# data[].attributes.headline
1) in the middle of the day                                    2) on the site                         

# data[].attributes.subject
1) in the middle of the day                                    2) on the site                         

# data[].attributes.headline
a) although pieces of old pots are dug up more than anything.               b) there are risked involved, but  in order to avoid accidents.                           

# data[].attributes.subject
a) although pieces of old pots are dug up more than anything.               b) there are risked involved, but  in order to avoid accidents.                           

# data[].attributes.headline
1- Who dig up and study the remains of ancient buildinds . 2- Who work without beings paid .3- Which usually run a number of projects for students and non - students . 

# data[].attributes.subject
1- Who dig up and study the remains of ancient buildinds . 2- Who work without beings paid .3- Which usually run a number of projects for students and non - students . 

# data[].attributes.headline
1 - "people often don't remember", 2 - "In order to avoid accidents", 3 - "there are risks involved

# data[].attributes.subject
1 - "people often don't remember", 2 - "In order to avoid accidents", 3 - "there are risks involved

# data[].attributes.headline
1. "On the site" 2. "outside work" 3. "In the morning".

# data[].attributes.subject
1. "On the site" 2. "outside work" 3. "In the morning".

# data[].attributes.headline
1- "unusual family holiday" 2- "remains of ancient buildings about the past" 3- "In the morning".

# data[].attributes.subject
1- "unusual family holiday" 2- "remains of ancient buildings about the past" 3- "In the morning".

# data[].attributes.headline
1. 'Which is mentioned more than any other' 2.'Which usually run a number of projects for students and non-students'. 3.'Who dig up and study the remains of ancient buildings'  2.'Which usually run a number of projects for students and non-students'. 

# data[].attributes.subject
1. 'Which is mentioned more than any other' 2.'Which usually run a number of projects for students and non-students'. 3.'Who dig up and study the remains of ancient buildings'  2.'Which usually run a number of projects for students and non-students'. 

# data[].attributes.headline
1)'...these obvious points.' 2)'...during the summer...' 3)'...everyone on the site.'

# data[].attributes.subject
1)'...these obvious points.' 2)'...during the summer...' 3)'...everyone on the site.'

# data[].attributes.headline
1)'...people often don't remember,...' 2)'...,there are risks involved,...' 3) 'This can be challenging at first,...'

# data[].attributes.subject
1)'...people often don't remember,...' 2)'...,there are risks involved,...' 3) 'This can be challenging at first,...'

# data[].attributes.headline
1. For outside work.  2. In the morning. 3. On the site.

# data[].attributes.subject
1. For outside work.  2. In the morning. 3. On the site.

# data[].attributes.headline
1.'Because it may be impossible to work outside.'  2.'In order to avoid accidents.'  3.'Although pieces of old pots are are dug up more than anything.'

# data[].attributes.subject
1.'Because it may be impossible to work outside.'  2.'In order to avoid accidents.'  3.'Although pieces of old pots are are dug up more than anything.'

# data[].attributes.headline
1. which is mentioned more than any other  roaa 

# data[].attributes.subject
1. which is mentioned more than any other  roaa 

# data[].attributes.headline
clause:1-One is to have an unusual family holiday.2-Your best chance is with universities.3-Previous experience is not always necessary.

# data[].attributes.subject
clause:1-One is to have an unusual family holiday.2-Your best chance is with universities.3-Previous experience is not always necessary.

# data[].attributes.headline
1.'To speed up the project.'  2.'To learn about the past.'  3. (correction) 'For special projects ' 

# data[].attributes.subject
1.'To speed up the project.'  2.'To learn about the past.'  3. (correction) 'For special projects ' 

# data[].attributes.headline
1) 'remains of ancient building,' 2) 'unusual family holiday'

# data[].attributes.subject
1) 'remains of ancient building,' 2) 'unusual family holiday'

# data[].attributes.headline
Which usually run a number of projects for students and non students.

# data[].attributes.subject
Which usually run a number of projects for students and non students.

# data[].attributes.headline
1) '...,who dig up and study the remaining of ancient buildings,...' 2) '...,which usually run a number of projects for students and non-students.'

# data[].attributes.subject
1) '...,who dig up and study the remaining of ancient buildings,...' 2) '...,which usually run a number of projects for students and non-students.'

# data[].attributes.headline
1- In the morning 2- about the past 3- on the site.

# data[].attributes.subject
1- In the morning 2- about the past 3- on the site.

# data[].attributes.headline
kubra- which is mentioned more than any other

# data[].attributes.subject
kubra- which is mentioned more than any other

# data[].attributes.headline
1. 'Which is mentioned more than any other' 2.'Which usually run a number of projects for students and non-students'. 3.'Who dig up and study the remains of ancient buildings'  2.'Which usually run a number of projects for students and non-students'. 

# data[].attributes.subject
1. 'Which is mentioned more than any other' 2.'Which usually run a number of projects for students and non-students'. 3.'Who dig up and study the remains of ancient buildings'  2.'Which usually run a number of projects for students and non-students'. 

# data[].attributes.headline
1.'Who dig up and study the remains of ancient buildings'  2.'Which is mentioned more than any other'  3.'Which usually run a number of projects for students and non-students'. 

# data[].attributes.subject
1.'Who dig up and study the remains of ancient buildings'  2.'Which is mentioned more than any other'  3.'Which usually run a number of projects for students and non-students'. 

# data[].attributes.headline
1- Who dig up and study the remains of ancient buildings. 2- which is mentioned more than any other. 3- Who work without being paid. 4- what human life was like.

# data[].attributes.subject
1- Who dig up and study the remains of ancient buildings. 2- which is mentioned more than any other. 3- Who work without being paid. 4- what human life was like.

# data[].attributes.headline
1) who dig up and study the remains of ancient buildings.    2)which usually run a number of project for student and non-student

# data[].attributes.subject
1) who dig up and study the remains of ancient buildings.    2)which usually run a number of project for student and non-student

# data[].attributes.headline
Let's find more clauses and phrases in this extract.

# data[].attributes.subject
Let's find more clauses and phrases in this extract.

# data[].attributes.headline
List three (3) clauses and three (3) phrases from the extract.

# data[].attributes.subject
List three (3) clauses and three (3) phrases from the extract.