| 模型 | 模型答案 | 正确答案 |
|---|---|---|
| 金声玉亮2.0 | ```python { "Harvest.Year": "x0YTt9hPYFI", "Color": "vU50Gku+N1g", "Variety": "fg/VVHUVHIQ", "Aroma": "zfzQ4Z9Dt5o", "Processing.Method": "iJKOBRCgJI0", "Continent.of.Origin": "LOldZF4dJII" } ``` |
{"Continent.of.Origin": "LOldZF4dJII", "Variety": "zfzQ4Z9Dt5o", "REC_ID": "fg/VVHUVHIQ", "Color": "vU50Gku+N1g", "Processing.Method": "iJKOBRCgJI0", "Harvest.Year": "x0YTt9hPYFI", "Aroma": "6oyt+mdSeHI"} |
| deepseek-r1 | {'Harvest.Year': 'x0YTt9hPYFI', 'Color': 'vU50Gku+N1g', 'Variety': 'zfzQ4Z9Dt5o', 'Aroma': '6oyt+mdSeHI', 'Processing.Method': 'iJKOBRCgJI0', 'Continent.of.Origin': 'LOldZF4dJII'} |
{"Continent.of.Origin": "LOldZF4dJII", "Variety": "zfzQ4Z9Dt5o", "REC_ID": "fg/VVHUVHIQ", "Color": "vU50Gku+N1g", "Processing.Method": "iJKOBRCgJI0", "Harvest.Year": "x0YTt9hPYFI", "Aroma": "6oyt+mdSeHI"} |
| gpto1 | ```python { 'Harvest.Year': 'x0YTt9hPYFI', 'Color': 'vU50Gku+N1g', 'Variety': 'zfzQ4Z9Dt5o', 'Processing.Method': 'iJKOBRCgJI0', 'Aroma': '6oyt+mdSeHI', 'Continent.of.Origin': 'LOldZF4dJII', 'Species': '9lfBveG7CWM' } ``` |
{"Continent.of.Origin": "LOldZF4dJII", "Variety": "zfzQ4Z9Dt5o", "REC_ID": "fg/VVHUVHIQ", "Color": "vU50Gku+N1g", "Processing.Method": "iJKOBRCgJI0", "Harvest.Year": "x0YTt9hPYFI", "Aroma": "6oyt+mdSeHI"} |
| gpt-4o-2024-08-06 | ```python { "Species": None, "Continent.of.Origin": "LOldZF4dJII", "Country.of.Origin": None, "Harvest.Year": "x0YTt9hPYFI", "Expiration": None, "Variety": "zfzQ4Z9Dt5o", "Color": "vU50Gku+N1g", "Processing.Method": "iJKOBRCgJI0", "Aroma": None } ``` |
{"Continent.of.Origin": "LOldZF4dJII", "Variety": "zfzQ4Z9Dt5o", "REC_ID": "fg/VVHUVHIQ", "Color": "vU50Gku+N1g", "Processing.Method": "iJKOBRCgJI0", "Harvest.Year": "x0YTt9hPYFI", "Aroma": "6oyt+mdSeHI"} |
| DeepSeek-Coder-V2-Lite-Instruct | ```python { "REC_ID": "x0YTt9hPYFI", "Species": "vU50Gku+N1g", "Continent.of.Origin": "fg/VVHUVHIQ", "Country.of.Origin": "zfzQ4Z9Dt5o", "Harvest.Year": "9lfBveG7CWM", "Expiration": "6oyt+mdSeHI", "Variety": "iJKOBRCgJI0", "Color": "LOldZF4dJII" } ``` |
{"Continent.of.Origin": "LOldZF4dJII", "Variety": "zfzQ4Z9Dt5o", "REC_ID": "fg/VVHUVHIQ", "Color": "vU50Gku+N1g", "Processing.Method": "iJKOBRCgJI0", "Harvest.Year": "x0YTt9hPYFI", "Aroma": "6oyt+mdSeHI"} |
| Meta-Llama-3.1-405B-Instruct-Turbo | {'Harvest.Year': 'x0YTt9hPYFI', 'Color': 'vU50Gku+N1g', 'REC_ID': None, 'Variety': 'fg/VVHUVHIQ', 'Aroma': '9lfBveG7CWM', 'Processing.Method': '6oyt+mdSeHI', 'Continent.of.Origin': 'iJKOBRCgJI0', 'Country.of.Origin': None, 'Species': None, 'Expiration': None} | {"Continent.of.Origin": "LOldZF4dJII", "Variety": "zfzQ4Z9Dt5o", "REC_ID": "fg/VVHUVHIQ", "Color": "vU50Gku+N1g", "Processing.Method": "iJKOBRCgJI0", "Harvest.Year": "x0YTt9hPYFI", "Aroma": "6oyt+mdSeHI"} |
