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| {"result": "**Output:**\n\n<|COMPLETE|>", "input": "\n-Target activity-\nYou are an intelligent assistant that helps a human analyst to analyze claims against certain entities presented in a text document.\n\n-Goal-\nGiven a text document that is potentially relevant to this activity, an entity specification, and a claim description, extract all entities that match the entity specification and all claims against those entities.\n\n-Steps-\n1. Extract all named entities that match the predefined entity specification. Entity specification can either be a list of entity names or a list of entity types.\n2. For each entity identified in step 1, extract all claims associated with the entity. Claims need to match the specified claim description, and the entity should be the subject of the claim.\nFor each claim, extract the following information:\n- Subject: name of the entity that is subject of the claim, capitalized. The subject entity is one that committed the action described in the claim. Subject needs to be one of the named entities identified in step 1.\n- Object: name of the entity that is object of the claim, capitalized. The object entity is one that either reports/handles or is affected by the action described in the claim. If object entity is unknown, use **NONE**.\n- Claim Type: overall category of the claim, capitalized. Name it in a way that can be repeated across multiple text inputs, so that similar claims share the same claim type\n- Claim Status: **TRUE**, **FALSE**, or **SUSPECTED**. TRUE means the claim is confirmed, FALSE means the claim is found to be False, SUSPECTED means the claim is not verified.\n- Claim Description: Detailed description explaining the reasoning behind the claim, together with all the related evidence and references.\n- Claim Date: Period (start_date, end_date) when the claim was made. Both start_date and end_date should be in ISO-8601 format. If the claim was made on a single date rather than a date range, set the same date for both start_date and end_date. If date is unknown, return **NONE**.\n- Claim Source Text: List of **all** quotes from the original text that are relevant to the claim.\n\nFormat each claim as (<subject_entity><|><object_entity><|><claim_type><|><claim_status><|><claim_start_date><|><claim_end_date><|><claim_description><|><claim_source>)\n\n3. Return output in English as a single list of all the claims identified in steps 1 and 2. Use **##** as the list delimiter.\n\n4. When finished, output <|COMPLETE|>\n\n-Examples-\nExample 1:\nEntity specification: organization\nClaim description: red flags associated with an entity\nText: According to an article on 2022/01/10, Company A was fined for bid rigging while participating in multiple public tenders published by Government Agency B. The company is owned by Person C who was suspected of engaging in corruption activities in 2015.\nOutput:\n\n(COMPANY A<|>GOVERNMENT AGENCY B<|>ANTI-COMPETITIVE PRACTICES<|>TRUE<|>2022-01-10T00:00:00<|>2022-01-10T00:00:00<|>Company A was found to engage in anti-competitive practices because it was fined for bid rigging in multiple public tenders published by Government Agency B according to an article published on 2022/01/10<|>According to an article published on 2022/01/10, Company A was fined for bid rigging while participating in multiple public tenders published by Government Agency B.)\n<|COMPLETE|>\n\nExample 2:\nEntity specification: Company A, Person C\nClaim description: red flags associated with an entity\nText: According to an article on 2022/01/10, Company A was fined for bid rigging while participating in multiple public tenders published by Government Agency B. The company is owned by Person C who was suspected of engaging in corruption activities in 2015.\nOutput:\n\n(COMPANY A<|>GOVERNMENT AGENCY B<|>ANTI-COMPETITIVE PRACTICES<|>TRUE<|>2022-01-10T00:00:00<|>2022-01-10T00:00:00<|>Company A was found to engage in anti-competitive practices because it was fined for bid rigging in multiple public tenders published by Government Agency B according to an article published on 2022/01/10<|>According to an article published on 2022/01/10, Company A was fined for bid rigging while participating in multiple public tenders published by Government Agency B.)\n##\n(PERSON C<|>NONE<|>CORRUPTION<|>SUSPECTED<|>2015-01-01T00:00:00<|>2015-12-30T00:00:00<|>Person C was suspected of engaging in corruption activities in 2015<|>The company is owned by Person C who was suspected of engaging in corruption activities in 2015)\n<|COMPLETE|>\n\n-Real Data-\nUse the following input for your answer.\nEntity specification: ['organization', 'person', 'geo', 'event']\nClaim description: Extract baggage measurements, weight limits, and restrictions from airline documentation.\nText: was damaged or you are missing items from your suitcase, you must contact us within 7 days from the day you received your baggage.\nIn the event of a delay in receiving your baggage outside your country of residence, you must contact us within 21 days from the day you received your baggage.\nIn the event of lost baggage, you must contact us after 21 days from the day of the incident.\nWhen contacting us, please attach a copy of the following documents to your claim and hold onto the originals:\n\nFlight tickets\nBoarding passes\nBaggage tags (the stickers affixed to the flight ticket and/or the object)\nLost or damaged baggage report from the airport\nReceipts that support the claim \n \n\nPlease note that the claim will be handled in accordance with the terms of the contract of carriage and in accordance with international conventions and laws, which determine the carrier's liability. EL AL Israel Airlines reserves the right to refuse to accept liability if the claim concerns, either wholly or in part, fragile or perishable items, food, liquids, cash, jewelry, cameras, computers, video devices, electronics, negotiable instruments or securities, legacies, antiques, valuable items, works of art, gold and silver items, rare books or publications, business documents, precious metals or other valuables.\nOutput:", "parameters": {"model": "gpt-4o-mini", "temperature": 0.0, "frequency_penalty": 0.0, "presence_penalty": 0.0, "top_p": 1.0, "max_tokens": 4000, "n": 1}, "history": null} |