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 .
Claims 1-4 and 6-21 are pending.
Claims 1, 3, 4, 7-9, 11, 12, 16-18, and 20 are amended. Claim 5 was previously cancelled. Claim 21 is added.
Response to Arguments
Applicant's amendments and arguments with respect to Section 101 have been fully considered but they are not persuasive. Applicant argues that "generating metadata" is not related to any human activity, nor is it a mental process that can be performed in the human mind. Similarly, a "semantic similarity search of the indexed case data and the indexed component data" is not related to any human activity nor mental process. However, as noted in the updated rejection, the existence of additional elements does not negate the finding that the claims, as a whole are directed to an abstract idea. In addition, the addition of the term the “complex data structures” does not change the analysis. It is noted that a physical book may be considered a complex data structure, but that does not make it patentable or not directed to an abstract idea. The use of terms case file components and indexing in the claim amount to “collecting information, analyzing it, and displaying certain results of the collection and analysis,” where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind, Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016). Furthermore, Applicants’ analysis does not address the rejection as written, including the presence of additional elements. As such, this argument is not persuasive.
With regards to Prong Two of Step 2A of the Eligibility Analysis, Applicant argues the claims limitations include "an improvement in the functioning of a computer, or an improvement to other technology or technical field," but fails to clearly identify how a database is improved. Indexed case files are well known and are widely used, including in the prosecution of this application. The filings transmitted to create the response are indexed by document type, receipt date, and application number, among other things. As such, the claimed additional elements generally link the use of the judicial exception to a particular technological environment, but do not integrate the abstract idea into a practical application. The claimed processes use computer software to establish a technical environment, but do not address any technical problem or provide a technical solution. This method is similar to building an index of a book, database, or encyclopedia by mining words and phrases to compile an index of terms and phrases used in the database/work and their frequency. See, for example, Appeal 2020-000978, Application 14/668,682, page 14. As such, the claimed additional elements amount to the use of commercially available software for its intended purpose to implement an abstract idea. The rejections have been updated to address the amended claims.
Applicant’s arguments with respect to the Section 103 rejections have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. The Examiner disagrees with the assertion that Heller fails to teach “decomposing, by the data processor, one or more legal case files of the set of legal case files into constituent components, the one or more legal case files associated with complex data structures, wherein decomposing a case file of the one or more legal case files comprises: extracting a plurality of components from the case file, and generating metadata that tracks a relationship between the plurality of components and the case file”. The rejection has been updated to address the added claim limitations below.
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 1-4 and 6-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Representative claim 1 recites “receiving a set of legal case files….; decomposing, …, one or more legal case files of the set of legal case files into constituent components, the one or more legal case files associated with complex data structures, wherein decomposing a case file of the one or more legal case files comprises: extracting a plurality of components from the case file, and …; obtaining, …, an input prompt regarding the set of legal case files; encoding, …, the input prompt to produce an encoded representation of the input prompt; retrieving, …, a plurality of contextual information from the searchable database based on a semantic similarity search of the indexed case data and the indexed component data using the encoded representation; combining, …, the plurality of contextual information with the input prompt to produce a timeline prompt in accordance with a plurality of parameters associated with the set of legal case files, wherein the plurality of parameters includes two or more of a chronological event, a geographical location, and an identification of involved individuals; processing, …, the timeline prompt … to interpret the timeline prompt to generate a timeline response; and outputting, …, the timeline response comprising an interactive timeline of at least a subset of the set of legal case files”. Therefore, the claim as a whole is directed to “Creating legal case file based timelines”, which is an abstract idea because it is a method of organizing human activity, including legal interactions (including legal obligations); and managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions), and mental process, including concepts performed in the human mind (including an observation, evaluation, judgment, opinion). “Creating legal case file based timelines” is considered to be is a method of organizing human activity the process of reading and interpreting documents in order to determine a timeline of legal events is a process regularly performed by humans such as lawyers or paralegals, in reviewing case histories for judges, preparing event timelines for criminal prosecutions, and reviewing case files for possible appeals. As such, the claims are directed to an abstract idea.
“Creating legal case file based timelines” is also considered to be is a mental process because the process of reading files to determine their content, creating notes and summaries of those files, and creating a timeline of legal events is a human process often performed mentally or with pen and paper, by paralegals, clerks, lawyers, judges, investigators, and police officers. These processes are performed regularly in the process of performing legal tasks, such as patent prosecution task, in order to make mental determinations such as determining whether particular documents determined to be relevant may qualify as prior at. This method is similar to building an index of a book, database, or encyclopedia by mining words and phrases to compile an index of terms and phrases used in the database/work and their frequency, which were traditionally performed mentally by people with pen and paper. Such ideas, when recited at a high level of generality, recite an abstract idea as illustrated by the holding in Intellectual Ventures I LLC v. Erie Indemnity Co., 850 F.3d 1315 (Fed. Cir. 2017). See, for example, Appeal 2020-000978, Application 14/668,682, page 14. As such, the claims are directed to an abstract idea.