| Meta-Llama-3.1-70B-Instruct-Turbo | {'Harvest.Year': 'x0YTt9hPYFI', 'Color': 'vU50Gku+N1g', 'Variety': 'fg/VVHUVHIQ', 'Aroma': '6oyt+mdSeHI', 'Processing.Method': 'iJKOBRCgJI0', 'Continent.of.Origin': 'LOldZF4dJII'} | {"Continent.of.Origin": "LOldZF4dJII", "Variety": "zfzQ4Z9Dt5o", "REC_ID": "fg/VVHUVHIQ", "Color": "vU50Gku+N1g", "Processing.Method": "iJKOBRCgJI0", "Harvest.Year": "x0YTt9hPYFI", "Aroma": "6oyt+mdSeHI"} |
| Qwen2-72B-Instruct | {'Harvest.Year': 'x0YTt9hPYFI', 'Color': 'vU50Gku+N1g', 'Variety': 'iJKOBRCgJI0', 'Processing.Method': 'LOldZF4dJII', 'Continent.of.Origin': '9lfBveG7CWM'} | {"Continent.of.Origin": "LOldZF4dJII", "Variety": "zfzQ4Z9Dt5o", "REC_ID": "fg/VVHUVHIQ", "Color": "vU50Gku+N1g", "Processing.Method": "iJKOBRCgJI0", "Harvest.Year": "x0YTt9hPYFI", "Aroma": "6oyt+mdSeHI"} |
| baichuan4 | Based on the provided CSV tables, it appears that there are no direct one-to-one mappings between the columns of Table A and Table B. However, I can infer some potential relationships based on the data types and context of the columns. Here's a possible mapping that could be used for joining these tables: ```python { "Harvest.Year": "Harvest.Year", # Direct match based on column name "Color": "Color", # Direct match based on column name "Variety": "Variety", # Direct match based on column name "Processing.Method": "Processing.Method", # Direct match based on column name "Aroma": "Aroma" # Direct match based on column name } ``` Please note that this mapping assumes that the columns with the same names in both tables contain compatible data for joining. If the actual data in these columns does not align properly, the join operation may not produce meaningful results. Additionally, other columns in Table A such as "REC_ID", "Species", "Continent.of.Origin", "Country.of.Origin", and "Expiration" do not have direct matches in Table B based on the provided information. |
{"Continent.of.Origin": "LOldZF4dJII", "Variety": "zfzQ4Z9Dt5o", "REC_ID": "fg/VVHUVHIQ", "Color": "vU50Gku+N1g", "Processing.Method": "iJKOBRCgJI0", "Harvest.Year": "x0YTt9hPYFI", "Aroma": "6oyt+mdSeHI"} |
| doubao | {"Harvest.Year": "2012.0", "Color": "Bluish-Green", "Variety": "Typica"} | {"Continent.of.Origin": "LOldZF4dJII", "Variety": "zfzQ4Z9Dt5o", "REC_ID": "fg/VVHUVHIQ", "Color": "vU50Gku+N1g", "Processing.Method": "iJKOBRCgJI0", "Harvest.Year": "x0YTt9hPYFI", "Aroma": "6oyt+mdSeHI"} |
