{"components":{"schemas":{"BatchTranslateSchema":{"example":{"documents":[{"extracted":"2022-12-30T22:59:57.502Z","id":"c34ac671a1b0b80078f9acd7e80217e28e8c554e14e1de707fb4370e52299add"},{"extracted":"2022-12-28T13:15:06.644Z","id":"0d285bcb024438d022c91d75556c4159786e72b7f3b4b3a22562ca9d1dbabb4a"}],"fields":["title","text"],"language":"french"},"properties":{"documents":{"description":"List of documents to translate","items":{"properties":{"extracted":{"description":"The document's extraction date. 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See [Language Support](/guide/languages#translation) page for more information.","example":"italian","format":"language-code","title":"Target language","type":"string"}},"required":["documents"],"title":"Documents Translate","type":"object"},"BrowseSchema":{"example":{"entity_of_interest":"apple","properties_list":["chief_executive_officer","domain","founders","legal_name","subsidiaries","ticker"],"source":"corporate_kg"},"properties":{"entity_of_interest":{"description":"The identifier of an Entity.","title":"Entity identifier","type":"string"},"properties_list":{"description":"The properties to look for in the KG.<br/> If *source* is corporate_kg, defaults to *[ \"chief_executive_officer\", \"domain\", \"founders\", \"legal_name\", \"subsidiaries\", \"ticker\" ]*<br/>  If *source* is general_kg, defaults to the full list of properties corresponding to the entity provided.","items":{"type":"string"},"title":"Properties list parameter","type":"array"},"source":{"default":"corporate_kg","description":"The knowledge graph source.","enum":["general_kg","corporate_kg"],"example":"corporate_kg","title":"Kg source","type":"string"},"uuid":{"description":"The uuid identifier of an Entity. 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Works like a boolean `AND`.\n*Example*: \n  - `keywords : [\"TotalEnergy\"]`\n  - `co_mentions: [\"gas\", \"oil price\"]`\n\n*Behavior:* TextReveal\u00ae API will look for documents relevant to at least one of the co_mentions. For the above example, below are the different cases of relevancy:\n - `TotalEnergy` and `gas`\n - `TotalEnergy` and `oil price`\n - `TotalEnergy` and `oil price` and `gas`\n\n*N.B*: Search of `co_mentions` is operated in full-text and is case insensitive.\n","items":{"example":["tablets"],"type":"string"},"title":"Co Mentions","type":"array"},"concepts":{"additionalProperties":{"description":"List of keywords for the concept","example":"social","items":{"example":["inequality"],"type":"string"},"type":"array"},"description":"List of concepts or risks that are to be analyzed. Each individual concept is defined by its own list of keywords.<br/> Punctuation is not handled in the concept labels. Each concept label must be unique (case insensitive).\n","title":"Concepts","type":"object"},"concepts_filter":{"additionalProperties":{"description":"List of keywords for the concept","example":"social","items":{"example":["inequality"],"type":"string"},"type":"array"},"description":"Same as `concepts` but filters out documents that does not contain the concepts. <br/>**Note**: You can either use `concepts` or `concepts_filter`\n","title":"Concepts Filter","type":"object"},"countries":{"description":"List of countries to search (field `thread.country`). <br/>\n*N.B*: Use `alpha-2` format.\n","items":{"example":["US"],"type":"string"},"title":"Countries","type":"array"},"end_date":{"description":"The date when the anaysis should end.","example":"2019-02-01","format":"date","title":"End Date","type":"string"},"entities":{"items":{"example":[{"context":"Apple is a technology company that designs, manufactures, and markets consumer electronics, personal computers, and software.","entity_of_interest":"Q312","keywords":["Tim Cook","Apple TV"],"neg_keywords":["apple"]},{"context":"Boeing Company manufactures and sells aircraft, rotorcraft, rockets, and satellites and provides product leasing and support services.","entity_of_interest":"Q66","keywords":["Boeing","Alteon Training"],"neg_keywords":["insitu"]}],"properties":{"context":{"description":"The context used for the analysis.","title":"Context","type":"string"},"entity_of_interest":{"description":"The entity identifier. Commas are not allowed inside.","title":"Entity Identifier","type":"string"},"keywords":{"description":"List of keywords to search.