Smart logistics

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is RE: Relation Extraction.

Here is an example of task execution:

{'Schema': [{'designed': {'domain': 'Person', 'range': 'Structure'}}, {'located_in': {'domain': 'Structure', 'range': 'Location'}}, {'part_of': {'domain': 'City', 'range': 'Country'}}, {'friends_with': {'domain': 'Person', 'range': 'Person'}}, {'lives_at': {'domain': 'Person', 'range': 'Location'}}, {'visits': {'domain': 'Person', 'range': 'Location'}}, {'accompanied_by': {'domain': 'Person', 'range': 'Person'}}, {'shares': {'domain': 'Person', 'range': 'Product'}}], 'Text': 'Gustave Eiffel designed the Eiffel Tower, which is located in Paris, France.', 'Relations': [['Gustave Eiffel', 'designed', 'Eiffel Tower'], ['Eiffel Tower', 'located_in', 'Paris'], ['Paris', 'part_of', 'France']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Subject", "Relation", "Object"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: [{"part_of": {"domain": "Organization", "range": "Organization"}}, {"parent_company_of": {"domain": "Organization", "range": "Organization"}}, {"subsidiary_of": {"domain": "Organization", "range": "Organization"}}, {"acquired": {"domain": "Organization", "range": "Organization"}}, {"divested": {"domain": "Organization", "range": "Organization"}}, {"owns_brand": {"domain": "Organization", "range": "Product/Brand"}}, {"holds_stake_in": {"domain": "Organization", "range": "Organization"}}, {"spun_off": {"domain": "Organization", "range": "Organization"}}, {"formed_from": {"domain": "Organization", "range": "Organization"}}, {"founded_by": {"domain": "Organization", "range": "Person"}}, {"has_CEO": {"domain": "Organization", "range": "Person"}}, {"manufactures": {"domain": "Organization", "range": "ProductType"}}, {"develops": {"domain": "Organization", "range": "ProductType"}}, {"produces": {"domain": "Organization", "range": "ProductType"}}, {"sells": {"domain": "Organization", "range": "ProductType"}}, {"has_product_line": {"domain": "Organization", "range": "Product/Brand"}}, {"is_a_type_of": {"domain": "Product/Brand", "range": "ProductType"}}, {"is_brand_of": {"domain": "Product/Brand", "range": "Organization"}}, {"features_technology": {"domain": "Product/Brand", "range": "Technology"}}, {"uses_material": {"domain": "Product/Brand", "range": "Material"}}, {"launched_product": {"domain": "Organization", "range": "Product/Brand"}}, {"had_revenue_of": {"domain": "Organization", "range": "Amount"}}, {"had_profit_of": {"domain": "Organization", "range": "Amount"}}, {"in_year": {"domain": "FinancialMetric", "range": "Year"}}, {"market_value_of": {"domain": "Organization", "range": "Amount"}}, {"is_publicly_traded": {"domain": "Organization", "range": "Boolean"}}, {"listed_on_exchange": {"domain": "Organization", "range": "StockExchange"}}, {"experienced_growth": {"domain": "Organization", "range": "FinancialMetric"}}, {"occurred_in_year": {"domain": "Event/Action", "range": "Year"}}, {"occurred_on_date": {"domain": "Event/Action", "range": "SpecificDate"}}, {"resulted_in": {"domain": "Event/Action", "range": "Outcome"}}, {"preceded": {"domain": "Event/Action", "range": "Event/Action"}}, {"followed_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"marked_milestone": {"domain": "Event/Action", "range": "Organization"}}, {"influenced_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"led_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"was_a_response_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"has_trademark": {"domain": "Organization", "range": "Trademark"}}, {"uses_logo": {"domain": "Organization", "range": "Logo"}}, {"acquired_trademark_from": {"domain": "Organization", "range": "Organization"}}, {"is_known_for": {"domain": "Organization", "range": "Characteristic"}}, {"launched_campaign": {"domain": "Organization", "range": "BusinessConcept"}}]
Text: article: Alibaba_Group, Smart logistics: In 2013, Alibaba and six large Chinese logistics companies (including SF Express) established a company calledCainiaofor delivery of packages in China. This network gradually grew to 14 local logistics companies in 2014.In 2016, Alibaba'sTaobaoandTmall, two of the world's largest and most popular online retail marketplaces, achieved a total transaction volume of 3 trillion yuan (US$478.6 billion). The company aims to double the transaction volume to 6 trillion yuan by 2020. As of February 2018[update], Taobao reached 580 millionmonthly active users, while Tmall achieved 500 million monthly active users.It is also rapidly expanding its e-commerce network abroad.Alibaba has also announced that it will invest 100 billion yuan over five years to build a global logistics network, underpinning an aggressive overseas expansion, and demonstrating Alibaba's commitment to building the most efficient logistics network in China and around the world. It is investing a further 5.3 billion yuan inCainiaoLogistics to boost its stake to 51 percent from 47 percent.The investment would value Cainiao, a joint venture of top Chinese logistics firms, at around US$20 billion. Alibaba usesCainiaosoftware at its Belgian-European sales hub. The software is able to access data about retailers, products, transport details and flows, a person familiar with the company's IT systems told the British newspaperFinancial Times. Chinese companies are legally obliged to pass on their data to China's authorities and security services.The BelgiumState Security Serviceis monitoring the hub in Lütich because of this fact and possibleespionage.According to theFinancial Times, Cainiao denied suggestions of wrongdoing, noting that the firm operates in compliance with relevant laws and regulations. According to theReuters, Alibaba Group Holding Ltd has divested its logistics arm for $8.5 billion to a consortium led by investment firmsBoyu CapitalandPrimavera Capital Group.

