computer-implemented method/a non-transitory computer readable medium with instruction to implement the method/system, claims 1, 8 and 15, further comprising, after accessing the digitally stored corpus data and tokenizing the corpus data into sequences of tokens, storing the sequences of tokens in persistent data storage as processed corpus data (0026, 0037).
As per claims 3, 10 and 17, Parng et al., teach the computer-implemented method/a non-transitory computer readable medium with instruction to implement the method/system, claims 1, 8 and 15, wherein the corpus data comprises a large-scale set of digitally stored natural language text organized at least in part in a plurality of sentences (0043).
As per claims 4, 11 and 18, Parng et al., teach the computer-implemented method/a non-transitory computer readable medium with instruction to implement the method/system, claims 1, 8 and 15, further comprising storing and managing during execution of the computer-implemented method, in the memory of the one or more computing devices, all of the sequences of tokens, possible POS sequences, candidate parses, and the updated parse (0043).
As per claims 5, 12 and 19, Parng et al., teach the computer-implemented method/a non-transitory computer readable medium with instruction to implement the method/system, claims 1, 8 and 15, further comprising training a constituency parser using the second treebank data set (0051).
As per claims 6, 13 and 20, Parng et al., teach the computer-implemented method/a non-transitory computer readable medium with instruction to implement the method/system, claims 1, 8 and 15, wherein the digitally stored corpus data comprises greater than 100,000 sentences (0043 – 0045).
As per claims 7, 14 and 21, Parng et al., teach the computer-implemented method/a non-transitory computer readable medium with instruction to implement the method/system, claims 1, 8 and 15, wherein the digitally stored corpus data comprises WIKIPEDIA and the digitally stored lexical database comprises WORDNET (0043-0045).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Please see attached form PTO-892.
The following is related closest prior art.
Boxwell et al., (US 2021/0209163 A1) disclose a method, apparatus and computer program product for creating parse trees from mixed records. A mixed record is received including a first entry containing a first natural language phrase and a second entry containing a first structured data entry. Using the first natural language phrase, a first parse tree structure is created joining words in the first natural language phrase with natural links indicating their semantic relationship within the first natural language phrase. A first synthetic node is created which represents the first structured data entry. The first synthetic is joined to the first parse tree structure using a synthetic link to a node in the parse tree to produce a pseudo parse tree. The pseudo parse tree is sent to a question answer system for answering user queries by reference to the pseudo parse tree.
Popescu et al., (US 2019/0354590 A1) teach corpus pattern paraphrasing method, system, and non-transitory computer readable medium, include aligning slots of patterns for verbal phrases based on syntactical and lexical features along with calculated synonyms to predict paraphrases that are not previously stored in a corpus of sentences in a database.
Hopkins et al., (US 2016/0259851 A1) teach Systems, apparatuses, and methods for generating a parser training set and ultimately a correct treebank for a corpus of text, based on using an existing parser that was trained on a different corpus. Also disclosed are systems, apparatuses, and methods for improving the operation of a parser in the case of using a less familiar set of training data than is typically used to train conventional parsers. This can be used to generate a more effective and accurate parser for a new corpus (and hence more accurate parse trees) with significantly less effort than would be required if it was necessary to generate a standard size training set.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to VIJAY B CHAWAN whose telephone number is (571)272-7601. The examiner can normally be reached 7-5 Monday thru Thursday.
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/VIJAY B CHAWAN/Primary Examiner, Art Unit 2658