This judicial exception is not integrated into a practical application. In particular, claim 1 recites the following additional elements: by a data processor configured to execute a large language model, generating metadata that tracks a relationship between the plurality of components and the case file; indexing, by the data processor, the set of legal case files to generate indexed case data that is stored in a searchable database, wherein the indexing comprises: separately indexing the plurality of components for each case file of the one or more legal case files to generate indexed component data that is stored, with the metadata, in the searchable database; and the large language model configured to interpret the timeline prompt. These additional elements individually or in combination do not integrate the exception into a practical application. That is, the recitations of additional elements amount merely reciting the words ‘‘apply it’’ (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). The recited additional elements are recited at a high level of generality that amount to the use of commercially available general purpose technology. The mere application of a large language model in a computer environment does not address any technical problem or provide any technical solution. Rather, such recitations of additional elements do no more than generally link the use of a judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)). 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. Claim 1 is directed to an abstract idea.
Claim 1 does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements, individually and in combination, are merely being used to apply the abstract idea to a technological environment. As noted above, the recited additional elements does not address any technical problem or provide any technical solution. Rather, the additional elements are recited at high level of generality and are used to perform their ordinary functions. Accordingly, claim 1 is ineligible.
Claims 12 and 18 recite substantially similar features to those recited in representative claim 1 and are ineligible based on substantially the same reasons.
Dependent claims 2-4, 6-11, 13-17, 19 and 20 merely further limit the abstract idea and are thereby considered to be ineligible.
Dependent claim 3 further limits the abstract idea of “Creating legal case file based timelines” by introducing the element of the searchable database stores vector embeddings of the indexed data, and wherein the vector embeddings enable semantic similarity searches for retrieving the plurality of contextual information, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claim 3 is also non-statutory subject matter.
Dependent claims 4 and 15 further limit the abstract idea of “Creating legal case file based timelines” by introducing the element of combining the plurality of contextual information with the input prompt to produce the timeline prompt includes constructing a chronological sequence of events by identifying chronological events within the legal case files, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claims 4 and 15 are also non-statutory subject matter.
Dependent claim 6 further limits the abstract idea of “Creating legal case file based timelines” by introducing the element of outputting the timeline response as the interactive timeline of at least a subset of the set of legal case files includes displaying the interactive timeline on a user interface, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claim 6 is also non-statutory subject matter.
Dependent claims 7, 17, and 20 further limit the abstract idea of “Creating legal case file based timelines” by introducing the element of generating a geospatial representation of at least a subset of the set of legal case files based on the indexed case data, the indexed component data, or both, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claims 7, 17, and 20 are also non-statutory subject matter.
Dependent claim 8 further limits the abstract idea of “Creating legal case file based timelines” by introducing the element of generating a narrative summary of at least a subset of the set of legal case files based on the indexed case data, the indexed component data, or both, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claim 8 is also non-statutory subject matter.
Dependent claim 9 further limits the abstract idea of “Creating legal case file based timelines” by introducing the element of providing a chatbot interface for user interaction with the large language model, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claim 9 is also non-statutory subject matter.
Dependent claims 10 and 13 further limit the abstract idea of “Creating legal case file based timelines” by introducing the element of the set of legal case files is received from a user device or a third-party platform/ receive the set of legal case files, the operations further include interacting with a plurality of sources including user devices and third-party platforms, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claims 10 and 13 are also non-statutory subject matter.
Dependent claim 11 further limits the abstract idea of “Creating legal case file based timelines” by introducing the element of the set of legal case files include multi-model datasets of text-based documents, portable document format documents, audio recordings, video recordings, images, or a combination thereof, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claim 11 is also non-statutory subject matter.
Dependent claim 14 further limits the abstract idea of “Creating legal case file based timelines” by introducing the element of the third-party platforms include one or combinations of: publicly available data sets, social media platforms, mobile phone service providers, financial institutions, surveillance systems, and ballistics repositories, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claim 14 is also non-statutory subject matter.
Dependent claim 16 further limits the abstract idea of “Creating legal case file based timelines” by introducing the element of to output the timeline response as the interactive timeline of the legal case files, the operations further include generate one or combinations of: graphical representations, geospatial maps, interactive elements, and textual descriptions, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claim 16 is also non-statutory subject matter.