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company product service industry brand country location organization person founder position event action founding accusition merger partnership expansion restructuring divestment sale bankruptcy financial_metric business_concept revenue profit loss investment funding market_share competition market_trend regulation innovation sustainability corporate_social_responsibility award date/time year period

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is NER: Named Entity Recognition.

Here is an example of task execution:

{'Schema': ['Person', 'Organization', 'Location', 'Date', 'Product'], 'Text': 'The Eiffel Tower in Paris, designed by Gustave Eiffel, is one of the most famous landmarks in France.', 'Entities': [['Eiffel Tower', 'Location'], ['Paris', 'Location'], ['Gustave Eiffel', 'Person'], ['France', 'Location']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Entity", "Type"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: ["company", "product", "service", "industry", "brand", "country", "location", "organization", "person", "founder", "position", "event", "action", "founding", "accusition", "merger", "partnership", "expansion", "restructuring", "divestment", "sale", "bankruptcy", "financial_metric", "business_concept", "revenue", "profit", "loss", "investment", "funding", "market_share", "competition", "market_trend", "regulation", "innovation", "sustainability", "corporate_social_responsibility", "award", "date/time", "year", "period"]
Text: article: Alibaba_Group, Cloud computing and artificial intelligence technology: In conjunction with the company's 10th anniversary, Alibaba launchedAlibaba Cloudin September 2009, aiming to build a cloud computing service platform, including e-commerce data mining, e-commerce data processing, and data customization.It has R&D centres and operators in Hangzhou, Beijing, Hong Kong, Singapore, Silicon Valleyand Dubai.In July 2014, Alibaba Cloud entered into a partnership deal with Inspur. Alibaba Cloud is the largest high-end cloud computing company in China.In 2009, Alibaba acquired HiChina, the largest domain registration service and web hosting service company in China, and built it into Alibaba Cloud.On 28 July 2011, Alibaba Cloud releasedAliOS(formerlyYun OSandAliyun OS), aLinux distributiondesigned for mobile devices.In the 2017 Computing Conference in Hangzhou, Alibaba launchedAliGenie, a China-based open-platform intelligent personal assistant. It is currently used in theTmall Geniesmart speaker. In 2018, Alibaba's Wanli Min presentedCity Brain,a technology geared towards urban solutions such as streamlining traffic, detecting accidents and improving transport efficiency. China's government designated Alibaba as one of its "AIchampions" in 2018.: 281 On 27 July 2019, Alibaba unveiled a64-bitRISC-Vprocessorcalled the XuanTie-910 (Black Iron 910). It is a12 nm16-corewith a clockrate of 2.5 GHz, and was designed by Alibaba's subsidiary T-Head (also known as Pingtouge). Alibaba claim the Xuantie-910 is faster than theARM Cortex-A73and is capable of 7.1 Coremark/MHz. On 25 September 2019, Alibaba announced anAI acceleratorcalled the Hanguang 800. The Hanguang 800 contains 17 billion transistors built with a12 nmprocess and was designed by T-Head and DAMO Academy (Alibaba's research team). Alibaba claim it is capable of 78,563 images per second (IPS) inference and 500 IPS/W in ResNet-50. The Hanguang 800 will be available to be rented on Alibaba Cloud. In April 2023, Alibaba revealed its plans to releaseTongyi Qianwen, a ChatGPT-like chatbot. Its name means "seeking an answer by asking a thousand questions". This AI product, which can support both English and Chinese languages, will be incorporated into the company's various business operations. It will initially be integrated into the messaging app, DingTalk, and the voice-activated smart speaker, Tmall Genie. According to Alibaba, drafting emails, creating business proposals, and converting meeting dialogues into written notes are among Tongyi Qianwen's capabilities. Media reported that the company has received more than 200,000 requests from businesses to join its beta testing program, from industries as varied as fintech, electronics, transport, fashion and dairy farming as of April 2023.Alibaba is also integrating Tongyi Qianwen into a digital assistant called Tingwu. Tongyi Tingwu, the AI-powered assistant, can analyze multimedia content and generate a text summary from video and audio files. In November 2024, Alibaba unveiled QwQ-32B-Preview, a groundbreaking 32.5 billion parameter AI reasoning model that challenges OpenAI's o1 series by demonstrating superior performance on AIME and MATH benchmark.This innovative model, developed by Alibaba's Qwen team, can process prompts up to 32,000 words long and features a unique self-fact-checking mechanism that allows it to solve complex logic puzzles and mathematical problems.While impressive, the model is not without limitations, as it may unexpectedly switch languages, get stuck in reasoning loops, and struggle with common sense reasoning.Notably, the model is available under an Apache 2.0 license on Hugging Face, making it commercially accessible, though only certain components have been released.Its development comes amid growing skepticism about traditional AI scaling laws and represents a new approach to AI reasoning that involves giving models more processing time to complete tasks. In April 2025, Alibaba Cloud release Wan 2.1-FLF2V-14B Artificial Intelligence Video Generation Model under Apache license. In December 2020,The New York Timesreported that Alibaba had developed and marketed facial recognition and surveillance software configured to detectUyghurfaces and those of otherethnic minorities in China.Alibaba responded that they "do not and will not permit our technology to be used to target or identify specific ethnic groups" and that it was "dismayed to learn" that its Alibaba Cloud subsidiary had developed this feature,defending that the technology was developed "in a testing environment" and that it "was not deployed by any customer."However,IPVMreported in December 2020 that Alibaba refused to provide any proof the Uyghur recognition feature was just a "test" or "trial" and that Alibaba's own website showed Uyghur recognition as a live feature.

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Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is RE: Relation Extraction.

