DETAILED ACTION
This communication is in response to the Application filed on 28 January 2025. Claims 1-20 are pending and have been examined.
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 .
Priority
Applicant claims the benefit of US Provisional Application No. 63/734,885, filed 17 December 2024. Claims 1-20 have been afforded the benefit of this filing date.
Information Disclosure Statement
The IDS dated 28 January 2025 has been considered and placed in the application file.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. All of the claims are method claims (1-10), apparatus/machine claims (11-20) or manufacture claim under (Step 1), but under Step 2A all of these claims recite abstract ideas and specifically mental processes. These mental processes are more particularly recited in claims 1, 11, and 20 as:
splitting, by a device, a payload of a prompt for input to a language model into partitions…
identifying, by the device and based on attributes of the partitions, candidate segments of the partitions for modification…
generating, by the device, modified segments of the partitions from a portion of the candidate segments of the partitions…
replacing, by the device, the prompt with a revised prompt for input to the language model that includes the modified segments of the partitions…
Under Step 2A Prong One, claims 1, 11, and 20 are directed to an abstract idea and specifically a mental process. As detailed above, the steps of splitting, identifying, generating, replacing, etc. may be practically performed in the human mind with the use of a physical aid such as a pen and paper. For example, a human could receive an incoming query, partition the query to create a plurality of subqueries, identify entities within each subquery, think of synonyms for each entity, and replace the entities of the incoming query with the synonyms to generate a revised query.
Under Step 2A Prong Two, this judicial exception is not integrated into a practical application because claims 1-20 do not recite additional elements that integrate the exception into a practical application. In particular, claims 1, 11, and 20 recite the additional elements of a device (pg. 4, Paragraph 2), a language model (pg. 9, Paragraphs 1-2), a network interface (pg. 6, Paragraph 1), a processor (pg. 6, Paragraph 2), and memory storing instructions (pg. 6, Paragraph 2). These additional elements are recited at a high level of generality and merely equate to “apply it” or otherwise merely uses a generic computer as a tool to perform an abstract which are not indicative of integration into a practical application as per MPEP 2106.05(f). Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Under Step 2B, the claims do not recite additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional elements of using a computer is noted as a general computer {device (pg. 4, Paragraph 2); network interface (pg. 6, Paragraph 1); processor (pg. 6, Paragraph 2); memory storing instructions (pg. 6, Paragraph 2)}. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claims are not patent eligible.
With respect to claims 2 and 12, the claim relates to replacing portions of a candidate segment with a label generated for that segment. This relates to a human replacing entities within a query with a label for the type of entity. No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to claims 3 and 13, the claim relates to identifying segments for modification using a tabular or object characterization. This relates to a human deciding which entities to replace using table of known entities. No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to claims 4-5 and 14-15, the claim relates to classifying a task based on the revised query. This relates to a human understanding the intent of the query based on the synonyms used to revise the query. No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to claims 6-8 and 16-18, the claim relates to identifying segments within a query as either code or language using a scoring system. This relates to a human labelling each entity within a query as either code or language with an associated confidence score for each. No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to claims 9 and 19, the claim relates to submitting the revised prompt and metadata to feature extraction for task classification. This relates to a human identifying task-related features within a revised prompt using additional information regarding the user who input the query. No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to claims 10, the claim relates to replacing portions of a candidate segment with a label generated for that segment. This relates to a human failing to understand the intent of the original query, performing entity synonym replacement, and then understanding the revised query. No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
For all of the above reasons, taken alone or in combination, claims 1-20 recite a non-statutory mental process.
Claim Rejections - 35 USC § 102
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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1, 3, 11, 13, and 20 are rejected under 35 U.S.C. 102(a)(1) and (a)(2) as being anticipated by US Patent Publication 20170097936 A1 (Glover).
