Task: Table-QA (source dataset: TableBench)

Task: 
You are given a table containing structured data and a natural language question referring to the table. Your goal is to analyze the table and provide an accurate and concise answer based on the given data.

Instructions:
1. Understand the Table: Examine the structure, headers, and data in the table. Identify relevant columns and rows related to the question.
2. Interpret the Question: Determine whether the question requires direct retrieval, aggregation, comparison, sorting, filtering, or inference.
3. Extract the Answer: Use logical reasoning and numerical operations (if necessary) to derive the correct response from the table.
4. Format the Answer: No explanation, return the answer in a structured JSON format: {"answer": <answer>}. If the question cannot be answered due to missing or ambiguous data, return a JSON response with {"answer": null}.

Table:
|   round |   pick |   overall | name              | position   | college             |
|--------:|-------:|----------:|:------------------|:-----------|:--------------------|
|       1 |     10 |        10 | forest evashevski | rb         | michigan            |
|       3 |     10 |        25 | fred davis        | ot         | alabama             |
|       5 |     10 |        40 | jim stuart        | ot         | oregon              |
|       6 |     10 |        50 | ed cifers         | e          | tennessee           |
|       7 |     10 |        60 | al krueger        | e          | southern california |
|       8 |     10 |        70 | henry wilder      | rb         | iowa state          |
|       9 |     10 |        80 | bill grimmett     | e          | tulsa               |
|      10 |     10 |        90 | ed hickerson      | g          | alabama             |
|      11 |     10 |       100 | joe aguirre       | e          | st mary 's (cal)    |
|      12 |     10 |       110 | jack banta        | hb         | southern california |
|      13 |     10 |       120 | roy conn          | ot         | arizona             |
|      14 |     10 |       130 | deward tornell    | rb         | san josé state      |
|      15 |     10 |       140 | morris buckingham | c          | san josé state      |
|      16 |     10 |       150 | ken dow           | fb         | oregon state        |
|      17 |     10 |       160 | stan mcrae        | e          | michigan state      |
|      18 |     10 |       170 | joe osmanski      | fb         | holy cross          |
|      19 |     10 |       180 | earl fullilove    | ot         | georgetown          |
|      20 |     10 |       190 | ed hiestand       | e          | vanderbilt          |
|      21 |      5 |       195 | tom riggs         | ot         | illinois            |
|      22 |      5 |       200 | lee gentry        | hb         | tulsa               |

Question:
In the context of the NFL draft, the "pick efficiency" of a college is calculated as the total number of players drafted from that college divided by the total number of players drafted in the round. Based on this definition, which college has the highest pick efficiency in the first 10 rounds of the draft?


id: b23a9876b3db50bf256522a0342f666d
qtype: NumericalReasoning
label: alabama