Here is an example of task execution:

{'Schema': [{'designed': {'domain': 'Person', 'range': 'Structure'}}, {'located_in': {'domain': 'Structure', 'range': 'Location'}}, {'part_of': {'domain': 'City', 'range': 'Country'}}, {'friends_with': {'domain': 'Person', 'range': 'Person'}}, {'lives_at': {'domain': 'Person', 'range': 'Location'}}, {'visits': {'domain': 'Person', 'range': 'Location'}}, {'accompanied_by': {'domain': 'Person', 'range': 'Person'}}, {'shares': {'domain': 'Person', 'range': 'Product'}}], 'Text': 'Gustave Eiffel designed the Eiffel Tower, which is located in Paris, France.', 'Relations': [['Gustave Eiffel', 'designed', 'Eiffel Tower'], ['Eiffel Tower', 'located_in', 'Paris'], ['Paris', 'part_of', 'France']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Subject", "Relation", "Object"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: [{"part_of": {"domain": "Organization", "range": "Organization"}}, {"parent_company_of": {"domain": "Organization", "range": "Organization"}}, {"subsidiary_of": {"domain": "Organization", "range": "Organization"}}, {"acquired": {"domain": "Organization", "range": "Organization"}}, {"divested": {"domain": "Organization", "range": "Organization"}}, {"owns_brand": {"domain": "Organization", "range": "Product/Brand"}}, {"holds_stake_in": {"domain": "Organization", "range": "Organization"}}, {"spun_off": {"domain": "Organization", "range": "Organization"}}, {"formed_from": {"domain": "Organization", "range": "Organization"}}, {"founded_by": {"domain": "Organization", "range": "Person"}}, {"has_CEO": {"domain": "Organization", "range": "Person"}}, {"manufactures": {"domain": "Organization", "range": "ProductType"}}, {"develops": {"domain": "Organization", "range": "ProductType"}}, {"produces": {"domain": "Organization", "range": "ProductType"}}, {"sells": {"domain": "Organization", "range": "ProductType"}}, {"has_product_line": {"domain": "Organization", "range": "Product/Brand"}}, {"is_a_type_of": {"domain": "Product/Brand", "range": "ProductType"}}, {"is_brand_of": {"domain": "Product/Brand", "range": "Organization"}}, {"features_technology": {"domain": "Product/Brand", "range": "Technology"}}, {"uses_material": {"domain": "Product/Brand", "range": "Material"}}, {"launched_product": {"domain": "Organization", "range": "Product/Brand"}}, {"had_revenue_of": {"domain": "Organization", "range": "Amount"}}, {"had_profit_of": {"domain": "Organization", "range": "Amount"}}, {"in_year": {"domain": "FinancialMetric", "range": "Year"}}, {"market_value_of": {"domain": "Organization", "range": "Amount"}}, {"is_publicly_traded": {"domain": "Organization", "range": "Boolean"}}, {"listed_on_exchange": {"domain": "Organization", "range": "StockExchange"}}, {"experienced_growth": {"domain": "Organization", "range": "FinancialMetric"}}, {"occurred_in_year": {"domain": "Event/Action", "range": "Year"}}, {"occurred_on_date": {"domain": "Event/Action", "range": "SpecificDate"}}, {"resulted_in": {"domain": "Event/Action", "range": "Outcome"}}, {"preceded": {"domain": "Event/Action", "range": "Event/Action"}}, {"followed_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"marked_milestone": {"domain": "Event/Action", "range": "Organization"}}, {"influenced_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"led_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"was_a_response_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"has_trademark": {"domain": "Organization", "range": "Trademark"}}, {"uses_logo": {"domain": "Organization", "range": "Logo"}}, {"acquired_trademark_from": {"domain": "Organization", "range": "Organization"}}, {"is_known_for": {"domain": "Organization", "range": "Characteristic"}}, {"launched_campaign": {"domain": "Organization", "range": "BusinessConcept"}}]