<br/> *All keywords with a length strictly lower than 3 characters are filtered out except for `Japanese`, `Chinese` and `Korean` languages.*","items":{"type":"string"},"title":"Keywords","type":"array"},"neg_keywords":{"description":"List of keywords not used for search but for named entity resolution or annotation task. <br/>\nDetailed explanation: \n- Using generic keywords or high cardinality keywords can bring huge volume of data to process or reduce quality of the data extracted.\n- `neg_keywords` parameter allows you to add such keywords so that you can use them to annotate sentence containing them within documents already containing less generic keywords.\n\nExample: \n- `keywords: ['Microsoft']` (Used for search in datalake)\n- `neg_keywords: ['MSFT']` (Not used for search in datalake)\n\n*Behavior:* Textreveal\u00ae API will look for documents containing only microsoft, then after, it will annotate every sentence mentionning `MSFT` or `Microsoft`\n","items":{"type":"string"},"title":"Negative keywords","type":"array"}},"required":["context","entity_of_interest","keywords"],"title":"Entity","type":"object"},"title":"Entities","type":"array"},"keywords_exclude":{"description":"List of keywords to exclude from the search. Works like a boolean `AND NOT`. <br/>\n*Example*: \n- `keywords: [\"apple\", \"iphone\"]`\n- `keywords_exclude: [\"Steve Jobs\", \"Tim Cook\"]`\n*Behavior*: TextReveal\u00ae API will look for documents relevant to `apple` the company or `Iphone` but *NOT* containing either `Steve Jobs` or `Tim Cook`.\n\n*N.B*: Search of `keywords_exclude` is operated in full-text and is case insensitive.\n","items":{"example":["Steve Jobs"],"type":"string"},"title":"Keywords Exclude","type":"array"},"languages":{"default":["english"],"description":"List of languages to search, see [Language Support](/guide/languages#analyze) page for more information.\n\n*Note:* We do not recommend using multiple values.\n","example":["french"],"items":{"format":"analyze-language-code","type":"string"},"title":"Languages","type":"array"},"min_match":{"default":1,"description":"The message must contain at least `min_match` keywords. <br/>\nWhen used, each entity must have at least `min_match` keywords.<br/>\n*Example*: \n- `keywords: [\"apple\", \"iphone\", \"macbook\"]`\n- `min_match: 2`\n\n*Behavior:* TextReveal\u00ae API will only keep the document if and only if at least 2 elements from the keywords list appear in the document.\n","example":1,"title":"Minimum Match","type":"number"},"min_repeat":{"default":1,"description":"The message must contain at least `min_repeat` occurrence of a keyword. <br/>\n*Example*: \n- `keywords: [\"apple\", \"iphone\"]`\n- `min_repeat: 2`\n\n*Behavior:* TextReveal\u00ae API will only keep the document if and only if it contains at least 2 occurrences of either `apple` or `iphone`.\n","example":1,"title":"Minimum Repeat","type":"number"},"qscore":{"default":50,"description":"Quality threshold to filter out unreadable data. <br/>\nNo filtering is applied if the `quality-score` worker is not provided.\n","example":50,"format":"float","maximum":100,"minimum":0,"title":"Quality score","type":"number"},"search_in":{"default":["title","text"],"description":"Allows to define if the documents extraction has to be done by searching entity keywords in the title and/or in the text. <br/>\n*Example*: \n- `search_in: [\"title\", \"text\"]`\n\n**Note:**\n- This parameter is only applied on the keywords of entity, not on `keywords_exclude`, `co_mentions`, `neg_keywords`, `min_repeat`, `min_match`.