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Culture","lang",{"id":564,"unique_code":565,"title":566,"icon":8,"intro":567,"cate":483,"detail":568,"create_time":569,"update_time":570,"price":571,"view_count":572,"download_count":573,"unit":573,"amount":574,"is_create_order":573,"enterprise_id":488,"seo_keywords":575,"seo_description":576,"data_format":577,"file_size":578,"apply_scene":579,"training_task":580,"version":581,"dataset_type_id":492,"dataset_scene_id":488,"sample_file":522,"banner":8,"unit_name":8,"cate_name":449,"icon_url":8,"banner_url":8,"sample_file_url":8,"data_dict":582,"qa_list":675,"sample_metadatas":692,"text_sample_content":742,"enterprise_name":743,"enterprise_logo":744,"data_distribution":745},1074,"33f0fcf8f887d29fc5c2c5f7a08f863f","Transportation Planning Forecast Fact Verification Training Dataset","Connect webpage text, evidence paragraphs, and structured verification labels to help models assess the temporal and scenario boundaries of transportation forecasts.","\u003Cp>This dataset focuses on transportation demand forecasts and related planning claims found in transportation planning webpages. Records organize claim categories and temporal attributes alongside forecast metrics, values, units, target years, baseline scenarios, and assumptions. Each record links the original webpage text to an evidence paragraph, an evidence-claim relation, and a supervised verification label, supporting analysis of forecast versus observed values and checks for temporal and scenario alignment. It is suitable for fact verification model training, evaluation, and transportation planning information extraction research.\u003C\u002Fp>","2026-10-09 18:47:36","2026-10-19 17:20:00","0.00",50,0,5000,"transportation planning dataset, demand forecasting, fact verification training data, forecast validation, web text dataset, evidence annotation, scenario verification, transportation AI","Structured forecast details, evidence passages, and verification labels for transportation planning claims, supporting fact-checking model training and temporal","JSON","0.2GB","transportation planning, traffic forecast verification, transportation policy assessment","fact verification, temporal reasoning, evidence-based classification","V1.0",[583,588,593,598,604,609,614,619,624,630,635,640,645,650,655,660,665,670],{"id":573,"name":584,"field":585,"intro":586,"type":587},"File Name","file_name","File name","string",{"id":589,"name":590,"field":591,"intro":592,"type":587},7807,"Claim to Verify","claim_text","A transportation demand forecast or related planning claim extracted from the webpage text.",{"id":594,"name":595,"field":596,"intro":597,"type":587},7808,"Source Webpage URL","source_url","The URL of the original webpage containing the transportation planning text.",{"id":599,"name":600,"field":601,"intro":602,"type":603},7809,"Target Year","target_year","The year targeted by the forecast; may be left blank if the source does not specify a year.","integer",{"id":605,"name":606,"field":607,"intro":608,"type":587},7810,"Original Webpage Text","webpage_text","The original text retrieved from the source webpage and used as the basis for claim and evidence annotations.",{"id":610,"name":611,"field":612,"intro":613,"type":587},7811,"Forecast Unit","forecast_unit","The unit or measurement method associated with the forecast value, such as passenger trips, vehicle count, or percentage.",{"id":615,"name":616,"field":617,"intro":618,"type":587},7812,"Claim Category","claim_category","The category addressed by the claim, such as a demand forecast, target year, baseline scenario, or forecast assumption.",{"id":620,"name":621,"field":622,"intro":623,"type":587},7813,"Forecast Value","forecast_value","The forecast value or range stated in the claim, retained in its original wording to accommodate ranges, approximations, and nonstandard formats.",{"id":625,"name":626,"field":627,"intro":628,"type":629},7814,"Scenario Match","scenario_match","Indicates whether the scenario described by the evidence matches the baseline scenario applicable to the claim; may be left blank when it cannot be determined.","boolean",{"id":631,"name":632,"field":633,"intro":634,"type":587},7815,"Forecast Metric","forecast_metric","The transportation demand metric covered by the claim, such as passenger volume, trip count, or traffic flow.",{"id":636,"name":637,"field":638,"intro":639,"type":587},7816,"Forecast Period","forecast_period","The time interval or point covered by the forecast, such as a particular year, planning period, or phase.",{"id":641,"name":642,"field":643,"intro":644,"type":587},7817,"Baseline Scenario","baseline_scenario","The baseline or planning scenario on which the forecast is based, including its name and relevant details.",{"id":646,"name":647,"field":648,"intro":649,"type":587},7818,"Claim