Finding first intersections in each row pandas dataframe

I have a dataframe:

import pandas as pd
data =[[28, ['first'], 'apple edible', 23, 'apple is an edible fruit'],
 [28, ['first'], 'apple edible', 34, 'fruit produced by an apple tree'],
 [28, ['first'], 'apple edible', 39, 'the apple is a pome edible fruit'],
 [21, ['second'], 'green plants', 11, 'plants are green'],
 [21, ['second'], 'green plants', 7, 'plant these perennial green flowers']]
df = pd.DataFrame(data, columns=['day', 'group',  'bigram', 'count', 'sentence'])
+---+--------+------------+-----+-----------------------------------+
|day|group   |bigram      |count|sentence                           |
+---+--------+------------+-----+-----------------------------------+
|28 |[first] |apple edible|23   |apple is an edible fruit           |
|28 |[first] |apple edible|34   |fruit produced by an apple tree    |
|28 |[first] |apple edible|39   |the apple is a pome edible fruit   |
|21 |[second]|green plants|11   |plants are green                   |
|21 |[second]|green plants|7    |plant these perennial green flowers|
+---+--------+------------+-----+-----------------------------------+

I need to find intersections of bigram with a sentence. Moreover, find the first intersection and mark it True.
That is, after the first intersection, the remaining intersections will already be marked as False. Word order is not important.

So I would like this result:

+---+--------+------------+-----+--------------------------------+--------+
|day|group   |bigram      |count|sentence                        |        |
+---+--------+------------+-----+--------------------------------+--------+
|28 |[first] |apple edible|23   |apple is an edible fruit        |True    |
|28 |[first] |apple edible|34   |fruit produced by an apple tree |False   |
|28 |[first] |apple edible|39   |the apple is a pome edible fruit|False   |
|21 |[second]|green plants|11   |plant these perennial flowers   |False   |
|21 |[second]|green plants|7    |plants are green                |True    |
+---+--------+------------+-----+--------------------------------+--------+

>Solution :

First test all intersection by converted splitted values to sets with issubset and then select only first Trues per bigram:

df['new'] = [set(b.split()).issubset(a.split()) for a,b in zip(df['sentence'],df['bigram'])]
df['new'] = ~df.duplicated(['bigram','new']) & df['new']
print (df)
   day     group        bigram  count                             sentence  \
0   28   [first]  apple edible     23             apple is an edible fruit   
1   28   [first]  apple edible     34      fruit produced by an apple tree   
2   28   [first]  apple edible     39     the apple is a pome edible fruit   
3   21  [second]  green plants     11                     plants are green   
4   21  [second]  green plants      7  plant these perennial green flowers   

     new  
0   True  
1  False  
2  False  
3   True  
4  False  

If order in bigram should be swapped and need first intersection use:

df['new'] = ~df.assign(bigram=df['bigram'].apply(lambda x: frozenset(x.split()))).duplicated(['bigram','new']) & df['new']