Dependent claim 17 further limits the abstract idea of “Creating legal case file based timelines” by introducing the element of to generate a geospatial representation of the legal case files based on the indexed data and the timeline response, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claim 17 is also non-statutory subject matter.
Dependent claim 21 further limits the abstract idea of “Creating legal case file based timelines” by introducing the element of the case file of the one or more legal case files comprises a portable document format (PDF) file and the extracted plurality of components from the case file comprises a text component and an image component; the case file of the one or more legal case files comprises a video file and the extracted plurality of components from the case file comprises at least two of: a series of image frames, an audio track, embedded metadata, and subtitles; or the case file of the one or more legal case files comprises an image and the extracted plurality of components from the case file comprises one or more objects identified within the image and text extracted from the image, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claim 21 is also non-statutory subject matter.
Dependent claims 2-4, 6-11, 13-17, and 19-21 also do not integrated into a practical application. The dependent claims recite claim 3 recites the searchable database stores vector embeddings of the indexed data, and wherein the vector embeddings enable semantic similarity searches for retrieving the plurality of contextual information; claim 6 recites displaying the interactive timeline on a user interface; claim 9 recites providing a chatbot interface for user interaction with a large language model; and claims 10 and 13 recite the set of legal case files is received from a user device or a third-party platform/receive the set of legal case files, the operations further include interacting with a plurality of sources including user devices and third-party platforms. These additional elements merely generally link the abstract idea to a particular technological environment or field of use. MPEP 2106.04(d)(I) indicates that generally linking an abstract idea to a particular technological environment or field of use cannot provide a practical application. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application. This has been re-evaluated under the “significantly more” analysis and has also been found insufficient to provide significantly more. MPEP 2106.05(A) indicates that generally linking an abstract idea to a particular technological environment or field of use cannot provide significantly more. These elements are recited at a high level of generality and the use of commercially available technology by human personnel performing the abstract idea. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of a computing system is merely being used to apply the abstract idea to a technological environment. That is, the claims provide no practical limits or improvements to any technology. Accordingly, dependent claims 2-4, 6-11, 13-17, and 19-21 are also ineligible.
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 1, 2, 4, and 6-20 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication No. 20240273309 to Heller et al. in view of U.S. Patent Application Publication No. 20150106683 to Lindsey et al. and U.S. Patent Application Publication No. 20210406290 to Sharma et al.
With regards to claims 1, 12, and 18, Heller et al. teaches:
at least one memory configured to store instructions; and at least one processor configured to execute the instructions and a large language model to perform operations (paragraph [0021], “The text generation interface system receives a request from a client machine and processes it to produce a prompt to the large language model. After the prompt is provided to the large language model, the text generation interface system receives one or more responses. At this point, the text generation interface system may perform one or more further interactions with the text generation system and large language model.”; paragraphs [0466]-[0467]), wherein the operations include:
receiving a set of legal case files by a data processor configured to execute a large language model (paragraph [0028], “In some embodiments, techniques and mechanisms described herein may be applied to generate novel text in domain-specific contexts, such as legal analysis.”; paragraph [00029], “According to various embodiments, techniques and mechanisms described herein may be used to automate complex, domain-specific tasks that were previously the sole domain of well-trained humans. Moreover, such tasks may be executed in ways that are significantly faster, less expensive, and more auditable than the equivalent tasks performed by humans. For example, a large language model may be employed to produce accurate summaries of legal texts, to perform legal research tasks, to generate legal documents, to generate questions for legal depositions, and the like.).”);
decomposing, by the data processor, one or more legal case files of the set of legal case files into constituent components (paragraph [0442], “According to various embodiments, combining the parsed complaint response message may involve dividing the text into a number of different complaints. Each complaint may include one or more paragraphs, pages, or sections of text.”), the one or more legal case files associated with complex data structures, wherein decomposing a case file of the one or more legal case files comprises:
extracting a plurality of components from the case file (paragraph [0085], “The method 500 may be performed in order to divide a body of text into potentially smaller units that fall beneath a designated size threshold, such as a size threshold imposed by an interface providing access to a large language model. For instance, a text generation modeling system implementing a large language model may specify a size threshold in terms of a number of tokens (e.g., words). As one example of such a threshold, a text generation modeling system may impose a limit of 8,193 tokens per query.”), and
generating metadata that tracks a relationship between the plurality of components and the case file (paragraph [0060], “For instance, the method 300 may be performed on the text generation interface system 230 shown in FIG. 2 . The method 300 may be performed in order to convert a document into usable text while at the same time retaining metadata information about the text, such as the page, section, and/or document at which the text was located.”; paragraph [0086], “For instance, a text generation interface system may formulate a prompt that includes input text as well as metadata such as one or more instructions for a large language model. In addition, the output of the large language model may be included in the threshold. If the external text generation modeling system imposes a threshold (e.g., 8,193 tokens), the text generation interface system 230 may need to impose a somewhat lower threshold when dividing input text in order to account for the metadata included in the prompt and/or the response provided by the large language model.”);