\n- Not available with `ner-linking` worker.\n","items":{"example":["title","text"],"type":"string"},"title":"Search In","type":"array"},"sentiments_filter":{"description":"Partial object containing a min/max values for each sentiments. The end analysis will contains documents that match these filters. <br/> \n**Note:** This can be compared to a filter on: \n- `document_{sentiment}.mean` key for `positive`, `negative` and `neutral`\n- `document_{sentiment}` key for `polarity`\n","properties":{"negative":{"properties":{"max":{"description":"Maximum negative sentiment score. Accepted range is between 0 and 1.","maximum":1,"minimum":0,"title":"Maximum Negative","type":"number"},"min":{"description":"Minimum negative sentiment score. Accepted range is between 0 and 1.","maximum":1,"minimum":0,"title":"Minimum Negative","type":"number"}},"type":"object"},"neutral":{"properties":{"max":{"description":"Maximum neutral sentiment score. Accepted range is between 0 and 1.","maximum":1,"minimum":0,"title":"Maximum Neutral","type":"number"},"min":{"description":"Minimum neutral sentiment score. 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Should contain at least 'raw-matcher' or 'ner-linking'.","items":{"enum":["quality-score","ner-linking","raw-matcher","concept","entity-similarity","embedder-indicators"],"example":["quality-score","ner-linking","raw-matcher","concept","entity-similarity","embedder-indicators"],"type":"string"},"minimum":1,"title":"Workers","type":"array"}},"required":["end_date","entities","start_date","workers"],"title":"Analyze Dataset","type":"object"},"DownloadSchema":{"properties":{"concept":{"description":"Detected concept in the documents. This concept must be part of the instance.","example":"pollution","title":"Concept","type":"string"},"date":{"description":"Extract date of the documents. Must be within the instance's date range.","example":"2019-02-01","format":"date","title":"Date","type":"string"},"entity":{"description":"Detected entity in the documents. This entity must be part of the instance.","example":"sesamm","title":"Entity","type":"string"},"fields":{"description":"List of fields to be extracted in documents.","items":{"enum":["concepts","document_entity_negative","document_entity_neutral","document_entity_polarity","document_entity_positive","document_negative","document_neutral","document_polarity","document_positive","entities","extract_date","id","language","mentions","qscore","sentences","thread","title","url","summary"],"example":"title","type":"string"},"title":"Fields","type":"array"},"instance":{"description":"The identifier of an analysis. 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You can use the ASC and DESC keywords to specify ascending (smallest value first) or descending (largest value first) order","enum":["ASC","DESC"],"example":"ASC","title":"Order","type":"string"}},"title":"Sort","type":"object"}},"required":["instance","limit"],"title":"Analyze Download","type":"object"},"EntitiesBulkSchema":{"description":"You need to provide at least one value in *uuids* or *entitied_ids*.","example":{"entities_ids":["apple","sesamm"],"language":"english","properties_list":["chief_executive_officer","domain","founders","legal_name","subsidiaries","ticker"],"source":"corporate_kg","uuids":[]},"properties":{"entities_ids":{"example":["apple","sesamm"],"items":{"type":"string"},"title":"An array of the wanted entity ids.","type":"array"},"properties_list":{"description":"The properties to look for in the KG.