Claim 1
Regarding claim 1, Glover discloses a method, comprising:
splitting, by a device, a payload of a prompt for input to a language model into partitions (Glover ¶ [0045], "The query understanding module 216 parses the search query 102 and identifies n-grams of terms in the query (e.g., single terms, bi-grams and tri-grams)." The contents of a search query is considered analogous to a payload of a prompt. Thus, n-grams of terms in the query are considered analogous to partitions of the payload. The prompt being for input to a language model is considered intended use);
identifying, by the device and based on attributes of the partitions, candidate segments of the partitions for modification (Glover ¶ [0045], "For each identified n-gram, the query understanding module 216 can search the 222 using the n-gram to identify any entities that are potentially contained in the search query 102. For instance, the query understanding module 216 may query the inverted index or lookup table using the n-gram to identify the entity records 242 that correspond thereto (e.g., contain a matching entity.");
generating, by the device, modified segments of the partitions from a portion of the candidate segments of the partitions (Glover ¶ [0060], "FIG. 2D illustrates an example query lookup table 252. A query lookup table 252 relates specific entities, ε, to a set of alternate search queries,
Q
. Put another way, an entity,
ε
i
, maps to a set of alternate search queries
Q
i
(
q
i
,
1
,
q
i
,
2
, ...,
q
i
,
n
), where
q
i
,
1
,
q
i
,
2
, ...,
q
i
,
n
are
n
alternate queries that can be used to identify search results that are sufficient replacements for search results directed to the entity,
ε
i
." Identifying similar entities is considered analogous to generating modified segments); and
replacing, by the device, the prompt with a revised prompt for input to the language model that includes the modified segments of the partitions (Glover ¶ [0060], "The query lookup table 252 can be queried using an entity (e.g., an entity ID 244 or an entity name 246 and an entity type 248) and the query lookup table 252 returns a corresponding set of alternate search queries
Q
." Alternate search queries are considered analogous to revised prompts. The revised prompt being for input to a language model is considered intended use).
Claim 3
Regarding claim 3, the rejection of claim 1 is incorporated.
Glover further discloses identifying, based on one or more of a tabular characterization or an object characterization indicating that a segment of a partition is a data segment, the segment of the partition as a candidate segment for modification (Glover ¶ [0044], "In some implementations, the entity data store 240 includes a lookup table that indicates a set of entity records 244 that correspond to a known entity name. The lookup table may operate in a manner similar to the inverted index. Namely, the lookup table may receive a text string and may output the entity IDs of the entities that share the same entity name").
Claim 11
Regarding claim 11, Glover discloses an apparatus, comprising:
one or more network interfaces to communicate with a network (Glover ¶ [0120], "The components of the system can be interconnected by any form or medium of digital data communication, e.g., a communication network. Examples of communication networks include a local area network (“LAN”) and a wide area network (“WAN”), an inter-network (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks).");
a processor coupled to the one or more network interfaces and configured to execute one or more processes (Glover ¶ [0117], "The processes and logic flows described in this specification can be performed by one or more programmable processors executing one or more computer programs to perform functions by operating on input data and generating output. "); and
a memory configured to store a process that is executable by the processor (Glover ¶ [0115], "subject matter described in this specification can be implemented as one or more computer program products, i.e., one or more modules of computer program instructions encoded on a computer readable medium for execution by, or to control the operation of data processing apparatus.")….
The remaining limitations of claim 11 are similar to that of claim 1 and therefore are rejected for similar reasons as described above.
Claim 13
Regarding claim 13, the rejection of claim 11 is incorporated. The limitations of claim 13 are similar in scope to that of claim 3 and therefore are rejected for similar reasons as described above.
Claim 20
Regarding claim 20, Glover discloses a tangible, non-transitory, computer-readable medium having computer-executable instructions stored thereon (Glover ¶ [0115], "subject matter described in this specification can be implemented as one or more computer program products, i.e., one or more modules of computer program instructions encoded on a computer readable medium for execution by, or to control the operation of data processing apparatus.")….