Temporal Attribute","claim_temporality","Indicates whether the claim describes a future forecast, an actual observation, or another temporal attribute.",{"id":651,"name":652,"field":653,"intro":654,"type":587},7819,"Evidence-Claim Relation","evidence_relation","Indicates whether the evidence paragraph supports or contradicts the claim to be verified.",{"id":656,"name":657,"field":658,"intro":659,"type":587},7820,"Evidence Paragraph","evidence_paragraph","The original webpage paragraph used to support or verify the claim.",{"id":661,"name":662,"field":663,"intro":664,"type":587},7821,"Fact Verification Label","verification_label","The supervised verification conclusion assigned to the claim based on the evidence.",{"id":666,"name":667,"field":668,"intro":669,"type":587},7822,"Forecast Assumptions","forecast_assumptions","Key assumptions underlying the forecast, such as assumptions about population, land use, policy, or travel behavior.",{"id":671,"name":672,"field":673,"intro":674,"type":629},7823,"Temporal Scope Match","temporal_scope_match","Indicates whether the time scope of the evidence matches that of the claim; may be left blank when it cannot be determined.",[676,680,684,688],{"id":677,"question":678,"answer":679},5743,"What does the dataset contain?","The data covers demand forecasts and related claims from transportation planning webpages. Fields include source URLs, webpage text, claims, claim categories and temporal attributes, forecast metrics, values, units, target years, forecast periods, baseline scenarios, and assumptions. Records also provide evidence paragraphs, evidence relations, verification labels, and temporal and scenario match indicators.",{"id":681,"question":682,"answer":683},5744,"How can the data support model training and evaluation?","The structured fields connect claims with evidence and verification outcomes. They can support training or evaluating models that distinguish forecasts from observations, determine whether evidence supports a claim, and check temporal and scenario alignment. Review the accompanying documentation for label definitions, missing-value rules, and evaluation splits before use.",{"id":685,"question":686,"answer":687},5745,"How can I obtain and use the data?","Use the delivery method provided on the current dataset product page or platform, and consult the accompanying documentation for field definitions and data formats. Potential uses include fact verification, information extraction, transportation planning research, and related model evaluation.",{"id":689,"question":690,"answer":691},5746,"What licensing considerations apply to the webpage content?","Source URLs and webpage text may be subject to the original websites' copyright, access terms, or other restrictions. Before use, review the dataset license information and the source websites' terms. Confirm that you have the necessary rights and permissions before redistributing the content or using it commercially.",[693,713,728],{"id":694,"relate_table":695,"relate_id":696,"file_size":573,"file_name":8,"path":8,"duration":573,"cate":483,"file_format":8,"audio_rate":8,"audio_channel":522,"audio_bit_depth":522,"quality":8,"annotation":697,"cate_name":698,"claim_text":699,"source_url":8,"target_year":700,"webpage_text":701,"forecast_unit":702,"claim_category":703,"forecast_value":704,"scenario_match":705,"forecast_metric":706,"forecast_period":707,"baseline_scenario":708,"claim_temporality":709,"evidence_relation":710,"evidence_paragraph":711,"verification_label":710,"forecast_assumptions":712,"temporal_scope_match":705},14624,"union_cubo",791304327,"{\"claim_text\": \"Under the low-growth case, inbound rail demand during the morning peak is forecast at 18,000 passengers per hour in 2050.\", \"source_url\": \"\", \"target_year\": \"2050\", \"webpage_text\": \"Coastal Access Plan, 2050 demand assessment. Under the low-growth case, inbound rail demand during the morning peak is forecast at 18,000 passengers per hour in 2050. The low-growth case assumes annual population growth of 0.4 percent. The assessment compares low-growth, adopted-plan, and accelerated-development cases for 2050. The main-page summary does not provide the model table or an independent value for inbound morning-peak rail demand; detailed demand tables are listed in Appendix C.\", \"forecast_unit\": \"passengers per hour\", \"claim_category\": \"Demand Forecasting\", \"forecast_value\": \"18,000\", \"scenario_match\": \"true\", \"forecast_metric\": \"inbound rail demand during the morning peak\", \"forecast_period\": \"2050 morning peak\", \"baseline_scenario\": \"Low-growth case\", \"claim_temporality\": \"Prediction\", \"evidence_relation\": \"Insufficient Evidence\", \"evidence_paragraph\": \"The assessment compares low-growth, adopted-plan, and accelerated-development cases for 2050. The main-page summary does not provide the model table or an independent value for inbound morning-peak rail demand; detailed demand tables are listed in Appendix C.