indexing, by the data processor, the set of legal case files to generate indexed case data that is stored in a searchable database (paragraph [0032], “In some embodiments, techniques and mechanisms described herein may be used to link a large language model with a legal research database, allowing the large language model to automatically determine appropriate searches to perform and then ground its responses to a source of truth (e.g., in actual law) so that it does not “hallucinate” a response that is inaccurate.”; paragraph [0073], “In some embodiments, determining input text may involve executing a search query. For example, a search of a database, set of documents, or other data source may be executed base at least in part on one or more search parameters determined based on a request received from a client machine. For instance, the request may identify one or more search terms and a set of documents to be searched using the one or more search terms.”), wherein the indexing comprises:
separately indexing the plurality of components for each case file of the one or more legal case files to generate indexed component data (paragraph [0074], “For instance, all or a portion of the results from an initial request to summarizing a set of text portions may then be used to create a new set of more compressed input text, which may then be provided to the text generation modeling system for further summarization or other processing.”) that is stored, with the metadata (paragraph [0060], “FIG. 3 illustrates a document parsing method 300, performed in accordance with one or more embodiments. … The method 300 may be performed in order to convert a document into usable text while at the same time retaining metadata information about the text, such as the page, section, and/or document at which the text was located.”), in the searchable database (paragraph [0022], “The large language model's response is then parsed and potentially used to trigger additional analysis, such as one or more database searches, one or more additional prompts sent back to the large language model, and/or a response returned to a client machine.”; paragraph [0023], “According to various embodiments, techniques and mechanisms described herein provide for retrieval augmented generation. A search is conducted base on a search query. Then, the search results are provided to an artificial intelligence system. The artificial intelligence system then further processes the search results to produce an answer based on those search results. In this context, a large language model may be used to determine the search query, apply one or more filters and/or tags, and/or synthesize potentially many different types of search.”);
obtaining, by the data processor, an input prompt regarding the set of legal case files (paragraph [0037], “In some embodiments, the text generation flow may define a procedure for interacting with a large language model to generate output text based on the original input text. For instance, the text generation flow may define one or more prompts or instructions to provide to the large language model.”);
encoding, by the data processor, the input prompt to produce an encoded representation of the input prompt (paragraph [0052], “In some implementations, the chunker 240 is configured to divide text into smaller portions. Dividing text into smaller portions may be needed at least in part to comply with one or more size limitations associated with the text. For instance, the text generation API 274 may impose a maximum size limit on prompts provided to the text generation model 276. The chunker may be used to subdivide text included in a request from a client, retrieved from a document, returned in a search result, or received from any other source.”);
retrieving, by the data processor, a plurality of contextual information from the searchable database based on ….the indexed component data using the encoded representation (paragraph [0073], “In some embodiments, determining input text may involve executing a search query. For example, a search of a database, set of documents, or other data source may be executed base at least in part on one or more search parameters determined based on a request received from a client machine. For instance, the request may identify one or more search terms and a set of documents to be searched using the one or more search terms.”; paragraph [0274], “According to various embodiments, factual claims may include, for instance, citations to legal case law, statutes, or other domain-specific source documents. Factual claims may also include claims based on other accessible information sources such as privately held documents, information publicly available on the internet, and the like.”; paragraph [0320], “In some embodiments, the description may include information such as the party being deposed, the types of information that are sought, and the purpose of the interrogatory. The information relevant to the interrogatory may include one or more facts, conjectures, allegations, documents, or other information that may inform the selection of topics. The description and/or information may be included with the request received at 1302 or identified in some other way, for instance via retrieval from a database or document repository.”);
combining, by the data processor, the plurality of contextual information with the input prompt to produce a timeline prompt in accordance with a plurality of parameters associated with the set of legal case files (paragraph [0070], “In some embodiments, the request may include an input text portion. For example, the request may link to, upload, or otherwise identify documents. As another example, the request may characterize the task to be completed. For instance, the request may discuss the content of the desired email or other correspondence. The particular types of input text included in the request may depend in significant part on the type of request. Accordingly, many variations are possible.”; paragraph [0073], “In some embodiments, determining input text may involve executing a search query. For example, a search of a database, set of documents, or other data source may be executed base at least in part on one or more search parameters determined based on a request received from a client machine. For instance, the request may identify one or more search terms and a set of documents to be searched using the one or more search terms.”; paragraph [0201], “FIG. 10 illustrates an example of a method 1000 for generating a timeline, performed in accordance with one or more embodiments. The method 1000 may be performed at the text generation system 200 in order to generate an event timeline based on one or more documents provided or identified by a client machine. In some configurations, the method 1000 may be performed to generate a timeline based on one or more documents returned by a search query.”), …;