The remaining limitations of claim 20 are similar to that of claim 1 and therefore are rejected for similar reasons as described above.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 2 and 12 are rejected under 35 U.S.C. 103 as obvious over Glover as applied to claims 1 and 11 above, and further in view of US Patent Publication 20260099674 A1 (Domeniconi et al.).
Claim 2
Regarding claim 2, the rejection of claim 1 is incorporated.
Glover does not explicitly disclose all of replacing portions of a candidate segment with a label.
However, Domeniconi et al. disclose replacing a portion of a candidate segment with a label generated for the candidate segment (Domeniconi et al. ¶ [0070], "dataset generation process 200 involves a labeling operation 230 that performs identifying and labeling all the entity references present in new versions of the input samples with placeholders. ... In an example implementation of labeling operation 230, a second instance (or other) LLM identifies and labels all the entity references in the generated samples with placeholders such that labeled synthetic dataset
T
'
=
f
(
q
i
∈
Q
'
)
, where labeled synthetic dataset
T
'
represents the output, which is a labeled version of the rephrased samples." Entity references are considered analogous to candidate segments. Thus, replacing entity references with placeholder labels is considered analogous to replacing a portion of a candidate segment with a label generated for that segment).
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to modify Glover to incorporate Domeniconi et al.’s label replacements.
The suggestion/motivation for doing so would have been that, “The augmentation process described above provides a significant increase in the number of samples, which is directly related to the number of entities and associated values. … As a result, a labeled set is formed, which can be effectively utilized to train subsequent models,” as noted by the Domeniconi et al. disclosure in paragraph [0076].
Claim 12
Regarding claim 12, the rejection of claim 1 is incorporated. The limitations of claim 12 are similar in scope to that of claim 2 and therefore are rejected for similar reasons as described above.
Claims 4-5, 9-10, 14-15, and 19 are rejected under 35 U.S.C. 103 as obvious over Glover as applied to claims 1 and 11 above, and further in view of US Patent 12488184 B1 (Sun et al.).
Claim 4
Regarding claim 4, the rejection of claim 1 is incorporated.
Glover does not explicitly disclose all of classifying a task based on a revised prompt.
However, Sun et al. disclose classifying, based on the revised prompt including the modified segments of the partitions, tasks included in the payload of the prompt (Sun et al. ¶ (25), "The alternative input component 140 may determine an alternative input representation (e.g., a rephrased user input, a rewrite of the user input, etc.), for the user input, that results in a desired action being performed. For example, the user 105 may provide a user input “play [lyrics] by [artist name]” intending to request playback of a [song name] with the [lyrics] sung by the [artist name]. The NLU component 160 may be unable to identify the [song name] using the lyrics. The alternative input component 140 may determine an alternative input representation for the user input as “play [song name] by [artist name]”, which the NLU component 160 and the skill component 190 may use to identify and play the song desired by the user 105." Identifying an action associated with an alternative input is considered analogous to classifying tasks based on a revised prompt).
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to modify Glover’s query expansion method to include Sun et al.’s task classification because such a modification is the result of combining prior art elements according to known methods to yield predictable results. More specifically, Glover’s method as modified by Sun et al.’s task classification can yield a predictable result of widening system capabilities since the method would be able to detect the intended task of the query in addition to reformulating the query, thus enabling further downstream processing and actions such as performing the task. Thus, a person of ordinary skill would have appreciated including in Glover’s method the ability to do Sun et al.’s task classification since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Claim 5
Regarding claim 5, the rejection of claim 4 is incorporated.
Sun et al. further disclose wherein classifying the tasks included in the payload of the prompt includes identifying features of the prompt indicative of one or more of a task requested in the prompt (Sun et al. ¶ (96), "To perform IC processing, the NLU component 160 may communicate with a database of words linked to intents. For example, a music intent database may link words and phrases such as “quiet,” “volume off,” and “mute” to a <Mute> intent. "), a constraint applicable to completing the task, data needed to complete the task, or an output of the task.