| gpto1 | ```python { 'Harvest.Year': 'x0YTt9hPYFI', 'Color': 'vU50Gku+N1g', 'Variety': 'zfzQ4Z9Dt5o', 'Processing.Method': 'iJKOBRCgJI0', 'Aroma': '6oyt+mdSeHI', 'Continent.of.Origin': 'LOldZF4dJII', 'Species': '9lfBveG7CWM' } ``` |
{"Continent.of.Origin": "LOldZF4dJII", "Variety": "zfzQ4Z9Dt5o", "REC_ID": "fg/VVHUVHIQ", "Color": "vU50Gku+N1g", "Processing.Method": "iJKOBRCgJI0", "Harvest.Year": "x0YTt9hPYFI", "Aroma": "6oyt+mdSeHI"} |
| kimi | {'Harvest.Year': 'x0YTt9hPYFI', 'Color': 'vU50Gku+N1g', 'Variety': 'fg/VVHUVHIQ', 'Continent.of.Origin': 'LOldZF4dJII'} | {"Continent.of.Origin": "LOldZF4dJII", "Variety": "zfzQ4Z9Dt5o", "REC_ID": "fg/VVHUVHIQ", "Color": "vU50Gku+N1g", "Processing.Method": "iJKOBRCgJI0", "Harvest.Year": "x0YTt9hPYFI", "Aroma": "6oyt+mdSeHI"} |
| minimax | ```python { "Harvest.Year": "2012.0", "Color": "Green", "Variety": "Typica", "Processing.Method": "Washed / Wet", "Continent.of.Origin": "North America" } ``` |
{"Continent.of.Origin": "LOldZF4dJII", "Variety": "zfzQ4Z9Dt5o", "REC_ID": "fg/VVHUVHIQ", "Color": "vU50Gku+N1g", "Processing.Method": "iJKOBRCgJI0", "Harvest.Year": "x0YTt9hPYFI", "Aroma": "6oyt+mdSeHI"} |
| wenxinyiyan | {'Harvest.Year': 'x0YTt9hPYFI', 'Color': 'vU50Gku+N1g', 'Variety': 'fg/VVHUVHIQ', 'Aroma': 'zfzQ4Z9Dt5o', 'Processing.Method': '9lfBveG7CWM', 'Continent.of.Origin': 'LOldZF4dJII'} | {"Continent.of.Origin": "LOldZF4dJII", "Variety": "zfzQ4Z9Dt5o", "REC_ID": "fg/VVHUVHIQ", "Color": "vU50Gku+N1g", "Processing.Method": "iJKOBRCgJI0", "Harvest.Year": "x0YTt9hPYFI", "Aroma": "6oyt+mdSeHI"} |
| zhipu | ```python { "Harvest.Year": "x0YTt9hPYFI", "Color": "vU50Gku+N1g", "Variety": "fg/VVHUVHIQ", "Aroma": "9lfBveG7CWM", "Processing.Method": "6oyt+mdSeHI", "Continent.of.Origin": "LOldZF4dJII" } ``` |
{"Continent.of.Origin": "LOldZF4dJII", "Variety": "zfzQ4Z9Dt5o", "REC_ID": "fg/VVHUVHIQ", "Color": "vU50Gku+N1g", "Processing.Method": "iJKOBRCgJI0", "Harvest.Year": "x0YTt9hPYFI", "Aroma": "6oyt+mdSeHI"} |
| deepseek-v3 | {'REC_ID': 'zfzQ4Z9Dt5o', 'Species': 'vU50Gku+N1g', 'Continent.of.Origin': 'LOldZF4dJII', 'Country.of.Origin': '9lfBveG7CWM', 'Harvest.Year': 'x0YTt9hPYFI', 'Expiration': '6oyt+mdSeHI', 'Variety': 'iJKOBRCgJI0', 'Color': 'fg/VVHUVHIQ', 'Processing.Method': 'LOldZF4dJII', 'Aroma': 'iJKOBRCgJI0'} | {"Continent.of.Origin": "LOldZF4dJII", "Variety": "zfzQ4Z9Dt5o", "REC_ID": "fg/VVHUVHIQ", "Color": "vU50Gku+N1g", "Processing.Method": "iJKOBRCgJI0", "Harvest.Year": "x0YTt9hPYFI", "Aroma": "6oyt+mdSeHI"} |