processing, by the data processor, the timeline prompt by the large language model configured to interpret the timeline prompt to generate a timeline response (paragraph [0157], “FIG. 9 illustrates an example of a method 900 for generating a document timeline, performed in accordance with one or more embodiments. The method 900 may be performed at the text generation system 200 in order to summarize one or more documents provided or identified by a client machine. In some configurations, the method 900 may be performed to summarize one or more documents returned by a search query.”); and
outputting, by the data processor, the timeline response comprising an interactive timeline of at least a subset of the set of legal case files (paragraph [0201], “FIG. 10 illustrates an example of a method 1000 for generating a timeline, performed in accordance with one or more embodiments. The method 1000 may be performed at the text generation system 200 in order to generate an event timeline based on one or more documents provided or identified by a client machine. In some configurations, the method 1000 may be performed to generate a timeline based on one or more documents returned by a search query.”). Heller et al. fails to explicitly teach parameters including a geographical location. However, Lindsey et al. teaches case data visualization application is provided that, when executed on a device, allows a user to visualize a chronology of events associated with a case, view a summary of one or more supporting details of an event (see abstract),
combining, by the data processor, the plurality of contextual information with the input prompt to produce a timeline prompt in accordance with a plurality of parameters associated with the set of legal case files (paragraph [0047], “According to the embodiments, an “event” is a representation of case data associated with a point in time, or a duration is time, where the event can be visually represented within user interface 320. An event can take on one of many visual representations, including a block or a milestone. The user can also associate summary information to the event, such as a date and/or time, or a title, by entering the summary information within user interface 320. The user can also associate one or more files to the event, where the one or more files each include case data, by selecting the one or more files (or a folder that contains the one or more files) that can be displayed within user interface 320.”)
wherein the plurality of parameters includes two or more of a chronological event, a geographical location, and an identification of involved individuals (paragraph [0076], “Case data visualization application 710 can further generate case data. Examples of case data can include image data, audio data, video data, visualization data, geospatial data, or document data. For example, case data visualization application 710 can interface with a camera stored within device 700 and collect one or more images or videos. Each image or video can be stored in an image file or video file respectively. As another example, case data visualization application 710 can interface with a global positioning system (“GPS”) receiver stored within device 700 and collect geospatial data, where the geospatial data can be recorded as metadata for collected files.”; paragraph [0087], “The flow begins and then proceeds to step 910. At step 910, a timeline is displayed that includes one or more events associated with a case. The one or more events can be displayed within the timeline in a chronological order. In certain embodiments, each event of the one or more events is associated with a date and/or time. In certain embodiments, at least one event is associated with a timespan.”).
This part of Lindsey et al. is applicable to the system of Heller et al as they both share characteristics and capabilities, namely, they are directed to event timeline generation. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Heller et al. to include the geographic data for timelines as taught by Lindsey et al. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Heller et al. in order to allow a plurality of users to collaborate on the case, and synchronize a plurality of supporting details created by a plurality of users that are associated with an event (see abstract of Lindsey et al.).
While Heller et al. discussed techniques to divide text into portions while respecting semantic boundaries and simultaneously reducing calls to the large language model, but Heller et al. fails to explicitly teach a semantic similarity search. However, Sharma et al. teaches
retrieving, by the data processor, a plurality of contextual information from the searchable database based on a semantic similarity search of the indexed case data and the indexed component data using the encoded representation (paragraph [0005], “identifying one or more argument paragraphs containing legal arguments from the legal brief, performing a textual search of a corpus of legal documents based on a selected set of the identified argument paragraphs, performing a semantic search of the corpus of legal documents based on the selected set of the identified argument paragraphs, combining results of the textual search and the semantic search, and presenting the combined results to a user.”; paragraph [0058], “In embodiments, the semantic search logic 52 may perform a semantic search by comparing the vector representation of an argument paragraph to a vector representation of an index item of the corpus index 38 c. In some examples, the corpus index 38 c may be quite large and it may not be practical to directly compare the vector representation of each argument paragraph to the vector representation of each index item of the corpus index 38 c. Accordingly, in some examples, the semantic search logic 52 may perform an approximate nearest neighbor search to determine the documents from the corpus index 38 c with the closest semantic similarity to an argument paragraph, based on the vector representations.”)