Claim 9
Regarding claim 9, the rejection of claim 1 is incorporated.
Glover does not explicitly disclose all of submitting a revised prompt and metadata to a feature extraction component to identify tasks.
However, Sun et al. disclose submitting copies of the revised prompt and metadata associated with the modified segments of the partitions to feature extraction components configured to extract task identification features from the revised prompt (Sun et al. ¶ (38), "The alternative input component 140 may send (step 7) the alternative input representation(s) for the user input to the NLU component 160. … the alternative input representation may be used by the NLU component 160, like an ASR hypothesis, to determine an NLU hypothesis corresponding to the alternative input representation. In some embodiments, the alternative input component 140 may also send, to the NLU component 160, intent data, entity data or a NLU hypothesis (including intent data, entity data, and a NLU processing score previously determined by the NLU component for the alternative input representation with respect to processing of a previous user input) corresponding to the alternative input representation." ¶ (96), "The NLU component 160 may perform intent classification (IC) processing on the ASR output data or text data to determine an intent of the natural language input." Intent data, entity data, or NLU hypotheses are considered analogous to metadata).
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to modify Glover’s query expansion method to include Sun et al.’s metadata and task classification.
The suggestion/motivation for doing so is similar to the suggestion/motivation described above with respect to claim 4.
Claim 10
Regarding claim 10, the rejection of claim 1 is incorporated.
Glover does not explicitly disclose all of selecting portions for modification based on the portion being insignificant for determining a task.
However, Sun et al. disclose selecting the portion of the candidate segments of the partitions for which the modified segments of the partitions are generated based on the portion of the candidate segments of the partitions being insignificant for determining task classification features for tasks included in the payload of the prompt (Sun et al. ¶ (25), "the user 105 may provide a user input “play [lyrics] by [artist name]” intending to request playback of a [song name] with the [lyrics] sung by the [artist name]. The NLU component 160 may be unable to identify the [song name] using the lyrics. The alternative input component 140 may determine an alternative input representation for the user input as “play [song name] by [artist name]”, which the NLU component 160 and the skill component 190 may use to identify and play the song desired by the user 105." Being unable to identify a song name from lyrics is considered analogous to a portion being insignificant for determining task classification features. Thus, selecting the “[lyrics]” entity for replacement with “[song name]” is considered analogous to selecting a portion based on that portion being insignificant for determining task classification).
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to modify Glover’s query expansion method to include Sun et al.’s task classification.
The suggestion/motivation for doing so is similar to the suggestion/motivation described above with respect to claim 4.
Claim 14
Regarding claim 14, the rejection of claim 11 is incorporated. The limitations of claim 14 are similar in scope to that of claim 4 and therefore are rejected for similar reasons as described above.
Claim 15
Regarding claim 15, the rejection of claim 14 is incorporated. The limitations of claim 15 are similar in scope to that of claim 5 and therefore are rejected for similar reasons as described above.
Claim 19
Regarding claim 19, the rejection of claim 11 is incorporated. The limitations of claim 19 are similar in scope to that of claim 9 and therefore are rejected for similar reasons as described above.
Claims 6-8 and 16-18 are rejected under 35 U.S.C. 103 as obvious over Glover as applied to claims 1 and 11 above, and further in view of US Patent Publication 20220269706 A1 (Balasubramanian et al.).
Claim 6
Regarding claim 6, the rejection of claim 1 is incorporated.
Glover does not explicitly disclose all of identifying candidate segments as one or more of a code segment or a language segment.
However, Balasubramanian et al. disclose identifying, based on a characterization indicating that a segment of a partition is one or more of a code segment or a language segment (Balasubramanian et al. ¶ [0069], "In step 302, the search query is split into technology based entities, natural language based entities, and programming language based code entities." Both technology based entities and programming language based code entities are considered analogous to code segments. Natural language based entities are considered analogous to a language segment), whether the segment is a candidate segment for modification (Balasubramanian et al. ¶ [0069], "In step 304, the natural language entities are enhanced using machine learning techniques and their most critical phrases are marked for prioritization. In step 305, the code entities are enhanced." See Figure 3, which illustrates the separate processes for enhancing each of language segments and code segments).
