PHPCLANCHILDES with regular expressions

6 matches in 6 utterances

2.58 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (538 utterances, 2,330 words searched).

  1. no we've not got a motorbike . MOT · eng_british_Manchester_II/warr06a.cha, line 496 · Warren 2;00
  2. we've got a policecar . MOT · eng_british_Manchester_II/warr06a.cha, line 498 · Warren 2;00
  3. we've failed you , haven't we Warren, ? MOT · eng_british_Manchester_II/warr06a.cha, line 509 · Warren 2;00
  4. now I think we've got enough for one more . MOT · eng_british_Manchester_II/warr06a.cha, line 1433 · Warren 2;00
  5. we've already done that [/] that one . MOT · eng_british_Manchester_II/warr06a.cha, line 1436 · Warren 2;00
  6. that's all we've got . MOT · eng_british_Manchester_II/warr06a.cha, line 1594 · Warren 2;00
  1. CHIwhere's my motorbike ?
    MOTmotor [//] we haven't got a motorbike I don't think .
    MOT*MOT: no we've not got a motorbike .
    MOTwe've got a policecar .
    MOTI've got your crane .
  2. MOTmotor [//] we haven't got a motorbike I don't think .
    MOTno we've not got a motorbike .
    MOT*MOT: we've got a policecar .
    MOTI've got your crane .
    MOTI've got the engine or the fire+engine .
  3. MOTbut we haven't got a motorbike .
    MOTI'm sorry .
    MOT*MOT: we've failed you , haven't we Warren, ?
    MOTno motorbike .
    CHIWarren toys .
  4. CHIxxx .
    MOTshall we put the elephant next to the sheep ?
    MOT*MOT: now I think we've got enough for one more .
    MOTwe've already done that [/] that one .
    MOTfind one from there and we'll do one more .
  5. MOTshall we put the elephant next to the sheep ?
    MOTnow I think we've got enough for one more .
    MOT*MOT: we've already done that [/] that one .
    MOTfind one from there and we'll do one more .
    CHIyeah .
  6. MOTwe haven't got enough soft stuff .
    CHImore .
    MOT*MOT: that's all we've got .
    MOT<we could make> [//] shall we make the goat's head ?
    MOTshall we do his head ?

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_II2.58
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_II/warr06a.chaWarren 2;0.032,330662.58

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. we've6 · 100.0%