This part of Sharma et al. is applicable to the system of Heller et al as they both share characteristics and capabilities, namely, they are directed to legal document analysis. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Heller et al. to include the semantic similarity search as taught by Sharma et al. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Heller et al. in order to allow a drafter of a legal brief may be required to sequentially perform a search of each topic associated with the legal brief (see paragraph [0004] of Sharma et al.).
With regards to claims 2 and 19, Heller et al. fails to explicitly teach parameters including a geographical location. However, Lindsey et al. teaches: the set of legal case files includes one or combinations of: police reports, ballistics reports, coroners' reports, social media data, mobile phone forensics data, mobile phone business records, financial records, video footage, photos, facial recognition results, and audio recordings (paragraph [0113], “According to certain embodiments, a data visualization application can provide a streamlined, intuitive, software application, that can receive digital files and documents (such as digital photos, audio samples, scanned documents, and digital video), and organize it in a manner that is easy to visualize.”).
This part of Lindsey et al. is applicable to the system of Heller et al as they both share characteristics and capabilities, namely, they are directed to event timeline generation. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Heller et al. to include the geographic data for timelines as taught by Lindsey et al. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Heller et al. in order to allow a plurality of users to collaborate on the case, and synchronize a plurality of supporting details created by a plurality of users that are associated with an event (see abstract of Lindsey et al.).
With regards to claims 4 and 15, Heller et al. teaches: combining the plurality of contextual information with the input prompt to produce the timeline prompt includes constructing a chronological sequence of events by identifying chronological events within the set of legal case files (paragraph [0201], “FIG. 10 illustrates an example of a method 1000 for generating a timeline, performed in accordance with one or more embodiments. The method 1000 may be performed at the text generation system 200 in order to generate an event timeline based on one or more documents provided or identified by a client machine. In some configurations, the method 1000 may be performed to generate a timeline based on one or more documents returned by a search query.”).
With regards to claim 6, Heller et al. teaches timeline generation but fails to explicitly teach that the timeline is an interactive timeline. However, Lindsey et al. teaches: outputting the timeline response as the interactive timeline of at least a subset of the set of legal case files includes displaying the interactive timeline on a user interface (paragraph [0100], “All the information for the events included in a project are prepopulated from the timeline. Also, in an embodiment, any changes made to the events or associated information within a project do not flow back into a case file. As a result, the details can be tailored to the specific requirements of a project without concern about those changes affecting or changing a case file. As illustrated in FIG. 11, project editor user interface 1100 may further include a preview pane 1160 which displays a preview of the project which can show how it will look when exported as an interactive multimedia presentation.”).
This part of Lindsey et al. is applicable to the system of Heller et al. as they both share characteristics and capabilities, namely, they are directed to event timeline generation. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Heller et al. to include the geographic data for timelines as taught by Lindsey et al. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Heller et al. in order to allow a plurality of users to collaborate on the case, and synchronize a plurality of supporting details created by a plurality of users that are associated with an event (see abstract of Lindsey et al.).
With regards to claims 7, 17, and 20, Heller et al. fails to explicitly teach parameters including a geographical location. However, Lindsey et al. teaches generating a geospatial representation of at least a subset of the set of legal case files based on the indexed case data, the indexed component data, or both
the legal case files based on the indexed data (paragraph [0076], “Case data visualization application 710 can further generate case data. Examples of case data can include image data, audio data, video data, visualization data, geospatial data, or document data. For example, case data visualization application 710 can interface with a camera stored within device 700 and collect one or more images or videos. Each image or video can be stored in an image file or video file respectively. As another example, case data visualization application 710 can interface with a global positioning system (“GPS”) receiver stored within device 700 and collect geospatial data, where the geospatial data can be recorded as metadata for collected files.”; paragraph [0087], “The flow begins and then proceeds to step 910. At step 910, a timeline is displayed that includes one or more events associated with a case. The one or more events can be displayed within the timeline in a chronological order. In certain embodiments, each event of the one or more events is associated with a date and/or time. In certain embodiments, at least one event is associated with a timespan.”; paragraph [0089], “New case data is case data that is not part of the case data included with the one or more events that are displayed within the timeline. In certain embodiments, the new case data can include at least one of image data, audio data, video data, visualization data, geospatial data or document data. Also in certain embodiments, the one or more files are selected from a user interface that can be displayed, where the user interface allows one or more files that are stored on a device to be selected.”).
This part of Lindsey et al. is applicable to the system of Heller et al as they both share characteristics and capabilities, namely, they are directed to event timeline generation. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Heller et al. to include the geographic data for timelines as taught by Lindsey et al. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Heller et al. in order to allow a plurality of users to collaborate on the case, and synchronize a plurality of supporting details created by a plurality of users that are associated with an event (see abstract of Lindsey et al.).