<br/> If *source* is corporate_kg, defaults to *[ \"chief_executive_officer\", \"domain\", \"founders\", \"legal_name\", \"subsidiaries\", \"ticker\" ]*<br/>  If *source* is general_kg, defaults to the full list of properties corresponding to the entity provided.","items":{"type":"string"},"title":"Properties list parameter","type":"array"},"source":{"default":"corporate_kg","description":"The knowledge graph source.","enum":["general_kg","corporate_kg"],"example":"corporate_kg","title":"Kg source","type":"string"},"uuid":{"default":false,"description":"Whether to return company uuid or not.","example":false,"type":"boolean"},"uuids":{"description":"Array of companies uuids to look for.","example":["923e84d9-f307-0b5e-c8f8-2696b7c4a320"],"items":{"format":"uuid","type":"string"},"title":"Uuids","type":"array"}},"title":"KG Entities Bulk","type":"object"},"GetDocumentsSchema":{"example":{"documents":[{"extracted":"2022-12-30T22:59:57.502Z","id":"c34ac671a1b0b80078f9acd7e80217e28e8c554e14e1de707fb4370e52299add"},{"extracted":"2022-12-28T13:15:06.644Z","id":"0d285bcb024438d022c91d75556c4159786e72b7f3b4b3a22562ca9d1dbabb4a"}],"fields":["title","text"]},"properties":{"documents":{"description":"List of documents","items":{"properties":{"extracted":{"description":"The document's extraction date. 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See [Language Support](/guide/languages#translation) page for more information.","example":"italian","format":"language-code","title":"Target language","type":"string"}},"required":["document_id"],"title":"Documents Translate","type":"object"}},"securitySchemes":{"oAuth2Sesamm":{"description":"Use your user account to get access to the API","flows":{"authorizationCode":{"authorizationUrl":"https://login.textreveal.com/authorize","scopes":{},"tokenUrl":"https://login.textreveal.com/oauth/token"}},"type":"oauth2"}}},"externalDocs":{"description":"Find out more","url":"https://www.sesamm.com"},"info":{"contact":{"email":"support@sesamm.com","name":"TextReveal API support"},"description":"<img src=\"https://static.textreveal.com/images/logos/TextReveal.svg\" width=\"300px\" height=\"auto\" /> <br><br> TextReveal\u00ae's user journey starts with a fuzzy query (e.g., \"I am interested in investing in a specific company\"), and its final goal is to provide a structured signal (e.g. \"I now have access to structured, times-series indicators for this company\"). These processes turn text data into numerical information and are described below.","license":{"name":"Copyright \u00a9 SESAMm"},"title":"TextReveal\u00ae API","version":"2.0"},"openapi":"3.0.3","paths":{"/api/2.0/analyze/dataset":{"post":{"requestBody":{"content":{"application/json":{"examples":{"--":{"value":{"concepts":{"environment":["environmental impact","environmental controversy","pesticide"],"governance":["offshore transaction","dupery","humbug"],"pollution":["fuel leakage","greenhouse gases"],"social":["unscrupulous","inequality","malfeasance","workplace violence"]},"countries":["US","FR"],"end_date":"2019-02-01","entities":[{"context":"Apple is a technology company that designs, manufactures, and markets consumer electronics, personal computers, and software.","entity_of_interest":"apple","keywords":["Apple Inc.","Steve Wozniak","Apple Computer","Ron Wayne","AC Wellness","FileMaker","Braeburn Capital","David Pakman","AAPL","Apple","Steve Jobs","apple.com"]},{"context":"SESAMm is a fintech company that specializes in big data and artificial intelligence for investment.","entity_of_interest":"sesamm","keywords":["SESAMm SAS","Florian Aubry","SESAMm","Pierre Rinaldi","Sylvain Fort\u00e9","sesamm.com"]}],"languages":["english"],"qscore":90,"sentiments_filter":{"positive":{"min":0.5}},"similarity_threshold":0.5,"site_type":["news","blogs","discussions"],"sites_exclude":["apple.com"],"start_date":"2019-01-31","workers":["quality-score","concept","raw-matcher","ner-linking","entity-similarity","embedder-indicators"]}},"Generate concepts risk scores using NER":{"value":{"concepts":{"environment":["environmental impact","environmental controversy","pesticide"],"governance":["offshore transaction","dupery","humbug"],"pollution":["fuel