Example sentences of "[Wh det] 's [vb pp] [prep] [adj] " in BNC.

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1 He admitted : ‘ After what 's gone on this summer , of course things could blow up .
2 But I usually arrange with a client over what 's seen in two years ' time or one year 's time , whatever .
3 Russia will be the leader of that alliance and therefore like America NATO will probably have the decisive say on what 's done with those nuclear weapons .
4 So what I 'm saying to you is if you like to refer to this , this will give you the clear definition of what , what 's covered in each case .
5 Tonight we 'll devote all our time to the National as here in Central South we have eleven horses running at Aintree , in what 's regarded as one of the greatest horse races in the world .
6 Really that was n't actually dis the staffing issues themselves were n't discussed , but just to recap on what the situation is with the staffing issues and what 's meant by that .
7 What 's happened about that book you
8 What 's happened between other one ?
9 Readable , full of erm , empirical evidence about costs of agricultural protection , and what 's happened to agricultural prices and I re I do recommend that you have a look at it if you , it 's an invaluable if you look at anything , look at , look at this one article .
10 What 's happened to all your brains , Frankie boy ?
11 what 's happened to all the , the stuff in , you know you could pick them up and just eat them straight away
12 Erm what 's happened to that ?
13 Mark what 's happened to that that test the P H paper there ?
14 No I do n't know what 's happened to that .
15 Oh what 's happened to that one ?
16 Well what 's happened to that other tooth .
17 What 's happened to that bloody light ?
18 What 's happened to old McWhirter ? ’ said Penny , deciding not to mention the comparison in the company of two young men who gave her some gratifying doggy devotion .
19 Has that come up in your er in your well we were coming back there one night from my aunt 's and er there were quite a lot of policemen about and I was only a little boy , it was before the First World War and my father said to one of these policemen , what 's happening so , oh we had a tip-off he says that er there 's these Whirly Gang folks and in the morning we saw somebody 'd been maimed or killed , but er that was another bit of interesting news around , and I remember down in Caldmore one day there used to be some ladies who used to come from , well they used to be , one of them used to call them the salt ladies , they used to come with blocks of salt on a , on a I think they used to come from and I saw a horse there as a kid and I , it had got a long gash right across its body and I said to this lady I said , what 's happened to this , she said oh the Whirly Gang and er I was in Paris in nineteen twenty two and er we got to this hotel and there was another Englishman on this trip and he said to me he said where do you come from ?
20 What 's happened to this .
21 Oh no , what 's happened to this man 's paint ?
22 Ooh what 's happened to this ?
23 Right , what we 're now going to do is incorporate that dummy variable as the regressor in our model as an explanatory variable , so what 's going to happen is that that dummy variable is turned off , alright in the first part of the sample right up until the war that dummy variable 's going to be off , right so it has a value of zero , right , then in nineteen forty through to nineteen forty five it 's switched on and what it 's going to do is to pick up any differential effects , right , in the intercept between wartime and peacetime right , we 'll talk a little bit more , more about that in a second , we 're going to add it in as a regressor , right , because it only comes on during the wartime it will pick up any shift in the intercept , right , that occurs due to the war if there is one , of course there may not be but it 's quite likely that there , there may well be , so if you type Q to come out of the data processing environment , go back to the action menu and test estimate forecast okay at the dialog box just add D one to your list of explanatory variables , alright then press the end key , right , yeah we 're gon na use the full sample right , we gon na use O L S , right you have now estimated the model with this dummy variable now just to see what 's happened to those coefficients the er incoming elasticity was at nought point six is now doubled right to one point one four more importantly , right , its T ratio has jumped from one point eight five right to six point eight , as a result , we now say that the incoming elasticity , the income coefficients , right , the significant zero , it 's important to explain the textiles as such the er , we are now getting a very different estimate for our
24 What 's happened with that camera , you 've
25 What 's happened with this fridge ?
26 So straight away you see what 's happened in this case his code becomes two eighty one H whereas previously we 've got quite a high code and yet his total income is er not er comparative to the change in code numbers and this is what has that effect , that all that tax on all this income has to be collected against his works pension , thereby causing a lot of confusion and difficulty for er people becoming retired .
27 It gives the impression we 're prepared to spend the money and that 's what 's happened in previous years and it should n't happen .
28 And then we get what 's known as neutral stress , these are conditions really that can cause stress , but it 's stress that could go either way .
29 Is this , is this what 's known as poetic licence , Bill ?
30 When I say nice people , people that well you know what 's come from all the different countries , from out there .
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