data/load_datasets.py

from datasets import load_dataset

# Load datasets for evaluation
# This script loads various datasets for evaluation purposes, including finance, legal, KILT, and Natural Questions (NQ).

# Finance dataset
ds_finance = load_dataset("PatronusAI/financebench")

# Legal dataset
ds_legal = load_dataset("nguha/legalbench","canada_tax_court_outcomes")
# Possible datasets in LegalBench:
# ['abercrombie', 'canada_tax_court_outcomes', 'citation_prediction_classification', 'citation_prediction_open', 'consumer_contracts_qa', 'contract_nli_confidentiality_of_agreement', 'contract_nli_explicit_identification', 'contract_nli_inclusion_of_verbally_conveyed_information', 'contract_nli_limited_use', 'contract_nli_no_licensing', 'contract_nli_notice_on_compelled_disclosure', 'contract_nli_permissible_acquirement_of_similar_information', 'contract_nli_permissible_copy', 'contract_nli_permissible_development_of_similar_information', 'contract_nli_permissible_post-agreement_possession', 'contract_nli_return_of_confidential_information', 'contract_nli_sharing_with_employees', 'contract_nli_sharing_with_third-parties', 'contract_nli_survival_of_obligations', 'contract_qa', 'corporate_lobbying', 'cuad_affiliate_license-licensee', 'cuad_affiliate_license-licensor', 'cuad_anti-assignment', 'cuad_audit_rights', 'cuad_cap_on_liability', 'cuad_change_of_control', 'cuad_competitive_restriction_exception', 'cuad_covenant_not_to_sue', 'cuad_effective_date', 'cuad_exclusivity', 'cuad_expiration_date', 'cuad_governing_law', 'cuad_insurance', 'cuad_ip_ownership_assignment', 'cuad_irrevocable_or_perpetual_license', 'cuad_joint_ip_ownership', 'cuad_license_grant', 'cuad_liquidated_damages', 'cuad_minimum_commitment', 'cuad_most_favored_nation', 'cuad_no-solicit_of_customers', 'cuad_no-solicit_of_employees', 'cuad_non-compete', 'cuad_non-disparagement', 'cuad_non-transferable_license', 'cuad_notice_period_to_terminate_renewal', 'cuad_post-termination_services', 'cuad_price_restrictions', 'cuad_renewal_term', 'cuad_revenue-profit_sharing', 'cuad_rofr-rofo-rofn', 'cuad_source_code_escrow', 'cuad_termination_for_convenience', 'cuad_third_party_beneficiary', 'cuad_uncapped_liability', 'cuad_unlimited-all-you-can-eat-license', 'cuad_volume_restriction', 'cuad_warranty_duration', 'definition_classification', 'definition_extraction', 'diversity_1', 'diversity_2', 'diversity_3', 'diversity_4', 'diversity_5', 'diversity_6', 'function_of_decision_section', 'hearsay', 'insurance_policy_interpretation', 'international_citizenship_questions', 'jcrew_blocker', 'learned_hands_benefits', 'learned_hands_business', 'learned_hands_consumer', 'learned_hands_courts', 'learned_hands_crime', 'learned_hands_divorce', 'learned_hands_domestic_violence', 'learned_hands_education', 'learned_hands_employment', 'learned_hands_estates', 'learned_hands_family', 'learned_hands_health', 'learned_hands_housing', 'learned_hands_immigration', 'learned_hands_torts', 'learned_hands_traffic', 'legal_reasoning_causality', 'maud_ability_to_consummate_concept_is_subject_to_mae_carveouts', 'maud_accuracy_of_fundamental_target_rws_bringdown_standard', 'maud_accuracy_of_target_capitalization_rw_(outstanding_shares)_bringdown_standard_answer', 'maud_accuracy_of_target_general_rw_bringdown_timing_answer', 'maud_additional_matching_rights_period_for_modifications_(cor)', 'maud_application_of_buyer_consent_requirement_(negative_interim_covenant)', 'maud_buyer_consent_requirement_(ordinary_course)', 'maud_change_in_law__subject_to_disproportionate_impact_modifier', 'maud_changes_in_gaap_or_other_accounting_principles__subject_to_disproportionate_impact_modifier', 'maud_cor_permitted_in_response_to_intervening_event', 'maud_cor_permitted_with_board_fiduciary_determination_only', 'maud_cor_standard_(intervening_event)', 'maud_cor_standard_(superior_offer)', 'maud_definition_contains_knowledge_requirement_-_answer', 'maud_definition_includes_asset_deals', 'maud_definition_includes_stock_deals', 'maud_fiduciary_exception__board_determination_standard', 'maud_fiduciary_exception_board_determination_trigger_(no_shop)', 'maud_financial_point_of_view_is_the_sole_consideration', 'maud_fls_(mae)_standard', 'maud_general_economic_and_financial_conditions_subject_to_disproportionate_impact_modifier', 'maud_includes_consistent_with_past_practice', 'maud_initial_matching_rights_period_(cor)', 'maud_initial_matching_rights_period_(ftr)', 'maud_intervening_event_-_required_to_occur_after_signing_-_answer', 'maud_knowledge_definition', 'maud_liability_standard_for_no-shop_breach_by_target_non-do_representatives', 'maud_ordinary_course_efforts_standard', 'maud_pandemic_or_other_public_health_event__subject_to_disproportionate_impact_modifier', 'maud_pandemic_or_other_public_health_event_specific_reference_to_pandemic-related_governmental_responses_or_measures', 'maud_relational_language_(mae)_applies_to', 'maud_specific_performance', 'maud_tail_period_length', 'maud_type_of_consideration', 'nys_judicial_ethics', 'opp115_data_retention', 'opp115_data_security', 'opp115_do_not_track', 'opp115_first_party_collection_use', 'opp115_international_and_specific_audiences', 'opp115_policy_change', 'opp115_third_party_sharing_collection', 'opp115_user_access,_edit_and_deletion', 'opp115_user_choice_control', 'oral_argument_question_purpose', 'overruling', 'personal_jurisdiction', 'privacy_policy_entailment', 'privacy_policy_qa', 'proa', 'rule_qa', 'sara_entailment', 'sara_numeric', 'scalr', 'ssla_company_defendants', 'ssla_individual_defendants', 'ssla_plaintiff', 'successor_liability', 'supply_chain_disclosure_best_practice_accountability', 'supply_chain_disclosure_best_practice_audits', 'supply_chain_disclosure_best_practice_certification', 'supply_chain_disclosure_best_practice_training', 'supply_chain_disclosure_best_practice_verification', 'supply_chain_disclosure_disclosed_accountability', 'supply_chain_disclosure_disclosed_audits', 'supply_chain_disclosure_disclosed_certification', 'supply_chain_disclosure_disclosed_training', 'supply_chain_disclosure_disclosed_verification', 'telemarketing_sales_rule', 'textualism_tool_dictionaries', 'textualism_tool_plain', 'ucc_v_common_law', 'unfair_tos']

# KILT dataset
ds_kilt = load_dataset("facebook/kilt_tasks", "nq")

# Natural Questions dataset
ds_nq = load_dataset("sentence-transformers/natural-questions")
    

def load_datasets():
    """Load and return the datasets."""
    return {
        "finance": ds_finance,
        "legal": ds_legal,
        "kilt": ds_kilt,
        "nq": ds_nq
    }