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to modify Glover’s partition identification to incorporate Balasubramanian et al.’s code and language segment identification.
The suggestion/motivation for doing so would have been that, “there is a need for such a system and method that performs a search to find the right software components, thereby significantly reducing any delays in software development that may affect the quality and security of the process,” as noted by the Balasubramanian et al. disclosure in paragraph [0009].
Claim 7
Regarding claim 7, the rejection of claim 6 is incorporated.
Balasubramanian et al. further disclose wherein the characterization includes a language score (Balasubramanian et al. ¶ [0090], " in step 1001, for the sample search query “mongodb find by id operation”, the query type ranking weights are 0.8 for “nlp” and 0.6 for “keyword”." The score associated with the "article" intent is considered analogous to a language score) determined for each token within a ngram converted from a corresponding partition (Balasubramanian et al. ¶ [0074], "Step 601 creates three type of tokens; unigram, bigram and trigram. ... In step 602 a software technology dictionary built from software technology documents such as a readme file is used to identify the technology terms present in the tokens from step 601. For example, from the unigram tokens (“mongodb,” “find,” “id,” “operation”) “mongodb” is identified as technology term." It follows that unigram tokens corresponding to language ngrams would also be individually identified in addition to code/technology ngrams).
Claim 8
Regarding claim 8, the rejection of claim 6 is incorporated.
Balasubramanian et al. further disclose wherein the characterization includes a code score (Balasubramanian et al. ¶ [0073], "in step 503 a machine learning and natural language processing technique is used to identify if the search query is of type keyword text or natural language or programming language code. ... If the passed search query is a programming language code, for example, List 1s=new ArrayList( )), then the code detector model identifies it as of type “code” and assigns a weight, for example, 0.9." Weights associated with identified code snippets are considered analogous to code scores) determined for each token within a ngram converted from a corresponding partition (Balasubramanian et al. ¶ [0074], "Step 601 creates three type of tokens; unigram, bigram and trigram. ... In step 602 a software technology dictionary built from software technology documents such as a readme file is used to identify the technology terms present in the tokens from step 601. For example, from the unigram tokens (“mongodb,” “find,” “id,” “operation”) “mongodb” is identified as technology term.").
Claim 16
Regarding claim 16, the rejection of claim 11 is incorporated. The limitations of claim 16 are similar in scope to that of claim 6 and therefore are rejected for similar reasons as described above.
Claim 17
Regarding claim 17, the rejection of claim 16 is incorporated. The limitations of claim 17 are similar in scope to that of claim 7 and therefore are rejected for similar reasons as described above.
Claim 18
Regarding claim 18, the rejection of claim 16 is incorporated. The limitations of claim 18 are similar in scope to that of claim 8 and therefore are rejected for similar reasons as described above.
Reference Cited
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
US Patent 11487795 B2 to Sun et al. discloses replacing entities in a query with entity labels for comparison to a database of revised queries.
US Patent Publication 20200043476 A1 to Hwang discloses splitting user queries into a goal component and parameter component, and classifying a user task based on the goal and parameter components.
“Code and Named Entity Recognition in StackOverflow” to Tabassum et al. discloses calculating a plurality of weights per word in an input text, the weights corresponding to the likelihood that the word is language, an entity, or code.
“Query Expansion via Wordnet for Effective Code Search” to Lu et al. discloses replacing code-based entities in a natural language query with synonyms from Wordnet.
“Generating Query Substitutions” to Jones et al. discloses various query expansion strategies, including direct synonym substitution to complete re-writing.
Conclusion
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/JACOB B VOGT/ Examiner, Art Unit 2653
/Paras D Shah/ Supervisory Patent Examiner, Art Unit 2653
07/17/2026
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