Text: article: Alibaba_Group, Cloud computing and artificial intelligence technology: In conjunction with the company's 10th anniversary, Alibaba launchedAlibaba Cloudin September 2009, aiming to build a cloud computing service platform, including e-commerce data mining, e-commerce data processing, and data customization.It has R&D centres and operators in Hangzhou, Beijing, Hong Kong, Singapore, Silicon Valleyand Dubai.In July 2014, Alibaba Cloud entered into a partnership deal with Inspur. Alibaba Cloud is the largest high-end cloud computing company in China.In 2009, Alibaba acquired HiChina, the largest domain registration service and web hosting service company in China, and built it into Alibaba Cloud.On 28 July 2011, Alibaba Cloud releasedAliOS(formerlyYun OSandAliyun OS), aLinux distributiondesigned for mobile devices.In the 2017 Computing Conference in Hangzhou, Alibaba launchedAliGenie, a China-based open-platform intelligent personal assistant. It is currently used in theTmall Geniesmart speaker. In 2018, Alibaba's Wanli Min presentedCity Brain,a technology geared towards urban solutions such as streamlining traffic, detecting accidents and improving transport efficiency. China's government designated Alibaba as one of its "AIchampions" in 2018.: 281 On 27 July 2019, Alibaba unveiled a64-bitRISC-Vprocessorcalled the XuanTie-910 (Black Iron 910). It is a12 nm16-corewith a clockrate of 2.5 GHz, and was designed by Alibaba's subsidiary T-Head (also known as Pingtouge). Alibaba claim the Xuantie-910 is faster than theARM Cortex-A73and is capable of 7.1 Coremark/MHz. On 25 September 2019, Alibaba announced anAI acceleratorcalled the Hanguang 800. The Hanguang 800 contains 17 billion transistors built with a12 nmprocess and was designed by T-Head and DAMO Academy (Alibaba's research team). Alibaba claim it is capable of 78,563 images per second (IPS) inference and 500 IPS/W in ResNet-50. The Hanguang 800 will be available to be rented on Alibaba Cloud. In April 2023, Alibaba revealed its plans to releaseTongyi Qianwen, a ChatGPT-like chatbot. Its name means "seeking an answer by asking a thousand questions". This AI product, which can support both English and Chinese languages, will be incorporated into the company's various business operations. It will initially be integrated into the messaging app, DingTalk, and the voice-activated smart speaker, Tmall Genie. According to Alibaba, drafting emails, creating business proposals, and converting meeting dialogues into written notes are among Tongyi Qianwen's capabilities. Media reported that the company has received more than 200,000 requests from businesses to join its beta testing program, from industries as varied as fintech, electronics, transport, fashion and dairy farming as of April 2023.Alibaba is also integrating Tongyi Qianwen into a digital assistant called Tingwu. Tongyi Tingwu, the AI-powered assistant, can analyze multimedia content and generate a text summary from video and audio files. In November 2024, Alibaba unveiled QwQ-32B-Preview, a groundbreaking 32.5 billion parameter AI reasoning model that challenges OpenAI's o1 series by demonstrating superior performance on AIME and MATH benchmark.This innovative model, developed by Alibaba's Qwen team, can process prompts up to 32,000 words long and features a unique self-fact-checking mechanism that allows it to solve complex logic puzzles and mathematical problems.While impressive, the model is not without limitations, as it may unexpectedly switch languages, get stuck in reasoning loops, and struggle with common sense reasoning.Notably, the model is available under an Apache 2.0 license on Hugging Face, making it commercially accessible, though only certain components have been released.Its development comes amid growing skepticism about traditional AI scaling laws and represents a new approach to AI reasoning that involves giving models more processing time to complete tasks. In April 2025, Alibaba Cloud release Wan 2.1-FLF2V-14B Artificial Intelligence Video Generation Model under Apache license. In December 2020,The New York Timesreported that Alibaba had developed and marketed facial recognition and surveillance software configured to detectUyghurfaces and those of otherethnic minorities in China.Alibaba responded that they "do not and will not permit our technology to be used to target or identify specific ethnic groups" and that it was "dismayed to learn" that its Alibaba Cloud subsidiary had developed this feature,defending that the technology was developed "in a testing environment" and that it "was not deployed by any customer."However,IPVMreported in December 2020 that Alibaba refused to provide any proof the Uyghur recognition feature was just a "test" or "trial" and that Alibaba's own website showed Uyghur recognition as a live feature.

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