leakage","greenhouse gases"],"social":["unscrupulous","inequality","malfeasance","workplace violence"]},"end_date":"2019-02-01","entities":[{"context":"Apple is a technology company that designs, manufactures, and markets consumer electronics, personal computers, and software.","entity_of_interest":"apple","keywords":["Apple Inc.","Steve Wozniak","Apple Computer","Ron Wayne","AC Wellness","FileMaker","Braeburn Capital","David Pakman","AAPL","Apple","Steve Jobs","apple.com"]},{"context":"SESAMm is a fintech company that specializes in big data and artificial intelligence for investment.","entity_of_interest":"sesamm","keywords":["SESAMm SAS","Florian Aubry","SESAMm","Pierre Rinaldi","Sylvain Fort\u00e9","sesamm.com"]}],"qscore":90,"start_date":"2019-01-31","workers":["quality-score","ner-linking","concept","entity-similarity"]}},"Generate concepts risk scores, sentiment and emotion indicators using NER":{"value":{"concepts":{"environment":["environmental impact","environmental controversy","pesticide"],"governance":["offshore transaction","dupery","humbug"],"pollution":["fuel leakage","greenhouse gases"],"social":["unscrupulous","inequality","malfeasance","workplace violence"]},"end_date":"2019-02-01","entities":[{"context":"Apple is a technology company that designs, manufactures, and markets consumer electronics, personal computers, and software.","entity_of_interest":"apple","keywords":["Apple Inc.","Steve Wozniak","Apple Computer","Ron Wayne","AC Wellness","FileMaker","Braeburn Capital","David Pakman","AAPL","Apple","Steve Jobs","apple.com"]},{"context":"SESAMm is a fintech company that specializes in big data and artificial intelligence for investment.","entity_of_interest":"sesamm","keywords":["SESAMm SAS","Florian Aubry","SESAMm","Pierre Rinaldi","Sylvain Fort\u00e9","sesamm.com"]}],"qscore":90,"start_date":"2019-01-31","workers":["quality-score","ner-linking","concept","entity-similarity","embedder-indicators"]}},"Generate sentiment and emotion indicators using NER":{"value":{"end_date":"2019-02-01","entities":[{"context":"Apple is a technology company that designs, manufactures, and markets consumer electronics, personal computers, and software.","entity_of_interest":"apple","keywords":["Apple Inc.","Steve Wozniak","Apple Computer","Ron Wayne","AC Wellness","FileMaker","Braeburn Capital","David Pakman","AAPL","Apple","Steve Jobs","apple.com"]},{"context":"SESAMm is a fintech company that specializes in big data and artificial intelligence for investment.","entity_of_interest":"sesamm","keywords":["SESAMm SAS","Florian Aubry","SESAMm","Pierre Rinaldi","Sylvain Fort\u00e9","sesamm.com"]}],"qscore":90,"start_date":"2019-01-31","workers":["quality-score","ner-linking","entity-similarity","embedder-indicators"]}},"Generate sentiment and emotion indicators using Raw-matcher and a similarity threshold":{"value":{"end_date":"2019-02-01","entities":[{"context":"an international retailer of body, face, fragrances and home products","entity_of_interest":"Q1880676","keywords":["OCCITANE","Occitane","Occitane en Provence","Occitane en Provence","occitane en provence","Olivier Baussan","Occitane En Provence"]},{"context":"Asclepius Ltd. 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Works like a boolean `AND`.\n*Example*: \n  - `keywords : [\"TotalEnergy\"]`\n  - `co_mentions: [\"gas\", \"oil price\"]`\n\n*Behavior:* TextReveal\u00ae API will look for documents relevant to at least one of the co_mentions. For the above example, below are the different cases of relevancy:\n - `TotalEnergy` and `gas`\n - `TotalEnergy` and `oil price`\n - `TotalEnergy` and `oil price` and `gas`\n\n*N.B*: Search of `co_mentions` is operated in full-text and is case insensitive.\n","items":{"example":["tablets"],"type":"string"},"title":"Co Mentions","type":"array"},"concepts":{"additionalProperties":{"description":"List of keywords for the concept","example":"social","items":{"example":["inequality"],"type":"string"},"type":"array"},"description":"List of concepts or risks that are to be analyzed. Each individual concept is defined by its own list of keywords.