PHPCLANCHILDES with regular expressions

14 matches in 14 utterances

6.55 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (523 utterances, 2,138 words searched).

  1. shall we put the boat on as well ? MOT · eng_british_Manchester_II/warr03a.cha, line 270 · Warren 1;10
  2. oh well . MOT · eng_british_Manchester_II/warr03a.cha, line 476 · Warren 1;10
  3. well you do it . MOT · eng_british_Manchester_II/warr03a.cha, line 694 · Warren 1;10
  4. well you do it then . INV · eng_british_Manchester_II/warr03a.cha, line 700 · Warren 1;10
  5. <well you put the bricks on> [>] . MOT · eng_british_Manchester_II/warr03a.cha, line 714 · Warren 1;10
  6. <well go on then> [<] . INV · eng_british_Manchester_II/warr03a.cha, line 716 · Warren 1;10
  7. well it's not really a bee . MOT · eng_british_Manchester_II/warr03a.cha, line 726 · Warren 1;10
  8. taking [//] well they were on the ground and taking off and landing . MOT · eng_british_Manchester_II/warr03a.cha, line 788 · Warren 1;10
  9. that's a very well balanced tower , isn't it ? MOT · eng_british_Manchester_II/warr03a.cha, line 927 · Warren 1;10
  10. well go on then . INV · eng_british_Manchester_II/warr03a.cha, line 959 · Warren 1;10
  11. well do it again then . MOT · eng_british_Manchester_II/warr03a.cha, line 961 · Warren 1;10
  12. well it's not actually a police van . MOT · eng_british_Manchester_II/warr03a.cha, line 1275 · Warren 1;10
  13. a police car says nee^naw@o as well , doesn't it ? MOT · eng_british_Manchester_II/warr03a.cha, line 1292 · Warren 1;10
  14. well spotted . MOT · eng_british_Manchester_II/warr03a.cha, line 1525 · Warren 1;10
  1. MOToh here's the trailer .
    MOThere's the trailer .
    MOT*MOT: shall we put the boat on as well ?
    MOTover the farmyard .
    MOTup your leg .
  2. MOTdo you know what it says ?
    MOTno .
    MOT*MOT: oh well .
    MOTnever mind .
    MOTthere's two men on the back of this trailer .
  3. MOToh there we go .
    CHIagain .
    MOT*MOT: well you do it .
    CHIagain .
    CHIagain .
  4. CHIagain .
    CHIagain .
    INV*INV: well you do it then .
    MOTWarren do it .
    INVI'm not gonna [: going to] do it .
  5. CHIWarren bricks on .
    CHII want bricks on .
    MOT*MOT: <well you put the bricks on> [>] .
    INV<well go on then> [<] .
    INVyou put them on .
  6. CHII want bricks on .
    MOT<well you put the bricks on> [>] .
    INV*INV: <well go on then> [<] .
    INVyou put them on .
    MOThow many are there already ?
  7. MOTthere's one .
    CHIbee .
    MOT*MOT: well it's not really a bee .
    MOTit's a butterfly .
    CHIin the sky .
  8. MOTyeah you see them in the sky in the garden .
    MOTbut we went somewhere where we saw them on the ground .
    MOT*MOT: taking [//] well they were on the ground and taking off and landing .
    MOTwhere did we go ?
    CHIin the sky .
  9. MOTare you reversing ?
    MOTdon't crash into me .
    MOT*MOT: that's a very well balanced tower , isn't it ?
    CHIover the top .
    MOTyou want some more bricks .
  10. MOTyou and your +/.
    CHIagain .
    INV*INV: well go on then .
    MOTwell do it again then .
    MOTtell you what Warren .
  11. CHIagain .
    INVwell go on then .
    MOT*MOT: well do it again then .
    MOTtell you what Warren .
    MOTyou build a tower on that one and I'll build a tower on this one , shall we ?
  12. MOTwhat is it ?
    CHIpolice van .
    MOT*MOT: well it's not actually a police van .
    MOTit's a fire+engine but it says the same thing , doesn't it ?
    MOTwhat do police vans say ?
  13. CHIpolice van .
    CHIpolice car .
    MOT*MOT: a police car says nee^naw@o as well , doesn't it ?
    MOTand a police bike says nee^naw@o .
    MOTI don't think you've ever seen a police bike , have you ?
  14. MOTI didn't realize .
    MOTit's the middle picture with a little tractor .
    MOT*MOT: well spotted .
    MOTI didn't notice that .
    MOTwhat else is there on here ?

Matches by age

One dot per transcript: matches per 1,000 words of everyone but CHI. Dots of the same child are joined.

Matches by child

Matches per 1,000 words, all transcripts of each child together, highest first.

  1. Warren eng_british_Manchester_II6.55
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_II/warr03a.chaWarren 1;10.292,13814146.55

What the pattern matched

1 different forms (lowercased). Useful to see what a pattern really catches: unexpected forms here usually mean the pattern is too broad.

  1. well14 · 100.0%