\", \"verification_label\": \"Insufficient Evidence\", \"forecast_assumptions\": \"Annual population growth of 0.4 percent.\", \"temporal_scope_match\": \"true\"}","文本","Under the low-growth case, inbound rail demand during the morning peak is forecast at 18,000 passengers per hour in 2050.","2050","Coastal Access Plan, 2050 demand assessment. Under the low-growth case, inbound rail demand during the morning peak is forecast at 18,000 passengers per hour in 2050. The low-growth case assumes annual population growth of 0.4 percent. The assessment compares low-growth, adopted-plan, and accelerated-development cases for 2050. The main-page summary does not provide the model table or an independent value for inbound morning-peak rail demand; detailed demand tables are listed in Appendix C.","passengers per hour","Demand Forecasting","18,000","true","inbound rail demand during the morning peak","2050 morning peak","Low-growth case","Prediction","Insufficient Evidence","The assessment compares low-growth, adopted-plan, and accelerated-development cases for 2050. The main-page summary does not provide the model table or an independent value for inbound morning-peak rail demand; detailed demand tables are listed in Appendix C.","Annual population growth of 0.4 percent.",{"id":714,"relate_table":695,"relate_id":715,"file_size":573,"file_name":8,"path":8,"duration":573,"cate":483,"file_format":8,"audio_rate":8,"audio_channel":522,"audio_bit_depth":522,"quality":8,"annotation":716,"cate_name":698,"claim_text":717,"source_url":8,"target_year":718,"webpage_text":719,"forecast_unit":720,"claim_category":703,"forecast_value":721,"scenario_match":705,"forecast_metric":722,"forecast_period":718,"baseline_scenario":723,"claim_temporality":709,"evidence_relation":724,"evidence_paragraph":725,"verification_label":724,"forecast_assumptions":726,"temporal_scope_match":727},14623,1415043402,"{\"claim_text\": \"Under the reference case, weekday vehicle trips are forecast to total 480,000 in 2035.\", \"source_url\": \"\", \"target_year\": \"2035\", \"webpage_text\": \"The Central Corridor Travel Demand Plan states: Under the reference case, weekday vehicle trips are forecast to total 480,000 in 2035. The forecast table lists 2035: 430,000 weekday vehicle trips; 2040: 480,000 weekday vehicle trips. Both figures use the reference case, which assumes adopted zoning and no additional road-capacity program beyond projects already funded. These are forecast values, not observed counts.\", \"forecast_unit\": \"trips per weekday\", \"claim_category\": \"Demand Forecasting\", \"forecast_value\": \"480,000\", \"scenario_match\": \"true\", \"forecast_metric\": \"weekday vehicle trips\", \"forecast_period\": \"2035\", \"baseline_scenario\": \"Reference case\", \"claim_temporality\": \"Prediction\", \"evidence_relation\": \"Refute\", \"evidence_paragraph\": \"The forecast table lists 2035: 430,000 weekday vehicle trips; 2040: 480,000 weekday vehicle trips. Both figures use the reference case, which assumes adopted zoning and no additional road-capacity program beyond projects already funded.\", \"verification_label\": \"Refute\", \"forecast_assumptions\": \"Adopted zoning and no additional road-capacity program beyond projects already funded.\", \"temporal_scope_match\": \"false\"}","Under the reference case, weekday vehicle trips are forecast to total 480,000 in 2035.","2035","The Central Corridor Travel Demand Plan states: Under the reference case, weekday vehicle trips are forecast to total 480,000 in 2035. The forecast table lists 2035: 430,000 weekday vehicle trips; 2040: 480,000 weekday vehicle trips. Both figures use the reference case, which assumes adopted zoning and no additional road-capacity program beyond projects already funded. These are forecast values, not observed counts.","trips per weekday","480,000","weekday vehicle trips","Reference case","Refute","The forecast table lists 2035: 430,000 weekday vehicle trips; 2040: 480,000 weekday vehicle trips. Both figures use the reference case, which assumes adopted zoning and no additional road-capacity program beyond projects already funded.","Adopted zoning and no additional road-capacity program beyond projects already funded.","false",{"id":729,"relate_table":695,"relate_id":730,"file_size":573,"file_name":8,"path":8,"duration":573,"cate":483,"file_format":8,"audio_rate":8,"audio_channel":522,"audio_bit_depth":522,"quality":8,"annotation":731,"cate_name":698,"claim_text":732,"source_url":8,"target_year":733,"webpage_text":734,"forecast_unit":735,"claim_category":703,"forecast_value":736,"scenario_match":705,"forecast_metric":737,"forecast_period":733,"baseline_scenario":738,"claim_temporality":709,"evidence_relation":739,"evidence_paragraph":740,"verification_label":739,"forecast_assumptions":741,"temporal_scope_match":705},14622,956695837,"{\"claim_text\": \"Under the adopted land-use baseline, weekday transit boardings are forecast to reach 1.26 million in 2045.