<br/> Punctuation is not handled in the concept labels. 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The end analysis will contains documents that match these filters. <br/> \n**Note:** This can be compared to a filter on: \n- `document_{sentiment}.mean` key for `positive`, `negative` and `neutral`\n- `document_{sentiment}` key for `polarity`\n","properties":{"negative":{"properties":{"max":{"description":"Maximum negative sentiment score. Accepted range is between 0 and 1.","maximum":1,"minimum":0,"title":"Maximum Negative","type":"number"},"min":{"description":"Minimum negative sentiment score. Accepted range is between 0 and 1.","maximum":1,"minimum":0,"title":"Minimum Negative","type":"number"}},"type":"object"},"neutral":{"properties":{"max":{"description":"Maximum neutral sentiment score. Accepted range is between 0 and 1.","maximum":1,"minimum":0,"title":"Maximum Neutral","type":"number"},"min":{"description":"Minimum neutral sentiment score. 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Should contain at least 'raw-matcher' or 'ner-linking'.","items":{"enum":["quality-score","ner-linking","raw-matcher","concept","entity-similarity","embedder-indicators"],"example":["quality-score","ner-linking","raw-matcher","concept","entity-similarity","embedder-indicators"],"type":"string"},"minimum":1,"title":"Workers","type":"array"}},"required":["end_date","entities","start_date","workers"],"title":"Analyze Dataset","type":"object"}}},"description":"Dataset Schema"},"responses":{"200":{"content":{"application/json":{"schema":{"example":{"instance":"a62caf56-5961-4fff-ba2e-6d4dcf98960f"},"properties":{"instance":{"description":"The identifier of an analysis. 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Allowed site types: ['blogs', 'news', 'discussions', 'premium_news'].","type":"string"},"statusCode":{"example":403,"type":"integer"}},"type":"object"}},"type":"object"}}},"description":"Forbidden"},"404":{"content":{"application/json":{"schema":{"properties":{"value":{"example":"string","type":"string"}},"type":"object"}}},"description":"Not Found"},"429":{"content":{"application/json":{"schema":{"properties":{"value":{"example":"string","type":"string"}},"type":"object"}}},"description":"Too Many Requests"},"500":{"content":{"application/json":{"schema":{"properties":{"value":{"example":"string","type":"string"}},"type":"object"}}},"description":"Request failed"}},"security":[{"oAuth2Sesamm":[]}],"summary":"Create a granular dataset in a secure web server for multiple Entities.","tags":["Analyze"]}},"/api/2.0/analyze/download":{"post":{"parameters":[{"in":"query","name":"json_lines","schema":{"description":"Set to true to download result in json lines format.","type":"boolean"}}],"requestBody":{"content":{"application/json":{"schema":{"properties":{"concept":{"description":"Detected concept in the documents. 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You can use the ASC and DESC keywords to specify ascending (smallest value first) or descending (largest value first) order","enum":["ASC","DESC"],"example":"ASC","title":"Order","type":"string"}},"title":"Sort","type":"object"}},"required":["instance","limit"],"title":"Analyze Download","type":"object"}}},"description":"Download Schema"},"responses":{"200":{"content":{"application/json":{"examples":{"--":{"value":[{"concepts":{},"document_entity_negative":{"apple":{"max":0.9670407,"mean":0.497277776,"median":0.40673238,"min":0.17257427}},"document_entity_neutral":{"apple":{"max":0.5155762,"mean":0.285450036,"median":0.310295895,"min":0.0075512277}},"document_entity_polarity":{"apple":-0.39186286},"document_entity_positive":{"apple":{"max":0.31184947,"mean":0.217272184,"median":0.28185567,"min":0.025408149}},"document_negative":{"max":0.9670407,"mean":0.47984254066667,"median":0.42040768,"min":0.044773154},"document_neutral":{"max":0.52536553,"mean":0.26162332989048,"median":0.28505275,"min":0.0075512277},"document_polarity":-0.29972293,"document_positive":{"max":0.6805551,"mean":0.25853412119048,"median":0.28185567,"min":0.025408149},"entities":{"apple":[{"Apple":5}]},"extract_date":"2019-02-01 