With regards to claim 8, Heller et al. teaches: generating a narrative summary of at least a subset of the set of legal case files based on the indexed case data, the indexed component data, or both (paragraph [0157], “The method 900 may be performed at the text generation system 200 in order to summarize one or more documents provided or identified by a client machine. In some configurations, the method 900 may be performed to summarize one or more documents returned by a search query.”; paragraph [0163], “The one or more summarize response messages are parsed at 918 to produce one or more parsed summary responses at 920. In some embodiments, the one or more summary response messages received at 916 may include ancillary information such as all or a portion of the summarize prompt messages sent at 912. Accordingly, parsing the summarize response messages may involve performing operations such as separating the newly generated summaries from the ancillary information included in the one or more summarize response messages.”).
With regards to claim 9, Heller et al. teaches: providing a chatbot interface for user interaction with a large language model (paragraph [0113], “FIG. 8 illustrates an example of a method 800 for conducting a chat session, performed in accordance with one or more embodiments. The method 800 may be performed at the text generation system 200 in order to provide one or more responses to one or more chat messages provided by a client machine. For instance, the method 800 may be performed at the text generation interface system 210 to provide novel text to the client machine 202 based on interactions with the text generation modeling system 270.”).
With regards to claims 10 and 13, Heller et al. teaches: the set of legal case files is received from a user device or a third-party platform/ receive the set of legal case files, the operations further include interacting with a plurality of sources including user devices and third-party platforms (paragraph [0043], “The orchestrator also includes API interfaces 250, which include a model interface 252, an external search interface 254, an internal search interface 256, and a chat interface 258.”; paragraph [0054], “In some embodiments, the external search interface 254 may be used to search one or more external data sources such as information repositories that are generalizable to multiple parties. For instance, the external search interface 254 may expose an interface for searching legal case law and secondary sources.”).
With regards to claim 11, Heller et al. fails to explicitly teach the set of legal case files include multi-model datasets. However, Lindsey et al. teaches the legal case files include multi-model datasets of text-based documents, portable document format documents, audio recordings, video recordings, images, or a combination thereof (paragraph [0113], “According to certain embodiments, a data visualization application can provide a streamlined, intuitive, software application, that can receive digital files and documents (such as digital photos, audio samples, scanned documents, and digital video), and organize it in a manner that is easy to visualize.”).
This part of Lindsey et al. is applicable to the system of Heller et al as they both share characteristics and capabilities, namely, they are directed to event timeline generation. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Heller et al. to include the geographic data for timelines as taught by Lindsey et al. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Heller et al. in order to allow a plurality of users to collaborate on the case, and synchronize a plurality of supporting details created by a plurality of users that are associated with an event (see abstract of Lindsey et al.).
With regards to claim 14, Heller et al. teaches: the third-party platforms include one or combinations of: publicly available data sets, social media platforms, mobile phone service providers, financial institutions, surveillance systems, and ballistics repositories (paragraph [0054], “In some embodiments, the external search interface 254 may be used to search one or more external data sources such as information repositories that are generalizable to multiple parties. For instance, the external search interface 254 may expose an interface for searching legal case law and secondary sources.”; paragraph [0270], “In some embodiments, one or more search queries may be executed against an external database such as a repository of case law, secondary sources, statutes, and the like.”).
With regards to claim 16, Heller et al. teaches timeline generation but fails to explicitly teach that the timeline is an interactive timeline. However, Lindsey et al teaches: to output the timeline response as the interactive timeline of the at least a subset of the set of legal case files, the operations further include generate one or combinations of: graphical representations, geospatial maps, interactive elements, and textual descriptions (paragraph [0100], “All the information for the events included in a project are prepopulated from the timeline. Also, in an embodiment, any changes made to the events or associated information within a project do not flow back into a case file. As a result, the details can be tailored to the specific requirements of a project without concern about those changes affecting or changing a case file. As illustrated in FIG. 11, project editor user interface 1100 may further include a preview pane 1160 which displays a preview of the project which can show how it will look when exported as an interactive multimedia presentation.”).
This part of Lindsey et al. is applicable to the system of Heller et al. as they both share characteristics and capabilities, namely, they are directed to event timeline generation. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Heller et al. to include the geographic data for timelines as taught by Lindsey et al. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Heller et al. in order to allow a plurality of users to collaborate on the case, and synchronize a plurality of supporting details created by a plurality of users that are associated with an event (see abstract of Lindsey et al.).