\", \"source_url\": \"\", \"target_year\": \"2045\", \"webpage_text\": \"Regional Mobility Outlook, adopted plan. The forecast covers average weekday service. Under the adopted land-use baseline, weekday transit boardings are forecast to reach 1.26 million in 2045. This is a modeled forecast, not an observed count. The baseline assumes adopted zoning, completion of the funded rapid-transit network, and population growth in line with the regional plan through 2045.\", \"forecast_unit\": \"boardings\", \"claim_category\": \"Demand Forecasting\", \"forecast_value\": \"1.26 million\", \"scenario_match\": \"true\", \"forecast_metric\": \"weekday transit boardings\", \"forecast_period\": \"2045\", \"baseline_scenario\": \"Adopted land-use baseline\", \"claim_temporality\": \"Prediction\", \"evidence_relation\": \"Support\", \"evidence_paragraph\": \"Under the adopted land-use baseline, weekday transit boardings are forecast to reach 1.26 million in 2045. This is a modeled forecast, not an observed count. The baseline assumes adopted zoning, completion of the funded rapid-transit network, and population growth in line with the regional plan through 2045.\", \"verification_label\": \"Support\", \"forecast_assumptions\": \"Adopted zoning, completion of the funded rapid-transit network, and population growth in line with the regional plan through 2045.\", \"temporal_scope_match\": \"true\"}","Under the adopted land-use baseline, weekday transit boardings are forecast to reach 1.26 million in 2045.","2045","Regional Mobility Outlook, adopted plan. The forecast covers average weekday service. Under the adopted land-use baseline, weekday transit boardings are forecast to reach 1.26 million in 2045. This is a modeled forecast, not an observed count. The baseline assumes adopted zoning, completion of the funded rapid-transit network, and population growth in line with the regional plan through 2045.","boardings","1.26 million","weekday transit boardings","Adopted land-use baseline","Support","Under the adopted land-use baseline, weekday transit boardings are forecast to reach 1.26 million in 2045. This is a modeled forecast, not an observed count. The baseline assumes adopted zoning, completion of the funded rapid-transit network, and population growth in line with the regional plan through 2045.","Adopted zoning, completion of the funded rapid-transit network, and population growth in line with the regional plan through 2045.","{\"claim_text\":\"Under the low-growth case, inbound rail demand during the morning peak is forecast at 18,000 passengers per hour in 2050.\",\"source_url\":\"\",\"target_year\":\"2050\",\"webpage_text\":\"Coastal Access Plan, 2050 demand assessment. Under the low-growth case, inbound rail demand during the morning peak is forecast at 18,000 passengers per hour in 2050. The low-growth case assumes annual population growth of 0.4 percent. The assessment compares low-growth, adopted-plan, and accelerated-development cases for 2050. The main-page summary does not provide the model table or an independent value for inbound morning-peak rail demand; detailed demand tables are listed in Appendix C.\",\"forecast_unit\":\"passengers per hour\",\"claim_category\":\"Demand Forecasting\",\"forecast_value\":\"18,000\",\"scenario_match\":\"true\",\"forecast_metric\":\"inbound rail demand during the morning peak\",\"forecast_period\":\"2050 morning peak\",\"baseline_scenario\":\"Low-growth case\",\"claim_temporality\":\"Prediction\",\"evidence_relation\":\"Insufficient Evidence\",\"evidence_paragraph\":\"The assessment compares low-growth, adopted-plan, and accelerated-development cases for 2050. The main-page summary does not provide the model table or an independent value for inbound morning-peak rail demand; detailed demand tables are listed in Appendix C.\",\"verification_label\":\"Insufficient Evidence\",\"forecast_assumptions\":\"Annual population growth of 0.4 percent.\",\"temporal_scope_match\":\"true\"}","MOBIUSI INC","https:\u002F\u002Fstatic.mobiusi.com\u002Fmobiwusi\u002F20250829\u002F7bf4ac62b4533e2b809998a6f1c5491e.png?Expires=1792463130&OSSAccessKeyId=LTAI5tH8MQqhgeiAtrzCHrxM&Signature=v6Tr8jBrdm4s5wU1SnnyGsYg%2Bhw%3D&x-oss-process=image%2Fresize%2Cm_fill%2Cw_35%2Ch_35",[746,752],{"type":747,"title":748,"count_data":749},"bar","Length distribution",[750],{"name":751,"value":483},"1k lower",{"type":753,"title":754,"count_data":755},"pie","Language distribution",[756],{"name":757,"value":483},"English"]