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accidentally triggering the LED flashlight buttons on their iPhone X and iPhone XS smartphones.","type":0},{"entities":[],"matches":[],"results":{"anger":0.04590232,"anticipation":0.6254213,"fear":0.09198925,"joy":0.067284614,"negative":0.3540335,"neutral":0.3094324,"polarity":-0.025340585,"polarity_exp":0.49562526,"positive":0.3365341,"sadness":0.025783245,"surprise":0.0912158,"trust":0.052403588},"sentence_id":1,"text":"They want to change the button right now.","type":0},{"entities":[],"matches":[{"class":"mentions","count":{"apple":1},"entity_id":"apple","entity_type":null,"label":null,"similarity":0.735459}],"results":{"anger":0.07085259,"anticipation":0.7368077,"fear":0.012537896,"joy":0.12224379,"negative":0.43085948,"neutral":0.28505275,"polarity":-0.20529026,"polarity_exp":0.4633728,"positive":0.28408778,"sadness":0.012477765,"surprise":0.040162556,"trust":0.004917645},"sentence_id":2,"text":"| TIMESOFINDIA.COM | Updated: Feb 1, 2019, 11:45AM IST NEW DELHI: If you are an Apple iPhone X or iPhone XS user and have often wondered how your smartphone\u2019s LED flashlight turns on without you doing anything, you are definitely not alone.","type":0},{"entities":["apple"],"matches":[{"class":"entity","count":null,"entity_id":"apple","entity_type":"ORG","label":"Apple","similarity":0.741567},{"class":"mentions","count":{"apple":1},"entity_id":"apple","entity_type":null,"label":null,"similarity":0.741567}],"results":{"anger":0.046930943,"anticipation":0.45820284,"fear":0.009315267,"joy":0.24439734,"negative":0.17257427,"neutral":0.5155762,"polarity":0.28750697,"polarity_exp":0.5347626,"positive":0.31184947,"sadness":0.006900535,"surprise":0.21061417,"trust":0.023638977},"sentence_id":3,"text":"Several iPhone X and iPhone XS users have taken it to Apple\u2019s discussion forum, talking about 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That feature and others such as an improved floppy drive design and a low-cost hard drive that made data retrieval faster helped Apple cultivate a reputation for innovation.\n\n\nApple was named as the most admired company in the United States in 2008 and in the world from 2008 to 2012 by the Fortune magazine.\n\n\nThe company was founded by Steven Paul Jobs, Steve Wozniak, and Ronald Gerald Wayne on April 1, 1976, and is headquartered in Cupertino, California.","employee_count":"10000+","founded_on":"1976-04-01T00:00:00.000Z","funding_total":6180230000,"ipo_status":"public","last_funding_type":"post_ipo_equity","legal_name":"Apple Inc.","operating_status":"active","revenue_range":"10B+","sectors":["Consumer Electronics","Hardware","Mobile","Platforms","Software"],"status":"ipo","sub_sectors":["Consumer Electronics","Hardware","Mobile Devices","Operating Systems","Wearables"]}},"SESAMm (923e84d9-f307-0b5e-c8f8-2696b7c4a320) information":{"value":{"aliases":["SESAMm 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available sectors with the associated sub-sectors in the Corporate Knowledge Graph.","tags":["Knowledge Graph"]}}},"servers":[{"url":"https://api.textreveal.com"}],"tags":[{"description":"Launch custom Natural Language Processing (NLP) pipelines and retrieve timeseries of indicators","name":"Analyze"},{"description":"Use Knowledge Graph (KG) routes to retrieve data information before analysis","name":"Knowledge Graph"},{"description":"Use documents routes to perform actions on SESAMm's datalake documents","name":"Documents"}]}