With regards to claim 17, Heller et al. teaches timeline generation but fails to explicitly teach that the timeline includes a geospatial representation. However, Lindsey et al teaches: the operations further include: generate a geospatial representation of at least a subset of the set of legal case files based on the indexed case data, the indexed component data, or both (paragraph [0076], “As another example, case data visualization application 710 can interface with a global positioning system (“GPS”) receiver stored within device 700 and collect geospatial data, where the geospatial data can be recorded as metadata for collected files. As yet another example, case data visualization application 710 can generate a digital document, where the digital document can be stored in a document file. Case data visualization application 710 can then transmit the generated case data to another device, such as a client or server.”; paragraph [0093], “In other embodiments, the display of the timeline can be switched to a view of one or more case files associated with the one or more events. In some embodiments, an ability to edit the case data displayed within the timeline can be disabled. In other embodiments, the case data can be generated, where the case data comprises at least one of, image data, audio data, video data, visualization data, geospatial data, or document data.”).
This part of Lindsey et al. is applicable to the system of Heller et al. as they both share characteristics and capabilities, namely, they are directed to event timeline generation. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Heller et al. to include the geographic data for timelines as taught by Lindsey et al. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Heller et al. in order to allow a plurality of users to collaborate on the case, and synchronize a plurality of supporting details created by a plurality of users that are associated with an event (see abstract of Lindsey et al.).
With regards to claim 21, Heller et al. teaches: the case file of the one or more legal case files comprises a portable document format (PDF) file and the extracted plurality of components from the case file comprises a text component and an image component; the case file of the one or more legal case files comprises a video file and the extracted plurality of components from the case file comprises at least two of: a series of image frames, an audio track, embedded metadata, and subtitles; or the case file of the one or more legal case files comprises an image and the extracted plurality of components from the case file comprises one or more objects identified within the image and text extracted from the image (paragraph [0062], “The document is converted to portable document format (PDF) or another suitable document format at 304. In some embodiments, the document need only be converted to PDF if the document is not already in the PDF format. Alternatively, PDF conversion may be performed even on PDFs to ensure that PDFs are properly formatted. PDF conversion may be performed, for instance, by a suitable Python library or the like. For instance, PDF conversion may be performed with the Hyland library.”; paragraph [0432], “A complaint chunk may be parsed by the text generation model using a complaint parsing prompt. A complaint parsing prompt for parsing the complaint chunk is determined at 1608 through 1610, after which the complaint parsing prompt is sent to the text generation model.”; and paragraph [0433], “According to various embodiments, the complaint parsing prompt may be used to extract text from a complaint that potentially has been converted to text from an image based format and then divided into chunks. The complaint parsing prompt template may have one or more fillable portions such as that may be filled with text determined based on the complaint, for instance by dividing the complaint into chunks.”).
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication No. 20240273309 to Heller et al. and U.S. Patent Application Publication No. 20150106683 to Lindsey et al. and U.S. Patent Application Publication No. 20210406290 to Sharma et al. in view of U.S. Patent Application Publication No. 20210081899 to Venkatasubramanian et al.
With regards to claim 3, modified Heller et al. fails to explicitly teach, but Venkatasubramanian et al teaches: the searchable database stores vector embeddings of the indexed case data and the indexed component data, and wherein the vector embeddings enable semantic similarity searches for retrieving the plurality of contextual information (paragraph [0021], “In this case, the number of attributes is the features of the vectors obtained upon vectorization of each correspondence thread text. In one embodiment, a pre-trained vectorization model uses text2vec library for text vectorization, topic modeling, word embeddings, and similarities. The first step is to vectorize text using vocabulary based vectorization. Here unique terms are collected from a group of input documents (e.g., groups of email correspondence and threads) and each term is marked with a unique ID. Then the risk detection system 100 creates a vocabulary based document term matrix (DTM) using the pre-trained vectorization model in text2vec. This process transforms each correspondence thread into a numerical representation in the vector space. This process transforms text into a numerical representation (an embedding) of the text's semantic meaning. If two words or documents have a similar embedding, they are semantically similar. Thus using the numerical representation, the risk detection system 100 is capable of capturing the context of a word in a document, semantic and syntactic similarity, relation with other words, etc.”).
This part of Venkatasubramanian et al. is applicable to the system of modified Heller et al. as they both share characteristics and capabilities, namely, they are directed to organizing data for analysis. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Heller et al. to include the timeline processing of legal documents as taught by Venkatasubramanian et al. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Heller et al. in order to identify early signs of potential issues that could lead to larger disputes or litigations (see paragraph [0003] of Venkatasubramanian et al.).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/J.D.S./Examiner, Art Unit 3626
/JESSICA LEMIEUX/Supervisory Patent Examiner, Art Unit 3626
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